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Feng S, Huang Y, Li H, Zhou S, Ning Y, Han W, Zhang Z, Liu C, Li J, Zhong L, Wu K, Wu F. Dynamic effective connectivity in the cerebellar dorsal dentate nucleus and the cerebrum, cognitive impairment, and clinical correlates in patients with schizophrenia. Schizophr Res 2024; 271:394-401. [PMID: 38729789 DOI: 10.1016/j.schres.2024.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/16/2024] [Accepted: 05/03/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Schizophrenia (SZ) is characterized by disconnected cerebral networks. Recent studies have shown that functional connectivity between the cerebellar dorsal dentate nucleus (dDN) and cerebrum is correlated with psychotic symptoms, and processing speed in SZ patients. Dynamic effective connectivity (dEC) is a reliable indicator of brain functional status. However, the dEC between the dDN and cerebrum in patients with SZ remains largely unknown. METHODS Resting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC). Granger causality analysis and sliding time window methods were used to calculate dDN-based dEC maps for all subjects, and k-means clustering was performed to obtain several dEC states. Finally, between-group differences in dynamic effective connectivity variability (dECV) and clinical correlations were obtained using two-sample t-tests and correlation analysis. RESULTS We detected four dEC states from the cerebrum to the right dDN (IN states) and three dEC states from the right dDN to the cerebrum (OUT states), with SZ group having fewer transitions in the OUT states. SZ group had increased dECV from the right dDN to the right middle frontal gyrus (MFG) and left lingual gyrus (LG). Correlations were found between the dECV from the right dDN to the right MFG and symptom severity and between the dECV from the right dDN to the left LG and working memory performance. CONCLUSIONS This study reveals a dynamic causal relationship between cerebellar dDN and the cerebrum in SZ and provides new evidence for the involvement of cerebellar neural circuits in neurocognitive functions in SZ.
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Affiliation(s)
- Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Liangda Zhong
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China; Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China.
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Cattarinussi G, Grimaldi DA, Aarabi MH, Sambataro F. Static and Dynamic Dysconnectivity in Early Psychosis: Relationship With Symptom Dimensions. Schizophr Bull 2024:sbae142. [PMID: 39212653 DOI: 10.1093/schbul/sbae142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
BACKGROUND AND HYPOTHESIS Altered functional connectivity (FC) has been frequently reported in psychosis. Studying FC and its time-varying patterns in early-stage psychosis allows the investigation of the neural mechanisms of this disorder without the confounding effects of drug treatment or illness-related factors. STUDY DESIGN We employed resting-state functional magnetic resonance imaging (rs-fMRI) to explore FC in individuals with early psychosis (EP), who also underwent clinical and neuropsychological assessments. 96 EP and 56 demographically matched healthy controls (HC) from the Human Connectome Project for Early Psychosis database were included. Multivariate analyses using spatial group independent component analysis were used to compute static FC and dynamic functional network connectivity (dFNC). Partial correlations between FC measures and clinical and cognitive variables were performed to test brain-behavior associations. STUDY RESULTS Compared to HC, EP showed higher static FC in the striatum and temporal, frontal, and parietal cortex, as well as lower FC in the frontal, parietal, and occipital gyrus. We found a negative correlation in EP between cognitive function and FC in the right striatum FC (pFWE = 0.009). All dFNC parameters, including dynamism and fluidity measures, were altered in EP, and positive symptoms were negatively correlated with the meta-state changes and the total distance (pFWE = 0.040 and pFWE = 0.049). CONCLUSIONS Our findings support the view that psychosis is characterized from the early stages by complex alterations in intrinsic static and dynamic FC, that may ultimately result in positive symptoms and cognitive deficits.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia, USA
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
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Maksymchuk N, Bustillo JR, Mathalon DH, Preda A, Miller RL, Calhoun VD. Static and Dynamic Cross-Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.15.599084. [PMID: 38948857 PMCID: PMC11212858 DOI: 10.1101/2024.06.15.599084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Schizophrenia (SZ) patients exhibit abnormal static and dynamic functional connectivity across various brain domains. We present a novel approach based on static and dynamic inter-network connectivity entropy (ICE), which represents the entropy of a given network's connectivity to all the other brain networks. This novel approach enables the investigation of how connectivity strength is heterogeneously distributed across available targets in both SZ patients and healthy controls. We analyzed fMRI data from 151 schizophrenia patients and demographically matched 160 healthy controls. Our assessment encompassed both static and dynamic ICE, revealing significant differences in the heterogeneity of connectivity levels across available brain networks between SZ patients and healthy controls (HC). These networks are associated with subcortical (SC), auditory (AUD), sensorimotor (SM), visual (VIS), cognitive control (CC), default mode network (DMN) and cerebellar (CB) functional brain domains. Elevated ICE observed in individuals with SZ suggests that patients exhibit significantly higher randomness in the distribution of time-varying connectivity strength across functional regions from each source network, compared to healthy control group. C-means fuzzy clustering analysis of functional ICE correlation matrices revealed that SZ patients exhibit significantly higher occupancy weights in clusters with weak, low-scale functional entropy correlation, while the control group shows greater occupancy weights in clusters with strong, large-scale functional entropy correlation. k-means clustering analysis on time-indexed ICE vectors revealed that cluster with highest ICE have higher occupancy rates in SZ patients whereas clusters characterized by lowest ICE have larger occupancy rates for control group. Furthermore, our dynamic ICE approach revealed that it appears healthy for a brain to primarily circulate through complex, less structured connectivity patterns, with occasional transitions into more focused patterns. However, individuals with SZ seem to struggle with transiently attaining these more focused and structured connectivity patterns. Proposed ICE measure presents a novel framework for gaining deeper insights into understanding mechanisms of healthy and disease brain states and a substantial step forward in the developing advanced methods of diagnostics of mental health conditions.
