The DOI matches its Crossref record; 69 of the 74 references it cites were found in a registry or an index.
Representation of Accumulating Evidence for a Decision in Two Parietal Areas
Open accessAbstract
Decisions are often made by accumulating evidence for and against the alternatives. The momentary evidence represented by sensory neurons is accumulated by downstream structures to form a decision variable, linking the evolving decision to the formation of a motor plan. When decisions are communicated by eye movements, neurons in the lateral intraparietal area (LIP) represent the accumulation of evidence bearing on the potential targets for saccades. We now show that reach-related neurons from the medial intraparietal area (MIP) exhibit a gradual modulation of their firing rates consistent with the representation of an evolving decision variable. When decisions were communicated by saccades instead of reaches, decision-related activity was attenuated in MIP, whereas LIP neurons were active while monkeys communicated decisions by saccades or reaches. Thus, for decisions communicated by a hand movement, a parallel flow of sensory information is directed to parietal areas MIP and LIP during decision formation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A DV in standard drift-diffusion model (DDM) (3–5, 7) (Fig. 4A) accumulates sensory evidence (drift), accompanied by stochastic internal or sensory noise (diffusion) that, when reaches either upper (correct trials) or lower (error trials) bound, produces a decision at RT.”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“An important diagnostic signature of perceptual decision-making is the gradual accumulation of noise (5, 51) expected for most accumulation-to-bound decision models.”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“indicating accumulation of stochastic trial-by-trial diffusion noise (5, 51).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“We show that this variable is consistent with models of gradual accumulation of noisy sensory evidence to a decision bound.”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“Here, close to the top of the cortical hierarchy, internal decision variables (DV) are accumulated in a form of ramping neural activity (3–6) that is transformed into a decision when a decision boundary is reached (7).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“In what follows we argue the neural activity ramp during epoch 4 is consistent with a bounded integration mechanism of decision-making (3–5, 7).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“When VarCE is calculated from residuals (5, 51) (Materials and Methods), it is similar (Fig. 4G, black) showing linear increase between decision onset (Fig. 4G, up arrow) and decision termination (Fig. 4G, down arrow) times.”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“Overall, VarCE exhibits a linear increase during epoch 4, a characteristic signature of diffusion process consistent with an accumulation-to-bound model (5, 51).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“The calculated (Materials and Methods) CorCE matrix (Fig. 4J) indeed exhibits characteristic increase of correlation as a function of time and, for given time (e.g., along the top row), shows sequential decay as often observed (5, 51) during decision-making.”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [5]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856 · cited 1×
“The reported latencies are the times at which the ROC index significantly departed from 0.5 for at least 50 ms ( p 0.05; Hanley and McNeil, 1982).”
BackgroundInfluentialBrainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 20,012 · cited 2×
“Experimental control and stimulus presentation were achieved with either REX (Hays et al., 1982) in combination with the Psychophysics toolbox (Brainard, 1997) or with EXPO (developed by Peter Lennie, currently maintained by Rod Dotson, Center for Neural Science at New York University, New York,…”
MethodParallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations
Rumelhart, D. E., McClelland, J. L., & AU (1986) · doi:10.7551/mitpress/5236.001.0001 · Cited by 15,686 · cited 1×
“This is not the type of parallel processing that is often associated with neural networks (Rumelhart and McClelland, 1986) or computer systems but is instead a direct representation (Barlow, 1995) of a decision variable in the firing rates of neurons.”
BackgroundDistributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Ratcliff, R. (1978) · Psychological Review · doi:10.1037/0033-295x.85.2.59 · Cited by 4,513 · cited 4×
“Such an accumulation of noisy evidence has been likened to a random walk or diffusion process (Ratcliff, 1978; Gold and Shadlen, 2002).”
BackgroundMethodInfluentialThe Neural Basis of Decision Making
Gold, J. I., & Shadlen, M. N. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113038 · Cited by 3,764 · cited 6×
“…occurs in circuits associated with provisional behavioral responses to stim- uli (Schall, 2001; Romo et al., 2004; Rorie and Newsome, 2005; Gold and Shadlen, 2007; Lemus et al., 2007; Andersen and Cui, 2009; Cisek and Kalaska, 2010; Hernández et al., 2010; Westendorff et al., 2010),…”
BackgroundInfluentialSelf-citationPreface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,537
Spatiotemporal energy models for the perception of motion
Adelson, E. H., & Bergen, J. R. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.000284 · Cited by 3,442 · cited 10×
“We estimated the rate of this rise or decline by fitting lines to the response averages in the 150 ms epoch from the earliest point that these trends appear to emerge (see Materials and Methods).”
