Goals and Habits in the Brain
Open accessAbstract
An enduring and richly elaborated dichotomy in cognitive neuroscience is that of reflective versus reflexive decision making and choice. Other literatures refer to the two ends of what is likely to be a spectrum with terms such as goal-directed versus habitual, model-based versus model-free or prospective versus retrospective. One of the most rigorous traditions of experimental work in the field started with studies in rodents and graduated via human versions and enrichments of those experiments to a current state in which new paradigms are probing and challenging the very heart of the distinction. We review four generations of work in this tradition and provide pointers to the forefront of the field's fifth generation.
AI snapshot
Written from the paper’s full text.
TL;DR
This review traces five “generations” of research on the dichotomy between reflective/goal-directed/model-based control and reflexive/habitual/model-free control in instrumental decision making. It argues that these systems are more richly intertwined than originally supposed, with unresolved questions about how model-based computation is realized and how the two systems compete or cooperate.
Key findings
- Goal-directed instrumental behavior is defined by two criteria: response-outcome control and current motivational relevance of the outcome; habitual behavior persists despite outcome devaluation and is automatic, computationally efficient, and inflexible.
- Rodent work implicates dorsomedial striatum and prelimbic prefrontal cortex in goal-directed action, and dorsolateral striatum and infralimbic cortex in habits; human fMRI studies report devaluation-related BOLD decreases in ventral orbitofrontal cortex and, after extensive training, increased cue-related activity in right posterior putamen/globus pallidus.
- Model-based and model-free reinforcement learning map onto goal-directed and habitual control; two-step Markov tasks show hybrid control, and Daw et al. found ventral striatal prediction-error signal covaried with model-based predictions and with individual model-based behavior.
- Pharmacological and clinical findings include L-DOPA increasing model-based choice, acute phenylalanine/tyrosine depletion increasing slips of action, and Parkinson’s disease severity negatively covarying with goal-directed devaluation performance; the review also links altered model-based/model-free balance to OCD, addiction, and speculatively psychosis.
Methods
- Narrative review, not a primary empirical study; it organizes the literature into five “generations,” from cognitive maps and goal-directed/habit studies through human neuroimaging, model-based/model-free RL, elaborations, and future directions.
- Focus is primarily on human instrumental behavior, with animal studies sketched only as essential background.
- Main analysis is conceptual and computational synthesis of behavioral paradigms (outcome devaluation, contingency degradation, two-step Markov tasks, Pavlovian-instrumental transfer) and neural findings; no new data, systematic search, or formal meta-analysis is reported.
Limitations
- The paper states it is an inevitably selective review and that space prevents discussion of many issues; animal studies are only sketched, and there is no consensus on the primate homolog of rat infralimbic cortex.
- The paper states that how model-based calculations are realized remains unresolved, and that arbitration/competition between model-based and model-free control needs much more work.
- Evident from the text: as a narrative review, it does not systematically search or quantitatively synthesize the literature, and some cited evidence is described as personal communication or unpublished data.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 144 cited sources checked · 0 supported · 0 flagged
- Premisecitation
Lesions to dorsomedial striatum result in an early emergence of habitual behavior.
“a pattern that contrasts with the effect of lesions to dorsomedial striatum that result in an early emergence of habitual behavior (Yin and Knowlton, 2006).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Yin and Knowlton, 2006 source
Not checked in the free run.
- Interpretationreasoning
The coexistence of the two classes of control has a normative rationale as offering efficient solutions to complex and changing environments.
“The latter provides a normative rationale for their coexistence as offering efficient solutions to the demands of complex and changing environments and has also underpinned the design and interpretation of a collection of targeted empirical studies.”
Quote in the paperSubstantial claim - Premisecitation
If an outcome becomes equally available with and without a lever press, goal-directed control leads to a decrease in pressing.
“If the outcome subsequently becomes equally available with and without a lever press, goal-directed control leads to a decrease in pressing (Dickinson and Balleine, 1994; Dickinson and Charnock, 1985).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Dickinson and Balleine, 1994 source
Not checked in the free run.
- cites Dickinson and Charnock, 1985
Not checked in the free run.
- Premisereasoning
In a test session in extinction, there should be less instrumental responding for an outcome that has been devalued than for an outcome that has not, if behavior is goal directed.
“In this case, there should be less instrumental responding for an outcome that has been devalued (for example, a food reinforcer that has just been rendered unpalatable) than for an outcome that has not.”
Quote in the paperSubstantial claim - Premisecitation
In the psychology of decision making and choice, there is more than one class of possible strategy for acting.
“An important and pervasive idea in the psychology of decision making and choice is that there is more than one class of possible strategy for acting.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Dickinson, 1985
Not checked in the free run.
- cites Kahneman, 2011
Not checked in the free run.
- cites Stanovich and West, 2002
Not checked in the free run.
- Premisecitation
Rodent studies repeatedly highlight a dorsomedial striatum circuit that supports goal-directed behavior.
“Rodent studies repeatedly highlight a dorsomedial striatum circuit that supports goal-directed behavior (Balleine, 2005; Corbit and Balleine, 2005; Yin et al., 2005).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
A circuit centered on dorsolateral striatum supports habit-based behavior.
“Related studies show that a circuit centered on dorsolateral striatum supports habit-based behavior (Yin et al., 2004, 2005; White, 1997; Balleine, 2005; Balleine and Dickinson, 1998; Killcross and Coutureau, 2003; Yin and Knowlton, 2006).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
There is explicit evidence for transfer from dorsomedial to dorsolateral striatum over the course of training.
“There is also explicit evidence for the transfer from dorsomedial to dorsolateral over the course of training (Belin et al., 2009; Graybiel, 2008; Yin et al., 2009; Thorn et al., 2010).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Lesions to dorsolateral striatum result in maintenance of goal-directed behavior even with extended training.
“Lesions to dorsolateral striatum result in a maintenance of goal-directed behavior even with extended training, a pattern that contrasts with the effect of lesions to dorsomedial striatum that result in an early emergence of habitual behavior (Yin and Knowlton, 2006).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Yin and Knowlton, 2006 source
Not checked in the free run.
- Interpretationreasoning
Behavior is initially goal directed but then becomes habitual over the course of experience.
“The requirement for extensive experience is key and this also implies that behavior is initially goal directed but then becomes habitual over the course of experience.”
Quote in the paperSubstantial claim - Interpretationnone given
The two classes of control have partly distinct neural realizations.
“In turn, this has led to a set of important studies into the partly distinct neural realizations of these classes and thence to an understanding of their computational and statistical characteristics.”
Quote in the paperSubstantial claim - Premisecitation
Behavioral dissociations that mirror those seen following striatal lesions are also seen with lesions to distinct sectors of prefrontal cortex.
“Behavioral dissociations that mirror precisely those seen following striatal lesions are also seen with lesions to distinct sectors of prefrontal cortex, a testament to the close functional affinity of these regions.”
Quote in the paperSubstantial claim - Premisecitation
Extended training on interval schedules of reinforcement involving single actions and single outcomes promotes habitual responding.
“Various circumstances promote habitual responding, notably extended training on interval schedules of reinforcement involving single actions and single outcomes (Dickinson and Charnock, 1985; Dickinson and Balleine, 2002; Dickinson et al., 1983).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Dickinson and Charnock, 1985
Not checked in the free run.
- cites Dickinson and Balleine, 2002
Not checked in the free run.
- cites Dickinson et al., 1983 source
Not checked in the free run.
- Premisecitation
Reversible inactivation targeting infralimbic medial prefrontal cortex impacts the expression of habitual behavior.
“Likewise, a reversible inactivation targeting infralimbic medial prefrontal cortex impacts on the expression of habitual behavior (Coutureau and Killcross, 2003).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Coutureau and Killcross, 2003
Not checked in the free run.
- Premisecitation
Model-free control involves a particular sort of prediction error, the best known example of which is the temporal difference (TD) prediction error.
“By contrast, model-free control involves a particular sort of prediction error, the best known example of which is the temporal difference (TD) prediction error (Sutton, 1988).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sutton, 1988 source
Not checked in the free run.
- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Premisecitation
In Valentin et al. (2007), after moderate initial training, human behavior was goal directed, with actions leading to the devalued outcome selectively depressed in extinction.
“As expected from the moderate amount of initial training, behavior was goal directed, with actions leading to the devalued outcome being selectively depressed in extinction.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Valentin et al., 2007 source
Not checked in the free run.
- Premisecitation
Control of a simple spatial behavior (turning in a plus maze) transfers from a hippocampal-dependent, allocentric reference frame to a striatum-dependent, egocentric one.
“One is the transfer of control of a simple spatial behavior (turning in a “plus” maze) from a hippocampal-dependent, allocentric, reference frame to a striatum-dependent, egocentric one (Packard and McGaugh, 1996).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Packard and McGaugh, 1996
Not checked in the free run.
- Premisenone given
More recently, a plethora of paradigms has provided as sharp a contrast between model-free and model-based for human studies as animal paradigms have between goal-directed and habitual control.
“More recently, a plethora of paradigms has provided as sharp a contrast between model-free and model-based for human studies as animal paradigms have between goal-directed and habitual control.”
Quote in the paperNot a substantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Premisecitation
There is much work in humans, nonhuman primates, and rodents suggesting that ventral orbitofrontal cortex plays a key role in representing the values that underpin goal-directed control.
“Indeed, there has been much work in humans, nonhuman primates, and rodents suggesting that this region plays a key role in representing the sort of values that underpin goal-directed control (Daw et al., 2006b; Gottfried and Dolan, 2004; Hampton et al., 2006; Padoa-Schioppa and Assad, 2006; Schoenbaum and Roesch, 2005; Thorpe et al., 1983).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
In extensively trained subjects, later sessions when behavior was habitual compared to earlier sessions when it would likely have been goal directed showed increased cue-related activity in right posterior putamen/globus pallidum.
“A within-group analysis of fMRI data from the extensively trained subjects comparing later sessions (when behavior was habitual) to earlier sessions (when it would likely have been goal directed) highlighted increased cue-related activity in right posterior putamen/globus pallidum, consistent with the rodent findings showing involvement of the dorsolateral striatum in habitual responding.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Tricomi et al., 2009 source
Not checked in the free run.
- Interpretationcitation
The increased cue-related activity in right posterior putamen/globus pallidum is consistent with rodent findings showing involvement of dorsolateral striatum in habitual responding.
“consistent with the rodent findings showing involvement of the dorsolateral striatum in habitual responding.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Tricomi et al., 2009 source
Not checked in the free run.
- Interpretationreasoning
In a sequential two-choice Markov decision task, model-based control can correctly ascribe rewards following a rare transition to an alternative nonselected action, which, despite not predicting reward on the current trial, will be more likely to lead to reward on future trials.
“By contrast, model-based control, because it builds the decision tree, can correctly ascribe those rewards following a rare transition to an alternative (nonselected) action—which, despite not predicting reward on the current trial, will be more likely to lead to reward on future trials.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Premisenone given
In a sequential two-choice Markov decision task, model-free control simply prefers to repeat actions that lead to reward, irrespective of the likelihood of the first transition.
“Model-free control simply prefers to repeat actions that lead to reward, irrespective of the likelihood of that first transition.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Premisecitation
Much evidence points to phasic activity of dopamine neurons as reporting an appetitive prediction error.
“Much evidence points to phasic activity of dopamine neurons as reporting an appetitive prediction error (Schultz et al., 1997; Montague et al., 1996).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Schultz et al., 1997 source
Not checked in the free run.
- cites Montague et al., 1996 source
Not checked in the free run.
- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Interpretationreasoning
In extinction, model-free control, like habitual control, has no immediate sensitivity to devaluation.
“Thus, in extinction, model-free control, like habitual control, has no immediate sensitivity to devaluation (Figure 1).”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Premisecitation
During the interregnum in the Gläscher et al. task, behavior was best fit by a hybrid model in which both systems exerted some control.
“During the interregnum, behavior was best fit by a hybrid model in which both systems exerted some control.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gläscher et al., 2010 source
Not checked in the free run.
- Interpretationcitation
In the Gläscher et al. latent-learning task, appropriate initial behavior after utilities were revealed could only arise from model-based control.
“Appropriate initial behavior in the task once the utilities were revealed could only arise from model-based control.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gläscher et al., 2010 source
Not checked in the free run.
- Premisecitation
In Valentin et al. (2007), BOLD signal in a ventral sector of orbitofrontal cortex decreased for a devalued compared to a nondevalued action.
“Of note was the observation that the BOLD signal in a ventral sector of orbitofrontal cortex decreased for a devalued compared to a nondevalued action, leading the authors to conclude that this region plays a role in goal-directed choice.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Valentin et al., 2007 source
Not checked in the free run.
- Interpretationreasoning
Given information that transitions have changed, as in contingency degradation, the decision tree and associated optimal choices will adapt straightaway.
“Equally, given information that the transitions have changed, as in contingency degradation, the decision tree and the associated optimal choices will adapt straightaway.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
- Premisecitation
Control based on a hierarchical association scheme in which a stimulus implies that a response leads to a particular outcome is compromised by lesions to posterior dorsomedial striatum.
“Control apparently based on the latter representation is compromised by lesions to posterior dorsomedial striatum, whereas in complex circumstances, lesions to dorsolateral striatal actually enhanced learning, suggesting that a form of competition might be at work.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bradfield and Balleine, 2013
Not checked in the free run.
- Interpretationcitation
Ventral orbitofrontal cortex plays a role in goal-directed choice.
“leading the authors to conclude that this region plays a role in goal-directed choice.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Valentin et al., 2007 source
Not checked in the free run.