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Affiliation(s)
- Natalia Maksymchuk
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Juan R. Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Daniel H. Mathalon
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Mental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco, CA, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Robyn L. Miller
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
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Ibanez A, Kringelbach ML, Deco G. A synergetic turn in cognitive neuroscience of brain diseases. Trends Cogn Sci 2024; 28:319-338. [PMID: 38246816 DOI: 10.1016/j.tics.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/15/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024]
Abstract
Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.
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Affiliation(s)
- Agustin Ibanez
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile; Global Brain Health Institute (GBHI), University California San Francisco (UCSF), San Francisco, CA, USA; Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Department of Psychiatry, University of Oxford, Oxford, UK.
| | - Morten L Kringelbach
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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Masias Bruns M, Ramirez-Mahaluf JP, Valli I, Ortuño M, Ilzarbe D, de la Serna E, Navarro OP, Crossley NA, González Ballester MÁ, Baeza I, Piella G, Castro-Fornieles J, Sugranyes G. Altered Temporal Dynamics of Resting-State Functional Magnetic Resonance Imaging in Adolescent-Onset First-Episode Psychosis. Schizophr Bull 2024; 50:418-426. [PMID: 37607335 PMCID: PMC10919773 DOI: 10.1093/schbul/sbad107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
BACKGROUND Dynamic functional connectivity (dFC) alterations have been reported in patients with adult-onset and chronic psychosis. We sought to examine whether such abnormalities were also observed in patients with first episode, adolescent-onset psychosis (AOP), in order to rule out potential effects of chronicity and protracted antipsychotic treatment exposure. AOP has been suggested to have less diagnostic specificity compared to psychosis with onset in adulthood and occurs during a period of neurodevelopmental changes in brain functional connections. STUDY DESIGN Seventy-nine patients with first episode, AOP (36 patients with schizophrenia-spectrum disorder, SSD; and 43 with affective psychotic disorder, AF) and 54 healthy controls (HC), aged 10 to 17 years were included. Participants underwent clinical and cognitive assessments and resting-state functional magnetic resonance imaging. Graph-based measures were used to analyze temporal trajectories of dFC, which were compared between patients with SSD, AF, and HC. Within patients, we also tested associations between dFC parameters and clinical variables. STUDY RESULTS Patients with SSD temporally visited the different connectivity states in a less efficient way (reduced global efficiency), visiting fewer nodes (larger temporal modularity, and increased immobility), with a reduction in the metabolic expenditure (cost and leap size), relative to AF and HC (effect sizes: Cohen's D, ranging 0.54 to.91). In youth with AF, these parameters did not differ compared to HC. Connectivity measures were not associated with clinical severity, intelligence, cannabis use, or dose of antipsychotic medication. CONCLUSIONS dFC measures hold potential towards the development of brain-based biomarkers characterizing adolescent-onset SSD.
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Affiliation(s)
- Mireia Masias Bruns
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Pablo Ramirez-Mahaluf
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Isabel Valli
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - María Ortuño
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Daniel Ilzarbe
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Olga Puig Navarro
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Nicolas A Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Miguel Ángel González Ballester
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Inmaculada Baeza
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Gemma Piella
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Josefina Castro-Fornieles
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Gisela Sugranyes
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
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Van Dyken PC, MacKinley M, Khan AR, Palaniyappan L. Cortical Network Disruption Is Minimal in Early Stages of Psychosis. SCHIZOPHRENIA BULLETIN OPEN 2024; 5:sgae010. [PMID: 39144115 PMCID: PMC11207789 DOI: 10.1093/schizbullopen/sgae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Background and Hypothesis Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness. Study Design Diffusion and T1-weighted 7T MR scans were obtained from N = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with N = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset. Study Results Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics. Conclusions The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.
