Decision-related activity in sensory neurons reflects more than a neuron’s causal effect

During perceptual decisions, the activity of sensory neurons correlates with a subject’s percept, even when the physical stimulus is identical. The origin of this correlation is unknown. Current theory proposes a causal effect of noise in sensory neurons on perceptual decisions, but the correlation could result from different brain states associated with the perceptual choice (a top-down explanation). These two schemes have very different implications for the role of sensory neurons in forming decisions. Here we use white-noise analysis to measure tuning functions of V2 neurons associated with choice and simultaneously measure how the variation in the stimulus affects the subjects’ (two macaques) perceptual decisions. In causal models, stronger effects of the stimulus upon decisions, mediated by sensory neurons, are associated with stronger choice-related activity. However, we find that over the time course of the trial these measures change in different directions—at odds with causal models. An analysis of the effect of reward size also supports this conclusion. Finally, we find that choice is associated with changes in neuronal gain that are incompatible with causal models. All three results are readily explained if choice is associated with changes in neuronal gain caused by top-down phenomena that closely resemble attention. We conclude that top-down processes contribute to choice-related activity. Thus, even forming simple sensory decisions involves complex interactions between cognitive processes and sensory neurons.

[1]  B. Richmond,et al.  Implantation of magnetic search coils for measurement of eye position: An improved method , 1980, Vision Research.

[2]  N. Logothetis,et al.  Neuronal correlates of subjective visual perception. , 1989, Science.

[3]  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.

[4]  A. Ahumada Perceptual Classification Images from Vernier Acuity Masked by Noise , 1996 .

[5]  A. Grinvald,et al.  Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses , 1996, Science.

[6]  N. Logothetis,et al.  Activity changes in early visual cortex reflect monkeys' percepts during binocular rivalry , 1996, Nature.

[7]  K. H. Britten,et al.  A relationship between behavioral choice and the visual responses of neurons in macaque MT , 1996, Visual Neuroscience.

[8]  Dario L. Ringach,et al.  Dynamics of orientation tuning in macaque primary visual cortex , 1997, Nature.

[9]  Christopher W. Tyler,et al.  One Eye is Usually Centred Horizontally (and near the Golden Section Vertically) in Portraits over the Past 500 Years , 1997 .

[10]  A. Parker,et al.  Binocular Neurons in V1 of Awake Monkeys Are Selective for Absolute, Not Relative, Disparity , 1999, The Journal of Neuroscience.

[11]  Stefan Treue,et al.  Feature-based attention influences motion processing gain in macaque visual cortex , 1999, Nature.

[12]  Colin Blakemore,et al.  Probing the human stereoscopic system with reverse correlation , 1999, Nature.

[13]  J. Gold,et al.  Representation of a perceptual decision in developing oculomotor commands , 2000, Nature.

[14]  A. Parker,et al.  Perceptually Bistable Three-Dimensional Figures Evoke High Choice Probabilities in Cortical Area MT , 2001, The Journal of Neuroscience.

[15]  David A. Leopold,et al.  Stable perception of visually ambiguous patterns , 2002, Nature Neuroscience.

[16]  J. Schall Neural correlates of decision processes: neural and mental chronometry , 2003, Current Opinion in Neurobiology.

[17]  M. Shadlen,et al.  A role for neural integrators in perceptual decision making. , 2003, Cerebral cortex.

[18]  David J. Heeger,et al.  Neuronal correlates of perception in early visual cortex , 2003, Nature Neuroscience.

[19]  S. Treue,et al.  Feature-Based Attention Increases the Selectivity of Population Responses in Primate Visual Cortex , 2004, Current Biology.

[20]  K. Krug A common neuronal code for perceptual processes in visual cortex? Comparing choice and attentional correlates in V5/MT. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[21]  G. DeAngelis,et al.  Contribution of Area MT to Stereoscopic Depth Perception Choice-Related Response Modulations Reflect Task Strategy , 2004, Neuron.

[22]  A. Dean The variability of discharge of simple cells in the cat striate cortex , 2004, Experimental Brain Research.

[23]  T. Pasternak,et al.  Working memory in primate sensory systems , 2005, Nature Reviews Neuroscience.

[24]  D. Bradley,et al.  Neural population code for fine perceptual decisions in area MT , 2005, Nature Neuroscience.

[25]  Ichiro Fujita,et al.  Neural Correlates of Fine Depth Discrimination in Monkey Inferior Temporal Cortex , 2005, The Journal of Neuroscience.

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

[27]  Wei Ji Ma,et al.  Bayesian inference with probabilistic population codes , 2006, Nature Neuroscience.

[28]  B. Cumming,et al.  Macaque V2 Neurons, But Not V1 Neurons, Show Choice-Related Activity , 2006, The Journal of Neuroscience.

[29]  Michael N. Shadlen,et al.  Probabilistic reasoning by neurons , 2007, Nature.

[30]  J. Gold,et al.  The neural basis of decision making. , 2007, Annual review of neuroscience.

[31]  B. Cumming,et al.  Psychophysically measured task strategy for disparity discrimination is reflected in V2 neurons , 2007, Nature Neuroscience.

[32]  C. Gilbert,et al.  Brain States: Top-Down Influences in Sensory Processing , 2007, Neuron.

[33]  K. H. Britten,et al.  A relationship between behavioral choice and the visual responses of neurons in macaque , 2008 .