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Sunday, July 19 • 7:00pm - 8:00pm
P200: Computational modeling of the input/output mapping in the cerebellar cortex

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Akshay Markanday
, Sungho Hong, Junya Inoue, Peter Dicke, Erik De Schutter, Peter Thier

The cerebellar cortex is a brain region deeply involved in sensorimotor coordination and adaptation. It receives external inputs via axons called the mossy fibers (MF), delivering diverse information, including sensory- and motor signals, from other brain regions. Then, the output neurons, Purkinje cells (PC), transmit the result of computation by the network. Many studies have elucidated how different stages of computation in this neural circuit represents sensory and motor information. However, circuit-level information processing has not been well-understood.

Here we investigated this question by characterizing how MF firings transform into PC outputs in recording data from those cells (n=110 and 135, respectively) in rhesus monkeys that were performing a sensorimotor task (M. Mulatta; n=2). We trained the animals for a saccadic eye movement task, where they followed a target jumping back and forth between two horizontal target locations. The fast pace and repetitive nature of the task led to a gradual decline in saccade velocities (fatigue).

We found that the firing rates of MFs linearly encoded eye speed and saccade duration, consistent with previous studies (e.g. [1]). Using the linear rate coding property of MFs and also PCs, we constructed the rate coding models of individual cells from the data and formed the virtual populations of those models for each cell type. This method enabled us to analyze eye speed- dependent variability of the population responses beyond the firing rate across trials.

By using the virtual population of MFs and PCs, we found that the activities of MFs and PCs can be both characterized by low dimensional “manifolds” [2] that resemble the limit cycles. Here, the PC manifold is higher-dimensional as compared to that of MFs and has more complex representations of variability in eye movements. Nonetheless, there exists a linear transformation between the two populations [3], which can accurately predict the average and also velocity-dependent variability in the firing rate of individual neurons.

Based on these results, we suggest that the MFs deliver a compressed, low dimensional copy of sensorimotor information from other brain areas, possibly via convergence [3], and the cerebellar cortical circuit decompresses/transforms it to higher dimensional outputs, carrying the reorganized representation of the behavioral variability.


1\. Ohtsuka K, Noda H. Burst discharges of mossy fibers in the oculomotor vermis of macaque monkeys during saccadic eye movements. Neurosci Res. 1992, 15, 102–114.

2\. Gallego JA, Perich MG, Miller LE, et al. Neural manifolds for the control of movement. Neuron. 2017, 94, 978–984.

3\. Tanaka H, Ishikawa T, Kakei S. Neural evidence of the cerebellum as a state predictor. Cerebellum. 2019, 18, 349–371.

avatar for Sungho Hong

Sungho Hong

Computational Neuroscience Unit, Okinawa Institute of Science and Technology

Sunday July 19, 2020 7:00pm - 8:00pm CEST
Slot 19