Cited by 203Neural and Behavioral Psychology StudiesNeurotransmitter Receptor Influence on BehaviorDecision-Making and Behavioral Economics

The DOI matches its Crossref record; 90 of the 91 references it cites were found in a registry or an index; none of the 65 sources its claims cite is checked for support yet.

Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development

Open access

Hauser, Tobias U., Iannaccone, Reto, Walitza, Susanne, Brandeis, Daniel, Brem, Silvia·2015·NeuroImage

DOI 10.1016/j.neuroimage.2014.09.018PMC PMC4330550

Open this paper in CoChat — free account

Abstract

Adolescence is associated with quickly changing environmental demands which require excellent adaptive skills and high cognitive flexibility. Feedback-guided adaptive learning and cognitive flexibility are driven by reward prediction error (RPE) signals, which indicate the accuracy of expectations and can be estimated using computational models. Despite the importance of cognitive flexibility during adolescence, only little is known about how RPE processing in cognitive flexibility deviates between adolescence and adulthood. In this study, we investigated the developmental aspects of cognitive flexibility by means of computational models and functional magnetic resonance imaging (fMRI). We compared the neural and behavioral correlates of cognitive flexibility in healthy adolescents (12-16years) to adults performing a probabilistic reversal learning task. Using a modified risk-sensitive reinforcement learning model, we found that adolescents learned faster from negative RPEs than adults. The fMRI analysis revealed that within the RPE network, the adolescents had a significantly altered RPE-response in the anterior insula. This effect seemed to be mainly driven by increased responses to negative prediction errors. In summary, our findings indicate that decision making in adolescence goes beyond merely increased reward-seeking behavior and provides a developmental perspective to the behavioral and neural mechanisms underlying cognitive flexibility in the context of reinforcement learning.

AI snapshot

Written from the paper’s full text.

TL;DR

Adolescents (12–16 years) and adults performed a probabilistic reversal learning task during fMRI; computational modeling showed adolescents learned faster from negative reward prediction errors (RPEs) than adults. This behavioral difference was accompanied by altered RPE-related anterior insula responses, mainly increased responses to negative RPEs in adolescents.

Key findings

Overall task performance did not differ between groups: adults made 73.83% ± 4.4% correct responses and adolescents 73.38% ± 4.6% (t(34) = .296, p = .769); reversals also did not differ (adults 23.35 ± 8.80, adolescents 26.11 ± 8.31; t(34) = −.965, p = .341).
The risk-sensitive model with anticorrelated valuation (RSAV) outperformed the other models, and adolescents had a significantly increased learning rate for negative RPEs in chosen objects (αc−: adults .49 ± .05, adolescents .69 ± .05; t(34) = −2.816, p = .04, corrected); other parameters did not differ significantly.
fMRI showed a significant group difference in the right anterior insula (peak MNI x = 33, y = 18, z = 3; t = 4.60, k = 33), with increased activation for decreasing RPEs in adolescents.
Exploratory binning of RPEs showed the anterior insula difference was driven by negative RPEs (adolescents vs adults: t(34) = −4.08, p < .001, corrected), while neutral (p = .734) and positive (p = .142) RPEs did not differ significantly.

Methods

Thirty-seven subjects participated; one adolescent was excluded for excessive movement (> 2.5 mm scan-to-scan motion). Final groups were 19 adolescents aged 12–16 years (14.7 ± 1.3, 10 females) and 17 adults aged 20–29 years (25.6 ± 2.4, 10 females).
Participants performed a probabilistic reversal learning task during fMRI: two runs of 60 trials each, plus 20 null trials per run; one stimulus was correct with 80% reward probability and the other with 20%, with reversals after at least 6 correct choices (maximum 10, randomly determined).
Three reinforcement learning models were compared (Rescorla–Wagner, risk-sensitive, and RSAV); parameters were estimated by maximum log-likelihood using a genetic search algorithm, compared with AIC and Bayesian model selection. fMRI analysis used SPM8, with model-derived RPEs entered as a parametric modulator at feedback; group comparisons were restricted to RPE-processing areas and used p < .05 cluster-extent FWE (voxel height p < .001).

