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001017081 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-03923
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001017081 1001_ $$0P:(DE-Juel1)176777$$aEssink, Simon$$b0$$eCorresponding author$$ufzj
001017081 1112_ $$aBernstein Conference 2023$$cBerlin$$d2023-09-26 - 2023-09-29$$gBC23$$wGermany
001017081 245__ $$aBimodal distribution of preferred directions to hand movements in visuo-parietal areas
001017081 260__ $$c2023
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001017081 520__ $$aDecades of intense research established that neurons in monkey motor cortex are tuned to hand movement direction with a cosine-like function that can be characterized by a preferred direction (PD) [1]. Although PDs across neurons were assumed to be uniformly distributed, recent experiments showed that PDs are bimodally distributed if hand movements are constrained to a horizontal work area [2,3]. Several modeling studies [4,5,6] attribute this biased distribution to the limb biomechanics.In electrophysiological recordings via multiple Utah electrode arrays along the dorsal visual stream of macaque monkeys [7], we reproduce the biased distribution of PDs in motor cortex and further elucidate if such a bias extends to visual and parietal areas.Macaque monkeys were trained to perform a visually guided sequential reaching task using a robotic exoskeleton system (KINARM Exoskeleton Laboratory, BKIN Technologies) that constrains movements to the horizontal plane. Both eye and hand movements were recorded along with extracellular potentials from 224 channels across visual (V1/V2), parietal (DP, 7A) and motor (M1/PMd) areas. After spike sorting, we relate spiking activity of single units to the instantaneous hand movement direction through Poisson Generalized Linear Models (GLMs) [8], thus estimating the directional tuning curve and the preferred direction of each unit. The resulting distributions of PDs per area were tested for bimodality using the Rayleigh r statistic.We confirm the bimodality (at forward-left and backwards-right directions) of the distribution of PDs for neurons in the motor cortex. Interestingly, we observe the same tendencies in all visual and parietal areas and find statistical significance of the results.We then investigate whether our observations are a genuine expression of the hand movement or rather arise in response to co-occurring sensory and/or behavioral events (e.g. appearance of visual stimuli toward which the monkeys moved their hands). To exclude such confounds, we chose to fit more complex GLMs to the neural activity that account for the impact of various modalities (visual input, eye/hand position, saccade, and hand movement) on the activity. Even after such a control, we observe significant bimodal distributions of PDs in V1/V2, DP and 7A being attributed only to the hand movement regressors, suggesting an influence of limb biomechanics even in the lower hierarchies of the dorsal visual stream.References    [1] Georgopoulos, A., Kalaska, J., Caminiti, R. & Massey, J. On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. J. Neurosci. 2, 1527–1537 (1982)., 10.1523/JNEUROSCI.02-11-01527.1982    [2] Scott, S. H., Gribble, P. L., Graham, K. M. & Cabel, D. W. Dissociation between hand motion and population vectors from neural activity in motor cortex. Nature 413, 161–165 (2001)., 10.1038/35093102    [3] Suminski, A. J., Mardoum, P., Lillicrap, T. P. & Hatsopoulos, N. G. Temporal evolution of both premotor and motor cortical tuning properties reflect changes in limb biomechanics. Journal of Neurophysiology 113, 2812–2823 (2015)., 10.1152/jn.00486.2014    [4] Lillicrap, T. P. & Scott, S. H. Preference Distributions of Primary Motor Cortex Neurons Reflect Control Solutions Optimized for Limb Biomechanics. Neuron 77, 168–179 (2013)., 10.1016/j.neuron.2012.10.041    [5] Verduzco-Flores, S. O. & De Schutter, E. Self-configuring feedback loops for sensorimotor control. eLife 11, e77216 (2022)., 10.7554/eLife.77216    [6] Codol, O., Michaels, J. A., Kashefi, M., Pruszynski, J. A. & Gribble, P. L. MotorNet: a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks. bioarxiv (2023), 10.1101/2023.02.17.528969    [7] de Haan, M. J., Brochier, T., Grün, S., Riehle, A. & Barthélemy, F. V. Real-time visuomotor behavior and electrophysiology recording setup for use with humans and monkeys. Journal of Neurophysiology 120, 539–552 (2018)., 10.1152/jn.00262.2017    [8] McCullagh, P. & Nelder, J. A. Generalized Linear Models. (Springer US, 1989)., 10.1007/978-1-4899-3242-6
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