The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.
Neural Basis of a Perceptual Decision in the Parietal Cortex (Area LIP) of the Rhesus Monkey
Abstract
We recorded the activity of single neurons in the posterior parietal cortex (area LIP) of two rhesus monkeys while they discriminated the direction of motion in random-dot visual stimuli. The visual task was similar to a motion discrimination task that has been used in previous investigations of motion-sensitive regions of the extrastriate cortex. The monkeys were trained to decide whether the direction of motion was toward one of two choice targets that appeared on either side of the random-dot stimulus. At the end of the trial, the monkeys reported their direction judgment by making an eye movement to the appropriate target. We studied neurons in LIP that exhibited spatially selective persistent activity during delayed saccadic eye movement tasks. These neurons are thought to carry high-level signals appropriate for identifying salient visual targets and for guiding saccadic eye movements. We arranged the motion discrimination task so that one of the choice targets was in the LIP neuron's response field (RF) while the other target was positioned well away from the RF. During motion viewing, neurons in LIP altered their firing rate in a manner that predicted the saccadic eye movement that the monkey would make at the end of the trial. The activity thus predicted the monkey's judgment of motion direction. This predictive activity began early in the motion-viewing period and became increasingly reliable as the monkey viewed the random-dot motion. The neural activity predicted the monkey's direction judgment on both easy and difficult trials (strong and weak motion), whether or not the judgment was correct. In addition, the timing and magnitude of the response was affected by the strength of the motion signal in the stimulus. When the direction of motion was toward the RF, stronger motion led to larger neural responses earlier in the motion-viewing period. When motion was away from the RF, stronger motion led to greater suppression of ongoing activity. Thus the activity of single neurons in area LIP reflects both the direction of an impending gaze shift and the quality of the sensory information that instructs such a response. The time course of the neural response suggests that LIP accumulates sensory signals relevant to the selection of a target for an eye movement.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“It suggests that the accumulated evidence, represented in LIP, tends to plateau or saturate at the longer viewing durations used in previous experiments (Shadlen and Newsome, 2001).”
From Bounded Integration in Parietal Cortex Underlies Decisions Even When Viewing Duration Is Dictated by the Environment (2008) · cites this paper as Shadlen and Newsome, 2001
In the citing paper
“In contrast to this approach, a stimulus duration that is fixed or predictable (Britten et al., 1993;Shadlen and Newsome, 2001;Parker et al., 2002;DeAngelis and Newsome, 2004;Krug, 2004;Krug et al., 2004;Uka and DeAngelis, 2004) would allow subjects to start the decision process at times other than the beginning of stimulus.”
From Bounded Integration in Parietal Cortex Underlies Decisions Even When Viewing Duration Is Dictated by the Environment (2008) · cites this paper as Shadlen and Newsome, 2001
In the citing paper
“The neural activity following motion onset underwent a brief dip and then diverged to indicate the monkey’s decision for Tin or Topp. The activity persisted through the delay period until the eye movement (18).”
From Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex (2009) · cites this paper as [18]
In the citing paper
“This accumulation, which we call a decision variable, v(t), is represented by the firing rates of LIP neurons.”
From Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex (2009) · cites this paper as [18]
In the citing paper
“This accumulation is encoded in the firing rates of LIP neurons with response fields aligned to the choice targets representing the direction alternatives (18, 55–57).”
From Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex (2009) · cites this paper as [18]
In the citing paper
“Thus, LIP appears to play a role in transforming motion information into a saccadic choice, although that role might be shared among several oculomotor regions including the frontal eye field and superior colliculus that show similar responses during task performance27, 28.”
From Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area (2008) · cites this paper as [24]
In the citing paper
“In trained monkeys, multiple brain areas including LIP, the superior colliculus and parts of the prefrontal cortex including the FEF exhibit similar sensory-motor responses during performance of the discrimination task24, 25, 27, 28.”
From Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area (2008) · cites this paper as [24]
In the citing paper
“Specifically, when stimulus motion favors the target in the response field (RF) of an LIP neuron, firing rates build up progressively as monkeys form their decisions; the rate of buildup is proportional to motion strength.”
