Noise correlations in cortical area MT and their potential impact on trial-by-trial variation in the direction and speed of smooth-pursuit eye movements.

Smooth-pursuit eye movements are variable, even when the same tracking target motion is repeated many times. We asked whether variation in pursuit could arise from noise in the response of visual motion neurons in the middle temporal visual area (MT). In physiological experiments, we evaluated the mean, variance, and trial-by-trial correlation in the spike counts of pairs of simultaneously recorded MT neurons. The correlations between responses of pairs of MT neurons are highly significant and are stronger when the two neurons in a pair have similar preferred speeds, directions, or receptive field locations. Spike count correlation persists when the same exact stimulus form is repeatedly presented. Spike count correlations increase as the analysis window increases because of correlations in the responses of individual neurons across time. Spike count correlations are highest at speeds below the preferred speeds of the neuron pair and increase as the contrast of a square-wave grating is decreased. In computational analyses, we evaluated whether the correlations and variation across the population response in MT could drive the observed behavioral variation in pursuit direction and speed. We created model population responses that mimicked the mean and variance of MT neural responses as well as the observed structure and amplitude of noise correlations between pairs of neurons. A vector-averaging decoding computation revealed that the observed variation in pursuit could arise from the MT population response, without postulating other sources of motor variation.

[1]  William Bialek,et al.  Spikes: Exploring the Neural Code , 1996 .

[2]  W. Bair,et al.  Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior , 2001, The Journal of Neuroscience.

[3]  A. P. Georgopoulos,et al.  Variability and Correlated Noise in the Discharge of Neurons in Motor and Parietal Areas of the Primate Cortex , 1998, The Journal of Neuroscience.

[4]  Michael N. Shadlen,et al.  Noise, neural codes and cortical organization , 1994, Current Opinion in Neurobiology.

[5]  Jaime de la Rocha,et al.  Supplementary Information for the article ‘ Correlation between neural spike trains increases with firing rate ’ , 2007 .

[6]  K. Hoffmann,et al.  Continuous mapping of direction selectivity in the cat's visual cortex , 1976, Neuroscience Letters.

[7]  R. Reid,et al.  Rules of Connectivity between Geniculate Cells and Simple Cells in Cat Primary Visual Cortex , 2001, The Journal of Neuroscience.

[8]  G. P. Moore,et al.  Neuronal spike trains and stochastic point processes. I. The single spike train. , 1967, Biophysical journal.

[9]  G. Orban,et al.  Human velocity and direction discrimination measured with random dot patterns , 1988, Vision Research.

[10]  Haim Sompolinsky,et al.  Nonlinear Population Codes , 2004, Neural Computation.

[11]  Terrence J. Sejnowski,et al.  Neuronal Tuning: To Sharpen or Broaden? , 1999, Neural Computation.

[12]  G. L. Gerstein,et al.  Interactions between cat striate cortex neurons , 2004, Experimental Brain Research.

[13]  W. Newsome,et al.  Deficits in visual motion processing following ibotenic acid lesions of the middle temporal visual area of the macaque monkey , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[14]  A. Pouget,et al.  Neural correlations, population coding and computation , 2006, Nature Reviews Neuroscience.

[15]  S G Lisberger,et al.  Shifts in the Population Response in the Middle Temporal Visual Area Parallel Perceptual and Motor Illusions Produced by Apparent Motion , 2001, The Journal of Neuroscience.

[16]  J T McIlwain,et al.  Distributed spatial coding in the superior colliculus: A review , 1991, Visual Neuroscience.

[17]  W T Newsome,et al.  How Is a Sensory Map Read Out? Effects of Microstimulation in Visual Area MT on Saccades and Smooth Pursuit Eye Movements , 1997, The Journal of Neuroscience.

[18]  W. Bialek,et al.  Time Course of Information about Motion Direction in Visual Area MT of Macaque Monkeys , 2004, The Journal of Neuroscience.

[19]  Anthony J. Movshon,et al.  Optimal representation of sensory information by neural populations , 2006, Nature Neuroscience.

[20]  T. Wiesel,et al.  Clustered intrinsic connections in cat visual cortex , 1983, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[21]  Maninder K. Kahlon,et al.  Visual Motion Analysis for Pursuit Eye Movements in Area MT of Macaque Monkeys , 1999, The Journal of Neuroscience.

[22]  W. Bialek,et al.  A sensory source for motor variation , 2005, Nature.

[23]  Jan J. Koenderink,et al.  Information in channel-coded systems: correlated receivers , 1992, Biological Cybernetics.

[24]  H. Sompolinsky,et al.  Population coding in neuronal systems with correlated noise. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Robert G. Turcott,et al.  Temporal correlation in cat striate-cortex neural spike trains , 1996 .

