Incorporation of PPG-AMP and Pupil Diameter into Autonomic Correction of fMRI Signal
Poster No:
1339
Submission Type:
Abstract Submission
Authors:
Belal Tavashi1, Kübra Eren1, Kadir Yildirim1, Elif Can1, Cem Karakuzu1, Lina Alqam1, Alp Dincer2, Pinar S Ozbay1
Institutions:
1Bogazici University, Istanbul, Turkey, 2Acibadem University, Istanbul, Turkey
First Author:
Co-Author(s):
Introduction:
To understand the impact of autonomic correction on spatiotemporal patterns in the fMRI-systemic signals relationship, we used PPG amplitude and pupil size. Stress-induced hormonal responses, affecting alertness and pulse rate, prompted our examination of removing autonomic and behavioral effects from fMRI data. We hypothesized that eliminating these components, due to their strong co-variation with fMRI data, would influence outcomes. This research aims to assess the contribution of autonomic processes to spatiotemporal correlations and active brain regions during a cognitive task.
Methods:
FMRI data were obtained at 3 T with GRE-EPI (FA = 90, TR = 3 s, TE = 36 ms, in-place resolution = 2.5 mm, number of TRs = 135). The cognitive task involved solving arithmetic equations with one unknown, displayed against a grey background with a fixation dot in a block design (6 blocks, each: 45s OFF, 9s ON, and 36s OFF). Preprocessing of fMRI data followed the suggested 'afni_proc' pipeline (AFNI (1)), including removal of signal drifts, slice-timing correction, realignment of consecutive volumes, registration to MNI template, smoothing (3 mm fwhm), and regression of motion parameters while removing outliers (threshold = 0.2). PPG and respiratory signals were collected with a pulse oximeter attached to the fingertip and respiratory bellows, respectively. PPG amplitude (PPG-AMP), as an index of peripheral vascular volume (2), and respiratory volumes per time (RVT) (3) were calculated. An MRI-compatible camera was used to track a subject's eye movement. Pupil diameters were recorded automatically as a secondary measure of sympathetic activity. So far we acquired 4 subjects data, and performed the following analysis: We averaged event-locked physiological signals (based on cardiac, respiratory and pupil size variations) and fMRI responses within grey matter, task (e.g., Visual, IPS) and non-task (e.g., DMN, Insula) related regions. We performed voxel-wise correlations of PPG-AMP and pupil diameter with fMRI across subjects. Each preprocessed fMRI data set were subjected to General Linear Modelling (GLM). This part includes all timing information regarding mental task according to the experiment. The modeling step was combined with regression of motion parameters and their derivatives (3dDeconvolve) in 'afni_proc'. To incorporate further regressors of no interest, as described below, we included each time-series. Various methods developed to reduce the effects of cardiac and respiratory cycles in the fMRI data (4). Among them, we used one of the most common approaches: RETROICOR (5), and included in the GLM as nuisance regressors, as implemented in AFNI's "RetroTS.m". To evaluate the contribution of better captured autonomic processes, we performed a regression analysis employing RETROICOR + RVT, PPG-AMP, and pupil diameter time-series (and combinations), adding time-shifted versions. To our knowledge, this will be the first study incorporating PPG-AMP or pupil diameter as regressors in such detail during wake conditions in humans.
Results:
The study found task-related increases in fMRI signal, particularly in areas like IPS and visual regions, peaking at 6-9 seconds. Pupil size increased with a 6-second lag, peaking around 12 seconds, showing a time-dependent relationship with the fMRI signal. Negative correlations between pupil and fMRI in negative lags were attributed to sympathetic activity. Cross-correlation maps illustrated sympathetic-driven patterns around ventricular regions for negative lags and task-driven patterns around IPS and visual regions for positive lags. Removing time-shifted autonomic regressors reduced activity, especially in DMN and insular regions, as well as negative activations in ventricular regions.
Conclusions:
Our results showed that contributions of the sympathetic activity to fMRI signal which could not be revealed with RVT, can be explained with other autonomic signals like PPG-AMP and pupil size, which could be complementary to each other.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 1
Exploratory Modeling and Artifact Removal 2
Methods Development
Multivariate Approaches
Physiology, Metabolism and Neurotransmission :
Neurophysiology of Imaging Signals
Keywords:
Data analysis
Design and Analysis
fMRI CONTRAST MECHANISMS
FUNCTIONAL MRI
Modeling
MRI
Multivariate
Systems
1|2Indicates the priority used for review
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