Literature DB >> 28100751

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout.

Stephane Clery1, Bruce G Cumming2, Hendrikje Nienborg3.   

Abstract

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal "noise" correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. SIGNIFICANCE STATEMENT: Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain.
Copyright © 2017 the authors 0270-6474/17/370715-11$15.00/0.

Keywords:  V2; choice probability; discrimination; disparity; nonhuman primate; readout

Mesh:

Year:  2017        PMID: 28100751      PMCID: PMC5242413          DOI: 10.1523/JNEUROSCI.2445-16.2016

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  61 in total

1.  A specialization for relative disparity in V2.

Authors:  O M Thomas; B G Cumming; A J Parker
Journal:  Nat Neurosci       Date:  2002-05       Impact factor: 24.884

2.  Contribution of middle temporal area to coarse depth discrimination: comparison of neuronal and psychophysical sensitivity.

Authors:  Takanori Uka; Gregory C DeAngelis
Journal:  J Neurosci       Date:  2003-04-15       Impact factor: 6.167

3.  Neuronal correlates of decision-making in secondary somatosensory cortex.

Authors:  Ranulfo Romo; Adrián Hernández; Antonio Zainos; Luis Lemus; Carlos D Brody
Journal:  Nat Neurosci       Date:  2002-11       Impact factor: 24.884

4.  Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4.

Authors:  Jude F Mitchell; Kristy A Sundberg; John H Reynolds
Journal:  Neuron       Date:  2009-09-24       Impact factor: 17.173

5.  A computational analysis of the relationship between neuronal and behavioral responses to visual motion.

Authors:  M N Shadlen; K H Britten; W T Newsome; J A Movshon
Journal:  J Neurosci       Date:  1996-02-15       Impact factor: 6.167

6.  How Can Single Sensory Neurons Predict Behavior?

Authors:  Xaq Pitkow; Sheng Liu; Dora E Angelaki; Gregory C DeAngelis; Alexandre Pouget
Journal:  Neuron       Date:  2015-07-15       Impact factor: 17.173

Review 7.  Measuring and interpreting neuronal correlations.

Authors:  Marlene R Cohen; Adam Kohn
Journal:  Nat Neurosci       Date:  2011-06-27       Impact factor: 24.884

8.  Estimates of the contribution of single neurons to perception depend on timescale and noise correlation.

Authors:  Marlene R Cohen; William T Newsome
Journal:  J Neurosci       Date:  2009-05-20       Impact factor: 6.167

9.  Neurons in dorsal visual area V5/MT signal relative disparity.

Authors:  Kristine Krug; Andrew J Parker
Journal:  J Neurosci       Date:  2011-12-07       Impact factor: 6.167

10.  Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT.

Authors:  Klaus Wimmer; Albert Compte; Alex Roxin; Diogo Peixoto; Alfonso Renart; Jaime de la Rocha
Journal:  Nat Commun       Date:  2015-02-04       Impact factor: 14.919

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  4 in total

1.  Differentiating between Models of Perceptual Decision Making Using Pupil Size Inferred Confidence.

Authors:  Katsuhisa Kawaguchi; Stephane Clery; Paria Pourriahi; Lenka Seillier; Ralf M Haefner; Hendrikje Nienborg
Journal:  J Neurosci       Date:  2018-08-31       Impact factor: 6.167

2.  A general decoding strategy explains the relationship between behavior and correlated variability.

Authors:  Amy M Ni; Chengcheng Huang; Brent Doiron; Marlene R Cohen
Journal:  Elife       Date:  2022-06-06       Impact factor: 8.713

3.  Serotonin Decreases the Gain of Visual Responses in Awake Macaque V1.

Authors:  Lenka Seillier; Corinna Lorenz; Katsuhisa Kawaguchi; Torben Ott; Andreas Nieder; Paria Pourriahi; Hendrikje Nienborg
Journal:  J Neurosci       Date:  2017-10-17       Impact factor: 6.167

4.  Can Serial Dependencies in Choices and Neural Activity Explain Choice Probabilities?

Authors:  Jan-Matthis Lueckmann; Jakob H Macke; Hendrikje Nienborg
Journal:  J Neurosci       Date:  2018-02-12       Impact factor: 6.167

  4 in total

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