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Infra-slow brain dynamics as a marker for cognitive function and decline

Ajmera, S and Rajagopal, S and Ur Rehman, R and Sridharan, D (2019) Infra-slow brain dynamics as a marker for cognitive function and decline. In: 33rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 8-14 December 2019, Vancouver; Canada.

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Abstract

Functional magnetic resonance imaging (fMRI) enables measuring human brain activity, in vivo. Yet, the fMRI hemodynamic response unfolds over very slow timescales (<0.1-1 Hz), orders of magnitude slower than millisecond timescales of neural spiking. It is unclear, therefore, if slow dynamics as measured with fMRI are relevant for cognitive function. We investigated this question with a novel application of Gaussian Process Factor Analysis (GPFA) and machine learning to fMRI data. We analyzed slowly sampled (1.4 Hz) fMRI data from 1000 healthy human participants (Human Connectome Project database), and applied GPFA to reduce dimensionality and extract smooth latent dynamics. GPFA dimensions with slow (<1 Hz) characteristic timescales identified, with high accuracy (>95), the specific task that each subject was performing inside the fMRI scanner. Moreover, functional connectivity between slow GPFA latents accurately predicted inter-individual differences in behavioral scores across a range of cognitive tasks. Finally, infra-slow (<0.1 Hz) latent dynamics predicted CDR (Clinical Dementia Rating) scores of individual patients, and identified patients with mild cognitive impairment (MCI) who would progress to develop Alzheimer's dementia (AD). Slow and infra-slow brain dynamics may be relevant for understanding the neural basis of cognitive function, in health and disease. © 2019 Neural information processing systems foundation. All rights reserved.

Item Type: Conference Paper
Publication: Advances in Neural Information Processing Systems
Publisher: Neural information processing systems foundation
Additional Information: The copyright of this article belongs to Neural information processing systems foundation
Keywords: Brain; Dynamics; Magnetic resonance imaging; Neurodegenerative diseases, Alzheimer's dementia; Cognitive functions; Functional connectivity; Functional magnetic resonance imaging; Hemodynamic response; Inter-individual differences; Mild cognitive impairments (MCI); Orders of magnitude, Functional neuroimaging
Department/Centre: Division of Biological Sciences > Centre for Neuroscience
Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 22 Sep 2020 06:22
Last Modified: 22 Sep 2020 06:22
URI: http://eprints.iisc.ac.in/id/eprint/66562

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