# Spatiotemporal signatures of neural activity and neurophysiology in the BOLD signal

> **NIH NIH R01** · EMORY UNIVERSITY · 2020 · $383,236

## Abstract

The blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) fluctuations used to
map functional connectivity contain a wealth of information about neural activity and physiological processes
in the brain. Most functional connectivity studies wish to detect time-varying activity related to cognition and
information processing, and view the presence of other contributors to the spontaneous BOLD fluctuations as a
complication. However, evidence is growing that sources of “noise” in the BOLD signal contain clinically-
relevant information about activity at different spatial and temporal scales. The challenge lies in separating
contributions from different processes so that selective sensitivity to the process of interest can be achieved.
 We propose to combine spatial, spectral and temporal signal characteristics with multi-modal imaging to
separate the BOLD fluctuations into four components with different spatial and temporal scales: 1) a
quasiperiodic spatiotemporal pattern (QPP) linked to infraslow electrical activity; 2) oscillations that arise from
properties of the vasculature; 3) global signal variations that do not reflect local neural processing; and 4) the
remaining variability, which should have increased sensitivity to time-varying interactions between regions.
The two key elements that make the isolation of BOLD components possible are the direct measurement of
neural activity in conjunction with imaging experiments in the rat model, and dynamic analysis techniques that
can capture spatial and temporal patterns in the imaging and recording data. While the foundational work
described in this proposal will be performed in the rat, the tools we develop will be optimized and applied to
standard resting state functional MRI (rs-fMRI) studies in humans.
 Our preliminary data shows that the BOLD signal contains contributions from two separable types of
neural activity: infraslow activity, which produces quasiperiodic spatiotemporal patterns of BOLD activation;
and activity in typical EEG bands, which is more closely tied to time-varying activity between areas. Using only
analytical tools, we show that we can separate and identify similar processes in human data, a strong argument
for the ultimate translatability of these techniques. We also show that the QPPs alone account for the
differences in connectivity observed between patients with major depressive disorder and healthy controls,
which demonstrates how selective analysis methods can aid in the diagnosis of psychiatric and neurological
disorders and provide new insight into the alterations in connectivity that many disorders exhibit. We exhibit
preliminary evidence for both neural and vascular contributions to the global BOLD signal, and describe a
method for mapping the contribution of vascular oscillations. Specific aims are: 1.Determine the neural and
hemodynamic correlates of the global BOLD signal; 2. Characterize the contributions of vascular oscillations;
3.Disting...

## Key facts

- **NIH application ID:** 9971574
- **Project number:** 5R01MH111416-05
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Shella D Keilholz
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $383,236
- **Award type:** 5
- **Project period:** 2016-09-14 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971574

## Citation

> US National Institutes of Health, RePORTER application 9971574, Spatiotemporal signatures of neural activity and neurophysiology in the BOLD signal (5R01MH111416-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9971574. Licensed CC0.

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