# Integrated brain network and cell-circuit models of slow network fluctuations

> **NIH NIH P50** · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · 2024 · $321,975

## Abstract

ABSTRACT: The overarching goal of Project 4 is subsumed under Center Aim 3: Develop iterative
interactions between modeling and empirical studies to integrate knowledge across data scales. To do
so, Project 4 will develop novel computational models of neural circuit dynamics and apply them to fit features
of multi-modal neural recordings in Projects 1-3. Models will be used to test hypotheses and gain insight into
dynamical and biophysical mechanisms underlying slow brain network fluctuations (SBNFs) and their impact
on local circuit processing of sensory information. Aim 1 will fit a dynamical systems model to capture the
dynamics of spectral states in a cortical region, as measured by LFP, EEG, and iEEG. In addition, these
regional models will be interconnected in a large-scale network model to simulate brain wide dynamical
phenomena as measured by fMRI, such as functional connectivity and CAP states. We will test the specific
hypotheses that slow (~0.1-1 Hz) fluctuations in spectral state can be captured through bistability with
transitions induced by noise and adaptation, that even slower fluctuations (e.g, in arousal, or internal vs.
external attention) can be captured by shifts between bistable and monostable dynamical regimes, and that
these dynamics can account for spatiotemporal effects observed in fMRI. Aim 2 will develop biophysically
detailed models of neocortical circuits with laminar resolution specifically designed to bring macroscale human
iEEG/EEG to microscale cellular and circuit-level phenomena (cell spiking, LFP/CSD). Detailed models will be
applied to study mechanisms of slow fluctuations in a small number key circuits that are the target of study in
NHP in Project 3. We will systematically explore the manner in which cell type-specific properties, and layer
specific thalamocortical and cortical connectivity, must be combined to replicate the multiscale dynamics
revealed by NHP studies. We will test the specific hypothesis that patterns of exogenous drive together with
cell-type-specific neuromodulation of channel conductances can induce slow fluctuations in circuit activity that
translates across electrophysiological scales and species from cell activity up to EEG. We will also
characterize how ongoing slow fluctuations impact circuit responses to bottom-up sensory evoked signals,
linking slow neural dynamics to task performance. Exploratory Aim 3 will develop a multi-scale model to
explore the interplay between microcircuit and large-scale network dynamics. Specifically, we will embed the
biophysically detailed microcircuit models from Aim 2 as distinct nodes in a large-scale network in which the
other nodes are simulated as phenomenological dynamical systems from Aim 1. Collectively, the aims of
Project 4 will synthesize multi-modal recordings from Project 1-3 to develop multi-scale mechanistic
computational models of cortical dynamics and SBNFs.

## Key facts

- **NIH application ID:** 10834837
- **Project number:** 5P50MH109429-07
- **Recipient organization:** NATHAN S. KLINE INSTITUTE FOR PSYCH RES
- **Principal Investigator:** STEPHANIE Ruggiano JONES
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $321,975
- **Award type:** 5
- **Project period:** 2017-04-15 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10834837

## Citation

> US National Institutes of Health, RePORTER application 10834837, Integrated brain network and cell-circuit models of slow network fluctuations (5P50MH109429-07). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10834837. Licensed CC0.

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