ReviewBrain informatics2017
Multiscale modeling in the clinic: diseases of the brain and nervous system.
Review in Brain informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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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
17 citing papers in PubMed.
- In silico models in oncology, neurology, and epidemiology: systems-level and multiscale perspectives.NPJ systems biology and applications · 2026Review
- Harnessing Nonlinear Mechanics to Transform Medical Diagnostics.Applied mechanics reviews · 2025Article
- The Cerebellar Role in Emotions at a Turning Point: Bibliometric Analysis and Collaboration Networks.Cerebellum (London, England) · 2025Review
- Multiscale brain modeling: bridging microscopic and macroscopic brain dynamics for clinical and technological applications.Frontiers in cellular neuroscience · 2025Review
- Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!Interface focus · 2024Article
- Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- Dysfunction of motor cortices in Parkinson's disease.Cerebral cortex (New York, N.Y. : 1991) · 2024Review
- Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics.Cell reports · 2023Article
- Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair.Communications biology · 2023Review
- Modeling psychopathology: From data models to formal theories.Psychological methods · 2022Review
- Article
- Multiscale modeling meets machine learning: What can we learn?Archives of computational methods in engineering : state of the art reviews · 2021Article
- From digital hype to analogue reality: Universal simulation beyond the quantum and exascale eras.Journal of computational science · 2020Article
- In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia.NPJ schizophrenia · 2020Article
- Integrating machine learning and multiscale modeling-perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences.NPJ digital medicine · 2019Review
- Dynamics of spontaneous activity in random networks with multiple neuron subtypes and synaptic noise : Spontaneous activity in networks with synaptic noise.Journal of computational neuroscience · 2018Article
- Material properties of the brain in injury-relevant conditions - Experiments and computational modeling.Journal of the mechanical behavior of biomedical materials · 2018Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Computational neuroscience is a field that traces its origins to the efforts of Hodgkin and Huxley, who pioneered quantitative analysis of electrical activity in the nervous system. While also continuing as an independent field, computational neuroscience has combined with computational systems biology, and neural multiscale modeling arose as one offshoot. This consolidation has added electrical, graphical, dynamical system, learning theory, artificial intelligence and neural network viewpoints with the microscale of cellular biology (neuronal and glial), mesoscales of vascular, immunological and neuronal networks, on up to macroscales of cognition and behavior. The complexity of linkages that produces pathophysiology in neurological, neurosurgical and psychiatric disease will require multiscale modeling to provide understanding that exceeds what is possible with statistical analysis or highly simplified models: how to bring together pharmacotherapeutics with neurostimulation, how to personalize therapies, how to combine novel therapies with neurorehabilitation, how to interlace periodic diagnostic updates with frequent reevaluation of therapy, how to understand a physical disease that manifests as a disease of the mind. Multiscale modeling will also help to extend the usefulness of animal models of human diseases in neuroscience, where the disconnects between clinical and animal phenomenology are particularly pronounced. Here we cover areas of particular interest for clinical application of these new modeling neurotechnologies, including epilepsy, traumatic brain injury, ischemic disease, neurorehabilitation, drug addiction, schizophrenia and neurostimulation.
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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.