ArticleNature methods2025
Mapping effective connectivity by virtually perturbing a surrogate brain.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- A personalized map of where, when, and how to stimulate the brain to elicit controlled responses.bioRxiv : the preprint server for biology · 2026Article
- Toward Optimizing Thalamic Deep Brain Stimulation for Cortical Modulation: A Surrogate Brain Approach.bioRxiv : the preprint server for biology · 2026Article
- A Deep Learning Framework for Spatiotemporal Modeling of Visual Task fMRI.bioRxiv : the preprint server for biology · 2026Article
- High-resolution electrophysiological mapping of effective connectivity of lateral prefrontal cortex.Brain : a journal of neurology · 2026Article
- Re-engineering the disordered mind: clinical experimentation, dynamical systems, and AI for personalized psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- Artificial intelligence as a surrogate brain: bridging neural dynamical models and data.National science review · 2026Review
- Machine learning with multitype functional connectivity uncovers whole-brain network disruption in primary angle-closure glaucoma.Brain informatics · 2025Article
- Constraining inference of across-region interactions using neural activity perturbations.bioRxiv : the preprint server for biology · 2025Article
- Dynamic excitation/inhibition balance preceding seizure onset and its link to functional and structural brain architecture.BMC medicine · 2025Article
- Investigating Disruptions in Information Flow due to Sickle Cell Disease Using Granger Causality.Human brain mapping · 2025Article
- Simultaneously determining regional heterogeneity and connection directionality from neural activity and symmetric connection.PLoS computational biology · 2025Article
- The subcortical brain regions influence the cortical areas during resting-state: an fMRI study.Frontiers in human neuroscience · 2024Article
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Authors and funding
9 authors.
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Abstract
Effective connectivity (EC), which reflects the causal interactions between brain regions, is fundamental to understanding information processing in the brain; however, traditional methods for obtaining EC, which rely on neural responses to stimulation, are often invasive or limited in spatial coverage, making them unsuitable for whole-brain EC mapping in humans. Here, to address this gap, we introduce Neural Perturbational Inference (NPI), a data-driven framework for mapping whole-brain EC. NPI employs an artificial neural network trained to model large-scale neural dynamics, serving as a computational surrogate of the brain. By systematically perturbing all regions in the surrogate brain and analyzing the resulting responses in other regions, NPI maps the directionality, strength and excitatory/inhibitory properties of brain-wide EC. Validation of NPI on generative models with known ground-truth EC demonstrates its superiority over existing methods such as Granger causality and dynamic causal modeling. When applied to resting-state functional magnetic resonance imaging data across diverse datasets, NPI reveals consistent, structurally supported EC patterns. Furthermore, comparisons with cortico-cortical evoked potential data show a strong resemblance between NPI-inferred EC and real stimulation propagation patterns. By transitioning from correlational to causal understandings of brain functionality, NPI marks a stride in decoding the brain's functional architecture and facilitating both neuroscience studies and clinical applications.
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