Intrinsic ?functional connectivity? (iFC), a measure of correlation between spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, reliably distinguish networks of cortical and subcortical areas during both rest and active task performance. iFC methods can map the functional architecture of the human brain in both healthy and pathological conditions, in high detail using as little as 5 minutes of data. Striking reproducibility and test-retest reliability of findings across centers have fueled a widespread application of iFC measures in clinical neuroscience, biomarker discovery, and human connectomics. However, the neural circuits and cellular processes underlying BOLD-iFC remain poorly specified. BOLD amplitude itself appears related to neural activity in the high gamma (HG) range (~70-200 Hz), and thus to an extent, with neuronal firing. However, BOLD?s relationship to the lower frequencies is controversial. This is a critical disconnect, as oscillatory activities below 40Hz reflect ongoing cell-circuit excitability fluctuations that control neuronal firing; i.e., the amplitude of neural population firing is ?coupled? to oscillatory phase. In this, the simplest form of such phase-amplitude coupling (PAC), amplitude variations in higher frequency activity (e.g., firing or HG) are coupled to the phase of a lower frequency (e.g., theta). PAC operates both pairwise and recursively over the spectrum, from the range of neuronal firing down to the slow/infraslow (<1Hz) range where BOLD amplitude fluctuations are observed using resting state fMRI (R-fMRI). Thus PAC may provide a key to connecting resting BOLD fluctuations to activity cycles in the underlying cell circuits. In our framework: 1) At a microscopic, cortical cell-circuit level, a complex of excitatory and inhibitory interactions between neurons generate rhythmic excitability fluctuations (oscillations). 2) PAC organizes slow (0.5-12) Hz and mid-range (13-40Hz) oscillations hierarchically, ultimately controlling temporal patterns of neuronal firing. 3) Infraslow (0.01-0.1 Hz) neural activity fluctuations synchronize to form the macroscale intrinsic connectivity networks (ICN) indexed by R- fMRI, and use PAC to orchestrate faster activity within a network. Our broad goal is to use integrated human and monkey studies to investigate the relationship between macroscale BOLD-derived iFC patterns, and their underlying mechanisms at the microscale cell-circuit level. We will study the sensorimotor network, as its ?nodal? organization and other properties are well understood, and it shows good human-simian correspondence. Focusing on key nodes in this network (e.g., face and hand areas), we will recapitulate prior work tying R-FMRI iFC to macroscale scalp EEG and mesoscale stereotactic (S)-EEG, and will use innovative laminar multielectrode methods to establish novel links to the cell circuit level. Established modeling and computational methods will help to construct a comprehensive model that connects macroscale iFC to underlying microscale, cell circuit activity.

Public Health Relevance

This research aims to define the neural mechanisms of Intrinsic ?Functional Connectivity? (iFC), as measured with resting-fMRI. iFC reliably maps the functional architecture of the brain in both healthy and pathological conditions, efficiently and in high detail. Our findings will have widespread implications for mental health, particularly in biomarker discovery, and human connectomics.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
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Special Emphasis Panel (ZMH1)
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Bennett, Yvonne
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Nathan Kline Institute for Psychiatric Research
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