ArticleSchizophrenia research2026
Motivation and pleasure deficits reflect altered network embedding of normal brain deviations in schizophrenia.
Article in Schizophrenia research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
backgroundNegative symptoms in schizophrenia are associated with significantly worse outcomes, and their factor structure (i.e., diminished motivation and pleasure [MAP] and diminished expressivity [EXP]) has only recently been clarified. Studies investigating structural imaging correlates of negative symptoms have largely focused on cortical regions involved in motivation, reward processing, affect expression, and language. Structural covariance network modeling provides a framework for examining covariance among these cortical regions in a network-like manner.
methodsClinical and imaging data from 203 individuals with schizophrenia were obtained from three independent data sites. Cortical thickness measures based on the Desikan-Killiany atlas were standardized using a normative modeling algorithm developed by the ENIGMA Lifespan Working Group. Structural covariance networks were constructed using a priori cortical regions of interest related to MAP and EXP. Linear regression models tested whether MAP and EXP severity predicted network embeddedness.
resultsBoth the MAP-related (F DISCUSSION: Results suggest that MAP is selectively associated with network-level over-coupling of cortical morphology, whereas EXP may reflect more distributed network properties. These findings underscore the potential role of cortical network rigidity in the pathophysiology of negative symptoms.
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.