# Mechanisms for Internal Models in a Cerebellum-like Circuit

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $350,000

## Abstract

Project Summary/Abstract
Humans and other animals learn and store sophisticated models of the causal relationships that govern their
interactions with the world. Such internal models are likely critical for transforming ambiguous and delayed
sensory data into stable perceptions and coordinated movements. For example, distinguishing external
sensory input from those that are self-generated could be accomplished via an internal model that predicts the
sensory consequences of an animal’s own motor commands. Despite their potential importance for both
normal brain function and neurological disorders, it has proven challenging to understand how internal models
are actually implemented in neural circuits. This renewal proposal applies a combination of experimental and
theoretical approaches to a model system—the weakly electric fish—with unique advantages for addressing
this question. Our previous studies of electric fish were successful in developing a detailed mechanistic model
of how neurons at the first stage of processing in the electrosensory lobe (ELL) predict and cancel out the
effects of the fish’s own electric organ discharge (EOD). However, these studies considered a highly simplified
version of the true problem facing the electrosensory system. Under natural conditions, electrosensory inputs
vary moment-to-moment depending both on the movements of the fish (i.e. the position of the electric organ in
the tail versus electroreceptors on the skin) and the temporal pattern of EOD motor commands emitted by the
fish. Solving this problem requires a more complex internal model, akin to those believed to be generated in
the mammalian brain. In addition, past models ignored key features of ELL circuitry, such as plasticity of
inhibitory synapses, which likely play key functional roles (both in ELL and in other vertebrate brain circuits). By
addressing these issues the proposed research will provide general insights into how neural circuits contribute
to distinguishing self-generated from external stimuli. The proposed studies will also provide direct links
between neural representations, well-defined circuitry, synaptic plasticity, and a behaviorally relevant systems
level function. Though forging such links is a primary goal of neuroscience, there are still relatively few cases in
which they can actually be made.

## Key facts

- **NIH application ID:** 9936257
- **Project number:** 5R01NS075023-09
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Nathaniel Sawtell
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $350,000
- **Award type:** 5
- **Project period:** 2012-07-01 → 2021-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9936257

## Citation

> US National Institutes of Health, RePORTER application 9936257, Mechanisms for Internal Models in a Cerebellum-like Circuit (5R01NS075023-09). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/9936257. Licensed CC0.

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