BackgroundInfluentialMountcastle, V. B., Lynch, J. C., Georgopoulos, A., Sakata, H., & Acuna, C. (1975) · Journal of Neurophysiology · doi:10.1152/jn.1975.38.4.871 · Cited by 2,061 · cited 1×
“…saccadic eye movements (Thier and Andersen, 1998), MIP neurons signal the spatial location of objects that are potential targets of reach movements (Mountcastle et al., 1975; Johnson et al., 1996; Snyder et al., 1997; Batista et al., 1999; Eskandar and Assad, 1999), as well as the outcome of…”
BackgroundThe analysis of visual motion: a comparison of neuronal and psychophysical performance
Britten, K., Shadlen, M., Newsome, W., & Movshon, J. (1992) · The Journal of Neuroscience · doi:10.1523/jneurosci.12-12-04745.1992 · Cited by 1,958 · cited 1×
“We recorded from single neurons in areas LIP and MIP of two rhesus monkeys that were trained to judge the direction of motion of a dynamic random-dot display (Britten et al., 1992).”
MethodSelf-citation
Research works printed but not linked: 7
- Barlow H (1995) The cognitive neurosciences, The neuron doctrine in perception (Massachusetts Institute of Technology, Cambridge, MA), pp 415–435.
- 10.1038/35006062 · DOI · Paper page
- 10.1016/S0896-6273(02)00971-6 · DOI
- Hays, 1982, A UNIX-based multiple process system for real-time data acquisition and control, WESCON Conf Proc, 2, 1
- 10.1002/1096-9861(20001204)428:1<79::AID-CNE7>3.0.CO;2-Q · DOI
- 10.1037//0033-295X.85.2.59 · DOI · Paper page
- Shadlen MN Kiani R Hanks T Churchland AK (2008) in Better than conscious? Decision making, the human mind, and implications for institutions, An intentional framework, eds Engel C Singer W (MIT, Cambridge), p 71. · DOI
Cited by
Sorted by citations
Active inference: a process theory
Friston, K., FitzGerald, T., Rigoli, F., Schwartenbeck, P., & Pezzulo, G. (2017) · Neural Computation · doi:10.1162/neco_a_00912 · Cited by 1,156
“…formally identical to evidence accumulation described by drift diffusion or race-to-bound models (Solway & Botvinick, 2012; Zhang & Maloney, 2012; de Lafuente et al., 2015; Kira et al., 2015) and nicely recapitulates the emergence of a choice as evaluation of options proceeds (Hunt et al., 2012).”
BackgroundThe graphical brain: Belief propagation and active inference
Friston, K. J., Parr, T., & de Vries, B. (2017) · Network Neuroscience · doi:10.1162/netn_a_00018 · Cited by 415
“This formulation also has some construct validity in relation to theoretical proposals and empirical work on evidence accumulation (de Lafuente, Jazayeri, & Shadlen, 2015; Kira, Yang, & Shadlen, 2015) and the neuronal encoding of probabilities (Deneve, 2008).”
BackgroundNavigating the Neural Space in Search of the Neural Code
Jazayeri, M., & Afraz, A. (2017) · Neuron · doi:10.1016/j.neuron.2017.02.019 · Cited by 240
“Movements with fine temporal structure, cognitive functions such as deliberation and integration (de Lafuente et al., 2015; Hanks et al., 2015;Merchant and Georgopoulos, 2006; Roitman and Shadlen, 2002; Shadlen and Gold, 2004; Thura and Cisek, 2014), and behaviors that depend on knowledge of…”
Self-citationBridging Neural and Computational Viewpoints on Perceptual Decision-Making
O’Connell, R. G., Shadlen, M. N., Wong‐Lin, K., & Kelly, S. P. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.06.005 · Cited by 217
“, [74]) In many of the decisions subjects face in their daily life, LIP, in fact, may not have a role at all.”
Self-citationUnraveling circuits of visual perception and cognition through the superior colliculus
Basso, M. A., Bickford, M. E., & Cang, J. (2021) · Neuron · doi:10.1016/j.neuron.2021.01.013 · Cited by 240
Scene Construction, Visual Foraging, and Active Inference
Mirza, M. B., Adams, R. A., Mathys, C. D., & Friston, K. J. (2016) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2016.00056 · Cited by 165
Posterior parietal cortex plays a causal role in perceptual and categorical decisions
Zhou, Y., & Freedman, D. J. (2019) · Science · doi:10.1126/science.aaw8347 · Cited by 142
Representational geometry of perceptual decisions in the monkey parietal cortex
Okazawa, G., Hatch, C. E., Mancoo, A., Machens, C. K., & Kiani, R. (2021) · Cell · doi:10.1016/j.cell.2021.05.022 · Cited by 115
Generalization of prior information for rapid Bayesian time estimation
Roach, N. W., McGraw, P. V., Whitaker, D., & Heron, J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1610706114 · Cited by 108
“Moreover, decision-related activity has been shown to occur in parallel in areas associated with different motor responses (44-46).”
