ArticleClinical psychological science : a journal of the Association for Psychological Science2015
Bridging Levels of Understanding in Schizophrenia Through Computational Modeling.
Article in Clinical psychological science : a journal of the Association for Psychological Science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A confirmatory factor analysis of hyperfocusing and inhibitory control as separable cognitive domains in schizophrenia.Journal of psychopathology and clinical science · 2026Article
- Cell Density and mRNA Expression of Inhibitory Interneurons in Schizophrenia: A Meta-Analysis.bioRxiv : the preprint server for biology · 2025Article
- Editorial: Natural language processing and artificial intelligence tools to explore the relationship between language and schizophrenia from diagnosis to care.Frontiers in psychiatry · 2025Article
- Aberrant sense of agency induced by delayed prediction signals in schizophrenia: a computational modeling study.Schizophrenia (Heidelberg, Germany) · 2023Article
- Increased noise relates to abnormal excitation-inhibition balance in schizophrenia: a combined empirical and computational study.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Dense attention network identifies EEG abnormalities during working memory performance of patients with schizophrenia.Frontiers in psychiatry · 2023Article
- A survey of brain network analysis by electroencephalographic signals.Cognitive neurodynamics · 2022Article
- Temporal-thalamic and cingulo-opercular connectivity in people with schizophrenia.NeuroImage. Clinical · 2021Article
- Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder.Frontiers in psychiatry · 2020Article
- Dissociable Disruptions in Thalamic and Hippocampal Resting-State Functional Connectivity in Youth with 22q11.2 Deletions.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Biophysical Modeling of Large-Scale Brain Dynamics and Applications for Computational Psychiatry.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2018Review
- COMPASS: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry.Frontiers in neuroscience · 2018Article
- Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders.Biological psychiatry · 2017Review
- Schizophrenia is associated with a pattern of spatial working memory deficits consistent with cortical disinhibition.Schizophrenia research · 2017Article
- Toward understanding thalamocortical dysfunction in schizophrenia through computational models of neural circuit dynamics.Schizophrenia research · 2017Review
- Cortical thickness of neural substrates supporting cognitive empathy in individuals with schizophrenia.Schizophrenia research · 2017Article
- Clinical and biochemical study of d-serine metabolism among schizophrenia patients.Neuropsychiatric disease and treatment · 2017Article
- An Integrative Perspective on the Role of Dopamine in Schizophrenia.Biological psychiatry · 2017Review
- Challenges and promises for translating computational tools into clinical practice.Current opinion in behavioral sciences · 2016Article
- Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis.PloS one · 2016Article
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3 authors.
Funding
Abstract
Schizophrenia is an illness with a remarkably complex symptom presentation that has thus far been out of reach of neuroscientific explanation. This presents a fundamental problem for developing better treatments that target specific symptoms or root causes. One promising path forward is the incorporation of computational neuroscience, which provides a way to formalize experimental observations and, in turn, make theoretical predictions for subsequent studies. We review three complementary approaches: (a) biophysically based models developed to test cellular-level and synaptic hypotheses, (b) connectionist models that give insight into large-scale neural-system-level disturbances in schizophrenia, and (c) models that provide a formalism for observations of complex behavioral deficits, such as negative symptoms. We argue that harnessing all of these modeling approaches represents a productive approach for better understanding schizophrenia. We discuss how blending these approaches can allow the field to progress toward a more comprehensive understanding of schizophrenia and its treatment.
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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.