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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.
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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
Flagged first, then by citations
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
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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.
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