Evidence map›Paper›PMID 42390262›Full record

ReviewScience progress

Neuroimaging in schizophrenia: From group-average abnormalities to individualised circuit models.

Wesley Pyke, Sukhwinder S Shergill

Abstract readReview
In one paragraph

Review in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Wesley PykeSchool of Psychology, University of Kent, Canterbury, UK.ORCID 0000-0002-0975-1308
Sukhwinder S ShergillKent and Medway Medical School, Canterbury, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This narrative review synthesises advances in multimodal neuroimaging that, over the past five years, have substantially refined models of schizophrenia pathophysiology. Converging evidence from structural, diffusion, functional, molecular, and computational studies challenges static, regionally focal, or single-neurotransmitter accounts of the disorder. Instead, contemporary findings support a framework in which schizophrenia reflects heterogeneous, developmentally anchored deviations in distributed neural circuits that manifest as large-scale network instability. Structural and diffusion imaging reveal individually variable patterns of cortical, white matter, and thalamic subnuclei alterations. Functional MRI demonstrates impaired regulation across salience, default mode, executive, and thalamocortical systems, while positron emission tomography and magnetic resonance spectroscopy implicate subregion-specific dopaminergic and glutamatergic abnormalities. Computational modelling further indicates that these multilevel disturbances may converge on altered synaptic gain and excitation-inhibition imbalance within cortical microcircuits, providing a mechanistic substrate for systems-level dysconnectivity. Importantly, heterogeneity is not incidental but central: normative modelling and biologically informed subgrouping demonstrate that while group-level effects are robust, the anatomical and neurochemical loci of deviation vary substantially across individuals. We propose that shared network instability may arise from diverse developmental perturbations across cortico-striato-thalamo-cortical circuits. Future progress will depend on longitudinal, harmonised, and multimodal study designs capable of modelling individual trajectories across risk stages and treatment exposure. Conceptualising schizophrenia as a dynamically evolving circuit disorder therefore offers an integrative framework that bridges molecular dysfunction and clinical expression and provides a roadmap for mechanism-informed stratification, while clinical translation remains a longer-term objective.

Indexed as

BrainModels, NeurologicalNeuroimagingSchizophreniaHumansNerve NetPositron-Emission Tomographydopamine–glutamate interactionnetwork dysconnectivityneuroimagingnormative modellingprecision psychiatryschizophreniathalamocortical circuits

Identifiers

PMID42390262
PMCPMC13328984

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.