Sensory Population Decoding for Visually Guided Movements

• Published in: Neuron (Cambridge, Mass.) Mass.), 2013-07, Vol.79 (1), p.167-179
• Main Authors: Hohl, Sonja S., Chaisanguanthum, Kris S., Lisberger, Stephen G.
• Format: Article
• Language: English
• Subjects: Action Potentials - physiology; Animals; Behavior; Eye Movements - physiology; Hypotheses; Macaca mulatta; Male; Models, Neurological; Motion Perception - physiology; Neurons; Neurons - physiology; Noise; Photic Stimulation; Population; Pursuit, Smooth - physiology; Reaction Time - physiology; Studies; Visual Cortex - physiology
• ISSN: 0896-6273; 1097-4199
• DOI: 10.1016/j.neuron.2013.05.026

We have used a new approach to study the neural decoding function that converts the population response in extrastriate area MT into estimates of target motion to drive smooth pursuit eye movement. Experiments reveal significant trial-by-trial correlations between the responses of MT neurons and the initiation of pursuit. The preponderance of significant correlations and the relatively low reduction in noise between MT and the behavioral output support the hypothesis of a sensory origin for at least some of the trial-by-trial variation in pursuit initiation. The finding of mainly positive MT-pursuit correlations, whether the target speed is faster or slower than the neuron’s preferred speed, places strong constraints on the neural decoding computation. We propose that decoding is based on normalizing a weighted population vector of opponent motion responses; normalization comes from neurons uncorrelated with those used to compute the weighted population vector. •The responses of single MT neurons predict trial-to-trial variation in eye movement•The correlations imply that variation in pursuit initiation arises in sensory noise•Noise reduction between MT and pursuit initiation is relatively small•Sensory decoding normalizes with an uncorrelated estimate of MT population response Hohl et al. show that responses of individual sensory neurons in extrastriate visual area MT predict trial-by-trial variation in the initiation of visually-guided eye movement. The nature of the “MT-pursuit” correlations reveals how the brain uses a population of neurons to estimate sensory parameters.