From Decision-making with multiple alternatives (2008) · cites this paper as [7]
In the citing paper
“Finally, in the RT version, firing rates are similar at decision end when the monkey selects a target in the neuron’s RF, for all motion strengths and RTs.”
From Decision-making with multiple alternatives (2008) · cites this paper as [7]
In the citing paper
“Second, neuronal firing rates in the lateral intraparietal area (LIP) are consistent with evidence accumulation 2,7–9.”
From Decision-making with multiple alternatives (2008) · cites this paper as [7]
In the citing paper
“However, a causal role for LIP neurons in decision-making has not been established.”
From Microstimulation of macaque area LIP affects decision-making in a motion discrimination task (2006) · cites this paper as [11]
In the citing paper
“Several other brain structures such as the superior colliculus, the dorsolateral prefrontal cortex (Walker area 46), and the FEF are thought to represent quantities like the accumulated evidence in area LIP2,10,11,34–37”
From Microstimulation of macaque area LIP affects decision-making in a motion discrimination task (2006) · cites this paper as [11]
In the citing paper
“The relationship between neuronal activity and choice outcome indicates that neural processors compute behavioral decision variables by integrating afferent inputs over time (Hanes and Schall, 1996;Kim and Shadlen, 1999;Platt and Glimcher, 1999;Shadlen and Newsome, 2001;Cook and Maunsell, 2002;Roitman and Shadlen, 2002;Hanks et al., 2006;Gold and Shadlen, 2007).”
From Evidence accumulation and the moment of recognition: dissociating perceptual recognition processes using fMRI (2007) · cites this paper as Shadlen and Newsome, 2001
In the citing paper
“Such models also appear to describe the evolution of neural spiking rates in macaque frontal eye fields during initiation of eye movements (Hanes and Schall, 1996), the lateral intraparietal area (Shadlen and Newsome, 2001) and dorsolateral prefrontal cortex (dlPFC) (Kim and Shadlen, 1999) during motion detection, and superior colliculus during distance judgments (Ratcliff et al., 2003).”
From Evidence accumulation and the moment of recognition: dissociating perceptual recognition processes using fMRI (2007) · cites this paper as Shadlen and Newsome, 2001
In the citing paper
“In our view, however, the tight coupling of the rate of activity buildup and T R in our data and in single-unit studies in nonhuman primates (Kim and Shadlen, 1999;Shadlen and Newsome, 2001) suggests that a purely epiphenomenal account is unlikely.”
From Evidence accumulation and the moment of recognition: dissociating perceptual recognition processes using fMRI (2007) · cites this paper as Shadlen and Newsome, 2001
In the citing paper
“The pattern of T R -dependent accumulation of BOLD activity observed in these regions is consistent with the buildup of neural activity found in studies of nonhuman primates making perceptual decisions (Hanes and Schall, 1996;Kim and Shadlen, 1999;Platt and Glimcher, 1999;Shadlen and Newsome, 2001;Ratcliff et al., 2003).”
From Evidence accumulation and the moment of recognition: dissociating perceptual recognition processes using fMRI (2007) · cites this paper as Shadlen and Newsome, 2001
Citations
Cites
(1966) · Medical Entomology and Zoology · Cited by 10,293
Applied Regression Analysis (2nd ed).
