# Mechanisms for internal models in a cerebellum-like circuit

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2022 · $533,681

## Abstract

Project Summary/Abstract
Predicting the consequences of action is a vital function of the nervous system. The hypothesized neural
substrate are so-called internal models that transform information about outgoing motor commands and the
current sensory state into predictions of sensory input. Such internal models are likely critical for a wide range
of sensory, motor, and cognitive functions and their disruption has been implicated in neurological disorders
such as autism and schizophrenia. Nevertheless, it has proven challenging to understand how internal models
are implemented in neural circuits in the mammalian brain. Our prior studies were successful in developing a
detailed mechanistic understanding of how neurons in the electrosensory lobe (ELL) of mormyrid fish predict
and cancel out the sensory consequences of a simple behavior--the electric organ discharge (EOD) pulse.
However, because these studies were performed in immobilized animals, the nature of the predictions studied
was limited in scope and complexity. This renewal uses novel methods for neural recording and high-resolution
behavior monitoring in freely swimming fish to study the more complex internal models underlying the
remarkable active electrolocation abilities of electric fish. Computational modeling approaches will be used
both to rigorously define the problem facing the active electrosensory system and to generate and test realistic
circuit-level models of how they may be solved. The key components of such models, including synaptic
plasticity, recurrent and feedforward connectivity, and biophysical compartmentalization of axonal and dendritic
spikes, are common to many neural systems including the cerebellum, hippocampus, and neocortex. Hence
insights from these studies are expected to be widely relevant to understanding how internal models are
implemented in neural systems.

## Key facts

- **NIH application ID:** 10359759
- **Project number:** 5R01NS075023-11
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Laurence F. Abbott
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $533,681
- **Award type:** 5
- **Project period:** 2021-06-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10359759

## Citation

> US National Institutes of Health, RePORTER application 10359759, Mechanisms for internal models in a cerebellum-like circuit (5R01NS075023-11). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10359759. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*