ArticleNeuroImage2011
Effective connectivity: influence, causality and biophysical modeling.
Article in NeuroImage, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 159 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
159 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The research progress on effective connectivity in adolescent depression based on resting-state fMRI.Frontiers in neurology · 2025Pooled it
- Toward a cumulative science of functional integration: A meta-analysis of psychophysiological interactions.Human brain mapping · 2016Pooled it
- Cause or effect: Altered brain and network activity in cervical dystonia is partially normalized by botulinum toxin treatment.NeuroImage. Clinical · 2019Trial
- The salience network causally influences default mode network activity during moral reasoning.Brain : a journal of neurology · 2013Trial
- BOLD Granger causality reflects vascular anatomy.PloS one · 2013Trial
- Distributed Neural Substrates for Autonomic Control During Human Thermoregulation: Brain Network Configurations of Sympathetic and Parasympathetic Innervation.Brain topography · 2026Article
- Dynamic Bayesian networks for neural information flow: evaluation of continuous and discrete scoring metrics.Journal of computational neuroscience · 2026Article
- Chaotic and complex dynamics expose the limits of counterfactual reasoning.Scientific reports · 2026Article
- Metric validation for detection of delayed and directed coupling.Journal of neural engineering · 2026Article
- Clarifying the conceptual dimensions of representation in neuroscience.Nature reviews. Neuroscience · 2026Review
- Lifespan development of EEG alpha and aperiodic component sources is shaped by the connectome and axonal delays.National science review · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- Target-level convergence of directional prefrontal connectivity across Alzheimer's disease stages: an fNIRS study.Frontiers in aging neuroscience · 2026Article
- Brain metabolic-functional (de)coupling from health to glioma dysfunction.Communications biology · 2025Article
- Identification of modulated whole-brain dynamical models from nonstationary electrophysiological data.Journal of neural engineering · 2025Article
- Simultaneously determining regional heterogeneity and connection directionality from neural activity and symmetric connection.PLoS computational biology · 2025Article
- Comparison of derivative-based and correlation-based methods to estimate effective connectivity in neural networks.Scientific reports · 2025Article
- Structurally informed models of directed brain connectivity.Nature reviews. Neuroscience · 2025Review
- Translational network neuroscience: Nine roadblocks and possible solutions.Network neuroscience (Cambridge, Mass.) · 2025Article
- A ventromedial visual cortical 'Where' stream to the human hippocampus for spatial scenes revealed with magnetoencephalography.Communications biology · 2024Article
99 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This is the final paper in a Comments and Controversies series dedicated to "The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution". We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of Bayesian dependency graphs and Wiener-Akaike-Granger-Schweder influence measures. We show that some of the challenges faced in this field have promising solutions and speculate on future developments.
Indexed as
Identifiers
What OpenQuestion holds
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.