BackgroundFunctional dissection of signal and noise in MT and LIP during decision-making
Yates, J. L., Park, I. M., Katz, L. N., Pillow, J. W., & Huk, A. C. (2017) · Nature Neuroscience · doi:10.1038/nn.4611 · Cited by 120
Motor and Predictive Processes in Auditory Beat and Rhythm Perception
Proksch, S., Comstock, D. C., Médé, B., Pabst, A., & Balasubramaniam, R. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.578546 · Cited by 68
Generative models, linguistic communication and active inference
Friston, K. J., Parr, T., Yufik, Y. M., Sajid, N., Price, C. J., & Holmes, E. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.07.005 · Cited by 120
Laminar differences in decision-related neural activity in dorsal premotor cortex
Chandrasekaran, C., Peixoto, D., Newsome, W. T., & Shenoy, K. V. (2017) · Nature Communications · doi:10.1038/s41467-017-00715-0 · Cited by 98
Coherent neuronal ensembles are rapidly recruited when making a look-reach decision
Wong, Y. T., Fabiszak, M. M., Novikov, Y., Daw, N. D., & Pesaran, B. (2016) · Nature Neuroscience · doi:10.1038/nn.4210 · Cited by 101
Coallier, É., Michelet, T., & Kalaska, J. F. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00166.2014 · Cited by 88
Neural precursors of decisions that matter—an ERP study of deliberate and arbitrary choice
Maoz, U., Yaffe, G., Koch, C., & Mudrik, L. (2019) · eLife · doi:10.7554/elife.39787 · Cited by 162
Tagliabue, C. F., Veniero, D., Benwell, C., Cecere, R., Savazzi, S., & Thut, G. (2019) · Scientific Reports · doi:10.1038/s41598-019-41024-4 · Cited by 150
Twomey, D. M., Kelly, S. P., & O’Connell, R. G. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4162-15.2016 · Cited by 113
“…activity that discriminates the categorical alternatives even when the appropriate stimulus– response mapping is withheld until a response cue (Freedman and Assad, 2006; Bennur and Gold, 2011) or when hand movements are used to report decisions instead of saccades (de Lafuente et al., 2015).”
BackgroundFunctional definitions of parietal areas in human and non-human primates
Orban, G. A. (2016) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2016.0118 · Cited by 97
Balcı, F., & Simen, P. (2016) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2016.02.002 · Cited by 95
Jun, E. J., Bautista, A. R., Nunez, M. D., Allen, D. C., Tak, J. H., Alvarez, E. T., & Basso, M. A. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00878-6 · Cited by 96
Visual Decision-Making in an Uncertain and Dynamic World
Gold, J. I., & Stocker, A. A. (2017) · Annual Review of Vision Science · doi:10.1146/annurev-vision-111815-114511 · Cited by 106
Caminiti, R., Borra, E., Visco‐Comandini, F., Battaglia‐Mayer, A., Averbeck, B. B., & Luppino, G. (2017) · eNeuro · doi:10.1523/eneuro.0306-16.2017 · Cited by 77
“Interestingly, during accumulation of decision variables, neural activity in LIP is modulated when the decision outcome is not only a saccade, but also a reaching movement (de Lafuente et al., 2015).”
BackgroundInfluentialDifferentiating between integration and non-integration strategies in perceptual decision making
Stine, G. M., Zylberberg, A., Ditterich, J., & Shadlen, M. N. (2020) · eLife · doi:10.7554/elife.55365 · Cited by 93
Self-citationThe Role of the Lateral Intraparietal Area in (the Study of) Decision Making
Huk, A. C., Katz, L. N., & Yates, J. L. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031508 · Cited by 76
“These areas include the frontal eye fields (Ding & Gold 2012a, Gold & Shadlen 2000, Kim & Shadlen 1999), the parietal reach region (de Lafuente et al. 2015), and subcortical structures such as the superior colliculus (Horwitz & Newsome 1999) and the caudate nucleus (Ding & Gold 2010, 2012b).”
