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Novel Group ICA Incorporating Time-Frequency Information for Longitudinal Brain Network Analysis

Award Number: R21AG093534
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 03/15/2026
PERIOD OF PERFORMANCE END DATE: 02/29/2028

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Novel Group ICA Incorporating Time-Frequency Information for Longitudinal Brain Network Analysis - Abstract This R21 application aims to develop a novel group independent component analysis (ICA) algorithm, incorporating time-frequency information (GtfICA) to capture the temporal dynamics of functional networks (dFN) in longitudinal studies. The GrfICA will provide a comprehensive view of the spatiotemporal organization of brain activity by addressing the limitations of traditional functional connectivity methods. Our sample includes n=1000 cognitively normal participants aged 18-85 from the NKI-RS study, who were followed up to 3 years. All participants had both single- and multi-band resting-state fMRIs at each visit. We will identify age-related changes and assess the test-retest reliability of longitudinal changes in dFN between multi-band and single- band data. This is crucial for understanding the consistency and reproducibility of results across different imaging protocols that often occur in long-term longitudinal studies. In Aim 1, we will develop an independent component analysis utilizing time-frequency features and its extension to multi-subject analysis (GtfICA). We will evaluate their performance using extensive numerical experiments. Using NKI-RS baseline data, GtfICA will identify age-related changes in the dFN. We will assess the replicability of the identified age-associated dFN patterns across different fMRI acquisition sequences. In Aim 2, we will extend GtfICA to harmonize single- and multi-band longitudinal data collected longitudinally. We will incorporate the sampling rate changes in the GtfICA and quantify and test the longitudinal changes above and beyond the sequence changes. Also, we will evaluate the test-retest reliability of the longitudinal changes in dFN between multi- band and single-band data. Finally, we will evaluate the stability of the longitudinal changes in the dFN when the acquisition sequences change over time when only partial information on sequence changes is available. The outcome of this proposal is a crucial step toward accurately quantifying and testing the effect of aging and neurodegenerative disease on brain function across different image acquisition protocols and longitudinal changes. This study will enhance the generalizability of the inferences on dFN. The outcome of this proposal will be the basis for a future new R01 project. This subsequent research will evaluate longitudinal changes in the dFN in ADRD relative to aging in multiple clinical populations.


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 = $390,122 )
2026	2026	THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK	630 W 168TH ST FL 4	NEW YORK	NY	10032	NEW YORK	USA	Aging Research	000	1	3/12/2026	NEW	$390,122
														Subtotal = $390,122

Grand Total All Awards = $390,122

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Novel Group ICA Incorporating Time-Frequency Information for Longitudinal Brain Network Analysis

Award Number: R21AG093534

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 03/15/2026

PERIOD OF PERFORMANCE END DATE: 02/29/2028

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