ArticleNetwork neuroscience (Cambridge, Mass.)2024
Spectral dynamic causal modeling: A didactic introduction and its relationship with functional connectivity.
Article in Network neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The research progress on effective connectivity in adolescent depression based on resting-state fMRI.Frontiers in neurology · 2025Pooled it
- Directional Brain Connectivity Changes Induced by Heart Rate Variability Biofeedback: A Spectral Dynamic Causal Modeling Study.Research square · 2026Article
- Psychedelics align brain activity with context.Nature · 2026Article
- Multimodal Branched Transport Infers Anatomically Aligned Brain Reaction Maps.Neuroinformatics · 2026Article
- Predicting individual differences of fear and cognitive learning and extinction.Nature communications · 2026Article
- Spectral dynamic causal modeling of effective connectivity across multiple brain networks in pilot trainees.iScience · 2026Article
- A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.Neuroscience of consciousness · 2026Article
- Central autonomic network-heart interplay in anorexia nervosa. A cross-spectral dynamic causal modeling study.NeuroImage. Clinical · 2026Article
- The motion sensitivity and predictive utility of different estimates of interregional functional coupling in resting-state functional MRI.Network neuroscience (Cambridge, Mass.) · 2026Article
- Effective Connectivity Alterations of Directed Brain Network in Pediatric Patients With Spinal Cord Injury.CNS neuroscience & therapeutics · 2025Article
- Repetitive transcranial magnetic stimulation-driven modulation of unbiased functional connectivity in the supracallosal anterior cingulate cortex causally ameliorates information processing speed in amnestic mild cognitive impairment.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Simultaneously determining regional heterogeneity and connection directionality from neural activity and symmetric connection.PLoS computational biology · 2025Article
- Five Fristonian Formulae.Entropy (Basel, Switzerland) · 2025Article
- Structurally informed resting-state effective connectivity recapitulates cortical hierarchy.bioRxiv : the preprint server for biology · 2025Article
- A Novel Investigation of an In-Scanner Alternative to the Cold Pressor Test in Healthy Individuals.Human brain mapping · 2025Article
- Trialing addiction neurocircuitry targets and directionality of brain stimulation effects: A deep TMS/fMRI trial in people with alcohol use disorder.Contemporary clinical trials communications · 2025Article
- SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Minimum-Phase Property of the Hemodynamic Response Function, and Implications for Granger Causality in fMRI.Human brain mapping · 2025Article
- Neural mechanisms of disease pathology and cognition in young-onset Alzheimer's disease variants.Journal of Alzheimer's disease : JAD · 2025Article
- Spectral imprint of structural embedding in effective connectivity.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a didactic introduction to spectral dynamic causal modeling (DCM), a Bayesian state-space modeling approach used to infer effective connectivity from noninvasive neuroimaging data. Spectral DCM is currently the most widely applied DCM variant for resting-state functional MRI analysis. Our aim is to explain its technical foundations to an audience with limited expertise in state-space modeling and spectral data analysis. Particular attention will be paid to cross-spectral density, which is the most distinctive feature of spectral DCM and is closely related to functional connectivity, as measured by (zero-lag) Pearson correlations. In fact, the model parameters estimated by spectral DCM are those that best reproduce the cross-correlations between all measurements-at all time lags-including the zero-lag correlations that are usually interpreted as functional connectivity. We derive the functional connectivity matrix from the model equations and show how changing a single effective connectivity parameter can affect all pairwise correlations. To complicate matters, the pairs of brain regions showing the largest changes in functional connectivity do not necessarily coincide with those presenting the largest changes in effective connectivity. We discuss the implications and conclude with a comprehensive summary of the assumptions and limitations of spectral DCM.
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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.