BackgroundIntegrated neural dynamics of sensorimotor decisions and actions
Thura, D., Cabana, J., Feghaly, A., & Cisek, P. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001861 · Cited by 93
Direct observation of the neural computations underlying a single decisionPreprint
Steinemann, N. A., Stine, G. M., Trautmann, E. M., Zylberberg, A., Wolpert, D., & Shadlen, M. (2024) · bioRxiv · doi:10.1101/2022.05.02.490321 · Cited by 60
“This is surprising, but it could be explained by lack of power—a combination of small numbers of M in neurons, narrow sample windows (50 ms boxcar) and the focus on the long RT trials.”
BackgroundSelf-citationNeural Mechanisms That Make Perceptual Decisions Flexible
Okazawa, G., & Kiani, R. (2022) · Annual Review of Physiology · doi:10.1146/annurev-physiol-031722-024731 · Cited by 83
“This question can be answered with tasks in which subjects report the outcome of the same sensory discrimination through different motor actions (78, 79, 85–87).”
BackgroundInfluentialLakshminarasimhan, K. J., Avila, E., Neyhart, E., DeAngelis, G., Pitkow, X., & Angelaki, D. (2019) · bioRxiv · doi:10.1101/689786 · Cited by 58
“Consistent with this interpretation, there is overwhelming evidence for decision-related responses in primate oculomotor brain areas (de Lafuente et al., 2015; Shadlen and Newsome, 1996), and such responses are thought to drive eye movements (Joo et al., 2016).”
BackgroundFetsch, C. R., Odean, N. N., Jeurissen, D., El-Shamayleh, Y., Horwitz, G. D., & Shadlen, M. N. (2018) · eLife · doi:10.7554/elife.36523 · Cited by 74
Self-citationPiercing of Consciousness as a Threshold-Crossing Operation
Kang, Y. H., Petzschner, F. H., Wolpert, D. M., & Shadlen, M. N. (2017) · Current Biology · doi:10.1016/j.cub.2017.06.047 · Cited by 90
“Presumably, the decision to report and the decision to move are not the same process, just as the decision to report with a saccade or a reach movement is subserved by different circuits [27, 28].”
Self-citationZoltowski, D. M., Latimer, K. W., Yates, J. L., Huk, A., & Pillow, J. (2018) · bioRxiv · doi:10.1101/433458 · Cited by 48
Gallivan, J. P., & Goodale, M. A. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63622-5.00023-1 · Cited by 73
Entrainment and maintenance of an internal metronome in supplementary motor area
Cadena-Valencia, J., García‐Garibay, O., Merchant, H., Jazayeri, M., & de Lafuente, V. (2018) · eLife · doi:10.7554/elife.38983 · Cited by 52
Self-citationWang, M., Montanède, C., Chandrasekaran, C., Peixoto, D., Shenoy, K. V., & Kalaska, J. F. (2019) · Nature Communications · doi:10.1038/s41467-019-09460-y · Cited by 39
“…brain areas associated with operantly-conditioned motor responses in sensorimotor decision-making processes leading to action choices (Brody and Hanks, 2016; de Lafuente et al., 2015; Glimcher, 2001; Huda et al., 2018; Roitman and Shadlen, 2002; Romo et al., 2004; Shadlen and Newsome, 1996).”
Temporal coding of reward-guided choice in the posterior parietal cortex
Hawellek, D. J., Wong, Y. T., & Pesaran, B. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1606479113 · Cited by 41
“We first established the presence of firing-rate encoding of choice and the temporal structure of the neuronal activity in the PPC (11, 32, 35) before testing whether and how decision coding varies with the temporal structure of neuronal activity.”