Limitations

The paper states that the adolescent group had a relatively large age range (12–16 years), so the design cannot detect differences that may occur only early or late in adolescence.
The paper states that the relatively small sample size prevented analysis of age-related changes within adolescence; larger samples and/or longitudinal designs are needed.
Evident from the text: the study is cross-sectional, and for fMRI the authors estimated one single set of canonical model parameters for all participants rather than individual parameters, so neural analyses were not designed to model individual behavioral differences.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2014.09.018

Cites

90 of 90 references verified0 citation errors · 0 not checkable

Statistics

19 tests recomputed · 0 with the reported and recomputed p on opposite sides of .05

Claims the paper makes

0 of 65 cited sources checked · 0 supported · 0 flagged

A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The fMRI analysis revealed that within the RPE network, the adolescents had a significantly altered RPE-response in the anterior insula.”
- Also stated in: § fMRI analysis · plain
  “We found one significant cluster in the right aIns (peak MNI x = 33, y = 18, z = 3; t = 4.60, k = 33, Fig. 3B) which showed increased activation for decreasing RPEs in adolescents.”
- Also stated in: § Discussion · plain
  “In the group comparison, we found a significantly different activation in the aIns.”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Abstract
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using a modified risk-sensitive reinforcement learning model, we found that adolescents learned faster from negative RPEs than adults.”
- Also stated in: § Model comparison and parameters · plain
  “Post-hoc t-tests revealed that adolescents had a significantly increased learning rate for negative RPEs in chosen objects (αc−: adults: .49 ± .05, adolescents: .69 ± .05, t(34) = − 2.816, p = .04, multiple comparison corrected, Fig. 2)”
- Also stated in: § Discussion · plain
  “By using an advanced reinforcement learning model, we found that adolescents learn more quickly from negative RPEs than adults.”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Abstract
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- Rests on an assumption: The adolescent and adult groups did not differ on unmeasured variables that could confound the comparison of RPE processing.

Show all 42 claims

It may state two separate claims as one. 9
The quote only partly states this claim. 1
Probably not a substantial claim. 26