de Carvalho, J. F., Draper, N. R., & Smith, H. (1981) · Journal of the American Statistical Association · doi:10.2307/2287608 · Cited by 3,054
Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex
Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989) · Journal of Neurophysiology · doi:10.1152/jn.1989.61.2.331 · Cited by 2,685
Mountcastle, 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
The 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
Self-citationNeural correlates of decision variables in parietal cortex
Platt, M. L., & Glimcher, P. W. (1999) · Nature · doi:10.1038/22268 · Cited by 1,721
SPACE AND ATTENTION IN PARIETAL CORTEX
Colby, C. L., & Goldberg, M. E. (1999) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.22.1.319 · Cited by 1,710
Newsome, W., & Pare, E. (1988) · The Journal of Neuroscience · doi:10.1523/jneurosci.08-06-02201.1988 · Cited by 1,615
Self-citationImplantation of magnetic search coils for measurement of eye position: An improved method
Judge, S. J., Richmond, B. J., & Chu, F. C. (1980) · Vision Research · doi:10.1016/0042-6989(80)90128-5 · Cited by 1,530
Maunsell, J. H. R., & Essen, D. C. V. (1983) · Journal of Neurophysiology · doi:10.1152/jn.1983.49.5.1127 · Cited by 1,462
Research works printed but not linked: 8
- Evarts EV, 1968, Methods Med Res, 11, 241
- Gold JI, 2000, Soc Neurosci Ann Mtg, 25, 668
- Hays AV, 1982, WESCON Conf Proc, 2, 1
- Horwitz GD, 1999, Soc Neurosci Abstr, 25, 805
- Roitman JD, 1999, Soc Neurosci Abstr, 25, 1164
- Roitman JD, 1998, Soc Neurosci Abstr, 24, 262
- Schmolesky MT, 1998, J Neurosci, 79, 3272
- Shadlen M, 1994, Soc Neurosci Abstr, 20, 1279
Cited by
Sorted by citations
Items 401–500 of 1,001
Integration of Reinforcement Learning and Optimal Decision-Making Theories of the Basal Ganglia
Bogacz, R., & Larsen, T. (2011) · Neural Computation · doi:10.1162/neco_a_00103 · Cited by 86
Baumgarten, T. J., Schnitzler, A., & Lange, J. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu247 · Cited by 83
Been There, Seen That: A Neural Mechanism for Performing Efficient Visual Search
Mirpour, K., Arcizet, F., Ong, W. S., & Bisley, J. W. (2009) · Journal of Neurophysiology · doi:10.1152/jn.00688.2009 · Cited by 88
van der Groen, O., Tang, M. F., Wenderoth, N., & Mattingley, J. B. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006301 · Cited by 89
Vertechi, P., Lottem, E., Sarra, D., Godinho, B., Treves, I. N., Quendera, T., Lohuis, M. N. O., & Mainen, Z. F. (2020) · Neuron · doi:10.1016/j.neuron.2020.01.017 · Cited by 85
Three aspects of representation in neuroscience
Baker, B., Lansdell, B., & Kording, K. P. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.08.014 · Cited by 94
Developmental trajectory of transmission speed in the human brain
van Blooijs, D., van den Boom, M., van der Aar, J. F., Huiskamp, G. J. M., Castegnaro, G., Demuru, M., Zweiphenning, W. J. E. M., van Eijsden, P., Miller, K. J., Leijten, F. S. S., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01272-0 · Cited by 88
Nitz, D. A. (2008) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2008.08.007 · Cited by 85
Topographic organization in the brain: searching for general principles
Patel, G. H., Kaplan, D. M., & Snyder, L. H. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.03.008 · Cited by 85
Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition
Grossberg, S. (2007) · Progress in brain research · doi:10.1016/s0079-6123(06)65006-1 · Cited by 82
Testing Multi-Alternative Decision Models with Non-Stationary Evidence
Tsetsos, K., Usher, M., & McClelland, J. L. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00063 · Cited by 83
Intertemporal Choice as Discounted Value Accumulation
Rodriguez, C. A., Turner, B. M., & McClure, S. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0090138 · Cited by 82
Integration of Motor and Visual Information in the Parietal Area 5 During Locomotion
Beloozerova, I. N., & Sirota, M. G. (2003) · Journal of Neurophysiology · doi:10.1152/jn.01147.2002 · Cited by 80
Interpreting neurodynamics: concepts and facts
Harald Atmanspacher, A., & Rotter, S. (2008) · Cognitive Neurodynamics · doi:10.1007/s11571-008-9067-8 · Cited by 79
Lavazza, A. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00262 · Cited by 90