MethodLatimer, K. W., Yates, J. L., Meister, M. L. R., Huk, A. C., & Pillow, J. W. (2016) · Science · doi:10.1126/science.aad3596 · Cited by 11
Self-citationHadjidimitrakis, K., Bò, G. D., Breveglieri, R., Galletti, C., & Fattori, P. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00486.2015 · Cited by 53
Riemer, M., Diersch, N., Bublatzky, F., & Wolbers, T. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.030 · Cited by 48
Evidence accumulation as a model for lexical selection
Anders, R., Riès, S., van Maanen, L., & Alario, F. ‐. (2015) · Cognitive Psychology · doi:10.1016/j.cogpsych.2015.07.002 · Cited by 48
Parieto-frontal networks for eye–hand coordination and movements
Battaglia‐Mayer, A., & Caminiti, R. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63622-5.00026-7 · Cited by 41
Sensory Evidence Accumulation Using Optic Flow in a Naturalistic Navigation Task
Alefantis, P., Lakshminarasimhan, K. J., Avila, E., Noel, J., Pitkow, X., & Angelaki, D. E. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.2203-21.2022 · Cited by 35
“…over time (e.g. random dot kinematograms) (de Bruyn & Orban, 1988; Glass & Pérez, 1973; Snowden & Braddick, 1990; Watanabe & Kikuchi, 2006; de Lafuente et al., 2015; Gold & Shadlen, 2000; Kim & Shadlen, 1999; Liu & Pleskac, 2011; Drugowitsch et al., 2015; Gu et al., 2008; Hou et al.,…”
Perceptual Decision-Making: A Field in the Midst of a Transformation
Najafi, F., & Churchland, A. K. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.017 · Cited by 41
Relating accumulator model parameters and neural dynamics
Purcell, B. A., & Palmeri, T. J. (2016) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2016.07.001 · Cited by 42
Sequential sampling from memory underlies action selection during abstract decision making
Shushruth, S., Zylberberg, A., & Shadlen, M. (2021) · bioRxiv · doi:10.1101/2021.04.30.442176 · Cited by 33
Self-citationA leaky evidence accumulation process for perceptual experience
Pereira, M., Perrin, D., & Faivre, N. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.03.003 · Cited by 56
Fetsch, C. R. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2015.12.002 · Cited by 29
Bakola, S., Passarelli, L., Huynh, T., Impieri, D., Worthy, K. H., Fattori, P., Galletti, C., Burman, K. J., & Rosa, M. G. P. (2017) · eNeuro · doi:10.1523/eneuro.0344-17.2017 · Cited by 33
Shushruth, S., Mazurek, M. E., & Shadlen, M. N. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.0668-18.2018 · Cited by 45
Self-citationDistinct dynamics of ramping activity in the frontal cortex and caudate nucleus in monkeys
Ding, L. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00395.2015 · Cited by 34
“It has been especially useful as a signature of neural computations related to temporal accumulation in the context of decision making (Churchland et al. 2011; de Lafuente et al. 2015; Marcos et al. 2013).”
BackgroundMohan, K., Zhu, O., & Freedman, D. J. (2020) · bioRxiv · doi:10.1101/2020.08.20.259820 · Cited by 27
Decision formation in parietal cortex transcends a fixed frame of reference
So, N., & Shadlen, M. (2022) · bioRxiv · doi:10.1101/2022.02.16.478899 · Cited by 25
“For example, the representation of an object relative to the hand could be achieved in parietal cortex using neurons that represent hand displacement in an oculocentric FoR (see Snyder et al., 1997; Batista, 1999; de Lafuente et al., 2015; Stuphorn et al., 2000).”
Self-citationKang, Y. H., Löffler, A., Jeurissen, D., Zylberberg, A., Wolpert, D. M., & Shadlen, M. N. (2021) · eLife · doi:10.7554/elife.63721 · Cited by 46
Self-citationConfidence Representation of Perceptual Decision by EEG and Eye Data in a Random Dot Motion Task
Shooshtari, S. V., Esmaily, J., Azizi, Z. R., & Ebrahimpour, R. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.03.031 · Cited by 31
Manning, C., Hassall, C. D., Hunt, L. T., Norcia, A. M., Wagenmakers, E., Snowling, M. J., Scerif, G., & Evans, N. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1232-21.2021 · Cited by 36
“…suggest that differences in dyslexia arise because of the efficiency with which evidence is extracted from global motion stimuli and integrated toward a decision bound, which is often attributed to parietal areas (Shadlen and Newsome, 1996, 2001; Hanks et al., 2006; de Lafuente et al., 2015).”
Ramp-to-threshold dynamics in a hindbrain population controls the timing of spontaneous saccades
Ramirez, A. D., & Aksay, E. R. F. (2021) · Nature Communications · doi:10.1038/s41467-021-24336-w · Cited by 24
Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates
Manning, C., Wagenmakers, E., Norcia, A. M., Scerif, G., & Boehm, U. (2020) · Computational Brain & Behavior · doi:10.1007/s42113-020-00087-7 · Cited by 30
“Future work could also investigate whether children ’ s responses may be captured better by models which incorporate urgency signals or collapsing boundaries (Cisek et al. 2009; Chandrasekaran and Hawkins 2019; Ditterich 2006; Hawkins et al. 2015).”
