# Advanced neuroimaging of arousal-state transition network dynamics in the human brain

> **NIH NIH F31** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2022 · $37,783

## Abstract

PROJECT SUMMARY
 Arousal regulatory systems are disrupted in a wide range of psychiatric and neurological disorders, yet
we know surprisingly little about the fundamental brain network mechanisms underlying transitions between the
sleep and wake arousal-states. Invasive animal studies have demonstrated the causal role of several deep-brain
regions including nuclei of the brainstem and thalamus in arousal from sleep, and recently, human functional
magnetic resonance imaging (fMRI) studies of arousal implicated such deep-brain regions as key contributors.
While we know shifts in brain rhythms, connectivity, and behavior accompany arousal-state transitions, how
brain-wide dynamics unfold across such key regions during this state-change remains unknown. Previous
studies have been limited by the spatiotemporal resolution necessary to capture whole-brain network dynamics
occurring at arousal. Invasive studies are limited by the number of regions they can record from simultaneously,
and traditional non-invasive methods lack the temporal resolution necessary to capture the fast dynamics
occurring at arousal. Our novel method will use encephalography (EEG) and behavioral response to detect
arousal-state changes combined with simultaneous fast fMRI (sample rate < 1 s) at 7 Tesla to measure deep-
brain activity in nuclei of the brainstem, individual nuclei of the thalamus, basal ganglia regions, and cortical
regions during human arousal from sleep. Preliminary data suggests that this fMRI acquisition method can detect
significant temporal differences in activity signatures between regions of interest. We hypothesize that activation
of the brainstem’s locus coeruleus, followed by a distinct activation sequence across thalamic nuclei and the
basal forebrain, will precede arousal, and deactivation of cortical regions will follow. We aim to build a
fundamental understanding of the basic network mechanisms supporting arousal-state transitions in humans
that will be necessary to ultimately understand how arousal regulatory system dynamics are altered in disorders.
Delineating such temporal network dynamics using fMRI will provide a more precise understanding of how the
brain switches between cognitive states by allowing us to link activity across dozens of subcortical nuclei
simultaneously. Identifying these network mechanisms in humans will also provide the opportunity for future
studies to identify fine-scale differences in neuropsychiatric disorders that was not previously possible.

## Key facts

- **NIH application ID:** 10537447
- **Project number:** 1F31MH127916-01A1
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** Beverly Setzer
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $37,783
- **Award type:** 1
- **Project period:** 2022-09-20 → 2024-09-19

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10537447

## Citation

> US National Institutes of Health, RePORTER application 10537447, Advanced neuroimaging of arousal-state transition network dynamics in the human brain (1F31MH127916-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10537447. Licensed CC0.

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