ArticleFrontiers in psychiatry2019
Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls.
Article in Frontiers in psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Emotion Processing in Schizophrenia: Insights From a Brain Imaging Study Comparing Patients, Siblings, and Healthy Controls.Human brain mapping · 2026Trial
- What Static Connectivity Misses: Dynamic Alpha-Band Brain Network States in First-Episode Psychosis.Brain topography · 2026Article
- Lurasidone induces developmental toxicity and behavioral impairments in zebrafish embryos.Frontiers in psychiatry · 2025Article
- Dysconnection and cognition in schizophrenia: A spectral dynamic causal modeling study.Human brain mapping · 2023Article
- The Difficult Path to the Discovery of Novel Treatments in Psychiatric Disorders.Advances in neurobiology · 2023Article
- Early Markers in Resistant Schizophrenia: Effect of the First Antipsychotic Drug.Diagnostics (Basel, Switzerland) · 2022Article
- Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm.Brain sciences · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
The study of brain networks, including those derived from functional neuroimaging data, attracts a broad interest and represents a rapidly growing interdisciplinary field. Comparing networks of healthy volunteers with those of patients can potentially offer new, quantitative diagnostic methods and a framework for better understanding brain and mind disorders. We explore resting state functional Magnetic Resonance Imaging (fMRI) data through network measures. We construct networks representing 15 healthy individuals and 12 schizophrenia patients (males and females), all of whom are administered three drug treatments: i) a placebo; and two antipsychotic medications ii) aripiprazole and iii) sulpiride. We compare these resting state networks to a performance at an "N-back" working memory task. We demonstrate that not only is there a distinctive network architecture in the healthy brain that is disrupted in schizophrenia but also that both networks respond to antipsychotic medication. We first reproduce the established finding that brain networks of schizophrenia patients exhibit increased efficiency and reduced clustering compared with controls. Our data then reveal that the antipsychotic medications mitigate this effect, shifting the metrics toward those observed in healthy volunteers, with a marked difference in efficacy between the two drugs. Additionally, we find that aripiprazole considerably alters the network statistics of healthy controls. Examining the "N-back" working memory task, we establish that aripiprazole also adversely affects their performance. This suggests that changes to macroscopic brain network architecture result in measurable behavioral differences. This is one of the first studies to directly compare different medications using a whole-brain graph theoretical analysis with accompanying behavioral data. The small sample size is an inherent limitation and means a degree of caution is warranted in interpreting the findings. Our results lay the groundwork for an objective methodology with which to calculate and compare the efficacy of different treatments of mind and brain disorders.
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