- Premisecitation
In the Gläscher et al. task, the initial supremacy of the model-based controller declined precipitately over time even in the absence of information that would contradict this controller.
“However, the authors observed that the initial supremacy of model-based controller declined rather precipitately over time, even in the absence of information that would contradict this controller (Gläscher et al., 2010).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gläscher et al., 2010 source
Not checked in the free run.
- Premisecitation
In a modern experiment into the irrelevant incentive effect, sudden revaluation in Pavlovian conditioning is associated with dramatic upregulation of activity in dopaminergic nuclei as inferred from elevated Fos activity (along with many other regions, including the orbitofrontal cortex).
“Finally, in a modern experiment into the irrelevant incentive effect (Krieckhaus and Wolf, 1968), it was observed that sudden revaluation in Pavlovian conditioning is associated with dramatic upregulation of activity in dopaminergic nuclei as inferred from elevated Fos activity (along with many other regions, including the orbitofrontal cortex) (Robinson and Berridge, 2013).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Robinson and Berridge, 2013
Not checked in the free run.
- Premisecitation
At decision points such as a branch point in a maze, hippocampal place cell responses can be observed to sweep forward from the actual location of the subject.
“In particular, at decision points such as a branch point in a maze, hippocampal place cell responses can be observed to sweep forward from the actual location of the subject.”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Recent evidence indicates that even the simplest type of instrumental learning task has model-based and model-free components.
“This is given added urgency by recent evidence that even the simplest type of instrumental learning task has model-based and model-free components (Collins and Frank, 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Collins and Frank, 2012
Not checked in the free run.
- Premisecitation
Across subjects in the Daw et al. task, there was a wide spread in the degree of dependence on each system.
“However, across subjects, there was a wide spread in the degree of dependence on each system.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Daw et al., 2011 source
Not checked in the free run.
- Interpretationcitation
Backward sweeps (reverse replay) seem particularly relevant for understanding the mechanisms supporting certain aspects of value learning, providing the means for the back propagation of value signals to the earliest predictor of their likely future occurrence, without needing a forward-looking prediction error.
“Backward sweeps (called reverse replay) seem particularly relevant for understanding the mechanisms supporting certain aspects of value learning, providing the means for the back propagation of value signals to the earliest predictor of their likely future occurrence, without needing a forward-looking prediction error (Foster and Wilson, 2006).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Foster and Wilson, 2006 source
Not checked in the free run.
- Premisecitation
Boosting dopaminergic function enhances psychological and electrophysiological signatures of maintenance processes.
“while boosting dopaminergic function enhances psychological and electrophysiological signatures of such maintenance processes (Moran et al., 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Moran et al., 2011 source
Not checked in the free run.
- Premisecitation
Substantial work in conditions such as Parkinson's disease shows that manipulations favoring D1 and D2 dopamine receptors result in effects that are most readily interpretable in a model-free manner.
“Substantial work in conditions such as Parkinson’s disease, in which dopamine is reduced, shows that manipulations favoring D1 and D2 dopamine receptors result in effects that are most readily interpretable in a model-free manner (Frank et al., 2004).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Frank et al., 2004 source
Not checked in the free run.
- Premisecitation
In the Daw et al. task, the extent of this covariation for an individual subject was correlated with the extent to which that subject's behavior was model based.
“The extent of this covariation for an individual subject was correlated with the extent to which that subject’s behavior was model based.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Daw et al., 2011 source
Not checked in the free run.
- Premisecitation
A recent mouse study has reported that units in ventral hippocampus mediate a form of goal-oriented search.
“In a similar vein, a recent mouse study has reported that units in ventral hippocampus, a region which is strongly connected to those supporting reward processing, mediates a form of goal-oriented search (Ruediger et al., 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Ruediger et al., 2012 source
Not checked in the free run.
- Premisecitation
When an animal is not running in its environment, or when it is sleeping, it is possible to observe a variety of forward and backward sweeps related to more or less recent experience in the world.
“However, when an animal is not running in its environment, or indeed when it is sleeping, it is also possible to observe a variety of forward and backward sweeps (Dragoi and Buzsáki, 2006; Foster and Wilson, 2006, 2007; Lee and Wilson, 2002; Louie and Wilson, 2001) related to more or less recent experience in the world.”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationcitation
Dopamine is likely to play a role in both model-based and model-free systems.
“However, complexities are to be expected since dopamine is likely to play a role in both systems (Cools, 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Cools, 2011
Not checked in the free run.
- Premisecitation
There is now an accumulating wealth of reports of the sort of neural response profile that would be predicted if an animal is evaluating a menu of internally represented actions and their consequences at critical decision points.
“Along with these human studies, there is now an accumulating wealth of reports of the sort of neural response profile that would be predicted if indeed an animal is evaluating a menu of internally represented actions and their consequences at critical decision points.”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationcitation
At a mechanistic level, dopamine is likely to affect model-based control via its impact on maintenance processes associated with the prefrontal cortex.
“At a mechanistic level, dopamine is likely to affect model-based control via its impact on maintenance processes associated with the prefrontal cortex.”
Quote in the paperSubstantial claim - Premisecitation
Lesions to nigrostriatal dopamine impair habit (stimulus-response) learning.
“Indeed, lesions to nigrostriatal dopamine impair habit (stimulus-response) learning (Faure et al., 2005).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Faure et al., 2005 source
Not checked in the free run.
- Premisecitation
Subjects were more model based in their behavior when under L-DOPA.
“By fitting the same class of model as in the original study, the authors showed that subjects were more model based in their behavior when under L-DOPA, favoring the notion that the dominant influence of this type of dopaminergic manipulation is over prefrontal function rather than over dorsolateral striatal habits (Wunderlich et al., 2012b).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012b
Not checked in the free run.
- Premisecitation
Disrupting prefrontal function using TMS renders behavior more habitual.
“For example, disrupting prefrontal function using TMS renders behavior more habitual (Smittenaar et al., 2013), while boosting dopaminergic function enhances psychological and electrophysiological signatures of such maintenance processes (Moran et al., 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Smittenaar et al., 2013 source
Not checked in the free run.
- Premisecitation
Phasic firing of dopamine neurons has been suggested as reporting the temporal difference prediction error for reward that underpins model-free evaluation and control via its influence over activity and plasticity.
“First, as noted, the phasic firing of dopamine neurons has been suggested as reporting the temporal difference prediction error for reward (Montague et al., 1996; Schultz et al., 1997) that underpins model-free evaluation and control via its influence over activity and plasticity (Reynolds et al., 2001; Frank, 2005).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
Tract strength between caudate and ventromedial prefrontal cortex predicted a disposition to express more flexible goal-directed action, evident in an ability to selectively respond to still rewarding outcomes.
“This contrasts with tract strength between caudate and ventromedial prefrontal cortex that predicted a disposition to express more flexible goal-directed action, evident in an ability to selectively respond to still rewarding outcomes (de Wit et al., 2012b).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites de Wit et al., 2012b
Not checked in the free run.
- Premisecitation
Rats who had learned repulsion to an unpleasant salt stimulus, when first reencountering this stimulus in a salt-deprived state, showed immediate attraction to this same stimulus.
“Specifically, rats who had learned repulsion to an unpleasant salt stimulus, when first reencountering this stimulus in a salt-deprived state, showed immediate attraction to this same stimulus.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Robinson and Berridge, 2013
Not checked in the free run.
- Interpretationcitation
The dominant influence of this type of dopaminergic manipulation is over prefrontal function rather than over dorsolateral striatal habits.
“favoring the notion that the dominant influence of this type of dopaminergic manipulation is over prefrontal function rather than over dorsolateral striatal habits (Wunderlich et al., 2012b).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012b
Not checked in the free run.
- Premisecitation
In the Daw et al. two-step task, when subjects had to accomplish a cognitively demanding dual-task, model-free control becomes rampant.
“unless subjects had to accomplish a cognitively demanding dual-task, in which case model-free control becomes rampant (Otto et al., 2013).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Otto et al., 2013 source
Not checked in the free run.
- Interpretationcitation
These forward sweeps are consistent with the idea that the subject is engaged in some form of deliberation regarding its future potential states and the worth thereof, for instance, being correlated with the subject's ultimate choices.
“They do so in a manner consistent with the idea that the subject is engaged in some form of deliberation regarding its future potential states and the worth thereof (Johnson and Redish, 2007; Pfeiffer and Foster, 2013; van der Meer and Redish, 2009), for instance, being correlated with the subject’s ultimate choices.”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
In the Daw et al. two-step task, the best account of the behavioral data was provided by a hybrid model in which model-based and model-free predictions were integrated during learning.
“The best account of the behavioral data in this task was provided by a hybrid model in which model-based and model-free predictions were integrated during learning”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Daw et al., 2011 source
Not checked in the free run.
- Premisecitation
Dopamine exerts a significant influence over prefrontal cortical functions such as working memory, in a manner that depends on initial levels or efficacy of this neuromodulator.
“Third, dopamine exerts a significant influence over prefrontal cortical functions such as working memory (Williams and Goldman-Rakic, 1995), in a manner that depends on initial levels or efficacy of this neuromodulator (Cools and D’Esposito, 2011).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Williams and Goldman-Rakic, 1995 source
Not checked in the free run.
- cites Cools and D’Esposito, 2011
Not checked in the free run.
- Premisecitation
In the APTD study, dopamine depletion tipped the balance of control toward more habitual responding as revealed in a greater frequency of slips of action.
“Instead, depletion tipped the balance of control toward more habitual responding as revealed in a greater frequency of slips of action.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites de Wit et al., 2012a
Not checked in the free run.
- Premisecitation
Activity in vmPFC encoded the winning outcome of the choice process (chosen value), irrespective of whether this choice was based on a model-based or model-free value.
“In stark contrast, activity in vmPFC encoded the winning outcome of the choice process (chosen value), irrespective of whether this choice was based on a model-based or model-free value.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
- Interpretationcitation
Specific PIT depends on a match between the particular outcome that is expected as both the Pavlovian and instrumental target and so appears to be model based.
“Specific PIT depends on a match between the particular outcome that is expected as both the Pavlovian and instrumental target and so appears to be model based.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Balleine, 2005 source
Not checked in the free run.
- Interpretationcitation
This pattern is exactly the pattern expected in a forward tree search during goal-directed (model-based) decision making, where values related to distinct options are prospectively represented.
“This is exactly the pattern expected in a forward tree search during goal-directed (model-based) decision making, where values related to distinct options are prospectively represented.”
Quote in the paperSubstantial claim - Premisecitation
The grid-sailing task has provided evidence that subjects use a model-based strategy to generalize learning.
“This task has provided evidence that subjects use a model-based strategy to generalize learning.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Fermin et al., 2010 source
Not checked in the free run.
- Premisecitation
In the Gershman et al. design, subjects acted in a manner consistent with a model-based system having trained by a model-free one during an earlier phase of learning, as in an online or offline form of the DYNA-Q algorithms.
“In fact, the authors observed that subjects acted in a manner consistent with a model-based system having trained by a model-free one during an earlier phase of learning, as in an online or offline form of the DYNA-Q algorithms mentioned above (Sutton, 1991).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Gershman et al., 2012
Not checked in the free run.
- cites Sutton, 1991 source
Not checked in the free run.
- Interpretationcitation
Intermediate points between model-based and model-free control can arise from temporally sophisticated representations of states that contain predictions about likely future states (thus being partly model based) but that can be used in a straightforward manner by the model-free controller, thereby including some facets of model-based control.
“Intermediate points between model-based and model-free control can arise from temporally sophisticated representations of states that contain predictions about likely future states (thus being partly model based) but that can be used in a straightforward manner by the model-free controller, thereby including some facets of model-based control.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Dayan, 1993 source
Not checked in the free run.
- Premisecitation
In the Simon and Daw spatial task, behavior was better fit by a model-based rather than a model-free method.
“The constant change in the structure of the maze invited subjects to use model-based planning, and indeed their behavior was better fit by a model-based rather than a model-free method.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Simon and Daw, 2011
Not checked in the free run.
- Premisecitation
In the full three-step decision tree, anterior caudate nucleus BOLD covaried with optimal and alternative values, such that during a root branch decision, caudate activity related to several values relevant to the choice, including those present at consecutive choices deeper in the tree.
“In the full three-step decision tree, anterior caudate nucleus BOLD covaried with optimal and alternative values, such that during a root branch decision, caudate activity related to several values relevant to the choice, including those present at consecutive choices deeper in the tree.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
- Premisecitation
The latter studies delivered neural evidence for tree-like calculations.
“Nevertheless, the latter studies delivered neural evidence for tree-like calculations.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
- cites Simon and Daw, 2011
Not checked in the free run.
- Premisecitation
Patients with OCD showed increased frequency in slips of action.
“Patients with OCD (albeit potentially confounded by the effects of their neuromodulatory therapies) showed no deficit in using rewarding feedback to guide action but instead showed both lack of sensitivity to outcome devaluation and increased frequency in slips of action.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gillan et al., 2011 source
Not checked in the free run.
- Rests on an assumption: The effects of neuromodulatory therapies in OCD patients do not account for the observed lack of sensitivity to outcome devaluation and increased frequency of slips of action.
- Interpretationcitation
These findings highlight cooperation, as opposed to competition, between the two systems.
“In effect, these findings highlight cooperation, as opposed to competition, between the two systems.”
Quote in the paperSubstantial claim - Premisecitation
When goal-directed and habit-based options compete, the activity in caudate and putamen covaried with planned and cached values even under situations where the relevant actions were not chosen.