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Affiliation(s)
- Peter C Van Dyken
- Neuroscience Graduate Program, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Michael MacKinley
- Lawson Health Research Institute, London Health Sciences Centre, London, ON, Canada
| | - Ali R Khan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, London, ON, Canada
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
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Tuovinen N, Hofer A. Resting-state functional MRI in treatment-resistant schizophrenia. FRONTIERS IN NEUROIMAGING 2023; 2:1127508. [PMID: 37554635 PMCID: PMC10406237 DOI: 10.3389/fnimg.2023.1127508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/17/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND Abnormalities in brain regions involved in the pathophysiology of schizophrenia (SCZ) may present insight into individual clinical symptoms. Specifically, functional connectivity irregularities may provide potential biomarkers for treatment response or treatment resistance, as such changes can occur before any structural changes are visible. We reviewed resting-state functional magnetic resonance imaging (rs-fMRI) findings from the last decade to provide an overview of the current knowledge on brain functional connectivity abnormalities and their associations to symptoms in treatment-resistant schizophrenia (TRS) and ultra-treatment-resistant schizophrenia (UTRS) and to look for support for the dysconnection hypothesis. METHODS PubMed database was searched for articles published in the last 10 years applying rs-fMRI in TRS patients, i.e., who had not responded to at least two adequate treatment trials with different antipsychotic drugs. RESULTS Eighteen articles were selected for this review involving 648 participants (TRS and control cohorts). The studies showed frontal hypoconnectivity before the initiation of treatment with CLZ or riluzole, an increase in frontal connectivity after riluzole treatment, fronto-temporal hypoconnectivity that may be specific for non-responders, widespread abnormal connectivity during mixed treatments, and ECT-induced effects on the limbic system. CONCLUSION Probably due to the heterogeneity in the patient cohorts concerning antipsychotic treatment and other clinical variables (e.g., treatment response, lifetime antipsychotic drug exposure, duration of illness, treatment adherence), widespread abnormalities in connectivity were noted. However, irregularities in frontal brain regions, especially in the prefrontal cortex, were noted which are consistent with previous SCZ literature and the dysconnectivity hypothesis. There were major limitations, as most studies did not differentiate between TRS and UTRS (i.e., CLZ-resistant schizophrenia) and investigated heterogeneous cohorts treated with mixed treatments (with or without CLZ). This is critical as in different subtypes of the disorder an interplay between dopaminergic and glutamatergic pathways involving frontal, striatal, and hippocampal brain regions in separate ways is likely. Better definitions of TRS and UTRS are necessary in future longitudinal studies to correctly differentiate brain regions underlying the pathophysiology of SCZ, which could serve as potential functional biomarkers for treatment resistance.
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Affiliation(s)
- Noora Tuovinen
- Division of Psychiatry I, Department of Psychiatry, Psychotherapy, Psychosomatics and Medical Psychology, Medical University of Innsbruck, Innsbruck, Austria
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Castro MN, Bocaccio H, De Pino G, Sánchez SM, Wainsztein AE, Drucaroff L, Costanzo EY, Crossley NA, Villarreal MF, Guinjoan SM. Abnormal brain network community structure related to psychological stress in schizophrenia. Schizophr Res 2023; 254:42-53. [PMID: 36801513 DOI: 10.1016/j.schres.2023.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 01/30/2023] [Accepted: 02/04/2023] [Indexed: 02/17/2023]
Abstract
Recent functional imaging studies in schizophrenia consistently report a disruption of brain connectivity. However, most of these studies analyze the brain connectivity during resting state. Since psychological stress is a major factor for the emergence of psychotic symptoms, we sought to characterize the brain connectivity reconfiguration induced by stress in schizophrenia. We tested the hypothesis that an alteration of the brain's integration-segregation dynamic could be the result of patients with schizophrenia facing psychological stress. To this end, we studied the modular organization and the reconfiguration of networks induced by a stress paradigm in forty subjects (twenty patients and twenty controls), thus analyzing the dynamics of the brain in terms of integration and segregation processes by using 3T-fMRI. Patients with schizophrenia did not show statistically significant differences during the control task compared with controls, but they showed an abnormal community structure during stress condition and an under-connected reconfiguration network with a reduction of hub nodes, suggesting a deficit of integration dynamic with a greater compromise of the right hemisphere. These results provide evidence that schizophrenia has a normal response to undemanding stimuli but shows a disruption of brain functional connectivity between key regions involved in stress response, potentially leading to altered functional brain dynamics by reducing integration capacity and showing deficits recruiting right hemisphere regions. This could in turn underlie the hyper-sensitivity to stress characteristic of schizophrenia.
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Affiliation(s)
- Mariana N Castro
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires (UBA), Argentina
| | - Hernán Bocaccio
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Departamento de Física, Facultad de Ciencias Exactas y Naturales, UBA, Argentina
| | - Gabriela De Pino
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Laboratorio de Neuroimágenes, Departamento de Imágenes, Fleni, Argentina; Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Argentina
| | - Stella M Sánchez
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina
| | - Agustina E Wainsztein
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Servicio de Psiquiatría, Fleni, Argentina
| | - Lucas Drucaroff
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires (UBA), Argentina
| | - Elsa Y Costanzo
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires (UBA), Argentina; Servicio de Psiquiatría, Fleni, Argentina
| | - Nicolás A Crossley
- Departamento de Psiquiatría, Facultad de Medicina, Pontificia Universidad Católica de Chile, Chile
| | - Mirta F Villarreal
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Departamento de Física, Facultad de Ciencias Exactas y Naturales, UBA, Argentina
| | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, USA; Department of Psychiatry, Health Sciences Center, Oklahoma University, Tulsa, Oklahoma, USA
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