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Abstract #2345

Multimodal Analysis of Autonomic Regression on Neuronal and Physiological Correlates

Kubra Eren1, Lina Alqam1, Belal Tavashi1, Cem Karakuzu1, Kadir Berat Yildirim1, Elif Can1, Alp Dincer2, and Pinar Senay Ozbay1
1Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey, 2Deparment of Radiology, Acıbadem Hospital, Istanbul, Turkey

Synopsis

Keywords: fMRI Analysis, fMRI (task based), physiology, general linear modeling, regression

Motivation: The fMRI BOLD signal is confounded by autonomic nervous system (ANS) effects, particularly in the low-frequency range, which can mimic task-induced brain activity. .

Goal(s): This project aims to identify and model the ANS-related contributions to the BOLD signal, enhancing fMRI’s specificity in task-based studies by accurately distinguishing true neural activity from systemic physiological effects.

Approach: Using multimodal recordings of sympathetic, respiratory, and cardiovascular measures alongside task-based fMRI, we quantified and corrected ANS-related effects in BOLD signals, integrating these corrections into fMRI processing workflows.

Results: We quantified and corrected autonomic nervous system-related effects in BOLD signals, integrating these corrections into the fMRI processing pipeline.

Impact: By integrating autonomic corrections into fMRI workflows, this study enhances the accuracy of brain activity measurements, providing a clearer understanding of neural dynamics during cognitive tasks.

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Keywords