“Thus, when goal-directed and habit-based options compete, the activity in caudate and putamen covaried with planned and cached values even under situations where the relevant actions were not chosen.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
- Premisecitation
Model-based effects were not evident in the putamen, which only encoded model-free values for extensively trained options at the time of choice.
“Notably, these model-based effects were not evident in another basal ganglia structure, the putamen, which only encoded model-free values for extensively trained options at the time of choice.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
- Premisecitation
During the third, deepest, choice in the three-step decision tree, caudate activity was still associated with the values of both current choice alternatives but no longer with the value of the previously rejected root branch.
“However, during the third, deepest, choice, caudate activity was still associated with the values of both current choice alternatives but no longer with the value of the previously rejected root branch (Wunderlich et al., 2012a).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
- Interpretationreasoning
General PIT depends solely on the valence of the Pavlovian cue, as expected for a model-free prediction.
“Conversely, general PIT depends solely on the valence of the Pavlovian cue, as expected for a model-free prediction.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Balleine, 2005 source
Not checked in the free run.
- Premisecitation
There are dissociations between the effect of devaluation in instrumental responding versus PIT.
“Further, there are dissociations between the effect of devaluation in instrumental responding versus PIT (Holland, 2004)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Holland, 2004 source
Not checked in the free run.
- Rests on an assumption: Animal findings on Pavlovian revaluation and PIT are relevant to human model-based and model-free control.
- Interpretationreasoning
This dissociation corresponds exactly to the response patterns of a model-free controller that depends on cached values (putamen) and a model-based controller that depends on values calculated on the fly (caudate).
“This dissociation corresponds exactly to the response patterns of a model-free controller that depends on cached values (putamen) and a model-based controller that depends on values calculated on the fly (caudate).”
Quote in the paperSubstantial claim - Premisecitation
Patients with OCD showed lack of sensitivity to outcome devaluation.
“Patients with OCD (albeit potentially confounded by the effects of their neuromodulatory therapies) showed no deficit in using rewarding feedback to guide action but instead showed both lack of sensitivity to outcome devaluation and increased frequency in slips of action.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gillan et al., 2011 source
Not checked in the free run.
- Rests on an assumption: The effects of neuromodulatory therapies in OCD patients do not account for the observed lack of sensitivity to outcome devaluation and increased frequency of slips of action.
- Premisecitation
Regions such as ventrolateral and ventromedial putamen, whose BOLD signals are traditionally supposed to covary with model-free values or prediction errors, turned out to covary with key model-based value signal.
“Regions such as ventrolateral and ventromedial putamen, whose BOLD signals are traditionally supposed to covary with model-free values or prediction errors, turned out to covary with key model-based value signal.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Simon and Daw, 2011
Not checked in the free run.
- Premisecitation
OCD patients, along with substance abusers and binge eaters, showed a lower dependence on model-based control in the two-step task.
“A similar conclusion has been derived from observations of the two-step task (Daw et al., 2011) in OCD patients, as they, along with substance abusers and binge eaters, showed a lower dependence on model-based control (V. Voon, personal communication).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Daw et al., 2011 source
Not checked in the free run.
- cites V. Voon, personal communication
Not checked in the free run.
- Rests on an assumption: The effects of neuromodulatory therapies in OCD patients do not account for the observed lack of sensitivity to outcome devaluation and increased frequency of slips of action.
- Premisecitation
More recent investigations have detected evidence for model-based computations in the amygdala.
“More recent investigations have looked closely at the distinction between model-based and model-free, detecting evidence for the former in areas such as the amygdala (Prévost et al., 2013).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Prévost et al., 2013 source
Not checked in the free run.
- Interpretationcitation
Evidence for abnormalities in components of a goal-directed system in OCD, particularly the caudate nucleus, aligns with a suggestion that key manifestations of this condition reflect an overdominance of a habitual system.
“Furthermore, evidence for abnormalities in components of a goal-directed system in OCD, particularly the caudate nucleus, aligns with a suggestion that key manifestations of this condition reflect on overdominance of a habitual system (Maia et al., 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Maia et al., 2008 source
Not checked in the free run.
- Rests on an assumption: The effects of neuromodulatory therapies in OCD patients do not account for the observed lack of sensitivity to outcome devaluation and increased frequency of slips of action.
- Premisecitation
Patients with OCD showed no deficit in using rewarding feedback to guide action.
“Patients with OCD (albeit potentially confounded by the effects of their neuromodulatory therapies) showed no deficit in using rewarding feedback to guide action but instead showed both lack of sensitivity to outcome devaluation and increased frequency in slips of action.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gillan et al., 2011 source
Not checked in the free run.
- Rests on an assumption: The effects of neuromodulatory therapies in OCD patients do not account for the observed lack of sensitivity to outcome devaluation and increased frequency of slips of action.
- Interpretationcitation
This distinction has been used to good effect in determining the substrates of model-based and model-free predictions, for instance, differentiating the role of basolateral and central nuclei of the amygdala and their connections to the core and shell of the nucleus accumbens.
“This distinction has been used to good effect in determining the substrates of model-based and model-free predictions (Balleine, 2005), for instance, differentiating the role of basolateral and central nuclei of the amygdala and their connections to the core and shell of the nucleus accumbens.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Balleine, 2005 source
Not checked in the free run.
- Interpretationreasoning
Model-based and model-free predictions and controls offer flexible and adaptive solutions to the manifest problems of exploring and exploiting potentially dangerous but lucrative environments.
“and thereby offer flexible and adaptive solutions to the manifest problems of exploring and exploiting potentially dangerous but lucrative environments.”
Quote in the paperSubstantial claim - Interpretationreasoning
A key mechanism underlying the emergence of compulsive drug seeking, as well as relapse into addictive behaviors, is the subversion of control by a contextually dominant habitual mode.
“What this entails is that a key mechanism underlying the emergence of compulsive drug seeking, as well as relapse into addictive behaviors, is the subversion of control by a contextually dominant habitual mode.”
Quote in the paperSubstantial claim - Premisecitation
In the treatment of Parkinson's disease, boosting dopamine function often leads to the emergence of psychotic phenomena.
“It is worth noting that in the treatment of Parkinson’s disease, boosting dopamine function often leads to the emergence of psychotic phenomena (Yaryura-Tobias et al., 1970).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Yaryura-Tobias et al., 1970
Not checked in the free run.
- Premisecitation
Boosting dopamine boosts the impact and control of model-based influences.
“We observed that boosting dopamine boosts the impact and control of such model-based influences (Wunderlich et al., 2012b)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012b
Not checked in the free run.
- Interpretationnone given
Model-based and model-free predictions and controls are more richly intertwined than originally supposed.
“it is becoming clear that model-based and model-free predictions and controls are more richly intertwined than originally supposed”
Quote in the paperNot a substantial claim
- Classified as probably not a substantial claim. 12
- May combine two claims. 42
Classified as probably not a substantial claim.
Interpretationnone givenThe strand of work singled out by the paper provides behaviorally rigorous criteria for separating goal-directed and habitual control.
“Here, we single out one particular strand that has arguably been the most fecund in cognitive and theoretical neuroscience, providing a set of behaviorally rigorous criteria for separating out the two classes of control.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationHabitual instrumental control is characterized by automaticity, computational efficiency, and inflexibility, while goal-directed control is characterized by active deliberation, high computational cost, and adaptive flexibility to changing environmental contingencies.
“Thus, key characteristics of habitual instrumental control include automaticity, computational efficiency, and inflexibility, while characteristics of goal-directed control include active deliberation, high computational cost, and an adaptive flexibility to changing environmental contingencies (Dayan, 2009).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Dayan, 2009 source
Not checked in the free run.
May combine two claims.
PremisecitationFrontal prelimbic lesions abolish sensitivity to both outcome devaluation manipulations and degradation of instrumental contingency.
“Frontal prelimbic lesions abolish sensitivity to both outcome devaluation manipulations as well as to degradation of instrumental contingency (Balleine and Dickinson, 1998; Corbit and Balleine, 2003).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationreasoningBuilding and evaluating a decision tree imposes processing and working memory demands that rapidly become unrealistic with increasing depth, so a model-based agent is confronted with overwhelming computational constraints reflecting capacity limitations within attention and working memory.
“It is easy to appreciate that building and evaluating a tree imposes processing and working memory demands that rapidly become unrealistic with increasing depth. Consequently, a model-based agent is confronted with overwhelming computational constraints that in psychological terms reflect the known capacity limitations within attention and working memory.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
PremisecitationSelective lesions to prelimbic medial prefrontal cortex induce lack of sensitivity to goal value following either limited or extended training, whereas selective lesions to infralimbic regions result in retained sensitivity to goal value after both limited and extended training.
“Furthermore, selective lesions to prelimbic medial prefrontal cortex induce lack of sensitivity to goal value following either limited or extended training, whereas selective lesions to infralimbic regions result in an opposite deficit, namely retained sensitivity to goal value after both limited and extended training (Killcross and Coutureau, 2003).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Killcross and Coutureau, 2003
Not checked in the free run.
May combine two claims.
InterpretationreasoningThe key difference between model-free and model-based control makes it possible to discern the influence of each controller on behavior and to determine whether neural signals are correlated with predictions and prediction errors specific to each controller.
“This key difference makes it possible to discern the influence of each controller on behavior and also to determine whether neural signals are correlated with predictions and prediction errors specific to each controller.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
PremisecitationIn the rat, caudal, but not rostral, infralimbic cortex projects to ventral parts of medial caudate putamen, and there is no known projection to dorsolateral striatum.
“The connection between infralimbic cotex and dorsolateral striatum is rather less clear and in the rat, caudal, but not rostral, infralimbic cortex projects to ventral parts of medial caudate putamen (Vertes, 2004), but there is no known projection to dorsolateral striatum.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Vertes, 2004 source
Not checked in the free run.
May combine two claims.
PremisecitationActivity of ensembles of neurons in dorsolateral striatum and infralimbic cortex reflects the creation and stabilization of habits, with differences between the regions in the evolution of these patterns.
“It is known that the activity of ensembles of neurons in dorsolateral striatum and the infralimbic cortex reflect the creation and stabilization of habits, with interesting differences between the regions in the evolution of these patterns (Smith and Graybiel, 2013).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Smith and Graybiel, 2013
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenA huge wealth of subsequent studies have confirmed and elaborated the picture that BOLD signal in dorsal and ventral striatum correlates with model-free temporal difference prediction error.
“A huge wealth of subsequent studies have confirmed and elaborated this picture.”
Quote in the paperNot a substantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
InterpretationcitationIn the intact animal, there is likely a dynamic interdependency between goal-directed and habitual systems, and control likely emerges simultaneously and competitively.
“However, it is likely that in the intact animal, there is a dynamic interdependency between goal-directed and habitual systems and that control is likely to emerge simultaneously and competitively (Wassum et al., 2009).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wassum et al., 2009 source
Not checked in the free run.
May combine two claims.
PremisecitationvmPFC is likely to have a complex role in value representation, with evidence linking it to stimulus value, outcome value, and action value.
“vmPFC is likely to have a complex role in value representation and there is strong evidence linking this region to both stimulus value and outcome value, and even recent evidence linking it to action value (FitzGerald et al., 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites FitzGerald et al., 2012 source
Not checked in the free run.
May combine two claims.
InterpretationreasoningCached values depend on past utilities and are divorced from the outcomes that they predict.
“Further, the cached values depend on past utilities and so are divorced from the outcomes that they predict.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
InterpretationreasoningModel-free control is fundamentally retrospective, and new cached values can only be acquired through direct experience.
“Thus, model-free control is fundamentally retrospective, and new cached values, as might arise with a change in the utility of an outcome in an environment, can only be acquired through direct experience.”
Quote in the paperSubstantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
InterpretationreasoningThe double dissociation makes a strong case that prelimbic regions are crucial for goal-directed performance, while infralimbic lesions prevent the emergence of habitual responding that overrides an initial dominance in goal-directed responding.
“This double dissociation makes a strong case that prelimbic regions are crucial for goal-directed performance, while infralimbic lesions prevent the emergence of habitual responding that overrides an initial dominance in goal-directed responding.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationHuman lesion data has led to the suggestion that orbital prefrontal cortex implements encoding of stimulus value with dorsal cingulate cortex implementing encoding of action value.
“We note also that human lesion data has led to the suggestion that orbital prefrontal cortex implements encoding of stimulus value with dorsal cingulate cortex implementing encoding of action value (Camille et al., 2011).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Camille et al., 2011 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisereasoningModel-based control conceives of goal-directed control as sophisticated, computationally demanding, prospective planning, in which a decision tree of possible future states and actions is built using a learned internal model of the environment.
“Model-based control conceives of this in terms of sophisticated, computationally demanding, prospective planning, in which a decision tree of possible future states and actions is built using a learned internal model of the environment.”
Quote in the paperNot a substantial claim- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
InterpretationcitationIn complex circumstances, lesions to dorsolateral striatum enhanced learning, suggesting that a form of competition might be at work.
“whereas in complex circumstances, lesions to dorsolateral striatal actually enhanced learning, suggesting that a form of competition might be at work.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bradfield and Balleine, 2013
Not checked in the free run.
May combine two claims.
PremisecitationPrelimbic prefrontal cortex and dorsomedial striatum both support goal-directed action, in line with the anatomical connectivity between these regions.
“The fact that prelimbic prefrontal cortex and dorsomedial striatum both support goal-directed action is in line with the anatomical connectivity between these regions (Groenewegen et al., 1990; McGeorge and Faull, 1989).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Groenewegen et al., 1990 source
Not checked in the free run.
