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Record W3028193777 · doi:10.1093/schbul/sbaa030.454

M142. INCREASED VENTRAL STRIATAL FUNCTIONAL CONNECTIVITY IN PATIENTS WITH SCHIZOPHRENIA DURING REWARD ANTICIPATION

2020· article· en· W3028193777 on OpenAlexaff
Fabien Carruzzo, Matthias Kirschner, Stefan Kaiser

Bibliographic record

VenueSchizophrenia Bulletin · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsVentral striatumPsychologyAnticipation (artificial intelligence)ApathyAnterior cingulate cortexStriatumNeuroscienceSchizophrenia (object-oriented programming)Posterior cingulateFunctional magnetic resonance imagingPsychiatryCognitionDopamine

Abstract

fetched live from OpenAlex

Abstract Background Recent studies have pointed at the ventral striatum as one of the main candidates underlying motivational dysfunctions in schizophrenia. Patients with negative symptoms show decreased BOLD activity in the ventral striatum and this activity strongly correlates with apathy scores during reward anticipation. While in patients with schizophrenia blunted ventral striatal activation during reward anticipation has been widely reported, little is known about abnormal striatal functional connectivity during reward anticipation. In this study, we performed generalized whole-brain psychophysiological interaction (gPPI) analyses using the right and left ventral striatum as seeds in schizophrenia patients with apathy and reduced ventral striatal activation from two published fMRI studies (Kirschner et al., 2016; Stepien et al., 2018). Methods Forty-four healthy controls (18 females, mean age = 31.1) and 40 patients with schizophrenia (10 females, mean age = 32.5) performed a variant of the Monetary Incentive Delay task within an fMRI design. Negative symptoms were assessed with the Brief Negative Symptoms Scale (BNSS). GPPI analyses were done using the PPPI toolbox on SPM 8. To examine potential difference in striatal functional connectivity, we performed two sample t-tests between patients with schizophrenia and healthy controls using the contrast [High Reward Anticipation – No Reward Anticipation]. Results Patients with schizophrenia showed increased functional connectivity between the right ventral striatum and the anterior cingulate cortex, posterior cingulate cortex, cerebellum, motor cortex, parietal cortex, temporo-parietal junction and thalamus compared to controls (cluster-level FDR p<0.05). No higher connectivity was found in controls compared to patients. For the regions with increased functional connectivity, we performed correlations between the patients’ gPPI signal and apathy. We found significant correlations between apathy and functional connectivity between the right ventral striatum and the right posterior cingulate cortex (r=0.40, p<.05) and right parietal cortex (r=0.39, p<.05). Discussion Our preliminary results indicate that physiological changes in the ventral striatum lead to dysfunctional connectivity with a cortex-wide network, affecting both cortico-striatal-thalamic-cortical and cortico-striatal-thalamic-cerebellar pathways. In addition, we show that some of these changes are related to apathy levels. This work provides novel insights in cortico-striatal network dysfunction during reward processing in patients with schizophrenia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.209
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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