Aug 2026· Neuroscience· Vol 615, pp. 220-231· 0 citations· 40 references
Medicine
Abstract
As traveling waves mediate neural information processing that depends on arousal states, we hypothesized that traveling waves would represent arousal states. To investigate this, we aimed to analyze brain-wide patterns of traveling waves during resting states using functional magnetic resonance imaging (rsfMRI). Specifically we focused on the temporal dynamics of the brain-wide patterns of rsfMRI traveling waves in association with arousal states. Using a publicly available dataset (N = 27), we extracted infra-slow (0.01-0.1 Hz) activity from blood oxygen level dependent (BOLD) signals. From infra-slow activity, we measured traveling waves via local phase gradient (LPG). Then, we clustered brain-wide LPGs through the k-means algorithm to extract brain-wide patterns of traveling waves, where each cluster represented each pattern. The optimal number of clusters was found to be 2. We analyzed the temporal dynamics of these clusters in relation to arousal states. During low-arousal states, brain-wide patterns of traveling waves featured in Cluster 1 appeared more often. During high-arousal states, those in Cluster 2 did so and lasted longer. As arousal increased, cluster dwell times shortened and transitions between clusters became more frequent, with the opposite pattern observed as arousal decreased. These findings suggest that brain-wide patterns of rsfMRI traveling waves reflect arousal states through their temporal dynamics, forming a syntax underlying arousal.
Microstate analysis studies dynamic brain activity through a discrete representation of electroencephalographic (EEG) signals and their topography. While the body of literature describing findings in diverse experimental and clinical settings is growing rapidly, the effects of several core components of the microstate...
F. von Wegner, Gesine Hermann, I. Tödt et al.· bioRxiv· 0 citations
Abstract Brain gradients provide a low-dimensional framework for describing cortical organization, linking functional connectivity, anatomy, development, and transcriptional architecture. Whether this macroscale organization also structures fast electrophysiological dynamics remains less clear. Here we used the longsta...
I. Gunko, S. M. Doesburg, G. Medvedev et al.· Cerebral Cortex· 0 citations
These multimodal findings reveal distinct neural signatures of spontaneous experience and demonstrate that coordinated large-scale network dynamics and alpha-band oscillations track the natural alternation between inward and outward focus in the human mind.
Tomáš Hampejs, D. Tomeček, Stanislav Jiříček et al.· Scientific Reports· 0 citations
This primer explains how EEG/MEG activity can be organized into neural state representations, projected onto axes organized by decreasing covariance, truncated into low-dimensional representations, and visualized as trajectories that capture how distributed activity evolves over time.
Vanessa Hadid, Hamza Abdelhedi, A. Pascarella et al.· 0 citations
Identifying altered functional brain networks is crucial for unraveling the neurobiological mechanisms underlying obesity. Resting-state functional magnetic resonance imaging (rs-fMRI) provides a noninvasive means to characterize spontaneous neural activity and map large-scale functional brain networks; however, conven...
A. Temtam, M. S. Sadique, Liang-Suo Ma et al.· Optics and Photonics for Inf...· 0 citations
A framework that combines generalized phase analysis and a graph-based algorithm for detection of cortical traveling waves is developed, enabling the decomposition of complex large-scale phase patterns into multiple simultaneously propagating TWs and the quantification of their properties in single-trial data.
Kuan-Ting Ho, Hirotaka Onoe, Tadashi Isa et al.· Frontiers in Computational N...· 0 citations
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