- cites McGeorge and Faull, 1989
Not checked in the free run.
May combine two claims.
InterpretationcitationModel-free control is computationally efficient because it replaces computation with memory, but the forward-looking nature of the prediction error makes it statistically inefficient.
“Model-free control is computationally efficient, since it replaces computation (i.e., the burdensome simulation of future states) with memory (i.e., stored discounted values of expected future reward); however, the forward-looking nature of the prediction error makes it statistically inefficient (Daw et al., 2005).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Daw et al., 2005 source
Not checked in the free run.
- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
PremisecitationTwo ends of a spectrum of reinforcement learning methods are model-based and model-free control, and these have been associated with goal-directed and habitual control, respectively.
“Two ends of a spectrum of RL methods are model-based and model-free control (where the term model refers to a mental as opposed to a computational model); it is these that have been associated with goal-directed and habitual control, respectively (Daw et al., 2005; Doya et al., 2002).”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationTransfer over the course of experience from allocentric to egocentric reference frames of a sequence of manual button presses was proposed to depend on two separate cortical regions that both interact with the basal ganglia.
“The other parallel is with the transfer over the course of experience from allocentric to egocentric reference frames of a sequence of manual button presses (Hikosaka et al., 1999), although this was proposed to depend on two separate cortical regions that both interact with the basal ganglia.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Hikosaka et al., 1999 source
Not checked in the free run.
May combine two claims.
PremisecitationPretraining, but not posttraining, lesions disrupt acquisition, but not expression, of goal-directed behavior.
“Pretraining, but not posttraining, lesions disrupt acquisition, but not expression, of goal-directed behavior (Ostlund and Balleine, 2005).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Ostlund and Balleine, 2005
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenGoal-directed or response-outcome learning has a strong declarative flavor but is conceptually distinct from hippocampal-dependent stimulus-stimulus learning.
“It is also worth noting here that although goal-directed or response-outcome learning has a strong declarative flavor, it is conceptually distinct from a hippocampal-dependent stimulus-stimulus form of learning.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe idea that prospective outcomes are explicitly represented allows states to be valued according to their current worth and choices to be immediately sensitive to devaluation.
“Critically, the idea that prospective outcomes are explicitly represented allows these states to be valued (putatively via the orbitofrontal or ventromedial prefrontal cortex) (Valentin et al., 2007; Fellows, 2011; O’Doherty, 2011) according to their current worth and so choices can be immediately sensitive to devaluation.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Valentin et al., 2007 source
Not checked in the free run.
- cites Fellows, 2011
Not checked in the free run.
- cites O’Doherty, 2011 source
Not checked in the free run.
- Rests on an assumption: All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
May combine two claims.
PremisecitationIn Tricomi et al. (2009), after outcome devaluation, the minimally trained group retained outcome sensitivity, while the extensively trained group did not.
“After outcome devaluation, performance showed that the minimally trained group retained outcome sensitivity, while the extensively trained group did not, just as in the animal studies.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Tricomi et al., 2009 source
Not checked in the free run.
May combine two claims.
PremisecitationIn the de Wit et al. instrumental conflict task, subjects with Parkinson's disease could solve the task, arguing that habit formation may not have been eliminated.
“They showed that subjects with the disease could solve the task, arguing that habit formation may not have been eliminated.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites de Wit et al., 2011 source
Not checked in the free run.
- Rests on an assumption: Parkinson’s disease involves the progressive death of dopamine cells and causes a decrease in dopamine release.
May combine two claims.
PremisecitationThe strength of white matter connections between premotor cortex and posterior putamen predicts vulnerability to "slips of action," a vulnerability also predicted by gray matter density in the putamen.
“For example, the strength of white matter connections between premotor cortex and posterior putamen is reported to predict vulnerability to “slips of action” (where non-goal-relevant, previously trained, actions are automatically elicited by environmental cues), a vulnerability also predicted by gray matter density in the putamen (de Wit et al., 2012b).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites de Wit et al., 2012b
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Study design and conductcitationIn a double-blind, fully counterbalanced (repeated-measures) design, Wunderlich et al. administered either L-DOPA or placebo while subjects solved the two-step Markov decision task of Daw et al. (2011).
“In a double-blind, fully counterbalanced (repeated-measures), design, Wunderlich et al. (2012b) administered either L-DOPA (to boost the influence of dopamine) or placebo while subjects solved the two-step Markov decision task of (Daw et al., 2011).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Wunderlich et al., 2012b
Not checked in the free run.
- cites Daw et al., 2011 source
Not checked in the free run.
May combine two claims.
PremisecitationAfter devaluation in the APTD study, dopamine depletion had no impact upon stimulus-response learning or response-outcome learning.
“After devaluation, depletion had no impact upon stimulus-response learning or response-outcome learning.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites de Wit et al., 2012a
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenThe frequency of slips of action does not offer a very precise measurement of the relative influence of model-based and model-free systems.
“The frequency of slips of action does not offer a very precise measurement of the relative influence of model-based and model-free systems.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationDopamine projects to the entire striatum, including regions such as dorsomedial striatum (or caudate), which have been implicated in model-based control, and dorsolateral striatum (or putamen), implicated in model-free control.
“Second, dopamine projects to the entire striatum, including regions such as dorsomedial striatum (or caudate), which have been implicated in model-based control, and dorsolateral striatum (or putamen), implicated in model-free control (Balleine, 2005).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Balleine, 2005 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenDepletion studies, whether experimental or disease based, are likely to exert a much less detrimental effect on dopamine function than the 6-OHDA lesions conventionally used in animal studies.
“However, depletion studies, whether experimental or disease based, are likely to exert a much less detrimental effect on dopamine function than the 6-OHDA lesions conventionally used in animal studies.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe model-based system is not thought to use temporal difference prediction errors for its own calculations; rather, it uses the state prediction error.
“One reason for a surprise at the presence of this signal is that the model-based system is not thought to use these prediction errors for its own calculations (rather, it uses the state prediction error, where a state prediction error is a measure of the surprise in a new state given a current estimate of state-action-state transition probabilities (Gläscher et al., 2010).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gläscher et al., 2010 source
Not checked in the free run.
May combine two claims.
PremisecitationIn the Gläscher et al. task, fMRI data highlighted a conventional model-free temporal difference reward prediction error in ventral striatum, whereas a different sort of state prediction error, associated with acquisition of the model, was seen in posterior inferior parietal and lateral prefrontal cortices.
“fMRI data highlighted a conventional model-free temporal difference reward prediction error in ventral striatum, whereas a different sort of state prediction error, associated with the acquisition of the model, was seen in posterior inferior parietal and lateral prefrontal cortices.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gläscher et al., 2010 source
Not checked in the free run.
May combine two claims.
PremisecitationIn a rat experiment, a posttraining manipulation of value coupled to a dopamine infusion into ventromedial PFC produced a bidirectional effect whereby the dopamine infusion decreased responding to a devalued outcome and enhanced responding to nondevalued outcomes, suggesting an influence on model-based valuation.
“For instance, in a rat experiment in which a posttraining manipulation of value was coupled to a dopamine infusion into ventromedial PFC (vmPFC) (Hitchcott et al., 2007), a bidirectional effect was evident whereby the dopamine infusion decreased responding to a devalued outcome and enhanced responding to nondevalued outcomes, suggesting an influence on model-based valuation.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hitchcott et al., 2007 source
Not checked in the free run.
May combine two claims.
InterpretationreasoningvmPFC can access both model-based and model-free values, consistent with parallel, and independent, operation of model-based and model-free valuation systems.
“Thus, vmPFC can access both model-based and model-free values, consistent with parallel, and independent, operation of model-based and model-free valuation systems.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationMany early fMRI studies into prediction errors used model-free accounts in Pavlovian paradigms and located prediction errors in striatal BOLD.
“Many early fMRI studies into prediction errors used model-free accounts in Pavlovian paradigms and located prediction errors in striatal BOLD (Berns et al., 2001; O’Doherty, 2004; O’Doherty et al., 2003; Haruno et al., 2004).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenHow control is parsed between model-based and model-free systems is likely to have psychopathological implications.
“How control is parsed between model-based and model-free systems is likely to have psychopathological implications.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationWhen subjects were required to choose between an overtrained pair and half the tree, the caudate represented the planned target value of the decision tree, while activity in the putamen pertained solely to the value of the overtrained pair.
“By contrast, when subjects were required to choose between an overtrained pair and half the tree, a situation requiring access to both model-based and model-free values, the caudate represented the planned target value of the decision tree, while activity in the putamen pertained solely to the value of the overtrained pair.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Wunderlich et al., 2012a
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationProtracted exposure to addictive drugs recruits dopamine-dependent striato-nigro-striatal ascending spirals from the nucleus accumbens to more dorsal regions of the striatum.
“One influential proposal is that a protracted exposure to addictive drugs recruits dopamine-dependent striato-nigro-striatal ascending spirals (Haber et al., 2000; Joel and Weiner, 2000) from the nucleus accumbens to more dorsal regions of the striatum (Everitt et al., 2008).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationThe irrelevant incentive effect shows a form of model-based motivationally sensitive evaluation and appears to depend on something akin to PIT.
“and the irrelevant incentive effect, which shows a form of model-based motivationally sensitive evaluation, appears to depend on something akin to PIT (Dickinson and Dawson, 1987a, 1987b) in a way that suggests this Pavlovian/instrumental difference.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Dickinson and Dawson, 1987a
Not checked in the free run.
- cites Dickinson and Dawson, 1987b
Not checked in the free run.
- Rests on an assumption: Animal findings on Pavlovian revaluation and PIT are relevant to human model-based and model-free control.
May combine two claims.
PremisecitationThere was little evidence that BOLD in the vmPFC was also related to value in the Simon and Daw spatial task, though parts of the medial temporal lobe also showed significant correlations with these and with reward predictions.
“By contrast, there was little evidence that BOLD in the vmPFC was also related to value, as might have been expected, though parts of the medial temporal lobe also showed significant correlations with these and with reward predictions.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Simon and Daw, 2011
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
InterpretationreasoningPavlovian conditioning differs from instrumental conditioning conceptually in the choice of action (automatic versus learned) rather than in the nature of the predictions, and so it is possible that it also has access to both model-free and model-based predictions.
“Second, Pavlovian conditioning differs from instrumental conditioning conceptually in the choice of action (automatic versus learned) rather than in the nature of the predictions, and so it is possible that it also has access to both model-free and model-based predictions.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationcitationThere is good evidence for Pavlovian predictions of actual outcomes, which what we argue underpins instrumental model-based control, and this seems to account for behavioral phenomena such as specific forms of Pavlovian instrumental transfer (PIT).
“There is good evidence for Pavlovian predictions of actual outcomes, which what we argue underpins instrumental model-based control, and this seems to account for behavioral phenomena such as specific forms of Pavlovian instrumental transfer (PIT) (Ostlund and Maidment, 2012; Kruse et al., 1983).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Ostlund and Maidment, 2012
Not checked in the free run.
- cites Kruse et al., 1983
Not checked in the free run.
May combine two claims.
PremisecitationInstant Pavlovian revaluation associated with saline deprivation occurs normally in decorticate animals and does not depend on regions strongly affiliated with model-based control such as the vmPFC.
“For instance, instant Pavlovian revaluation associated with saline deprivation happens normally in decorticate animals, evidently not depending on regions strongly affiliated with model-based control such as the vmPFC (Wirsig and Grill, 1982).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Wirsig and Grill, 1982
Not checked in the free run.
- Rests on an assumption: Animal findings on Pavlovian revaluation and PIT are relevant to human model-based and model-free control.
May combine two claims.
PremisecitationOther regions including the anterior insula, the precentral cortex, and the medial cingulate covaried with facets of the transitions available from a room, suggesting that they might be involved in realizing the model of the world.
“Other regions including the anterior insula, the precentral cortex, and the medial cingulate covaried with facets of the transitions available from a room, suggesting that they might be involved in realizing the model of the world.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Simon and Daw, 2011
Not checked in the free run.
May combine two claims.
PremisecitationIn the de Wit et al. study, goal-directed performance in a posttraining devaluation test covaried negatively with disease severity, arguing that model-based influences were impaired.
“They also showed that (goal-directed) performance in a posttraining devaluation test covaried negatively with disease severity, arguing that model-based influences were impaired.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites de Wit et al., 2011 source
Not checked in the free run.
- Rests on an assumption: Parkinson’s disease involves the progressive death of dopamine cells and causes a decrease in dopamine release.
May combine two claims.
PremisecitationOther related search tasks have found behavioral evidence for these calculations and have started to look at heuristics for pruning the tree, a necessity when it gets too wide or deep.
“Other related search tasks have found behavioral evidence for these calculations and have started to look at heuristics for pruning the tree, a necessity when it gets too wide or deep (Huys et al., 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Huys et al., 2012 source
Not checked in the free run.
May combine two claims.
InterpretationcitationThere is no unique form of model-free or model-based control and evidence hints that there are intermediate points on the spectrum between them.
“There is no unique form of model-free or model-based control and evidence hints that there are intermediate points on the spectrum between them.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThis recruitment results in a shift in control from action-outcome to stimulus-response mechanisms, a putative dominant mode of control in drug seeking and drug relapse.
“This results in a shift in control from action-outcome to stimulus-response mechanisms, a putative dominant mode of control in drug seeking and drug relapse.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Everitt et al., 2008 source
Not checked in the free run.
The paper relies on this without support.
