One of the important functions of visual inputs is to guide motor activity, especially eye movements.Primates can used smooth pursuit eye movements to rotate their eyes smoothly to keep them pointed atsmall objects that are moving slowly and smoothly, a function that is much more poorly expressed in mostother species. Moving objects cause neural activity in a part of the visual cortex called the 'middletemporal visual area' or MT, where neurons respond only to moving objects and encode the direction andspeed of object motion. MT provides the visual inputs for smooth pursuit eye movements, but speed anddirection are encoded only in the response of a large number of MT neurons, and not in the responses ofany individual neuron. Therefore, the population response in MT needs to be 'decoded' to provide motorcommands that indicate the required direction and speed of smooth eye velocity. This proposal usesawake, behaviorally-trained rhesus monkeys to ask how visual population decoding is done by neuralcircuits. First, it proposes to use a combination of recordings of the first 100 ms of pursuit eye movementsand the electrical activity of MT neurons to ask whether certain sub-populations of MT neurons areselectively involved in pursuit. The approach is to characterize the effect of changes in stimulus form onthe variation in eye movement, and then to determine whether the parallel effects on the responses ofcertain sub-populations of MT neurons vary in a way that is appropriate to cause the effects on eyemovement. Second, the proposal will use a combination of experiment and computation to characterizehow visual population responses are decoded using biologically-plausible models of neural circuits. Theapproach will be to create a library of different circuit models that make different predictions for theresponses of doable experiments. The experiments consist mainly of assessing the correlations betweenthe trial-by-trial variations of MT responses and pursuit eye movements. Special attention will be paid tohow the MT-pursuit correlations vary as a function of the preferred speed of an MT neuron, a feature thatis particularly sensitive to the details of how the neural circuit decoding model is implemented. Aninterplay between computation and experiment will constrain severely the neural mechanisms that areused for visual population decoding in the brain.

Public Health Relevance

Many of our actions are guided by what we see. This application asks how inputs through our eyes are processed by the brain and converted into contractions of the muscles that will cause us to move our eyes, focusing on eye tracking of moving objects. Understanding how visual inputs guide movement in normal subjects will inform diagnosis and therapy of eye movement disorders. It will be especially important for relieving the double vision caused by misalignments of the eyes and the poor vision that results from eye movement disorders that make it difficult to track moving objects.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
7R01EY003878-31
Application #
8470425
Study Section
Central Visual Processing Study Section (CVP)
Program Officer
Steinmetz, Michael A
Project Start
1981-09-01
Project End
2014-08-31
Budget Start
2012-06-01
Budget End
2012-08-31
Support Year
31
Fiscal Year
2011
Total Cost
$125,590
Indirect Cost
Name
Duke University
Department
Biology
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Lee, Joonyeol; Joshua, Mati; Medina, Javier F et al. (2016) Signal, Noise, and Variation in Neural and Sensory-Motor Latency. Neuron 90:165-76
Lisberger, Stephen G; Medina, Javier F (2015) How and why neural and motor variation are related. Curr Opin Neurobiol 33:110-6
Joshua, M; Lisberger, S G (2015) A tale of two species: Neural integration in zebrafish and monkeys. Neuroscience 296:80-91
Joshua, Mati; Tokiyama, Stefanie; Lisberger, Stephen G (2015) Interactions between target location and reward size modulate the rate of microsaccades in monkeys. J Neurophysiol 114:2616-24
Ravits, John (2014) Focality, stochasticity and neuroanatomic propagation in ALS pathogenesis. Exp Neurol 262 Pt B:121-6
Yang, Yan; Lisberger, Stephen G (2014) Purkinje-cell plasticity and cerebellar motor learning are graded by complex-spike duration. Nature 510:529-32
Yang, Yan; Lisberger, Stephen G (2014) Role of plasticity at different sites across the time course of cerebellar motor learning. J Neurosci 34:7077-90
Lee, Joonyeol; Lisberger, Stephen G (2013) Gamma synchrony predicts neuron-neuron correlations and correlations with motor behavior in extrastriate visual area MT. J Neurosci 33:19677-88
Huang, Xin; Lisberger, Stephen G (2013) Circuit mechanisms revealed by spike-timing correlations in macaque area MT. J Neurophysiol 109:851-66
Hohl, Sonja S; Chaisanguanthum, Kris S; Lisberger, Stephen G (2013) Sensory population decoding for visually guided movements. Neuron 79:167-79

Showing the most recent 10 out of 83 publications