# CRCNS: Assessing long-term impacts of disruption to large-scale brain networks

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $354,145

## Abstract

Large-scale complex networks support brain function across the lifespan, and features of brain networks 
are hypothesized to confer both vulnerability and resilience to the brain changes that accompany healthy 
and pathological aging. Brain network organization can be characterized during resting wakefulness using 
functional magnetic resonance imaging and system segregation is a measure of this organization which 
quantifies the degree to which an individual’s brain network contains functionally distinct brain systems. In 
healthy adult humans, increasing age is associated with decreasing system segregation; declining system 
segregation is associated with worsening memory ability, alterations in brain activity, and is prognostic of 
Alzheimer’s Disease dementia beyond brain atrophy and pathology. The precise mechanism of
aging-accompanied brain network changes is presently unclear and gaining a deeper understanding of 
them would be greatly advanced by the development of non-human models of brain network aging. A 
precision imaging-based approach will be used to develop and characterize a comprehensive longitudinal 
description of functional brain network changes across the mouse lifespan. Awake resting-state fMRI will 
be measured in individual mice as they grow older (from 3 to 21 months) and will be used to quantify 
changes in brain network organization (particularly segregation). Brain network changes will be related to 
behavior and cognition (including measures of memory, learning, and sensory-motor function), both as a 
function of age and sex. Targeted lesions to vulnerable brain network locations (network hubs) will be 
administered at younger and older ages, to test the causal contributions of hub nodes towards maintaining 
brain network integrity, and evaluate the susceptibility of older-age brain networks to focal damage. This 
work will broaden understanding of complex network function, large-scale network mechanisms
underlying aging-related behavioral alterations, and the impacts of brain network disruption occurring at 
different life stages. The characterization of large-scale brain network organization with respect to
aging-related decline in the intact brain, together with the use of targeted lesions, will set the stage to 
study the impact of neurodevelopmental and neurodegenerative pathologies on brain network 
organization and function in a valuable cross-species model.

## Key facts

- **NIH application ID:** 11083179
- **Project number:** 1R01AG092219-01
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Itamar Kahn
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $354,145
- **Award type:** 1
- **Project period:** 2024-09-15 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11083179

## Citation

> US National Institutes of Health, RePORTER application 11083179, CRCNS: Assessing long-term impacts of disruption to large-scale brain networks (1R01AG092219-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11083179. Licensed CC0.

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