# The cerebro-cerebellar-basal-gangliar network for visuomotor learning

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $1,025,216

## Abstract

ABSTRACT
Visual learning is critical to the lives of human and non-human primates. Visuomotor association, the
assignment of an arbitrary symbol to a particular movement (like a red light to a braking movement), is a well-
studied form of visual learning. This proposal tests the hypothesis that the brain accomplishes visuomotor
associative learning using an anatomically defined closed-loop network, including the prefrontal cortex, the
basal ganglia, and the cerebellum. In our preliminary work we have developed a task that studies how
monkeys learn to associate one of two novel fractal symbols with a right hand movement, and the other symbol
with a left hand movement. Every experiment begins with the monkeys responding to two overtrained symbols
that they have seen hundreds of thousands of times. At an arbitrary time we change the symbols to two fractal
symbols that the monkey has never seen. It takes the monkey 40 to 70 trials to learn the new associations. In
our preliminary results we have discovered that Purkinje cells in the midlateral cerebellar hemisphere track the
monkeys’ learning as they as they figure out the required associations. The neurons signal the result of the
prior decision. Half of the neurons respond more when the prior decision was correct; the others respond more
when the prior decision was wrong. The difference between the activity of these two types of neurons provides
a cognitive error signal that is maximal when the monkeys are performing at a chance level, and gradually
becomes not different from zero as the monkeys learn the task. The neurons do not predict the result of the
impending decision. Although the neurons change their activity dramatically at the symbol switch, the
kinematics of the movements do not change at all. This proposal takes this discovery as the starting point for
four aims: 1) to use viral transynaptic tract tracing to discover the cortical and basal ganglia regions that
project to the cerebellar visuomotor association area. 2) to record from the four nodes of the network as
anatomically defined (midlateral cerebellar hemisphere, dentate nucleus, basal ganglia, prefrontal cortex),
simultaneously, using multiple single neuron recordings, to see if these areas also have information about the
process of visuomotor association 3) to inactivate each node, to see how their inactivation affects the monkey’s
ability to learn new associations, and whether the inactivation affects the activity of the neurons at the other
nodes. 4) to develop computational methods to analyze the activity of neural activity recorded simultaneously
in all four nodes of the network (Aim 2) in the midlateral cerebellar cortex with regard to parameters such as
prior outcome and movement, hand, symbol, and the intensity and epoch of the prior cognitive error signal.
We will use dimensional reduction techniques to answer questions like whether hand or symbol can be
decoded from network activity. We will model how the cerebellum sim...

## Key facts

- **NIH application ID:** 9983219
- **Project number:** 5R01NS113078-02
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Stefano Fusi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,025,216
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9983219

## Citation

> US National Institutes of Health, RePORTER application 9983219, The cerebro-cerebellar-basal-gangliar network for visuomotor learning (5R01NS113078-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9983219. Licensed CC0.

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