All the tasks discussed in the paper can be mapped onto the reinforcement learning framework in a straightforward manner.
“All the tasks discussed above can be mapped onto this framework in a straightforward manner.”
The paper relies on this without support.
The utilities in the reinforcement learning framework depend on the motivations of the subject (e.g., water is more valuable given thirst).
“The utilities depend on the motivations of the subject (water is more valuable given thirst).”
The authors state this as an assumption.
The forward sweeps relevant to immediate choices start at the subject’s current location.
“The forward sweeps relevant to immediate choices are assumed to start at the subject’s current location.”
The paper relies on this without support.
Building and searching a deep tree imposes a huge burden on cognitive control and working memory.
“Building and searching a deep tree imposes a huge burden on cognitive control and working memory.”
The paper relies on this without support.
Prefrontal cortical functions such as working memory are particularly critical for the operation of model-based control.
“These functions are particularly critical for the operation of model-based control.”
The paper relies on this without support.
Parkinson’s disease involves the progressive death of dopamine cells and causes a decrease in dopamine release.
“Conversely, Parkinson’s disease involves the progressive death of dopamine cells and so causes a decrease in dopamine release.”
The paper relies on this without support.
The effects of neuromodulatory therapies in OCD patients do not account for the observed lack of sensitivity to outcome devaluation and increased frequency of slips of action.
“Patients with OCD (albeit potentially confounded by the effects of their neuromodulatory therapies) showed no deficit in using rewarding feedback to guide action but instead showed both lack of sensitivity to outcome devaluation and increased frequency in slips of action.”
The paper relies on this without support.
Animal findings on Pavlovian revaluation and PIT are relevant to human model-based and model-free control.
“For instance, instant Pavlovian revaluation associated with saline deprivation happens normally in decorticate animals, evidently not depending on regions strongly affiliated with model-based control such as the vmPFC (Wirsig and Grill, 1982).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Two parallel forms of reinforcement learning, model-based and model-free (or value-free), correspond to goal-directed and habitual strategies and develop concurrently during behavior acquisition.
“Supporting this, computational studies have proposed two parallel forms of reinforcement learning, model-based and model-free (or value-free) learning corresponding to goal-directed and habitual strategies, respectively, that develop concurrently during behavior acquisition2,41,42.”
From Dissociable roles of prefrontal plasticity in decision-making strategy and execution of habitual behavior (2026) · cites this paper as [2]
The 'Generation 3: Model-Based and Model-free Analyses' section associates model-based and model-free control with goal-directed and habitual control, respectively, and reports a hybrid model integrating both during learning (page unavailable). But the paper describes model-free control as using stored values of expected reward, so it does not support the parenthetical equivalence with 'value-free.' (LLM, conf=0.87)
Experimental — accuracy not yet measuredRewarded experience updates the model for stimulus-response-outcome associations when using a model-based learning strategy.
“As conceptualized by computational studies2,41,46, rewarded experience updates the model for stimulus-response-outcome associations when using a model-based learning strategy.”
From Dissociable roles of prefrontal plasticity in decision-making strategy and execution of habitual behavior (2026) · cites this paper as [2]
More recent formulations emphasize cooperation, rather than only competition, between behavioural controllers.
“More recent formulations emphasize cooperation, rather than only competition (Daw and Dayan, 2014, Dolan and Dayan, 2013, Keramati et al., 2011, O’Doherty et al., 2015, Pezzulo et al., 2013; see also Daw et al., 2011, Lee et al., 2014) for relevant empirical evidence that supports an integrative viewpoint.”
From Active Inference, homeostatic regulation and adaptive behavioural control (2015) · cites this paper as Dolan and Dayan, 2013
The neural substrates of the goal-directed control system are dissociable from those of the stimulus-response habit system.
“A host of basic neuroscience studies have been conducted in this area, converging on the notion that the neural substrates of the goal-directed control system are dissociable from that of the stimulus-response habit system (Dolan and Dayan, 2013).”
From The role of habit in compulsivity (2016) · cites this paper as Dolan and Dayan, 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Direction of training between systems is reversed
MinorThe account of the DYNA-Q task says the model-based system was trained by the model-free system. Earlier, the paper describes DYNA as the model-based system training the model-free system-the opposite direction.
“subjects acted in a manner consistent with a model-based system having trained by a model-free one during an earlier phase of learning, as in an online or offline form of the DYNA-Q algorithms mentioned above (Sutton, 1991).”
“It has been suggested that these are reflections of a model-based system training a model-free system, something that had been suggested in RL in the form of a technique called DYNA (Sutton, 1991).”
Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225 · see citing works
James, W. (1891) · Henry Holt and Company eBooks · doi:10.1037/11059-000 · Cited by 25,799 · see citing works
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,263 · see citing works
Bellman, R. E. (2010) · doi:10.1515/9781400835386 · Cited by 14,588 · see citing works
(2011) · Cited by 14,317 · see citing works
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388 · see citing works
Self-citation(1978) · UA Campus Repository (The University of Arizona) · Cited by 8,010 · see citing works
Cognitive maps in rats and men
Tolman, E. C. (1948) · Psychological Review · doi:10.1037/h0061626 · Cited by 6,641 · see citing works
Watkins, C. (1989) · OpenGrey (Institut de l'Information Scientifique et Technique) · doi:10.17863/cam.132164 · Cited by 5,406 · see citing works
McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995) · Psychological Review · doi:10.1037/0033-295x.102.3.419 · Cited by 5,256 · see citing works
Learning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148 · see citing works
The hippocampus as a cognitive map
Passingham, R. E. (1979) · Neuroscience · doi:10.1016/0306-4522(79)90015-0 · Cited by 5,128 · see citing works
The Psychology of Learning and Motivation
(2021) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/s0079-7421(21)x0002-3 · Cited by 5,081 · see citing works
Heuristics and Biases: The Psychology of Intuitive Judgment
Bottom, W. P., Gilovich, T., Griffin, D. W., & Kahneman, D. (2002) · Academy of Management Review · doi:10.2307/20159081 · Cited by 3,923 · see citing works
The reward circuit: linking primate anatomy and human imaging
Haber, S. N., & Knutson, B. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.129 · Cited by 3,718 · see citing works
Neuronlike adaptive elements that can solve difficult learning control problems
Barto, A. G., Sutton, R. S., & Anderson, C. W. (1983) · IEEE Transactions on Systems Man and Cybernetics · doi:10.1109/tsmc.1983.6313077 · Cited by 3,238 · see citing works
Individual differences in reasoning: Implications for the rationality debate?
Stanovich, K., & West, R. (2000) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00003435 · Cited by 2,987 · see citing works
Gallistel, C. R. (1990) · Cited by 2,571 · see citing works
Daw, N. D., Niv, Y., & Dayan, P. (2005) · Nature Neuroscience · doi:10.1038/nn1560 · Cited by 2,533 · see citing works
Self-citationThe role of the basal ganglia in habit formation
Yin, H. H., & Knowlton, B. J. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn1919 · Cited by 2,402 · see citing works
Remembering the past to imagine the future: the prospective brain
Schacter, D. L., Addis, D. R., & Buckner, R. L. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2213 · Cited by 2,394 · cited 1× · see citing works
“Cognitive maps occupy a central role in contemporary ideas related to active memory or prospection (Schacter et al., 2007), where the hippocampus (O’Keefe and Nadel, 1978) has been shown to play a critical role (O’Keefe and Nadel, 1978).”
Cortical substrates for exploratory decisions in humans
Daw, N. D., O'Doherty, J. P., Dayan, P., Seymour, B., & Dolan, R. J. (2006) · Nature · doi:10.1038/nature04766 · Cited by 2,224 · see citing works
Self-citationA framework for studying the neurobiology of value-based decision making
Rangel, A., Camerer, C., & Montague, P. R. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2357 · Cited by 2,184 · see citing works
A framework for mesencephalic dopamine systems based on predictive Hebbian learning
Montague, P., Dayan, P., & Sejnowski, T. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-05-01936.1996 · Cited by 2,066 · see citing works
Self-citationBy Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism
Frank, M. J., Seeberger, L. C., & O'Reilly, R. C. (2004) · Science · doi:10.1126/science.1102941 · Cited by 1,964 · see citing works
The Architecture of Cognitive Control in the Human Prefrontal Cortex
Koechlin, E., Ody, C., & Kouneiher, F. (2003) · Science · doi:10.1126/science.1088545 · Cited by 1,922 · see citing works
Model-based influences on humans’ choices and striatal prediction errors
Daw, N. D., Gershman, S. J., Seymour, B., Dayan, P., & Dolan, R. J. (2011) · Neuron · doi:10.1016/j.neuron.2011.02.027 · Cited by 1,779 · see citing works
Self-citationBalleine, B. W., & O'Doherty, J. P. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.131 · Cited by 1,775 · see citing works
Reverse replay of behavioural sequences in hippocampal place cells during the awake state
Foster, D. J., & Wilson, M. A. (2006) · Nature · doi:10.1038/nature04587 · Cited by 1,727 · see citing works
Habits, Rituals, and the Evaluative Brain
Graybiel, A. M. (2008) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112851 · Cited by 1,697 · see citing works
Inverted-U–Shaped Dopamine Actions on Human Working Memory and Cognitive Control
Cools, R., & D'Esposito, M. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.03.028 · Cited by 1,673 · see citing works
Haber, S. N., Fudge, J. L., & McFarland, N. R. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-06-02369.2000 · Cited by 1,610 · see citing works
Neurons in the orbitofrontal cortex encode economic value
Padoa-Schioppa, C., & Assad, J. A. (2006) · Nature · doi:10.1038/nature04676 · Cited by 1,598 · see citing works
Modulation of memory fields by dopamine Dl receptors in prefrontal cortex
Williams, G. V., & Goldman-Rakic, P. S. (1995) · Nature · doi:10.1038/376572a0 · Cited by 1,593 · see citing works
Differential projections of the infralimbic and prelimbic cortex in the rat
Vertes, R. P. (2004) · Synapse · doi:10.1002/syn.10279 · Cited by 1,550 · see citing works
Goal-directed instrumental action: contingency and incentive learning and their cortical substrates
Balleine, B. W., & Dickinson, A. (1998) · Neuropharmacology · doi:10.1016/s0028-3908(98)00033-1 · Cited by 1,541 · see citing works
Temporal difference models and reward-related learning in the human brain
O'Doherty, J. P., Dayan, P., Friston, K., Critchley, H., & Dolan, R. J. (2003) · Neuron · doi:10.1016/s0896-6273(03)00169-7 · Cited by 1,522 · see citing works
Self-citationPackard, M. G., & McGaugh, J. L. (1996) · Neurobiology of Learning and Memory · doi:10.1006/nlme.1996.0007 · Cited by 1,505 · see citing works
On-line Q-learning Using Connectionist Systems
Rummery, G. A. (1994) · Cited by 1,475 · see citing works
Reward representations and reward-related learning in the human brain: Insights from neuroimaging
O’Doherty, J. P. (2004) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2004.10.016 · Cited by 1,426 · see citing works
Patients with hippocampal amnesia cannot imagine new experiences
Hassabis, D., Kumaran, D., Vann, S. D., & Maguire, E. A. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610561104 · Cited by 1,414 · see citing works
The future of memory: remembering, imagining, and the brain
Schacter, D. L., Addis, D. R., Hassabis, D., Martin, V. C., Spreng, R. N., & Szpunar, K. K. (2012) · Neuron · doi:10.1016/j.neuron.2012.11.001 · Cited by 1,398 · see citing works
Sutton, R. S. (1990) · Elsevier eBooks · doi:10.1016/b978-1-55860-141-3.50030-4 · Cited by 1,348 · see citing works
The organization of the projection from the cerebral cortex to the striatum in the rat
McGeorge, A. J., & Faull, R. L. M. (1989) · Neuroscience · doi:10.1016/0306-4522(89)90128-0 · Cited by 1,345 · see citing works
Conditioning and Associative Learning
Hill, W. F., & Mackintosh, N. J. (1984) · The American Journal of Psychology · doi:10.2307/1422540 · Cited by 1,323 · see citing works
Memory of sequential experience in the hippocampus during slow wave sleep
Lee, A. K., & Wilson, M. A. (2002) · Neuron · doi:10.1016/s0896-6273(02)01096-6 · Cited by 1,296 · see citing works
Yin, H. H., Knowlton, B. J., & Balleine, B. W. (2004) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2004.03095.x · Cited by 1,226 · see citing works
Actions and habits: The development of behavioural autonomy
Dickinson, A. (1985) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1985.0010 · Cited by 1,217 · see citing works
Hippocampal place-cell sequences depict future paths to remembered goals
Pfeiffer, B. E., & Foster, D. J. (2013) · Nature · doi:10.1038/nature12112 · Cited by 1,216 · see citing works
A purely geometric module in the rat's spatial representation
Cheng, K. (1986) · Cognition · doi:10.1016/0010-0277(86)90041-7 · Cited by 1,182 · see citing works
Gläscher, J., Daw, N., Dayan, P., & O'Doherty, J. P. (2010) · Neuron · doi:10.1016/j.neuron.2010.04.016 · Cited by 1,166 · see citing works
Self-citationTemporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep
Louie, K., & Wilson, M. A. (2001) · Neuron · doi:10.1016/s0896-6273(01)00186-6 · Cited by 1,148 · see citing works
Tonic dopamine: Opportunity costs and the control of response vigor
Niv, Y., Daw, N. D., Joel, D., & Dayan, P. (2007) · Psychopharmacology · doi:10.1007/s00213-006-0502-4 · Cited by 1,133 · see citing works
Self-citationThe role of the dorsomedial striatum in instrumental conditioning
Yin, H. H., Ostlund, S. B., Knowlton, B. J., & Balleine, B. W. (2005) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2005.04218.x · Cited by 1,099 · see citing works
O’Reilly, R. C., & Frank, M. J. (2005) · Neural Computation · doi:10.1162/089976606775093909 · Cited by 1,066 · see citing works
Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point
Johnson, A., & Redish, A. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.3761-07.2007 · Cited by 1,003 · see citing works
Motivational control of goal-directed action
Dickinson, A., & Balleine, B. (1994) · Animal Learning & Behavior · doi:10.3758/bf03199951 · Cited by 995 · see citing works
Everitt, B. J., Belin, D., Economidou, D., Pelloux, Y., Dalley, J. W., & Robbins, T. W. (2008) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2008.0089 · Cited by 974 · see citing works
Frank, M. J. (2005) · Journal of Cognitive Neuroscience · doi:10.1162/0898929052880093 · Cited by 925 · see citing works
A cellular mechanism of reward-related learning
Reynolds, J. N. J., Hyland, B. I., & Wickens, J. R. (2001) · Nature · doi:10.1038/35092560 · Cited by 879 · see citing works
Interactions between frontal cortex and basal ganglia in working memory: A computational model
FRANK, M. J., LOUGHRY, B., & O'REILLY, R. C. (2001) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/cabn.1.2.137 · Cited by 879 · see citing works
The orbitofrontal cortex: Neuronal activity in the behaving monkey
Thorpe, S. J., Rolls, E. T., & Maddison, S. (1983) · Experimental Brain Research · doi:10.1007/bf00235545 · Cited by 836 · see citing works
Animal Intelligence. Experimental Studies
Thorndike, E. L., & Jelliffe (1912) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-191205000-00016 · Cited by 824 · see citing works
Dynamic reorganization of striatal circuits during the acquisition and consolidation of a skill
Yin, H. H., Mulcare, S. P., Hilário, M. R. F., Clouse, E., Holloway, T., Davis, M. I., Hansson, A. C., Lovinger, D. M., & Costa, R. M. (2009) · Nature Neuroscience · doi:10.1038/nn.2261 · Cited by 818 · see citing works
Parallel neural networks for learning sequential procedures
Hikosaka, O., Nakahara, H., Rand, M. K., Sakai, K., Lu, X., Nakamura, K., Miyachi, S., & Doya, K. (1999) · Trends in Neurosciences · doi:10.1016/s0166-2236(99)01439-3 · Cited by 799 · see citing works
Schenk, F. (1991) · Trends in Neurosciences · doi:10.1016/0166-2236(91)90036-t · Cited by 790 · see citing works
Dyna, an Integrated Architecture for Learning, Planning, and Reacting
Sutton, R. S. (1991) · ACM SIGART Bulletin · doi:10.1145/122344.122377 · Cited by 777 · cited 5× · see citing works
“In fact, the authors observed that subjects acted in a manner consistent with a model-based system having trained by a model-free one during an earlier phase of learning, as in an online or offline form of the DYNA-Q algorithms mentioned above (Sutton, 1991).”
