ReviewBiological psychiatry. Cognitive neuroscience and neuroimaging2018
Biophysical Modeling of Large-Scale Brain Dynamics and Applications for Computational Psychiatry.
Review in Biological psychiatry. Cognitive neuroscience and neuroimaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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
46 citing papers in PubMed, 80 citations in OpenAlex.
- Trial
- Convergent multidimensional neural phenotypes in human patients and schizophrenia-relevant mouse models identify reduced recurrent excitation in cortical circuits.medRxiv : the preprint server for health sciences · 2026Article
- Intrinsic timescale develops hierarchically from sensorimotor to association cortex in youth and stabilizes in adulthood.PLoS biology · 2026Article
- Data-driven reduced modeling of neural dynamics.Nature communications · 2026Article
- Trait-Relevant Tasks Improve Personality Prediction From Structural-Functional Brain Network Coupling.Human brain mapping · 2026Article
- Uncovering putative neural mechanisms of neurotherapeutic impacts on EEG using the Human Neocortical Neurosolver.bioRxiv : the preprint server for biology · 2026Article
- Functional connectivity-based attractor dynamics of the human brain in rest, task, and disease.eLife · 2026Article
- Advances in surrogate modeling for biological agent-based simulations: trends, challenges, and future prospects.Journal of mathematical biology · 2025Review
- Stable individualized brain computing model informed by spatiotemporal co-activity patterns.PLoS computational biology · 2025Article
- Trait-Relevant Tasks Improve Personality Prediction from Structural-Functional Brain Network Coupling.bioRxiv : the preprint server for biology · 2025Article
- Mechanisms of childhood trauma: an integrative review of a multimodal, transdiagnostic pathway.Neurobiology of stress · 2025Review
- Structural-functional brain network coupling during cognitive demand reveals intelligence-relevant communication strategies.Communications biology · 2025Article
- A Computational Account of the Development and Evolution of Psychotic Symptoms.Biological psychiatry · 2025Review
- Disorder-specific neurodynamic features in schizophrenia inferred by neurodynamic embedded contrastive variational autoencoder model.Translational psychiatry · 2024Article
- Revisiting the role of computational neuroimaging in the era of integrative neuroscience.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms.Translational psychiatry · 2024Review
- Generative AI for precision neuroimaging biomarker development in psychiatry.Psychiatry research · 2024Article
- Virtual brain twins: from basic neuroscience to clinical use.National science review · 2024Review
- Article
- Imaging Transcriptomics of the Brain for Schizophrenia.Alpha psychiatry · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Noninvasive neuroimaging has revolutionized the study of the organization of the human brain and how its structure and function are altered in psychiatric disorders. A critical explanatory gap lies in our mechanistic understanding of how systems-level neuroimaging biomarkers emerge from underlying synaptic-level perturbations associated with a disease state. We describe an emerging computational psychiatry approach leveraging biophysically based computational models of large-scale brain dynamics and their potential integration with clinical and pharmacological neuroimaging. In particular, we focus on neural circuit models, which describe how patterns of functional connectivity observed in resting-state functional magnetic resonance imaging emerge from neural dynamics shaped by inter-areal interactions through underlying structural connectivity defining long-range projections. We highlight the importance of local circuit physiological dynamics, in combination with structural connectivity, in shaping the emergent functional connectivity. Furthermore, heterogeneity of local circuit properties across brain areas, which impacts large-scale dynamics, may be critical for modeling whole-brain phenomena and alterations in psychiatric disorders and pharmacological manipulation. Finally, we discuss important directions for future model development and biophysical extensions, which will expand their utility to link clinical neuroimaging to neurobiological mechanisms.
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.