ArticleNeuroImage2021
Spatiotemporal trajectories in resting-state FMRI revealed by convolutional variational autoencoder.
Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 23 citations in OpenAlex.
- Deep learning reveals a neurocomputational mechanism predicting depression risk in adolescents.Science advances · 2026Article
- Brain functional network connectivity interpolation characterizes the neuropsychiatric continuum and heterogeneity.bioRxiv : the preprint server for biology · 2026Article
- Probabilistic Cognitive State Modeling (PCSM): Decoding dynamic brain states to derive emergent cognitive processing properties from task fMRI.NeuroImage · 2026Article
- Spatiotemporal Network Dynamics Reveal Alzheimer's Disease Progression.bioRxiv : the preprint server for biology · 2025Article
- Probabilistic Cognitive State Modeling (PCSM): Decoding Latent Spatiotemporal Dynamics to Reveal Serial-Parallel Processing, Cognitive Demand, and Serial Bottleneck in Task-Based fMRI.bioRxiv : the preprint server for biology · 2025Article
- Infraslow Dynamic Patterns in Human Cortical Networks Track a Spectrum of External to Internal Attention.Human brain mapping · 2025Article
- Providing context: Extracting non-linear and dynamic temporal motifs from brain activity.PloS one · 2025Article
- Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention.bioRxiv : the preprint server for biology · 2024Article
- Classification of cognitive ability of healthy older individuals using resting-state functional connectivity magnetic resonance imaging and an extreme learning machine.BMC medical imaging · 2024Article
- Article
- Leading basic modes of spontaneous activity drive individual functional connectivity organization in the resting human brain.Communications biology · 2023Article
- Spatiotemporal patterns of spontaneous brain activity: a mini-review.Neurophotonics · 2022Review
- Functional Connectivity of the Brain Across Rodents and Humans.Frontiers in neuroscience · 2022Review
- Brain functional network connectivity interpolation characterizes the neuropsychiatric continuum and heterogeneity.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Recent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.