Neural circuitry of judgment and decision mechanisms
Opriș, I. C., & Bruce, C. J. (2005) · Brain Research Reviews · doi:10.1016/j.brainresrev.2004.11.001 · Cited by 80
Stochastic Dynamics Underlying Cognitive Stability and Flexibility
Ueltzhöffer, K., Armbruster-Genç, D. J. N., & Fiebach, C. J. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004331 · Cited by 78
Nonlinear neurobiological probability weighting functions for aversive outcomes
Berns, G. S., Capra, C. M., Chappelow, J., Moore, S. E., & NOUSSAIR, C. N. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.028 · Cited by 85
Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence
Odegaard, B., Grimaldi, P., Cho, S. H., Peters, M. A. K., Lau, H. C., & Basso, M. A. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1711628115 · Cited by 78
Visual Guidance in Control of Grasping
Janssen, P., & Scherberger, H. (2015) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071714-034028 · Cited by 86
Dendritic Integration of Sensory Evidence in Perceptual Decision-Making
Groschner, L. N., Hak, L. C. W., Bogacz, R., Dasgupta, S., & Miesenböck, G. (2018) · Cell · doi:10.1016/j.cell.2018.03.075 · Cited by 81
Reaction Time Correlations during Eye–Hand Coordination: Behavior and Modeling
Dean, H. L., Marti, D. N., Tsui, E., Rinzel, J., & Pesaran, B. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.4591-10.2011 · Cited by 79
O’Callaghan, C., Hall, J. M., Tomassini, A., Muller, A. J., Walpola, I. C., Moustafa, A. A., Shine, J. M., & Lewis, S. J. G. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.04.007 · Cited by 81
The Urge to Decide and Act: Implications for Brain Function and Dysfunction
Carland, M. A., Thura, D., & Cisek, P. (2019) · The Neuroscientist · doi:10.1177/1073858419841553 · Cited by 84
A general mechanism for decision-making in the human brain?
Rorie, A. E., & Newsome, W. T. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.12.007 · Cited by 80
Self-citationColor Discrimination Involves Ventral and Dorsal Stream Visual Areas
Claeys, K. G. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh040 · Cited by 82
Neural 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
Subjective Perceptual Distortions and Visual Dysfunction in Children with Autism
Davis, R. A. O., Bockbrader, M. A., Murphy, R. R., Hetrick, W. P., & O’Donnell, B. F. (2006) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-005-0055-0 · Cited by 76
Sylvester, C. M., Shulman, G. L., Jack, A. I., & Corbetta, M. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1141-09.2009 · Cited by 80
Reaction Time for Object Categorization Is Predicted by Representational Distance
Carlson, T. A., Ritchie, J. B., Kriegeskorte, N., Durvasula, S., & Ma, J. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00476 · Cited by 81
Neural Characterization of the Speed–Accuracy Tradeoff in a Perceptual Decision-Making Task
Wenzlaff, H., Bauer, M., Maeß, B., & Heekeren, H. R. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.4000-10.2011 · Cited by 83
Working memory retrieval as a decision process
Pearson, B. L., Raskevicius, J., Bays, P. M., Pertzov, Y., & Husain, M. (2014) · Journal of Vision · doi:10.1167/14.2.2 · Cited by 79
Active encoding of decisions about stimulus absence in primate prefrontal cortex neurons
Merten, K., & Nieder, A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121084109 · Cited by 75
The Timing of Perceptual Decisions for Ambiguous Face Stimuli in the Human Ventral Visual Cortex
McKeeff, T. J., & Tong, F. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhk015 · Cited by 76
Parameter recovery for the Leaky Competing Accumulator model
Miletić, S., Turner, B. M., Forstmann, B. U., & van Maanen, L. (2017) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2016.12.001 · Cited by 78
Decoding perceptual awareness across the brain with a no-report fMRI masking paradigm
Hatamimajoumerd, E., Murty, N. A. R., Pitts, M. A., & Cohen, M. A. (2022) · Current Biology · doi:10.1016/j.cub.2022.07.068 · Cited by 78
Building bridges between neural models and complex decision making behaviour
Busemeyer, J. R., Jessup, R. K., Johnson, J. G., & Townsend, J. T. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.05.043 · Cited by 75
