ArticleNetwork neuroscience (Cambridge, Mass.)2022
It's about time: Linking dynamical systems with human neuroimaging to understand the brain.
Article in Network neuroscience (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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31 citing papers in PubMed.
- Arousal-driven critical roaming reproduces human functional connectivity dynamics.PLoS biology · 2026Article
- Dynamic fMRI networks of human emotion.eLife · 2026Article
- Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease.Nature communications · 2026Article
- Dynamical Cognitive Science! Wherefore Art Thou?Topics in cognitive science · 2026Article
- Cortical neuron classes and recursive curvature collapse: a neurobiological model of conscious dynamics.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- Spatiotemporal asymmetries on brain energy landscape uncover system entrapment related to depression severity.Nature communications · 2026Article
- Geometry of neural dynamics along the cortical attractor landscape reflects changes in attention.Nature communications · 2026Article
- The biological role of local and global fMRI BOLD signal variability in multiscale human brain organization.Nature communications · 2026Article
- Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- From genes to patterns: five key dynamical systems concepts to decode developmental regulatory mechanisms.Development (Cambridge, England) · 2025Review
- A Bayesian hierarchical model of trial-to-trial fluctuations in decision criterion.PLoS computational biology · 2025Article
- Article
- Impaired brain ability of older adults to transit and persist to latent states with well-organized structures at wakeful rest.GeroScience · 2025Article
- Exploring the suitability of piecewise-linear dynamical system models for cognitive neural dynamics.Frontiers in neuroscience · 2025Article
- Temporal variability of brain-behavior relationships in fine-scale dynamics of edge time series.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Analyzing the brain's dynamic response to targeted stimulation using generative modeling.Network neuroscience (Cambridge, Mass.) · 2025Review
- Article
- A computational mechanism of cue-stimulus integration for pain in the brain.Science advances · 2024Article
- Quantifying brain-functional dynamics using deep dynamical systems: Technical considerations.iScience · 2024Article
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6 authors.
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Abstract
Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these patterns are often interpreted in light of dynamic, information-processing concepts, the static, local, and inferential nature of the statistical approach makes it challenging to directly link neuroimaging results to plausible underlying neural mechanisms. Here, we argue that dynamical systems theory provides the crucial mechanistic framework for characterizing both the brain's time-varying quality and its partial stability in the face of perturbations, and hence, that this perspective can have a profound impact on the interpretation of human neuroimaging results and their relationship with behavior. After briefly reviewing some key terminology, we identify three key ways in which neuroimaging analyses can embrace a dynamical systems perspective: by shifting from a local to a more global perspective, by focusing on dynamics instead of static snapshots of neural activity, and by embracing modeling approaches that map neural dynamics using "forward" models. Through this approach, we envisage ample opportunities for neuroimaging researchers to enrich their understanding of the dynamic neural mechanisms that support a wide array of brain functions, both in health and in the setting of psychopathology.
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