None of the sources cited for this claim have been checked yet.
In the paper
“To test cognitive flexibility, probabilistic reversal learning tasks have often been used (e.g., Adleman et al., 2011; Britton et al., 2010; Clarke et al., 2004; Klanker et al., 2013; van der Plasse and Feenstra, 2008; Xue et al., 2013).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Introduction
What the sources say
- Not checked yetcites Adleman et al., 2011 source
- Not checked yetcites Britton et al., 2010 source
- Not checked yetcites Clarke et al., 2004 source
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim.
In the paper
“In cognitive neuroscience and neuropsychology, cognitive flexibility has mainly been operationalized by sudden and implicit shifts in reward contingencies that have to be detected based on external feedback (Scott, 1962).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Introduction
What the sources say
- Not checked yetcites Scott, 1962 source
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“While Cohen et al. (2010) found differential activations between adolescents and adults in striatal areas, van den Bos et al. (2012) were not able to replicate that finding, but found differences in the connectivity between the ventromedial prefrontal cortex and the ventral striatum.”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Introduction
What the sources say
- Not checked yetcites Cohen et al., 2010 source
- Not checked yetcites van den Bos et al., 2012 source
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Previous studies found developmental effects during tasks of cognitive flexibility (e.g., Christakou et al., 2009; Rubia et al., 2006; Smith et al., 2011) and in other cognitive domains (Christakou et al., 2011; Jarcho et al., 2012; Keulers et al., 2011; Masten et al., 2009; Somerville et al., 2011; Van Leijenhorst et al., 2010).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Christakou et al., 2009 source
- Not checked yetcites Rubia et al., 2006 source
- Not checked yetcites Smith et al., 2011 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The increased insular activity (esp. to negative RPEs) might indicate that adolescents weight the emotional information more strongly which then leads to a faster adaptation from negative feedbacks.”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
Strength:hedged· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- The authors state this as an assumption: The dorsomedial prefrontal cortex is mainly involved in processing cognitive aspects, whereas the anterior insula processes visceral and emotional information.
None of the sources cited for this claim have been checked yet.
In the paper
“Unsurprisingly, the aIns has been ascribed to a wide variety of functions from processing visceral and emotional information (Critchley, 2005) to controlling attention and task demands (Dosenbach et al., 2006, 2007; Nelson et al., 2010).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Critchley, 2005 source
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites Dosenbach et al., 2006, 2007
- Not checked yetcites Nelson et al., 2010 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“This is also in line with the assumption that the aIns is involved when a feedback is processed consciously (Nelson et al., 2010; Wheeler et al., 2008).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Nelson et al., 2010 source
- Not checked yetcites Wheeler et al., 2008 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“It is well known that aIns activity often coincides with activation in the dmPFC (cf. Hauser et al., 2014a, 2014b; Nelson et al., 2010; Seymour et al., 2004).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Hauser et al., 2014a, 2014b
- Not checked yetcites Nelson et al., 2010 source
- Not checked yetcites Seymour et al., 2004 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Adolescents are known to be more sensitive to the presence of peers (Chein et al., 2011) and peer rejection (Masten et al., 2009), and show a markedly increased prevalence in psychiatric disorders, such as anxiety, depression or substance abuse (Kessler et al., 2005, 2007).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Chein et al., 2011 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The aIns is a central hub in the brain and is one of the most commonly activated areas in human neuroimaging studies (Nelson et al., 2010).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Nelson et al., 2010 source
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Moreover, the aIns has been associated with processing information about risk (Burke and Tobler, 2011; Ishii et al., 2012; Paulus et al., 2003; Preuschoff et al., 2008).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Burke and Tobler, 2011
- Not checked yetcites Ishii et al., 2012 source
- Not checked yetcites Paulus et al., 2003 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“We additionally entered several regressors-of-no-interest into the GLM to improve model validity: choice values (value of chosen object) as parametric modulator at cue presentation, realignment-derived movement parameters, scan-to-scan movements greater than 1 mm, and cardiac pulsations (http://www.translationalneuromodeling.org/tapas/; Glover et al., 2000; Kasper et al., 2009).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Materials and methods > fMRI data analysis
What the sources say
- Not checked yetcites Glover et al., 2000 source
- Not checked yetcites Kasper et al., 2009
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Given that we have previously shown that reinforcement learning models with anticorrelated valuation fitted this task better than a standard Rescorla–Wagner model (Hauser et al., 2014a), we evaluated the risk-sensitive model with an anticorrelated valuation (RSAV) extension as a third model.”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Materials and methods > Reinforcement learning models
What the sources say
- Not checked yetcites Hauser et al., 2014a
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim.
In the paper
“it has a high predictive value for task switching in a similar cognitive flexibility task (Hampton and O'Doherty, 2007).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Hampton and O'Doherty, 2007
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Adolescents are known to be more sensitive to the presence of peers (Chein et al., 2011) and peer rejection (Masten et al., 2009), and show a markedly increased prevalence in psychiatric disorders, such as anxiety, depression or substance abuse (Kessler et al., 2005, 2007).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Masten et al., 2009 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“It is activated in a wide variety of cognitive and emotional tasks (Dosenbach et al., 2006) and forms the important salience network in resting state literature (Menon and Uddin, 2010).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Dosenbach et al., 2006 source
- Not checked yetcites Menon and Uddin, 2010 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“It has also been associated with depression, anxiety or substance abuse (for reviews cf. Craig, 2009; Naqvi and Bechara, 2009).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Craig, 2009 source
- Not checked yetcites Naqvi and Bechara, 2009 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“It is strongly involved in empathy-related processes (Singer et al., 2004, 2009) and social rejection (Masten et al., 2009).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not checked yetcites Masten et al., 2009 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“It is strongly involved in empathy-related processes (Singer et al., 2004, 2009) and social rejection (Masten et al., 2009).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites Singer et al., 2004, 2009
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Adolescents are known to be more sensitive to the presence of peers (Chein et al., 2011) and peer rejection (Masten et al., 2009), and show a markedly increased prevalence in psychiatric disorders, such as anxiety, depression or substance abuse (Kessler et al., 2005, 2007).”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites Kessler et al., 2005, 2007
Strength:boosted· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, an increased insular sensitivity to negative RPEs might not only affect decision making, but also other areas in which adolescence reflects a unique period, such as in social interactions or psychiatric disorders.”
§ Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development > Discussion
Strength:hedged· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- The authors state this as an assumption: Reward prediction error-like signals reflect a general neural update signal in a variety of domains, not only in decision making.