Statistical decision theory to relate neurons to behavior in the study of covert visual attention
Eckstein, M. P., Peterson, M., Pham, B. T., & Droll, J. A. (2009) · Vision Research · doi:10.1016/j.visres.2008.12.008 · Cited by 76
Short-term memory traces for action bias in human reinforcement learning
Bogacz, R., McClure, S. M., Li, J., Cohen, J. D., & Montague, P. R. (2007) · Brain Research · doi:10.1016/j.brainres.2007.03.057 · Cited by 77
Decoding representations of scenes in the medial temporal lobes
Bonnici, H. M., Kumaran, D., Chadwick, M. J., Weiskopf, N., Hassabis, D., & Maguire, E. A. (2011) · Hippocampus · doi:10.1002/hipo.20960 · Cited by 80
Capturing the temporal evolution of choice across prefrontal cortex
Hunt, L. T., Behrens, T. E. J., Hosokawa, T., Wallis, J. D., & Kennerley, S. W. (2015) · eLife · doi:10.7554/elife.11945 · Cited by 81
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
Atypical Integration of Motion Signals in Autism Spectrum Conditions
Robertson, C. E., Martin, A. D., Baker, C. I., & Baron‐Cohen, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048173 · Cited by 76
Inference in the Brain: Statistics Flowing in Redundant Population Codes
Pitkow, X., & Angelaki, D. E. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.028 · Cited by 79
Hou, H., Zheng, Q., Zhao, Y., Pouget, A., & Gu, Y. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.038 · Cited by 72
Accumulation of Evidence during Sequential Decision Making: The Importance of Top–Down Factors
de Lange, F. P., Jensen, O. B., & Dehaene, S. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.4080-09.2010 · Cited by 75
Subjective visual awareness emerges prior to P3
Koivisto, M., Salminen‐Vaparanta, N., Grassini, S., & Revonsuo, A. (2016) · European Journal of Neuroscience · doi:10.1111/ejn.13264 · Cited by 79
The 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
Zysset, S., Wendt, C. S., Volz, K. G., Neumann, J., Huber, O., & von Cramon, D. Y. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.017 · Cited by 74
Humans treat unreliable filled-in percepts as more real than veridical ones
Ehinger, B., Häusser, K., Ossandón, J., & Peter König, B. (2017) · eLife · doi:10.7554/elife.21761 · Cited by 74
Topographic organization of macaque area LIP
Patel, G. H., Shulman, G. L., Baker, J. T., Akbudak, E., Snyder, A. Z., Snyder, L. H., & Corbetta, M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908092107 · Cited by 73
Stochastic Computations in Cortical Microcircuit Models
Habenschuss, S., Jonke, Z., & Maass, W. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003311 · Cited by 73
Bayesian model of dynamic image stabilization in the visual system
Burak, Y., Rokni, U., Meister, M., & Sompolinsky, H. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1006076107 · Cited by 71
Unconscious information changes decision accuracy but not confidence
Vlassova, A., Donkin, C., & Pearson, J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403619111 · Cited by 70
Smith, P. L. (2010) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2009.12.002 · Cited by 71
Neurobiology of decision-making: quo vadis?
Paulus, M. P. (2005) · Cognitive Brain Research · doi:10.1016/j.cogbrainres.2005.01.001 · Cited by 76
Influence of Branding on Preference-Based Decision Making
Philiastides, M. G., & Ratcliff, R. (2013) · Psychological Science · doi:10.1177/0956797612470701 · Cited by 82
A neural circuit model of decision uncertainty and change-of-mind
Atiya, N. A. A., Rañó, I., Prasad, G., & Wong‐Lin, K. (2019) · Nature Communications · doi:10.1038/s41467-019-10316-8 · Cited by 69
Koyama, M., Minale, F., Shum, J. W. H., Nishimura, N., Schaffer, C. B., & Fetcho, J. R. (2016) · eLife · doi:10.7554/elife.16808 · Cited by 69
Calcium dynamics regulating the timing of decision-making in C. elegans
Tanimoto, Y., Yamazoe-Umemoto, A., Fujita, K., Kawazoe, Y., Miyanishi, Y., Yamazaki, S. J., Fei, X., Busch, K. E., Gengyo‐Ando, K., Nakai, J., et al. (2017) · eLife · doi:10.7554/elife.21629 · Cited by 70
A Fluctuation-Driven Mechanism for Slow Decision Processes in Reverberant Networks