InfluentialEfferent projections of the infralimbic cortex of the rat
Hurley, K. M., Herbert, H., Moga, M. M., & Saper, C. B. (1991) · Journal of Comparative Neurology · doi:10.1002/cne.903080210 · Cited by 777 · see citing works
A specific role for posterior dorsolateral striatum in human habit learning
Tricomi, E., Balleine, B. W., & O’Doherty, J. P. (2009) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2009.06796.x · Cited by 769 · see citing works
Anterior Prefrontal Function and the Limits of Human Decision-Making
Koechlin, É., & Hyafil, A. (2007) · Science · doi:10.1126/science.1142995 · Cited by 750 · see citing works
Coordination of Actions and Habits in the Medial Prefrontal Cortex of Rats
Killcross, S. (2003) · Cerebral Cortex · doi:10.1093/cercor/13.4.400 · Cited by 748 · see citing works
What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?
Doya, K. (1999) · Neural Networks · doi:10.1016/s0893-6080(99)00046-5 · Cited by 739 · see citing works
Temporal Encoding of Place Sequences by Hippocampal Cell Assemblies
Dragoi, G., & Buzsáki, G. (2006) · Neuron · doi:10.1016/j.neuron.2006.02.023 · Cited by 727 · see citing works
Reinforcement learning in the brain
Niv, Y. (2009) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2008.12.005 · Cited by 724 · see citing works
AUTO‐MAINTENANCE IN THE PIGEON: SUSTAINED PECKING DESPITE CONTINGENT NON‐REINFORCEMENT2
Williams, D. R., & Williams, H. G. (1969) · Journal of the Experimental Analysis of Behavior · doi:10.1901/jeab.1969.12-511 · Cited by 717 · see citing works
Predictability modulates human brain response to reward
Berns, G. S., McClure, S. M., Pagnoni, G., & Montague, P. R. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-08-02793.2001 · Cited by 711 · see citing works
Improving generalization for temporal difference learning: The successor representation
Dayan, P. (1993) · Neural Computation · doi:10.1162/neco.1993.5.4.613 · Cited by 693 · see citing works
Self-citationInstrumental Responding following Reinforcer Devaluation
Adams, C. D., & Dickinson, A. (1981) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/14640748108400816 · Cited by 687 · see citing works
Joel, D., & Weiner, I. (2000) · Neuroscience · doi:10.1016/s0306-4522(99)00575-8 · Cited by 614 · see citing works
<i>Spatial Cognition and the Brain</i>
Burgess, N. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.002 · Cited by 614 · see citing works
Gillan, C. M., Papmeyer, M., Morein-Zamir, S., Sahakian, B. J., Fineberg, N. A., Robbins, T. W., & de Wit, S. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.10071062 · Cited by 609 · see citing works
Corbit, L. H., & Balleine, B. W. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.4507-04.2005 · Cited by 589 · see citing works
Decision theory, reinforcement learning, and the brain
Dayan, P., & Daw, N. D. (2008) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/cabn.8.4.429 · Cited by 580 · see citing works
Self-citationThe determiners of behavior at a choice point.
Tolman, E. C. (1938) · Psychological Review · doi:10.1037/h0062733 · Cited by 543 · see citing works
Determining the neural substrates of goal-directed learning in the human brain
Valentin, V. V., Dickinson, A., & O'Doherty, J. P. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.0564-07.2007 · Cited by 529 · see citing works
Belin, D., Jonkman, S., Dickinson, A., Robbins, T. W., & Everitt, B. J. (2009) · Behavioural Brain Research · doi:10.1016/j.bbr.2008.09.027 · Cited by 520 · see citing works
Groenewegen, H. J., Berendse, H. W., Wolters, J. G., & Lohman, A. H. M. (1991) · Progress in brain research · doi:10.1016/s0079-6123(08)62677-1 · Cited by 506 · see citing works
Hampton, A. N., Bossaerts, P., & O’Doherty, J. P. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1010-06.2006 · Cited by 498 · see citing works
Multiple model-based reinforcement learning
Doya, K., Samejima, K., Katagiri, K.-I., & Kawato, M. (2002) · Neural Computation · doi:10.1162/089976602753712972 · Cited by 476 · see citing works
Introduction and removal of reward, and maze performance in rats.
Tolman, E. C., & Honzik, C. H. (1930) · Cited by 447 · see citing works
Huys, Q. J. M., Eshel, N., O'Nions, E., Sheridan, L., Dayan, P., & Roiser, J. P. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002410 · Cited by 439 · see citing works
Self-citationThe role of prelimbic cortex in instrumental conditioning
Corbit, L. H., & Balleine, B. W. (2003) · Behavioural Brain Research · doi:10.1016/j.bbr.2003.09.023 · Cited by 423 · see citing works
Collins, A. G. E., & Frank, M. J. (2012) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2011.07980.x · Cited by 419 · see citing works
Thorn, C. A., Atallah, H. E., Howe, M. W., & Graybiel, A. M. (2010) · Neuron · doi:10.1016/j.neuron.2010.04.036 · Cited by 412 · see citing works
Orbitofrontal cortex, associative learning and expectancies
Schoenbaum, G., & Roesch, M. (2005) · Neuron · doi:10.1016/j.neuron.2005.07.018 · Cited by 404 · see citing works
Lesion to the nigrostriatal dopamine system disrupts stimulus-response habit formation
Faure, A., Haberland, U., Condé, F., & Massioui, N. E. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.3894-04.2005 · Cited by 402 · see citing works
The misbehavior of value and the discipline of the will
Dayan, P., Niv, Y., Seymour, B., & Daw, N. D. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.03.002 · Cited by 389 · see citing works
Self-citationRelations between Pavlovian-instrumental transfer and reinforcer devaluation
Holland, P. C. (2004) · Journal of Experimental Psychology: Animal Behavior Processes · doi:10.1037/0097-7403.30.2.104 · Cited by 388 · see citing works
The Role of Learning in the Operation of Motivational Systems
Dickinson, A., & Balleine, B. W. (2002) · Wiley eBooks · doi:10.1002/0471214426.pas0312 · Cited by 387 · see citing works
Foster, D. J., & Wilson, M. A. (2007) · Hippocampus · doi:10.1002/hipo.20345 · Cited by 381 · see citing works
The ubiquity of model-based reinforcement learning
Doll, B. B., Simon, D. A., & Daw, N. D. (2012) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.08.003 · Cited by 380 · see citing works
de Wit, S., Watson, P., Harsay, H. A., Cohen, M. X., van de Vijver, I., & Ridderinkhof, K. R. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.1088-12.2012 · Cited by 373 · see citing works
The neural bases of obsessive-compulsive disorder in children and adults
Maia, T. V., Cooney, R. E., & Peterson, B. S. (2008) · Development and Psychopathology · doi:10.1017/s0954579408000606 · Cited by 362 · cited 1× · see citing works
“Furthermore, evidence for abnormalities in components of a goal-directed system in OCD, particularly the caudate nucleus, aligns with a suggestion that key manifestations of this condition reflect on overdominance of a habitual system (Maia et al., 2008).”
Gottfried, J. A., & Dolan, R. J. (2004) · Nature Neuroscience · doi:10.1038/nn1314 · Cited by 353 · see citing works
Self-citationOtto (2013) · doi:10.1177/0956797612463080 · Cited by 352 · see citing works
Speed/accuracy trade-off between the habitual and the goal-directed processes
Keramati, M., Dezfouli, A., & Piray, P. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002055 · Cited by 346 · see citing works
Coutureau, E., & Killcross, S. (2003) · Behavioural Brain Research · doi:10.1016/j.bbr.2003.09.025 · Cited by 342 · see citing works
The effect of the instrumental training contingency on susceptibility to reinforcer devaluation
Dickinson, A., Nicholas, D. J., & Adams, C. D. (1983) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/14640748308400912 · Cited by 338 · see citing works
Neurobiology of Sensation and Reward
Gottfried, J. A. (2011) · CRC Press eBooks · doi:10.1201/b10776 · Cited by 331 · see citing works
Frank, M. J., & Badre, D. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr114 · Cited by 330 · see citing works
Neural bases of food-seeking: affect, arousal and reward in corticostriatolimbic circuits
BALLEINE, B. (2005) · Physiology & Behavior · doi:10.1016/j.physbeh.2005.08.061 · Cited by 326 · see citing works
Instant transformation of learned repulsion into motivational “wanting”
Robinson, M. J. F., & Berridge, K. C. (2013) · Current Biology · doi:10.1016/j.cub.2013.01.016 · Cited by 320 · see citing works
Reward learning: reinforcement, incentives, and expectations
Berridge, K. C. (2000) · Psychology of Learning and Motivation · doi:10.1016/s0079-7421(00)80022-5 · Cited by 318 · see citing works
Mapping value based planning and extensively trained choice in the human brain
Wunderlich, K., Dayan, P., & Dolan, R. J. (2012) · Nature Neuroscience · doi:10.1038/nn.3068 · Cited by 310 · see citing works
Self-citationHaruno, M., Kuroda, T., Doya, K., Toyama, K., Kimura, M., Samejima, K., Imamizu, H., & Kawato, M. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.3417-03.2004 · Cited by 300 · see citing works
Covert expectation-of-reward in rat ventral striatum at decision points
van der Meer, M. A. A. (2009) · Frontiers in Integrative Neuroscience · doi:10.3389/neuro.07.001.2009 · Cited by 296 · see citing works
Dopamine enhances model-based over model-free choice behavior
Wunderlich, K., Smittenaar, P., & Dolan, R. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.042 · Cited by 294 · see citing works
Self-citationOstlund, S. B., & Balleine, B. W. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.1921-05.2005 · Cited by 291 · see citing works
Kimble, G. A., & Perlmuter, L. C. (1970) · Psychological Review · doi:10.1037/h0029782 · Cited by 279 · see citing works
Calculating Consequences: Brain Systems That Encode the Causal Effects of Actions
Tanaka, S. C., Balleine, B. W., & O'Doherty, J. P. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.1808-08.2008 · Cited by 268 · see citing works
The effect of the introduction of reward upon the maze performance of rats
Blodgett, H. C. (1929) · University of California Press eBooks · Cited by 248 · see citing works
Smittenaar, P., FitzGerald, T. H. B., Romei, V., Wright, N. D., & Dolan, R. J. (2013) · Neuron · doi:10.1016/j.neuron.2013.08.009 · Cited by 244 · see citing works
Self-citationAnimal Intelligence: Experimental Studies
Brown, W. M. (1912) · Nature · doi:10.1038/088306a0 · Cited by 230 · see citing works
Hierarchical reinforcement learning and decision making
Botvinick, M. (2012) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.05.008 · Cited by 230 · see citing works
Pavlovian conditioned stimulus effects upon instrumental choice behavior are reinforcer specific
Kruse, J. M., Overmier, J., Konz, W., & Rokke, E. (1983) · Learning and Motivation · doi:10.1016/0023-9690(83)90004-8 · Cited by 226 · see citing works
Contributions of the ventromedial prefrontal cortex to goal-directed action selection
O’Doherty, J. P. (2011) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2011.06290.x · Cited by 225 · see citing works
Dopaminergic control of the striatum for high-level cognition
Cools, R. (2011) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2011.04.002 · Cited by 221 · see citing works
Retrospective revaluation in sequential decision making: a tale of two systems
Gershman, S. J., Markman, A. B., & Otto, A. R. (2014) · Journal of Experimental Psychology General · doi:10.1037/a0030844 · Cited by 217 · see citing works
McDannald, M. A., Lucantonio, F., Burke, K. A., Niv, Y., & Schoenbaum, G. M. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5499-10.2011 · Cited by 215 · see citing works
Instructional control of reinforcement learning: A behavioral and neurocomputational investigation
Doll, B. B., Jacobs, W. J., Sanfey, A. G., & Frank, M. J. (2009) · Brain Research · doi:10.1016/j.brainres.2009.07.007 · Cited by 209 · see citing works
Mnemonic functions of the basal ganglia
White, N. M. (1997) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(97)80004-9 · Cited by 204 · see citing works
Camille, N., Tsuchida, A., & Fellows, L. K. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3164-11.2011 · Cited by 195 · see citing works
Reinforcement learning, conditioning, and the brain: Successes and challenges
Maia, T. V. (2009) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.9.4.343 · Cited by 184 · see citing works
Dopaminergic Genes Predict Individual Differences in Susceptibility to Confirmation Bias
Doll, B. B., Hutchison, K. E., & Frank, M. J. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.6486-10.2011 · Cited by 184 · see citing works
Neural Correlates of Forward Planning in a Spatial Decision Task in Humans
Simon, D. A., & Daw, N. D. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.4647-10.2011 · Cited by 181 · see citing works
Solway, A., & Botvinick, M. (2012) · Psychological Review · doi:10.1037/a0026435 · Cited by 180 · see citing works
Muenzinger, K. F. (1938) · The Pedagogical Seminary and Journal of Genetic Psychology · doi:10.1080/08856559.1938.10533799 · Cited by 178 · see citing works
(2007) · MPG.PuRe (Max Planck Society) · Cited by 169 · see citing works
Pezzulo, G., Rigoli, F., & Chersi, F. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00092 · Cited by 163 · see citing works
The Neural Basis of Following Advice
Biele, G., Rieskamp, J., Krugel, L. K., & Heekeren, H. R. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001089 · Cited by 157 · see citing works
Haruno, M., & Kawato, M. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.06.007 · Cited by 152 · see citing works
Signals in Human Striatum Are Appropriate for Policy Update Rather than Value Prediction
Li, J., & Daw, N. D. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.6316-10.2011 · Cited by 149 · see citing works
A critical review of latent learning and related experiments.