[26]  W. Newsome,et al.  Context-Dependent Changes in Functional Circuitry in Visual Area MT , 2008, Neuron.

[27]  M. A. Smith,et al.  Spatial and Temporal Scales of Neuronal Correlation in Primary Visual Cortex , 2008, The Journal of Neuroscience.

[28]  William Bialek,et al.  Time Course of Precision in Smooth-Pursuit Eye Movements of Monkeys , 2007, The Journal of Neuroscience.

[29]  W. Bialek,et al.  The Neural Basis for Combinatorial Coding in a Cortical Population Response , 2008, The Journal of Neuroscience.

[30]  Nicholas J. Priebe,et al.  Estimating Target Speed from the Population Response in Visual Area MT , 2004, The Journal of Neuroscience.

[31]  R. Zemel,et al.  Inference and computation with population codes. , 2003, Annual review of neuroscience.

[32]  T. Wiesel,et al.  Relationships between horizontal interactions and functional architecture in cat striate cortex as revealed by cross-correlation analysis , 1986, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[33]  M. A. Smith,et al.  Stimulus Dependence of Neuronal Correlation in Primary Visual Cortex of the Macaque , 2005, The Journal of Neuroscience.

[34]  D. Sparks,et al.  Size and distribution of movement fields in the monkey superior colliculus , 1976, Brain Research.

[35]  W. Newsome,et al.  Correlation between Speed Perception and Neural Activity in the Middle Temporal Visual Area , 2005, The Journal of Neuroscience.

[36]  S. Lisberger,et al.  Variation, Signal, and Noise in Cerebellar Sensory–Motor Processing for Smooth-Pursuit Eye Movements , 2007, The Journal of Neuroscience.

[37]  J. Movshon,et al.  A computational analysis of the relationship between neuronal and behavioral responses to visual motion , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[38]  A. P. Georgopoulos,et al.  Neuronal population coding of movement direction. , 1986, Science.

[39]  T. Albright,et al.  Recent History of Stimulus Speeds Affects the Speed Tuning of Neurons in Area MT , 2007, The Journal of Neuroscience.

[40]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[41]  S. Lisberger,et al.  Normal performance and expression of learning in the vestibulo-ocular reflex (VOR) at high frequencies. , 2005, Journal of neurophysiology.

[42]  D. Fitzpatrick,et al.  Orientation Selectivity and the Arrangement of Horizontal Connections in Tree Shrew Striate Cortex , 1997, The Journal of Neuroscience.

[43]  Ehud Zohary,et al.  Correlated neuronal discharge rate and its implications for psychophysical performance , 1994, Nature.

[44]  John H. R. Maunsell,et al.  Visual response latencies in striate cortex of the macaque monkey. , 1992, Journal of neurophysiology.

[45]  D. Sparks,et al.  Population coding of saccadic eye movements by neurons in the superior colliculus , 1988, Nature.

[46]  D C Van Essen,et al.  Functional properties of neurons in middle temporal visual area of the macaque monkey. I. Selectivity for stimulus direction, speed, and orientation. , 1983, Journal of neurophysiology.

[47]  D. Perrett,et al.  The `Ideal Homunculus': decoding neural population signals , 1998, Trends in Neurosciences.

[48]  Edward H. Adelson,et al.  Motion illusions as optimal percepts , 2002, Nature Neuroscience.

[49]  Nicholas J. Priebe,et al.  Constraints on the source of short-term motion adaptation in macaque area MT. I. the role of input and intrinsic mechanisms. , 2002, Journal of Neurophysiology.

[50]  G. P. Moore,et al.  Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains. , 1967, Biophysical journal.

[51]  R. Douglas,et al.  A functional microcircuit for cat visual cortex. , 1991, The Journal of physiology.

[52]  G. DeAngelis,et al.  A Logarithmic, Scale-Invariant Representation of Speed in Macaque Middle Temporal Area Accounts for Speed Discrimination Performance , 2005, The Journal of Neuroscience.

[53]  C. Rashbass,et al.  The relationship between saccadic and smooth tracking eye movements , 1961, The Journal of physiology.

[54]  TJ Gawne,et al.  How independent are the messages carried by adjacent inferior temporal cortical neurons? , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[55]  Peter Dayan,et al.  The Effect of Correlated Variability on the Accuracy of a Population Code , 1999, Neural Computation.

[56]  A. Pouget,et al.  Tuning curve sharpening for orientation selectivity: coding efficiency and the impact of correlations , 2004, Nature Neuroscience.

[57]  K. Hoffmann,et al.  Synchronization of Neuronal Activity during Stimulus Expectation in a Direction Discrimination Task , 1997, The Journal of Neuroscience.