Marti, D. N., Deco, G., Mattia, M., Gigante, G., & Giudice, P. D. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002534 · Cited by 68
Time to decide: Diurnal variations on the speed and quality of human decisions
Leone, M. J., Slezak, D. F., Golombek, D. A., & Sigman, M. (2016) · Cognition · doi:10.1016/j.cognition.2016.10.007 · Cited by 69
Stramaglia, S., Scagliarini, T., Daniels, B. C., & Marinazzo, D. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2020.595736 · Cited by 68
Time is a rubberband: neuronal activity in monkey motor cortex in relation to time estimation
Renoult, L., Roux, S., & Riehle, A. (2006) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2006.04824.x · Cited by 70
Pedersen, M. L., & Frank, M. J. (2020) · Computational Brain & Behavior · doi:10.1007/s42113-020-00084-w · Cited by 67
Optimality and Robustness of a Biophysical Decision-Making Model under Norepinephrine Modulation
Eckhoff, P. A., Wong‐Lin, K., & Holmes, P. J. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.5024-08.2009 · Cited by 67
Spontaneous Neural Fluctuations Predict Decisions to Attend
Bengson, J. J., Kelley, T. A., Zhang, X., Wang, J.-L., & Mangun, G. R. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00650 · Cited by 70
Woolgar, A., Golland, P., & Bode, S. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.04.059 · Cited by 67
The Human Brain Encodes Event Frequencies While Forming Subjective Beliefs
d’Acremont, M., Schultz, W., & Bossaerts, P. L. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.5829-12.2013 · Cited by 72
Mutual benefits: Combining reinforcement learning with sequential sampling models
Miletić, S., Boag, R. J., & Forstmann, B. U. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.107261 · Cited by 70
A simon effect with stationary moving stimuli.
Schütz‐Bosbach, S., Prinz, W., & Kerzel, D. (2004) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.30.1.39 · Cited by 67
How Awareness Changes the Relative Weights of Evidence During Human Decision-Making
de Lange, F. P., van Gaal, S., Lamme, V. A. F., & Dehaene, S. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001203 · Cited by 65
The encoding of alternatives in multiple-choice decision making
Albantakis, L., & Deco, G. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901621106 · Cited by 66
Temporal dynamics of decision-making during motion perception in the visual cortex
Grossberg, S., & Pilly, P. K. (2008) · Vision Research · doi:10.1016/j.visres.2008.02.019 · Cited by 67
Metastable dynamics of neural circuits and networks
Brinkman, B. A. W., Yan, H., Maffei, A., Park, I. M., Fontanini, A., Wang, J., & La Camera, G. (2022) · Applied Physics Reviews · doi:10.1063/5.0062603 · Cited by 64
Wyder, M. T., Massoglia, D. P., & Stanford, T. R. (2004) · Journal of Neurophysiology · doi:10.1152/jn.01221.2003 · Cited by 65
Neural representations of motor plans, desired trajectories, and controlled objects
Cisek, P. (2005) · Cognitive Processing · doi:10.1007/s10339-004-0046-7 · Cited by 67
Measuring Intuition: Nonconscious Emotional Information Boosts Decision Accuracy and Confidence
Lufityanto, G., Donkin, C., & Pearson, J. (2016) · Psychological Science · doi:10.1177/0956797616629403 · Cited by 63
Fang, X., & Wang, J. (2020) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-121219-081656 · Cited by 64
Nayebi, A., Sagastuy-Breña, J., Bear, D. M., Kar, K., Kubilius, J., Ganguli, S., Sussillo, D., DiCarlo, J. J., & Yamins, D. L. K. (2022) · Neural Computation · doi:10.1162/neco_a_01506 · Cited by 64
Ongoing, rational calibration of reward-driven perceptual biases
Fan, Y., Gold, J. I., & Ding, L. (2018) · eLife · doi:10.7554/elife.36018 · Cited by 64
Changes of Mind in an Attractor Network of Decision-Making
Albantakis, L., & Deco, G. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002086 · Cited by 67
Human visual and parietal cortex encode visual choices independent of motor plans
Hebart, M. N., Donner, T. H., & Haynes, J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.08.027 · Cited by 64
Pantoja, J., Ribeiro, S. T. G., Wiest, M., Soares, E. S., Gervasoni, D., Lemos, N. A. M., & Nicolelis, M. A. L. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.5279-06.2007 · Cited by 63
Neural correlates of a postponed decision report
