# Connecting across Scales: Integration of Cell-Specific Microstructure within Long-Range Brain Networks in the Macaque Monkey

> **NIH NIH R21** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $689,525

## Abstract

Project Summary
Structural alterations in brain networks are driven by changes in cortical microstructure, including
neuronal death, the disappearance or rewiring of a synapse, and glial changes like decreases in myelination or
astrocytic swelling. Disentangling cell-type specific signatures using accessible tools, such as in vivo MRI, and
determining how signatures of microstructure vary across individuals, is an important objective for the
advancement of mechanistic understanding of age-related decline and developing clinically relevant biomarkers.
Such work requires a more accurate “ground truth” mapping of brain networks and their cellular composition
using specialized analysis techniques to integrate multi-scale whole brain models. For this study, we propose to
investigate network architecture across scale – from cellular-level microstructure to network based structural
connectivity to better understand the unique demands of healthy aging. We will use carefully aligned multi-scale
reference data of rhesus macaque that includes multi-parametric in vivo MRI, high-resolution ex vivo MRI, and
histological markers of neuronal cell bodies (Nissl), myelination (Gallyas), astrocytes (GFAP), and microglial
(Iba-1). We will perform a whole brain network analysis to first establish the morphological and microstructural
signatures of regions connected by long-range anatomical projections. We hypothesize that regions connected
over long distances experience high neural and metabolic demand, leading to accelerated age-related decline.
We will investigate age-related decline in these cortical areas using a normative cohort of n=28 middle to older
aged adult macaques (equivalent to 25-80+ human years). The aims of this project will contribute towards the
development of a highly translational nonhuman primate reference data and network-based analyses for lifespan
health research, enhancing our ability to interpret multiscale features of the aging brain to allow for future
mechanistic studies that cannot be completed in humans.

## Key facts

- **NIH application ID:** 10988482
- **Project number:** 1R21AG083539-01A1
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Erika Pratt Raven
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $689,525
- **Award type:** 1
- **Project period:** 2024-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10988482

## Citation

> US National Institutes of Health, RePORTER application 10988482, Connecting across Scales: Integration of Cell-Specific Microstructure within Long-Range Brain Networks in the Macaque Monkey (1R21AG083539-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10988482. Licensed CC0.

---

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