# Application of the principle of symmetry to neural circuitry: From building blocks to neural synchronization in the connectome

> **NIH NIH R01** · CITY COLLEGE OF NEW YORK · 2020 · $1,064,970

## Abstract

Project Summary/Abstract
 The broad, long-term objective of this grant is to advance a new theoretical approach to identify
synchronized building blocks of neural circuits based on group theory and its application to understand the
permutation symmetries of these circuits. Based on the developed theoretical framework we will validate
our theory by probing brain dynamics at single-cell resolution and in real-time, i.e. sub-second scale, in C.
elegans, which is a system with a fully mapped synapse-resolution connectome. We will produce a software
tool that will allow end-users from the broad neuroscience community to identify and analyze the building
blocks of neural circuits and explore their relation with function. Specific Aims are:
 · Specific Aim 1. Develop a generalized theoretical framework of symmetry groups and their unique
 decomposition into normal subgroups to identify building blocks made of synchronized neural pop-
 ulations in brain networks. Based on our preliminary work in locomotion in C. elegans, we will
 evaluate the application of symmetry groups to more complex functions and more complex neural
 systems of other species to investigate the relation between symmetries of the connectome and neural
synchronization.
 · Specific Aim 2. Verify experimentally the predicted building blocks in C. elegans nervous system
 with system-wide Ca2+-imaging experiments. We will develop an experimental program to test the
 predictions of the theory on the synchronization of neural populations identified by symmetry groups,
 and the subsequent breaking of symmetry and asynchrony tested by single-cell laser ablation.
 · Specific Aim 3. Resource sharing plan and software development: Develop software and tools based
 on the algorithms developed in Aim 1 and evaluated in Aim 2 to identify the building blocks of
 neural circuits to study their synchronization and function. Optimize the usability of the software by
 experimentalists (end-user PD Manuel Zimmer) and other researchers for use in the larger scientific
community.
 Long term goals: The results of the present study should lead to improve our understanding of the
designing principles of neural circuits and how this structure influences function. Once completed, we trust
that the tools developed by this project will be able to be used by the larger neuroscience community
to study the building blocks of all connectomes. The development of theories of the organization of the
connectome should lead to the inference of general principles regarding network organization applicable to
areas outside neuroscience that include information processing complex systems in general.

## Key facts

- **NIH application ID:** 10006982
- **Project number:** 1R01EB028157-01A1
- **Recipient organization:** CITY COLLEGE OF NEW YORK
- **Principal Investigator:** HERNAN MAKSE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,064,970
- **Award type:** 1
- **Project period:** 2020-09-08 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10006982

## Citation

> US National Institutes of Health, RePORTER application 10006982, Application of the principle of symmetry to neural circuitry: From building blocks to neural synchronization in the connectome (1R01EB028157-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10006982. Licensed CC0.

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