Lemus, L., Hernández, A., Luna, R., Zainos, A., Nácher, V., & Romo, R. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707961104 · Cited by 63
Hyperpolarization-activated graded persistent activity in the prefrontal cortex
Winograd, M., Alain Destexhe, A., & Sanchez-Vives, M. V. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800360105 · Cited by 63
Active Vision in Parietal and Extrastriate Cortex
Merriam, E. P., & Colby, C. L. (2005) · The Neuroscientist · doi:10.1177/1073858405276871 · Cited by 62
Tasks and their role in visual neuroscience
Kay, K., Bonnen, K., Denison, R. N., Arcaro, M. J., & Barack, D. L. (2023) · Neuron · doi:10.1016/j.neuron.2023.03.022 · Cited by 61
The hippocampus and exploration: dynamically evolving behavior and neural representations
Johnson, A., Varberg, Z., Benhardus, J., Maahs, A., & Schrater, P. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00216 · Cited by 61
A brainstem integrator for self-location memory and positional homeostasis in zebrafish
Yang, E., Zwart, M., James, B., Rubinov, M., Wei, Z., Narayan, S., Vladimirov, N., Mensh, B. D., Fitzgerald, J. E., & Ahrens, M. B. (2022) · Cell · doi:10.1016/j.cell.2022.11.022 · Cited by 63
Dynamic Integration of Reward and Stimulus Information in Perceptual Decision-Making
Gao, J., Tortell, R. K., & McClelland, J. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016749 · Cited by 61
On the Evolution and Optimality of Mood States
Trimmer, P. C., Paul, E. S., Mendl, M., McNamara, J. M., & Houston, A. I. (2013) · Behavioral Sciences · doi:10.3390/bs3030501 · Cited by 61
Locus coeruleus in memory formation and Alzheimer's disease
James, T., Kula, B., Choi, S., Khan, S. S., Bekar, L. K., & Smith, N. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.15045 · Cited by 65
Costello, M. G., Zhu, D., Salinas, E., & Stanford, T. R. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1899-13.2013 · Cited by 60
Prefrontal Contribution to Decision-Making under Free-Choice Conditions
Funahashi, S. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00431 · Cited by 68
Herrington, T. M., & Assad, J. A. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1916-09.2009 · Cited by 62
Effect of target-distractor similarity on FEF visual selection in the absence of the target
Schall, J. D., Sato, T., Watanabe, K., & Thompson, K. G. (2003) · Experimental Brain Research · doi:10.1007/s00221-003-1461-1 · Cited by 62
Categorization=decision making+generalization
Seger, C. A., & Peterson, E. J. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.03.015 · Cited by 65
Theoretical tools for understanding and aiding dynamic decision making
Busemeyer, J. R., & Pleskac, T. J. (2009) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2008.12.007 · Cited by 62
Selection and inhibition mechanisms for human voluntary action decisions
Zhang, J., Hughes, L. E., & Rowe, J. B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.058 · Cited by 62
Metadata
- Authors
- Shadlen, M. N., & Newsome, W. T.
- Affiliations
- Howard Hughes Medical Institute (US)
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2001-10-01
- Volume
- 86
- Issue
- 4
- Pages
- 1916-1936
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- OpenAlex
- W2122066429
- Cited by
- 1,755
- References
- 95
- Citations by year
- 2026: 61 · 2025: 77 · 2024: 71 · 2023: 61 · 2022: 90 · 2021: 74 · 2020: 74 · 2019: 85 · 2018: 76 · 2017: 81 · 2016: 77 · 2015: 86 · 2014: 99 · 2013: 93 · 2012: 87
- FWCI
- 15.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Eye Institute (EY11378, EY 05603, R01EY011378)
- National Center for Research Resources (RR00166, P51RR000166)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- lateral intraparietal area, posterior parietal cortex, perceptual decision making, motion direction discrimination, random dot motion, saccades, persistent activity, single-unit activity, response fields, gaze shifts, rhesus monkeys
- MeSH terms
- Action Potentials, Animals, Discrimination, Psychological, Electrophysiology, Female, Macaca mulatta, Male, Motion Perception, Motor Neurons, Neurons, Afferent, Parietal Lobe, Photic Stimulation, Psychophysics, Saccades, Linear Models
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
