P280 Cerebellar neural manifold encoding complex eye movements in 2D
Juliana Silva de Deus1, Akshay Markanday2, Erik De Schutter1, Peter Thier2,Sungho Hong*1,3
1Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Okinawa, Japan
2Department of Cognitive Neurology, Hertie Institute, University of Tübingen, Tübingen, Germany
3Center for Cognition and Sociality, Institute for Basic Science, Daejeon, South Korea
*Email: sunghohong@ibs.re.kr
Introduction
Kinematic parameters of our movements, such as velocity and duration, can undergo random and systematic changes, but movement endpoints can be precisely maintained. The cerebellum is well-known for its role in thisfunction[1], but how its neurons concurrently encode several kinematic parameters, necessary for movement precision, has been unknown.We recently identified low-dimensional patterns, called the neural manifold, in the activity of the cerebellar neurons and showed that those multi-dimensional patterns encoded the peak velocity and duration of 1D eye movements, contributing to flexible control of those parameters [2]. In this study, we investigated how those findings can extend to 2D eye movements made in different directions.
Methods
We analyzed the activity of 54 cerebellar Purkinje cells (PC) from the oculomotor vermis in three adult male rhesus monkeys performing two different saccadic eye movement tasks. In the first, the animals made 15° saccades from a fixation point to a visual targetrandomly presented at one of the ten angles(0°-315°, 45° intervals).In the second, they performed a cross-axis adaptation task [3] where initial horizontal jumps of a target from a fixation point were followed by 5° vertical leapsbefore finishing the primary saccades. We analyzed the PC simple spike (SS) activity by identifying its low-dimensional manifold and examining how the manifold varies with the saccade angle and complex spike (CS) firing.
Results
In many PCs (n=39), CSs fired between 100ms and 200 ms after a targetonsetwith well-defined preference for certain target directions (θCS-ON), confirming the directional nature of CS firing for retinalslips[4-6]. We also identified the PC-SS manifold (d=4, explaining >88% variance) for saccadic eye movements with a remarkably simple structure comprising direction-independent latent dynamics and dependent, multi-dimensional gain field, generalizing previous studies [2,7]. How CS and SS firings depend on movement direction (θ) in individual PCs was too heterogeneous to show a clear correlation (P=0.22). However, we found that the gain field looked highly organized for θ-θCS-ONbut much less for θ.
Discussion
Together with our previous study [2], these results show that PC population firing has a remarkably simple structure for representing several kinematic parameters of eye movements, such as velocity, duration, and direction, simultaneously and independently via a low-dimensional neural manifold. Our findings suggest that the cerebellar neural circuit generates neural dynamics optimal for flexible and precise control of complex movements with many degrees of freedom.
Acknowledgements
A.M. and P.T. were supported by DFG Research Unit 1847 “The Physiology of distributed computing underlying higher brain functions in non-human primates.” J.S.D., S.H., and E.D.S. were supported by the Okinawa Institute of Science and Technology Graduate University. S.H. was also supported by the Center for Cognition and Sociality (IBS‐R001‐D2), Institute for Basic Science, South Korea.
References
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