Thistlethwaite, D. L. (1951) · Psychological Bulletin · doi:10.1037/h0055171 · Cited by 143 · see citing works
Bidirectional modulation of goal-directed actions by prefrontal cortical dopamine
Hitchcott, P. K., Quinn, J. J., & Taylor, J. R. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm010 · Cited by 143 · see citing works
Acquisition of sodium by rats: Interaction of innate mechanisms and latent learning.
Krieckhaus, E. E., & Wolf, G. (1968) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0025547 · Cited by 138 · see citing works
An in vivo assay of synaptic function mediating human cognition
Moran, R. J., Symmonds, M., Stephan, K. E., Friston, K. J., & Dolan, R. J. (2011) · Current Biology · doi:10.1016/j.cub.2011.06.053 · Cited by 137 · see citing works
Self-citationGoal-oriented searching mediated by ventral hippocampus early in trial-and-error learning
Ruediger, S., Spirig, D., Donato, F., & Caroni, P. (2012) · Nature Neuroscience · doi:10.1038/nn.3224 · Cited by 135 · see citing works
Liljeholm, M., Tricomi, E., O'Doherty, J. P., & Balleine, B. W. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3354-10.2011 · Cited by 130 · see citing works
A simple test of the vicarious trial-and-error hypothesis of hippocampal function.
Hu, D., & Amsel, A. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.12.5506 · Cited by 119 · see citing works
Pavlovian Processes in the Motivational Control of Instrumental Performance
Dickinson, A., & Dawson, G. (1987) · Quarterly Journal of Experimental Psychology · doi:10.1080/14640748708402264 · Cited by 118 · see citing works
Habitual versus goal-directed action control in Parkinson disease
de Wit, S., Barker, R. A., Dickinson, A. D., & Cools, R. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2010.21514 · Cited by 116 · see citing works
Contingency Effects with Maintained Instrumental Reinforcement
Dickinson, A., & Charnock, D. J. K. (1985) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/14640748508401177 · Cited by 115 · see citing works
Sample-based learning and search with permanent and transient memories
Silver, D., Sutton, R. S., & Müller, M. (2008) · International Conference on Machine Learning · doi:10.1145/1390156.1390278 · Cited by 110 · see citing works
Reliance on habits at the expense of goal-directed control following dopamine precursor depletion
de Wit, S., Standing, H. R., DeVito, E. E., Robinson, O. J., Ridderinkhof, K. R., Robbins, T. W., & Sahakian, B. J. (2012) · Psychopharmacology · doi:10.1007/s00213-011-2563-2 · Cited by 105 · see citing works
How to set the switches on this thing
Dayan, P. (2012) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.05.011 · Cited by 99 · see citing works
Self-citationGoal-directed control and its antipodes
Dayan, P. (2009) · Neural Networks · doi:10.1016/j.neunet.2009.03.004 · Cited by 93 · see citing works
Self-citationJohnson, A. C., & Redish, A. D. (2005) · Neural Networks · doi:10.1016/j.neunet.2005.08.009 · Cited by 91 · see citing works
Evidence for model-based computations in the human amygdala during Pavlovian conditioning
Prévost, C., McNamee, D., Jessup, R. K., Bossaerts, P., & O'Doherty, J. P. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002918 · Cited by 79 · see citing works
Cortico‐basal ganglia mechanisms for overcoming innate, habitual and motivational behaviors
Isoda, M., & Hikosaka, O. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2011.07698.x · Cited by 76 · see citing works
Recent breakthroughs in basal ganglia research
Bézard, E. (2006) · Nova Science Publishers eBooks · Cited by 71 · see citing works
Learning, motivation, and emotion
Stevens, S. S., & Gallistel, C. R. (2002) · Medical Entomology and Zoology · Cited by 71 · see citing works
Action-specific value signals in reward-related regions of the human brain
FitzGerald, T. H. B., Friston, K. J., & Dolan, R. J. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.3254-12.2012 · Cited by 68 · see citing works
Self-citationBradfield, L. A., & Balleine, B. W. (2013) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0030941 · Cited by 57 · see citing works
Ostlund, S. B., & Maidment, N. (2012) · Neuropsychopharmacology · doi:10.1038/npp.2011.217 · Cited by 52 · see citing works
Wirsig‐Wiechmann, C. R., & Grill, H. J. (1982) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0077911 · Cited by 47 · see citing works
Disruption of endogenous opioid activity during instrumental learning enhances habit acquisition
Wassum, K. M., Cely, I. C., Maidment, N. T., & Balleine, B. W. (2009) · Neuroscience · doi:10.1016/j.neuroscience.2009.06.071 · Cited by 46 · see citing works
Actions, policies, values, and the basal ganglia
Daw, N. D., Niv, Y., & Dayan, P. (2006) · MPG.PuRe (Max Planck Society) · Cited by 42 · see citing works
Self-citationAction of L-Dopa in drug induced extrapyramidalism.
Yaryura-Tobias, J. A., Wolpert, A., Dana, L., et al. (1970) · PubMed · Cited by 41 · see citing works
Evidence for model-based action planning in a sequential finger movement task
Fermin, A., Yoshida, T., Ito, M., Yoshimoto, J., & Doya, K. (2010) · Journal of Motor Behavior · doi:10.1080/00222895.2010.526467 · Cited by 36 · see citing works
Using hippocampal-striatal loops for spatial navigation and goal-directed decision-making
Chersi, F., & Pezzulo, G. (2012) · Cognitive Processing · doi:10.1007/s10339-012-0475-7 · Cited by 33 · see citing works
Using optogenetics to study habits
Smith, K. S., & Graybiel, A. M. (2013) · Brain Research · doi:10.1016/j.brainres.2013.01.008 · Cited by 29 · see citing works
The Role of the Instrumental Contingency in the Motivational Control of Performance
Dickinson, A., & Dawson, G. (1987) · Quarterly Journal of Experimental Psychology · doi:10.1080/14640748708402253 · Cited by 28 · see citing works
Fellows, L. K. (2011) · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16001837 · Cited by 2,550 · see citing works
Neuroscience-Inspired Artificial Intelligence
Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017) · Neuron · doi:10.1016/j.neuron.2017.06.011 · Cited by 1,557 · see citing works
Wood, W., & Rünger, D. (2016) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033417 · Cited by 1,445 · see citing works
Computational psychiatry as a bridge from neuroscience to clinical applications
Huys, Q. J. M., Maia, T. V., & Frank, M. J. (2016) · Nature Neuroscience · doi:10.1038/nn.4238 · Cited by 1,002 · see citing works
The hippocampus as a predictive map
Stachenfeld, K. L., Botvinick, M. M., & Gershman, S. J. (2017) · Nature Neuroscience · doi:10.1038/nn.4650 · Cited by 1,000 · see citing works
Motivation and cognitive control: from behavior to neural mechanism
Botvinick, M., & Braver, T. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010814-015044 · Cited by 909 · see citing works
Lieder, F., & Griffiths, T. L. (2020) · Behavioral and Brain Sciences · doi:10.1017/s0140525x1900061x · Cited by 892 · see citing works
Emotion and the prefrontal cortex: an integrative review
Dixon, M. L., Thiruchselvam, R., Todd, R., & Christoff, K. (2017) · Psychological Bulletin · doi:10.1037/bul0000096 · Cited by 745 · see citing works
Active inference and epistemic value
Friston, K., Rigoli, F., Ognibene, D., Mathys, C., Fitzgerald, T., & Pezzulo, G. (2015) · Cognitive Neuroscience · doi:10.1080/17588928.2015.1020053 · Cited by 731 · see citing works
Friston, K., FitzGerald, T., Rigoli, F., Schwartenbeck, P., ODoherty, J., & Pezzulo, G. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.06.022 · Cited by 674 · see citing works
Active Inference, homeostatic regulation and adaptive behavioural control
Pezzulo, G., Rigoli, F., & Friston, K. (2015) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2015.09.001 · Cited by 650 · see citing works
“Further, evidence indicates that hormones linked to metabolic processes such as insulin (Woods et al., 1970) and ghrelin (Drazen et al., 2006) can be conditioned and initiate anticipatory allostatic processes.”
BackgroundDisorders of compulsivity: A common bias towards learning habits
Voon, V, Derbyshire, K., Rück, C., Irvine, M. A., Worbe, Y., Enander, J., Schreiber, L. R. N., Gillan, C., Fineberg, N. A., Sahakian, B. J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.44 · Cited by 643 · see citing works
Self-citationReinforcement learning, fast and slow
Botvinick, M., Ritter, S., Wang, J. X., Kurth-Nelson, Z., Blundell, C., & Hassabis, D. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.02.006 · Cited by 667 · see citing works
Characterizing a psychiatric symptom dimension related to deficits in goal-directed control
Gillan, C. M., Kosinski, M., Whelan, R., Phelps, E. A., & Daw, N. D. (2016) · eLife · doi:10.7554/elife.11305 · Cited by 586 · see citing works
A fronto–striato–subthalamic–pallidal network for goal-directed and habitual inhibition
Jahanshahi, M., Obeso, I., Rothwell, J. C., & Obeso, J. A. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn4038 · Cited by 521 · see citing works
Obsessive-compulsive disorder: Puzzles and prospects
Robbins, T. W., Vaghi, M. M., & Banca, P. (2019) · Neuron · doi:10.1016/j.neuron.2019.01.046 · Cited by 510 · see citing works
Reinforcement learning and episodic memory in humans and animals: an integrative framework
Gershman, S. J., & Daw, N. D. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033625 · Cited by 446 · see citing works
If deep learning is the answer, what is the question?
Saxe, A., Nelli, S., & Summerfield, C. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-00395-8 · Cited by 397 · see citing works
Foster, D. J. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031538 · Cited by 375 · see citing works
Goal-directed learning and obsessive-compulsive disorder
Gillan, C. M., & Robbins, T. W. (2014) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2013.0475 · Cited by 348 · see citing works
Kool, W., & Botvinick, M. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0401-9 · Cited by 288 · see citing works
Striatal circuits, habits, and implications for obsessive-compulsive disorder
Burguière, E., Monteiro, P., Mallet, L., Feng, G., & Graybiel, A. M. (2015) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.08.008 · Cited by 286 · see citing works
Model-based learning protects against forming habits
Gillan, C. M., Otto, A. R., Phelps, E. A., & Daw, N. D. (2015) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-015-0347-6 · Cited by 283 · see citing works
The role of habit in compulsivity
Gillan, C. M., Robbins, T. W., Sahakian, B. J., van den Heuvel, O. A., & van Wingen, G. (2016) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.12.033 · Cited by 292 · see citing works
Deep reinforcement learning and its neuroscientific implications
Botvinick, M., Wang, J. X., Dabney, W., Miller, K. J., & Kurth-Nelson, Z. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.014 · Cited by 269 · see citing works
Miller, K. J., Shenhav, A., & Ludvig, E. A. (2019) · Psychological Review · doi:10.1037/rev0000120 · Cited by 280 · see citing works
When Does Model-Based Control Pay Off?
