Multi-modal imaging of the metabolic and neurochemical mechanisms underlying task-evoked negative BOLD signals

ABSTRACT
A large number of functional magnetic resonance imaging (fMRI) studies have shown that the brain’s default-
mode network (DMN)—a set of brain regions that are highly active at rest—exhibits a “de-activation”, i.e.,
reduced activity, when the subjects perform attention-demanding cognitive tasks. While disrupted DMN de-
activations have been associated with a broad range of psychiatric and neurological conditions, mechanisms
underlying such reduced fMRI signals remain elusive, hindering their potential use as an imaging marker for
disease diagnosis and treatment.
The goal of this project is to perform an in-depth investigation of the mechanisms underlying stimulus-driven
fMRI de-activations in DMN. To achieve this goal, we will integrate fMRI with a novel functional PET framework
and cutting-edge 3D functional MR spectroscopy imaging to enable concurrent measures of fMRI signals, blood
flow, glucose and oxygen metabolism, gamma-aminobutyric acid (GABA) and glutamate levels within a single
imaging session. These multi-faceted measures will be jointly analyzed to test a specific hypothesis on task-
negative fMRI signals in DMN. We will further leverage the sufficient spatial coverage and high sensitivity of our
multi-modal framework to assess how the characterized fMRI de-activation model varies in space and across
subjects.
Outcomes of this study will illuminate the metabolic and neurotransmitter processes contributing to task-evoked
DMN de-activations, providing testable hypotheses on their disruptions in various mental illnesses. If successful,
the proposed imaging and analytical framework will also enable a new line of inquiries to decipher the biophysical
basis of fMRI (de-)activations in broad cognitive and clinical settings.

Grant Number: 5R21MH135201-02
NIH Institute/Center: NIH
Principal Investigator: Jingyuan Chen