32 of 32

The paper relies on this without support.
The adolescent and adult groups did not differ on unmeasured variables that could confound the comparison of RPE processing.
“The adolescent group consisted of 19 participants between 12 and 16 years (14.7 y ± 1.3, 10 females). The adult group consisted of 17 participants between 20 and 29 years (25.6 y ± 2.4, 10 females).”
The authors state this as an assumption.
The dorsomedial prefrontal cortex is mainly involved in processing cognitive aspects, whereas the anterior insula processes visceral and emotional information.
“However, it is assumed that the dmPFC is mainly involved in processing cognitive aspects, whereas the aIns rather processes visceral and emotional information (Nelson et al., 2010).”
The authors state this as an assumption.
Reward prediction error-like signals reflect a general neural update signal in a variety of domains, not only in decision making.
“RPE-like signals are assumed to reflect a general neural update signal in a variety of domains, not only in decision making (Friston, 2010; Iglesias et al., 2013).”

3 of 3

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?

Statistics that don’t add up

Each reported p-value recomputed from its test statistic and degrees of freedom.

Inconsistent p-value: F(2,34) = 4.60, p = .013
Minor
The paper reports p = .013 here; recomputing from the test statistic and its degrees of freedom gives p = .017. The check cannot tell whether the statistic or the p-value is the misprint.
Reported p = .013 · recomputed p = .017

1 of 1

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

Doesn’t add upF(2, 34) = 4.6reported p = .013 · recomputed p = .017
“F(2,34) = 4.60, p = .013”
Consistentt(34) = 0.496reported p = .623 · recomputed p = .623
“t(34) = .496, p = .623”
Consistentt(34) = 0.64reported p = .527 · recomputed p = .526
“t(34) = .64, p = .527”
Consistentt(34) = 0.7reported p = .49 · recomputed p = .489
“t(34) = .70, p = .490”
Consistentt(34) = 0.296reported p = .769 · recomputed p = .769
“t(34) = .296, p = .769”
Consistentt(34) = -0.965reported p = .341 · recomputed p = .341
“t(34) = − .965, p = .341”
Consistentt(34) = 1.71reported p = .097 · recomputed p = .096
“t(34) = 1.71, p = .097”
ConsistentF(4, 136) = 73.45reported p < .001 · recomputed p < .001
“F(4,136) = 73.45, p < .001”
ConsistentF(4, 136) = 2.851reported p = .026 · recomputed p = .026
“F(4,136) = 2.851, p = .026”
Consistentt(34) = -2.816reported p = .04 · recomputed p = .008
“t(34) = − 2.816, p = .04”
The paper states a correction for multiple tests
Consistentt(34) = -1.336reported p = .95 · recomputed p = .190
“t(34) = − 1.336, p = .95”
The paper states a correction for multiple tests
Consistentt(34) = -0.581reported p = 1 · recomputed p = .565
“t(34) = − .581, p = 1.00”
The paper states a correction for multiple tests
Consistentt(34) = -0.636reported p = 1 · recomputed p = .529
“t(34) = − .636, p = 1.00”
The paper states a correction for multiple tests
Consistentt(34) = 1.595reported p = .6 · recomputed p = .120
“t(34) = 1.595, p = .60”
The paper states a correction for multiple tests
ConsistentF(2, 34) = 40.37reported p < .001 · recomputed p < .001
“F(2,34) = 40.37, p < .001”
ConsistentF(1, 34) = 1.77reported p = .193 · recomputed p = .192
“F(1,34) = 1.77, p = .193”
Consistentt(34) = -4.08reported p < .001 · recomputed p < .001
“t(34) = − 4.08, p < .001”
Consistentt(34) = 1.18reported p = .734 · recomputed p = .246
“t(34) = 1.18, p = .734”
The paper states a correction for multiple tests
Consistentt(34) = 2.06reported p = .142 · recomputed p = .047
“t(34) = 2.06, p = .142”
The paper states a correction for multiple tests