Kool, W., Cushman, F. A., & Gershman, S. J. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005090 · Cited by 211 · see citing works
Deserno, L., Huys, Q. J. M., Boehme, R., Buchert, R., Heinze, H.-J., Grace, A. A., Dolan, R. J., Heinz, A., & Schlagenhauf, F. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1417219112 · Cited by 233 · see citing works
Self-citationReinforcement learning in depression: a review of computational research
Chen, C., Takahashi, T., Nakagawa, S., Inoue, T., & Kusumi, I. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.05.005 · Cited by 233 · see citing works
Internally generated sequences in learning and executing goal-directed behavior
Pezzulo, G., van der Meer, M. A. A., Lansink, C. S., & Pennartz, C. M. A. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.06.011 · Cited by 217 · see citing works
Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
Butlin, P., Long, R., Elmoznino, E., Bengio, Y., Birch, J., Constant, A., Deane, G., Fleming, S. M., Frith, C., Ji, X., et al. (2023) · arXiv · doi:10.48550/arxiv.2308.08708 · Cited by 196 · see citing works
The Sense of Confidence during Probabilistic Learning: A Normative Account
Meyniel, F., Schlunegger, D., & Dehaene, S. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004305 · Cited by 163 · see citing works
A taxonomy of technology design features that promote potentially addictive online behaviours
Flayelle, M., Brevers, D., King, D. L., Maurage, P., Perales, J. C., & Billieux, J. (2023) · Nature Reviews Psychology · doi:10.1038/s44159-023-00153-4 · Cited by 195 · see citing works
The successor representation: Its computational logic and neural substrates
Gershman, S. J. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.0151-18.2018 · Cited by 191 · see citing works
The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action Selection
Akam, T., Rodrigues-Vaz, I., Marcelo, I., Zhang, X., Pereira, M., Oliveira, R. F., Dayan, P., & Costa, R. M. (2021) · Neuron · doi:10.1016/j.neuron.2020.10.013 · Cited by 170 · see citing works
Self-citationA trans-diagnostic perspective on obsessive-compulsive disorder
Gillan, C. M., Fineberg, N. A., & Robbins, T. W. (2017) · Psychological Medicine · doi:10.1017/s0033291716002786 · Cited by 158 · see citing works
Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network
Balaguer, J., Spiers, H., Hassabis, D., & Summerfield, C. (2016) · Neuron · doi:10.1016/j.neuron.2016.03.037 · Cited by 163 · see citing works
Enhanced habit formation in Gilles de la Tourette syndrome
Delorme, C., Salvador, A., Valabrègue, R., Roze, E., Palminteri, S., Vidailhet, M., de Wit, S., Robbins, T., Hartmann, A., & Worbe, Y. (2016) · Brain · doi:10.1093/brain/awv307 · Cited by 154 · see citing works
Humans primarily use model-based inference in the two-stage task
Feher da Silva, C., & Hare, T. A. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0905-y · Cited by 153 · see citing works
Formalizing Neurath’s ship: approximate algorithms for online causal learning.
Bramley, N. R., Dayan, P., Griffiths, T. L., & Lagnado, D. A. (2017) · Psychological Review · doi:10.1037/rev0000061 · Cited by 136 · see citing works
Self-citationDopamine, reward learning, and active inference
FitzGerald, T. H. B., Dolan, R. J., & Friston, K. (2015) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2015.00136 · Cited by 112 · see citing works
Self-citationReasoning supports utilitarian resolutions to moral dilemmas across diverse measures.
Patil, I., Zucchelli, M. M., Kool, W., Campbell, S., Fornasier, F., Calò, M., Silani, G., Cikara, M., & Cushman, F. (2021) · Journal of Personality and Social Psychology · doi:10.1037/pspp0000281 · Cited by 133 · see citing works
Model averaging, optimal inference, and habit formation
FitzGerald, T. H. B., Dolan, R. J., & Friston, K. J. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00457 · Cited by 121 · see citing works
Self-citationThe Neurocognitive Bases of Human Volition.
Haggard, P. (2019) · Annual Review of Psychology · doi:10.1146/annurev-psych-010418-103348 · Cited by 126 · see citing works
Learning action-oriented models through active inference
Tschantz, A., Seth, A. K., & Buckley, C. L. (2020) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1007805 · Cited by 121 · see citing works
Habitual versus goal-directed action control in Parkinson disease
de Wit, S., Barker, R. A., Dickinson, A. D., & Cools, R. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2010.21514 · Cited by 116 · see citing works
Predictive maps in rats and humans for spatial navigation
de Cothi, W., Nyberg, N., Griesbauer, E.-M., Ghanamé, C., Zisch, F., Lefort, J. M., Fletcher, L., Newton, C., Renaudineau, S., Bendor, D., et al. (2022) · Current Biology · doi:10.1016/j.cub.2022.06.090 · Cited by 109 · see citing works
Incentives Boost Model-Based Control Across a Range of Severity on Several Psychiatric Constructs
Patzelt, E. H., Kool, W., Millner, A. J., & Gershman, S. J. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.06.018 · Cited by 94 · see citing works
Reward revaluation biases hippocampal replay content away from the preferred outcome
Carey, A. A., Tanaka, Y., & van der Meer, M. A. A. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0464-6 · Cited by 106 · see citing works
Using fMRI to study reward processing in humans: past, present, and future
Wang, K. S., Smith, D. V., & Delgado, M. R. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00333.2015 · Cited by 105 · see citing works
Learning to lose control: A process-based account of behavioral addiction
Perales, J. C., King, D. L., Navas, J. F., Schimmenti, A., Sescousse, G., Starcevic, V., van Holst, R. J., & Billieux, J. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.12.025 · Cited by 101 · see citing works
Regulation of habit formation in the dorsal striatum
Malvaez, M., & Wassum, K. M. (2018) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.11.005 · Cited by 96 · see citing works
Hervig, M. E., Fiddian, L., Piilgaard, L., Božič, T., Blanco-Pozo, M., Knudsen, C., Olesen, S. F., Alsiö, J., & Robbins, T. W. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz144 · Cited by 65 · see citing works
P300 amplitude variations, prior probabilities, and likelihoods: a Bayesian ERP study
Kopp, B., Seer, C., Lange, F., Kluytmans, A., Kolossa, A., Fingscheidt, T., & Hoijtink, H. (2016) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-016-0442-3 · Cited by 60 · see citing works
Striatal dopamine, reward, and decision making in schizophrenia
Deserno, L., Schlagenhauf, F., & Heinz, A. (2016) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2016.18.1/ldeserno · Cited by 58 · see citing works
Habits are negatively regulated by histone deacetylase 3 in the dorsal striatum
Malvaez, M., Greenfield, V. Y., Matheos, D. P., Angelillis, N. A., Murphy, M. D., Kennedy, P. J., Wood, M. A., & Wassum, K. M. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.01.025 · Cited by 56 · see citing works
Loss of Adenylyl Cyclase Type-5 in the Dorsal Striatum Produces Autistic-Like Behaviors
Kim, H., Lee, Y., Park, J.-Y., Kim, J.-E., Kim, T.-K., Choi, J., Lee, J.-E., Lee, E.-H., Kim, D., Kim, K.-S., et al. (2017) · Molecular Neurobiology · doi:10.1007/s12035-016-0256-x · Cited by 50 · see citing works
Dong, C., Yang, Q., Liang, J., Seger, C. A., Han, H., Ning, Y., Chen, Q., & Peng, Z. (2020) · Psychological Medicine · doi:10.1017/s0033291719001429 · Cited by 43 · see citing works
Duan, L. Y., Horst, N. K., Cranmore, S. A. W., Horiguchi, N., Cardinal, R. N., Roberts, A. C., & Robbins, T. W. (2021) · Neuron · doi:10.1016/j.neuron.2021.06.003 · Cited by 41 · see citing works
The role of habits and motivation in human drug addiction: a reflection
Sjoerds, Z., Luigjes, J., van den Brink, W., Denys, D., & Yücel, M. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00008 · Cited by 40 · see citing works
Sebold, M., Schad, D. J., Nebe, S., Garbusow, M., Jünger, E., Kroemer, N. B., Kathmann, N., Zimmermann, U. S., Smolka, M. N., Rapp, M. A., et al. (2016) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00945 · Cited by 41 · see citing works
Nicotinic alteration of decision-making
Naudé, J., Dongelmans, M., & Faure, P. (2015) · Neuropharmacology · doi:10.1016/j.neuropharm.2014.11.021 · Cited by 39 · see citing works
Leveraging cognitive neuroscience for making and breaking real-world habits
Buabang, E. K., Donegan, K. R., Rafei, P., & Gillan, C. M. (2025) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.10.006 · Cited by 34 · see citing works
Computational approaches to schizophrenia: A perspective on negative symptoms
Deserno, L., Heinz, A., & Schlagenhauf, F. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2016.10.004 · Cited by 31 · see citing works
Denervaud, S., Knebel, J., Immordino‐Yang, M. H., & Hagmann, P. (2020) · Mind, Brain, and Education · doi:10.1111/mbe.12233 · Cited by 29 · see citing works
Model-based learning and individual differences in depression: The moderating role of stress
Heller, A. S., Ezie, C. E. C., Otto, A. R., & Timpano, K. R. (2018) · Behaviour Research and Therapy · doi:10.1016/j.brat.2018.09.007 · Cited by 29 · see citing works
Friedel, E. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00302 · Cited by 29 · see citing works
Recent developments in the habit hypothesis of OCD and compulsive disorders
Gillan, C. M. (2021) · Current Topics in Behavioral Neurosciences · doi:10.1007/7854_2020_199 · Cited by 27 · see citing works
Negative symptoms, striatal dopamine and model-free reward decision-making in schizophrenia
Brandl, F., Knolle, F., Avram, M., Leucht, C., Yakushev, I., Priller, J., Leucht, S., Ziegler, S., Wunderlich, K., & Sorg, C. (2023) · Brain · doi:10.1093/brain/awac268 · Cited by 24 · see citing works
Reinforcement learning and artificial agency
Butlin, P. (2024) · Mind & Language · doi:10.1111/mila.12458 · Cited by 40 · see citing works
Imbalance between the caudate and putamen connectivity in obsessive–compulsive disorder
Peng, Z., He, T., Ren, P., Jin, L., Yang, Q., Xu, C., Wen, R., Chen, J., Wei, Z., Verguts, T., et al. (2022) · NeuroImage: Clinical · doi:10.1016/j.nicl.2022.103083 · Cited by 20 · see citing works
Clinical neuroscience of addiction: what clinical psychologists need to know and why
Ray, L. A., & Grodin, E. N. (2021) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-081219-114309 · Cited by 18 · see citing works
Predictive Representations: Building Blocks of Intelligence
Carvalho, W., Tomov, M. S., de Cothi, W., Barry, C., & Gershman, S. J. (2024) · Neural Computation · doi:10.1162/neco_a_01705 · Cited by 15 · see citing works
Children’s automatic evaluation of self‐generated actions is different from adults
Denervaud, S., Hess, A., Sander, D., & Pourtois, G. (2021) · Developmental Science · doi:10.1111/desc.13045 · Cited by 11 · see citing works
Luna, R., Vadillo, M. A., & Luque, D. (2023) · Cortex · doi:10.1016/j.cortex.2023.06.009 · Cited by 3 · see citing works
Addressing altered anticipation as a transdiagnostic target through computational psychiatry
Sepúlveda, P., Aitsahalia, I., Kumar, K., Atkin, T., & Iigaya, K. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.02.014 · Cited by 3 · see citing works
Asaoka, N., Pagano, D., & Hayashi, Y. (2026) · Nature Communications · doi:10.1038/s41467-026-75706-1
“Habit formation has been conceptualized as a shift in decision-making — from a fl exible, motivation-dependent goal-directed strategy to a more rigid, automatic one 2,5,7 .”
- Authors
- Dolan, R. J., & Dayan, P.
- Affiliations
- Gatsby Computational Neuroscience Unit (GB)
- ORCID
- Dayan, Peter
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Issue
- 2
- Pages
- 312-325
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC3807793
- OpenAlex
- W1988699227
- Semantic Scholar
- d5e9f40771f7006f4901e437e6c54bfdf4f453e7
- Cited by
- 977
- References
- 173
- Citations by year
- 2026: 54 · 2025: 87 · 2024: 78 · 2023: 69 · 2022: 83 · 2021: 94 · 2020: 98 · 2019: 96 · 2018: 81 · 2017: 79 · 2016: 66 · 2015: 52 · 2014: 39 · 2013: 1
- FWCI
- 4.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Neuron (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (091593, 098362, 098362/Z/12/Z, 091593/Z/10/Z)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- goal-directed behavior, habitual behavior, decision-making, choice, model-based decision making
- MeSH terms
- Animals, Brain, Conditioning, Operant, Goals, Habits, Humans, Models, Psychological
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review