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The EEG spectrum as a marker of severity, burden, and psychiatric diagnosis

Award Number: R03MH143166
ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 05/15/2026
PERIOD OF PERFORMANCE END DATE: 05/14/2028

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The EEG spectrum as a marker of severity, burden, and psychiatric diagnosis - Summary There is an urgent need for objective and robust diagnostic indices related to psychiatric illnesses, including obsessive-compulsive and anxiety disorders. Brain-based indices are particularly suited for this purpose, but many of the available brain-based markers have limited scope, require specialized equipment, or have unknown reliability and validity. The proposed research aims to examine the value of data-based, quantitative, and objective markers of dysfunctional electrocortical processes associated with obsessive-compulsive and anxiety psychopathology. The proposed research aims to establish advanced computational indices based on resting electroencephalogram (EEG) recordings that are capable of (1) discriminating between diagnostic categories but also (2) predict transdiagnostic variables such as severity and comorbidity. Specifically, we use state-of-the- art data transformations to extract mechanistically informative indices of spectral shape and alpha-frequency phenomena inherent in EEG recordings during resting states. We will then establish their reliability and internal consistency—prerequisites for using them as markers of inter-individual differences. The indices will then be related to clinical data collected in a large sample of individuals presenting with symptoms on the obsessive- compulsive and anxiety spectrum. A Bayesian Hierarchical Model will be used to aid in data reduction and to measure and heighten reliability of the EEG-derived variables. Finding reliable and valid biomarkers of electrocortical processes has the potential of transforming diagnostic assessment by providing continuous indices of cortical dysfunction. If the goals of this application are met, then reliable and valid indices of electrocortical (dys)function may help to significantly shift clinical practice: In assessment, objective measures of EEG alpha reactivity could be used, for example, to objectively identify patients with perception/attention dysfunction, versus those with generally delayed oscillatory activity and thus more general cortical dysfunction. These inter-individual differences may in the future guide how patients are assigned to individualized treatment protocols as well as for predicting treatment outcome.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $151,761 )
2026	2026	UNIVERSITY OF FLORIDA	1523 UNION RD RM 207	GAINESVILLE	FL	32611	ALACHUA	USA	Mental Health Research Grants	000	1	5/18/2026	NEW	$151,761
														Subtotal = $151,761

Grand Total All Awards = $151,761

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The EEG spectrum as a marker of severity, burden, and psychiatric diagnosis

Award Number: R03MH143166

ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 05/15/2026

PERIOD OF PERFORMANCE END DATE: 05/14/2028

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