BackgroundConfidence through consensus: a neural mechanism for uncertainty monitoring
Paz, L., Insabato, A., Zylberberg, A., Deco, G., & Sigman, M. (2016) · Scientific Reports · doi:10.1038/srep21830 · Cited by 26
Nurislamova, Y. M., Александрович, Н. Н., Alexandrovna, Z. N., & Chernyshev, B. (2019) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2019.00014 · Cited by 20
Inferring decoding strategies for multiple correlated neural populations
Lakshminarasimhan, K. J., Pouget, A., DeAngelis, G. C., Angelaki, D. E., & Pitkow, X. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006371 · Cited by 18
“Time-varying weights have been shown to better predict animals’ choice in certain tasks [46], and psychophysical kernels are sometimes skewed towards one end of the trial[47,48], suggesting that decoding could also be suboptimal in time.”
BackgroundDecision-related perturbations of decision-irrelevant eye movements
Joo, S. J., Katz, L. N., & Huk, A. C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1520309113 · Cited by 21
Vich, C., Clapp, M., Rubin, J. E., & Verstynen, T. D. (2021) · bioRxiv · doi:10.1371/journal.pcbi.1010255 · Cited by 19
A Two-Stage Process Model of Sensory Discrimination: An Alternative to Drift-Diffusion
Sun, P., & Landy, M. S. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1367-16.2016 · Cited by 24
“…cortex (Gold and Shadlen, 2001; Shadlen and Newsome, 2001; Roitman and Shadlen, 2002; Yang and Shadlen, 2007; Kiani et al., 2008; Meister et al., 2013; Park et al., 2014; de Lafuente et al., 2015; Shadlen et al., 2016) and the frontal eye fields (Gold and Shadlen, 2000, 2003; Ding and Gold, 2012).”
BackgroundBattaglia‐Mayer, A. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx354 · Cited by 18
“Finally, a recent elegant study on the formation of motor intentions for reaches versus saccades in MIP and LIP (de Lafuente et al. 2015) has shown that the gradual accumulation of information about decision signals in the activity of neurons in MIP leads to the formation motor intentions for a…”
Population dynamics of choice representation in dorsal premotor and primary motor cortexPreprint
Peixoto, D., Kiani, R., Chandrasekaran, C., Ryu, S. I., Shenoy, K. V., & Newsome, W. T. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/283960 · Cited by 14
“The median latencies for PMd were significantly shorter than for M1 (Wilcoxon rank sum test, p 0.001) and were similar to other reports of decision-related signals in PMd (Thura and Cisek, 2014, Chandrasekaran et al., 2017) and MIP (de Lafuente et al., 2015).”
BackgroundResultInfluentialGherman, S., Markowitz, N., Tostaeva, G., Espinal, E., Mehta, A. D., O’Connell, R. G., Kelly, S. P., & Bickel, S. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01824-9 · Cited by 34
“…these sites is consistent with a process of evidence accumulation, building gradually over time at a rate that is proportional to the strength of the sensory information, reaching a fixed threshold just before a response is made, and reliably predicting the animal’s choice and response time 1–6 .”
Modelling behaviors relevant to brain disorders in the nonhuman primate: Are we there yet?
Scott, J. T., & Bourne, J. A. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102183 · Cited by 31
Distributed functions of prefrontal and parietal cortices during sequential categorical decisionsPreprint
Zhou, Y., Rosen, M. C., Swaminathan, S. K., Masse, N. Y., Zhu, O., & Freedman, D. J. (2020) · bioRxiv · doi:10.1101/2020.05.21.108910 · Cited by 17
“The lateral PFC, LIP and MIP are important processing stages for mediating decision-making tasks (de Lafuente et al., 2015; Ding and Gold, 2012; Gold and Shadlen, 2007; Huk et al., 2017; Kim and Shadlen, 1999; Padoa-Schioppa and Assad, 2006; Platt and Glimcher, 1999; Rossi-Pool et al., 2017;…”
BackgroundCause for pause before leaping to conclusions about steppingPreprint
Zylberberg, A., & Shadlen, M. N. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/085886 · Cited by 17
“In another brain area it might represent a plan to do something else, such as reach [9, 19] or implement a rule [20], perhaps.”
BackgroundSelf-citationMagri, C., Fabbri, S., Caramazza, A., & Lingnau, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.029 · Cited by 16
Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing
Tu, T., Schneck, N., Muraskin, J., & Sajda, P. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1677-17.2017 · Cited by 11
“A variety of neuroimaging studies have already demonstrated their roles in decision making (Heekeren et al., 2004, 2008; Philiastides and Sajda, 2007; Ruff et al., 2010; de Lafuente et al., 2015; Lamichhane et al., 2016).”