19 of 19

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Incorrect denominator degrees of freedom for the RPE-bin ANOVA
Minor
With 36 participants in two groups and three RPE bins, the within-subject RPE effect and group-by-RPE interaction should have denominator degrees of freedom of 2 × (36 − 2) = 68, not 34. The paper reports 34 for both tests.
Reported 34 · recomputed 68

1 of 1

Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,178
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
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,268
Lifetime Prevalence and Age-of-Onset Distributions of DSM-IV Disorders in the National Comorbidity Survey Replication
Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.6.593 · Cited by 20,391
Information Theory and an Extension of the Maximum Likelihood Principle
Akaike, H. (1998) · Springer series in statistics · doi:10.1007/978-1-4612-1694-0_15 · Cited by 18,636
Genetic Algorithms in Search, Optimization and Machine Learning
Goldberg, D. E., & Robson, D. (1988) · Cited by 18,391
Genetic Algorithms
Goldberg, D. E., & Shakespeare, W. (2002) · Cited by 16,088
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
The free-energy principle: a unified brain theory?
Friston, K. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2787 · Cited by 8,120 · cited 1×
“RPE-like signals are assumed to reflect a general neural update signal in a variety of domains, not only in decision making (Friston, 2010; Iglesias et al., 2013).”
Background
A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement
Rescorla, R. A. (1972) · Medical Entomology and Zoology · Cited by 7,268

Flagged first, then by citations

Show all 91 references

1 of the 91 references couldn’t be matched to a known paper.

Sorted by citations

Items 201–201 of 201

Reward Prediction Errors Drive Reinforcement Learning and Recognition Memory: Gender Differences in Methamphetamine Abusers
Liu, Y., Wang, D., Wang, L., Wang, S., Chen, Z., Wang, T., Jin, S., Zhou, Q., & Yang, L. (2026) · Brain and Behavior · doi:10.1002/brb3.71630

Authors: Hauser, T. U., Iannaccone, R., Walitza, S., Brandeis, D., & Brem, S.
Affiliations: Wellcome Centre for Human Neuroimaging (GB)
University of Zurich (CH)
Corresponding author: Hauser, Tobias U.
ORCID: Hauser, Tobias U.
Walitza, Susanne
Brem, Silvia
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2015-01
Volume: 104
Pages: 347-354
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2014.09.018
PMC: PMC4330550
OpenAlex: W2088333881
Semantic Scholar: 8130c15ff61aa1abdd0d9c20356489a71c12290d
Cited by: 203
References: 91
Citations by year: 2026: 11 · 2025: 25 · 2024: 21 · 2023: 21 · 2022: 19 · 2021: 24 · 2020: 22 · 2019: 14 · 2018: 15 · 2017: 12 · 2016: 12 · 2015: 7
FWCI: 5.72
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
creativecommons.org/licenses/by/3.0/ (vor)
Locations: NeuroImage (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
UCL Discovery (University College London) (submittedVersion)
Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by-nc-sa)
Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
ETH Zürich Research Collection
Zurich Open Repository and Archive (University of Zurich)
Funders: Swiss National Science Foundation (320030_130237, 151641)
Hartmann Müller Foundation (1460)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Keywords: cognitive flexibility, adolescence, reward prediction error, adaptive decision-making, probabilistic reversal learning, risk-sensitive reinforcement learning, anterior insula, neural development, computational modeling
MeSH terms: Adolescent, Brain, Brain Mapping, Child, Cognition, Decision Making, Female, Humans, Learning, Magnetic Resonance Imaging, Male, Reward

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.

A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

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

Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development

Abstract

Overview

AI snapshot

TL;DR

Key findings

Methods

Limitations

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Statistics that don’t add up

Statistics recomputed

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks