Biology subjects

Pourmotabbed, H.

Publications and source records attributed to Pourmotabbed, H..

3 recordsLinked to original sources

bioRxiv2026

Arousal state alters brain network switching and moderates cognitive task performance

Arousal relates to cognitive performance, but the neural underpinnings of this relationship remain unclear. One candidate marker is switching rate, a dynamic measure that has been linked to cognition and has been speculated to be sensitive to arousal. However, whether switching rate is altered across arousal states has not been directly tested. Here, using fMRI together with concurrent eye monitoring and EEG, we examined how the switching rates of the default mode, salience, and central executive networks are altered across arousal states. Default mode and anterior salience networks exhibited significant differences in switching rates across arousal states determined with eye tracking. Notably, thalamic subregions showed arousal-dependent changes in switching rate that were replicated across independent datasets and arousal measures. Additionally, arousal moderated the relationship between average network switching and performance on a relational processing task. Together, these findings suggest that switching rate may index neural underpinnings of arousal-dependent cognition.

neuroscience↗

bioRxiv2025

Distributed fMRI patterns coupled to low-frequency cardiorespiratory dynamics provide markers of aging

How aging affects brain-body connections can be investigated through changes in the coupling between functional magnetic resonance imaging (fMRI) signals and bodily autonomic processes across the adult lifespan. Recent studies using univariate approaches have identified age-related changes in the association between fMRI signals from multiple individual brain regions and low-frequency respiratory and cardiac activity. Here, we investigate if whole-brain spatial fMRI patterns associated with low-frequency physiological processes (heart rate and respiratory volume fluctuations) present generalizable changes with age. Data from human participants of both sexes are included in the analysis. We find that chronological age can be predicted statistically beyond chance from patterns of low-frequency fMRI-physiology coupling, even after accounting for individual differences in physiological signal characteristics and brain anatomy. Notably, brain areas implicated in central autonomic regulation, including nodes within salience and ventral attention networks (e.g., insula and middle cingulate cortex), are amongst the strongest contributors to age prediction. Further, we observe that after removing physiological effects from fMRI data, the residual blood oxygen level-dependent (BOLD) signal variability is still a reliable indicator of age. Together, these findings underscore the close integration between brain and body physiology, and highlight this interaction as a potential biomarker of the aging process. Significance StatementThe association between brain activity and respiratory or cardiac activity is often dismissed as "noise" in functional magnetic resonance imaging (fMRI) studies. However, emerging evidence suggests that coupling between fMRI and peripheral physiological signals can provide valuable insight into the brain-body connection. In this study, we show that whole brain patterns of coupling between fMRI signals and low-frequency respiratory and cardiac processes can reliably predict age across the adult lifespan. Brain regions involved in autonomic regulation, such as insula and cingulate cortex, were among the most informative predictors of age. These findings suggest that fMRI-physiology coupling may capture aging-related changes in brain vascular health and autonomic function and may have broader relevance for tracking disease-related disruptions in brain-body interaction.

neuroscience↗

bioRxiv2024

Multimodal state-dependent connectivity analysis of arousal and autonomic centers in the brainstem and basal forebrain

Vigilance is a continuously altering state of cortical activation that influences cognition and behavior and is disrupted in multiple brain pathologies. Neuromodulatory nuclei in the brainstem and basal forebrain are implicated in arousal regulation and are key drivers of widespread neuronal activity and communication. However, it is unclear how their large-scale brain network architecture changes across dynamic variations in vigilance state (i.e., alertness and drowsiness). In this study, we leverage simultaneous EEG and 3T multi-echo functional magnetic resonance imaging (fMRI) to elucidate the vigilance-dependent connectivity of arousal regulation centers in the brainstem and basal forebrain. During states of low vigilance, most of the neuromodulatory nuclei investigated here exhibit a stronger global correlation pattern and greater connectivity to the thalamus, precuneus, and sensory and motor cortices. In a more alert state, the nuclei exhibit the strongest connectivity to the salience, default mode, and auditory networks. These vigilance-dependent correlation patterns persist even after applying multiple preprocessing strategies to reduce systemic vascular effects. To validate our findings, we analyze two large 3T and 7T fMRI datasets from the Human Connectome Project and demonstrate that the static and vigilance-dependent connectivity profiles of the arousal nuclei are reproducible across 3T multi-echo, 3T single-echo, and 7T single-echo fMRI modalities. Overall, this work provides novel insights into the role of neuromodulatory systems in vigilance-related brain activity.

neuroscience↗