BackgroundUnified neural dynamics of decisions and actions in the cerebral cortex and basal gangliaPreprint
Thura, D., Cabana, J.-F., Feghaly, A., & Cisek, P. (2020) · bioRxiv · doi:10.1101/2020.10.22.350280 · Cited by 13
Evidence accumulation under uncertainty – a neural marker of emerging choice and urgency
Parés-Pujolràs, E., Travers, E., Ahmetoglu, Y., & Haggard, P. (2020) · bioRxiv · doi:10.1101/2020.06.30.179622 · Cited by 13
Dixon–Gordon, K. L., Tull, M. T., Hackel, L. M., & Gratz, K. L. (2017) · Journal of Personality Disorders · doi:10.1521/pedi_2017_31_299 · Cited by 15
Gaze Bias Differences Capture Individual Choice BehaviorPreprint
Thomas, A. W., Molter, F., Krajbich, I., Heekeren, H., & Mohr, P. N. C. (2017) · bioRxiv · doi:10.1101/228825 · Cited by 13
Parieto-frontal gradients and domains underlying eye and hand operations in the action space
Battaglia‐Mayer, A., Babicola, L., & Satta, E. (2016) · Neuroscience · doi:10.1016/j.neuroscience.2016.07.009 · Cited by 17
Secondary motor integration as a final arbiter in sensorimotor decision-making
Balsdon, T., Verdonck, S., Loossens, T., & Philiastides, M. G. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002200 · Cited by 14
Mudrik, L., Levy, D. J., Gavenas, J., & Maoz, U. (2019) · Psychology of Consciousness Theory Research and Practice · doi:10.1037/cns0000200 · Cited by 16
Cognition in Sensorimotor Control: Interfacing With the Posterior Parietal Cortex
Chivukula, S., Jafari, M., Aflalo, T., Yong, N. A., & Pouratian, N. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00140 · Cited by 14
Ramp-to-Threshold Dynamics in a Hindbrain Population Controls the Timing of Spontaneous SaccadesPreprint
Ramirez, A. D., & Aksay, E. R. F. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/430645 · Cited by 1
Archerfish fast-start decisions can take an additional variable into account
Reinel, C. P., & Schuster, S. (2016) · Journal of Experimental Biology · doi:10.1242/jeb.136812 · Cited by 12
“…have been confirmed in a simple but well-controlled perceptual task that by now has become the classical model of decision-making: the saccadic decisions made by appropriately trained monkeys (e.g. Palmer et al., 2005; Shadlen and Kiani, 2013; Kiani et al., 2014; de Lafuente et al., 2015).”
BackgroundHadjidimitrakis, K., Vitis, M. D., Ghodrati, M., Filippini, M., & Fattori, P. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111608 · Cited by 11
New insights on single-neuron selectivity in the era of population-level approaches
Vaccari, F., Diomedi, S., Filippini, M., Hadjidimitrakis, K., & Fattori, P. (2022) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2022.929052 · Cited by 12
Discrimination of Regular and Irregular Rhythms Explained by a Time Difference Accumulation Model
Espinoza-Monroy, M., & de Lafuente, V. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.01.035 · Cited by 12
Kubanek, J., & Snyder, L. H. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv230 · Cited by 10
“This supports a notion that choice-related signals in LIP are partially saccade-specific and partially general, whereas PRR signals are more strongly embodied (de Lafuente et al. 2015; Kubanek, Li, et al. 2015).”
InfluentialMulti-region coordination of evidence accumulation and decision commitment in the brainPreprint
Bondy, A., Charlton, J. A., Luo, T. Z., Kopec, C. D., Stagnaro, W. M., Venditto, S. J. C., Shi, K., Xie, E. Y., Beau, M., Lynch, L. A., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.21.609044 · Cited by 28
Functional organization of posterior parietal cortex circuitry based on inferred information flow
Kang, J. U., Mooshagian, E., & Snyder, L. H. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114028 · Cited by 9
“39 To account for these high-level roles, it has been proposed that LIP forms a ‘‘priority map’’ of space, identifying important spatial locations and then propagating that information to other areas, including PRR, to further cognitive or motor goals (Figure 1A, spatial hub or priority map model).”
