Editorial for “Alteration of single‐subject gray matter networks in major depressed patients with suicidality”

Abstract Schizophrenia is often regarded as a psychiatric disorder caused by disrupted connections in the brain. Evidence suggests that the gray matter of schizophrenia patients is damaged in a modular pattern. Recently, abnormal topological organization was observed in the gray matter networks of patients with schizophrenia. However, the modular-level alteration of gray matter networks in schizophrenia remains unclear. In this study, single-subject gray matter networks were constructed for a total of 217 subjects (116 patients with schizophrenia and 101 controls). We analyzed the topological characteristics of the brain network and the strengths of connections between and within modules. Compared with the outcomes in the control group, the global efficiency and participation coefficient values of the single-subject gray matter networks in schizophrenic patients were significantly reduced. The nodal participation coefficient of the regions involving the FPN, DMN and SCN were significantly decreased in subjects with schizophrenia. The intermodule connections between the FPN and VIS and between the DMN and SCN, in the FPN were significantly reduced in the patient group. In the FPN, the intramodule nodal connection strength of the left orbital inferior frontal gyrus and right inferior parietal gyrus was significantly decreased in schizophrenia patients. Reduced intermodule nodal connection strength between the FPN and VIS was associated with the severity of schizophrenia symptoms. These findings suggest that abnormal intramodule and intermodule connections in the structural brain network may a biomarker of schizophrenia symptoms.

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Individual Prediction of Psychotherapy Outcome in Posttraumatic Stress Disorder using Neuroimaging Data

10.1101/647925 ◽

2019 ◽

Author(s):

Paul Zhutovsky ◽

Rajat M. Thomas ◽

Miranda Olff ◽

Sanne J.H. van Rooij ◽

Mitzy Kennis ◽

...

Keyword(s):

Posttraumatic Stress Disorder ◽

Posttraumatic Stress ◽

Gray Matter ◽

Resting State ◽

Stress Disorder ◽

Gray Matter Volume ◽

Fmri Data ◽

Single Subject ◽

Permutation Testing ◽

Individual Level

AbstractObjectiveTrauma-focused psychotherapy is the first-line treatment for posttraumatic stress disorder (PTSD) but 30-50% of patients do not benefit sufficiently. We investigated whether structural and resting-state functional magnetic resonance imaging (MRI/rs-fMRI) data could distinguish between treatment responders and non-responders on the group and individual level.MethodsForty-four male veterans with PTSD underwent baseline scanning followed by trauma-focused psychotherapy. Voxel-wise gray matter volumes were extracted from the structural MRI data and resting-state networks (RSNs) were calculated from rs-fMRI data using independent component analysis. Data were used to detect differences between responders and non-responders on the group level using permutation testing, and the single-subject level using Gaussian process classification with cross-validation.ResultsA RSN centered on the bilateral superior frontal gyrus differed between responders and non-responder groups (PFWE < 0.05) while a RSN centered on the pre-supplementary motor area distinguished between responders and non-responders on an individual-level with 81.4% accuracy (P < 0.001, 84.8% sensitivity, 78% specificity and AUC of 0.93). No significant single-subject classification or group differences were observed for gray matter volume.ConclusionsThis proof-of-concept study demonstrates the feasibility of using rs-fMRI to develop neuroimaging biomarkers for treatment response, which could enable personalized treatment of patients with PTSD.

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Gray matter networks and cognitive impairment in multiple sclerosis

Multiple Sclerosis Journal ◽

10.1177/1352458517751650 ◽

2018 ◽

Vol 25 (3) ◽

pp. 382-391 ◽

Cited By ~ 7

Author(s):

Carolina M Rimkus ◽

Menno M Schoonheim ◽

Martijn D Steenwijk ◽

Hugo Vrenken ◽

Anand JC Eijlers ◽

...

Keyword(s):

Multiple Sclerosis ◽

Cognitive Impairment ◽

Gray Matter ◽

Random Network ◽

Neurological Dysfunction ◽

Single Subject ◽

Information Processing Speed ◽

Memory And Attention ◽

Network Disruptions ◽

Gray Matter Network

Background: Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS). Objective: To investigate whether single-subject gray matter network properties are related to impaired cognition in MS. Methods: We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level. Results: Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values. Conclusion: Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS.

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Modular-level alterations of single-subject gray matter networks in schizophrenia

Brain Imaging and Behavior ◽

10.1007/s11682-021-00571-z ◽

2021 ◽

Author(s):

Yuxiang Guo ◽

Yunxiao Ma ◽

GongShu Wang ◽

Ting Li ◽

Tong Wang ◽

...

Keyword(s):

Gray Matter ◽

Single Subject

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