A conflict between spatial selection and evidence accumulation in area LIP
Seideman, J. A., Stanford, T. R., & Salinas, E. (2022) · Nature Communications · doi:10.1038/s41467-022-32209-z · Cited by 18
Okazawa, G., Hatch, C. E., Mancoo, A., Machens, C., & Kiani, R. (2021) · bioRxiv · doi:10.1101/2021.01.04.425244 · Cited by 9
“Similar encoding of the DV has been found in many other brain structures (de Lafuente et al. 2015; Deverett et al. 2018; Ding and Gold 2010, 2012; Donner et al. 2009; Horwitz and Newsome 1999; Kiani et al. 2014b; Kim and Basso 2008; Kim and Shadlen 1999; Peixoto et al. 2018; Ratcliff et al. 2003)…”
BackgroundInfluentialDecision-making processes in perceptual learning depend on effectors
Ivanov, V., Manenti, G. L., Plewe, S. S., Kagan, I., & Schwiedrzik, C. M. (2024) · Scientific Reports · doi:10.1038/s41598-024-55508-5 · Cited by 8
Optimal Readout of Correlated Neural Activity in a Decision-Making Circuit
Calderini, M., Zhang, S., Berberian, N., & Thivierge, J. (2018) · Neural Computation · doi:10.1162/neco_a_01083 · Cited by 7
Leitão, J., Thielscher, A., Lee, H. L., Tünnerhoff, J., & Noppeney, U. (2017) · European Journal of Neuroscience · doi:10.1111/ejn.13743 · Cited by 10
“© 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd [e.g. lateral (LIP) or medial (MI) intraparietal areas (de Lafuente et al., 2015)] are thought to play a pivotal role by influencing perceptual decisions at two levels.”
BackgroundParés-Pujolràs, E., Kelly, S. P., & Murphy, P. (2024) · bioRxiv · doi:10.1038/s41467-025-58861-9 · Cited by 7
“…perceptual decisions in static environments have identi fi ed two human neurophysiological signals that evolve with similar integration dynamics, with one - the centroparietal positivity - appearing to compute the running integral and continuously feed it to the other - motor beta lateralisation.”
Prior probability cues bias sensory encoding with increasing task exposure
Walsh, K. S., McGovern, D. P., Dully, J., Kelly, S. P., & O’Connell, R. G. (2023) · eLife · doi:10.7554/elife.91135 · Cited by 21
“A mixed effect analysis showed a main effect of Cue Condition on alpha amplitude (F(1,52527) = 10.10, p = 0.001), such that there was significantly greater alpha desynchronisation in the neutral cue condition, consistent with increased task engagement in this condition.”
ResultInfluentialDecoding Adaptive Visuomotor Behavior Mediated by Non-linear Phase Coupling in Macaque Area MT
Khamechian, M. B., & Daliri, M. R. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00230 · Cited by 9
A doubly stochastic renewal framework for partitioning spiking variability
Aghamohammadi, C., Chandrasekaran, C., & Engel, T. A. (2025) · Nature Communications · doi:10.1038/s41467-025-63821-4 · Cited by 9
“(7) with a fi nite bin size have similar limitations 31,47 (Methods), although accurate estimation is possible using large bin sizes 48 .”
InfluentialGür, E., Duyan, Y. A., Türkakın, E., Arkan, S., Karson, A., & Balcı, F. (2020) · Brain Structure and Function · doi:10.1007/s00429-020-02101-x · Cited by 9
Beldzik, E., Domagalik, A., Gawłowska, M., Marek, T., & Mojsa‐Kaja, J. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1527-7 · Cited by 7
Latimer, K. W., Huk, A. C., & Pillow, J. W. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/160994 · Cited by 7
Neural precursors of deliberate and arbitrary decisions in the study of voluntary action
Maoz, U., Yaffe, G., Koch, C., & Mudrik, L. (2017) · bioRxiv · doi:10.1101/097626 · Cited by 6
Metadata
- Authors
- de Lafuente, V., Jazayeri, M., & Shadlen, M. N.
- Affiliations
- McGovern Institute for Brain Research (US)
- Howard Hughes Medical Institute (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2015-03-11
- Volume
- 35
- Issue
- 10
- Pages
- 4306-4318
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC4355201
- OpenAlex
- W2090544951
- Cited by
- 162
- References
- 74
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 15 · 2023: 11 · 2022: 17 · 2021: 17 · 2020: 14 · 2019: 14 · 2018: 12 · 2017: 18 · 2016: 21 · 2015: 7
- FWCI
- 11.63
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- decision-making, evidence accumulation, lateral intraparietal area, saccades, reach-to-grasp, decision variables, parietal cortex, eye movements, motor planning, parallel computing, firing rate modulation
- MeSH terms
- Action Potentials, Animals, Decision Making, Discrimination, Psychological, Eye Movements, Judgment, Functional Laterality, Macaca mulatta, Magnetic Resonance Imaging, Male, Motion Perception, Neurons, Parietal Lobe, Photic Stimulation, Psychometrics, Psychomotor Performance, Psychophysics, Time Factors
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.
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
