Identifying Neuroimaging-Based Markers for Distinguishing Brain Disorders

2020 ◽  
Keyword(s):  
Brain Disorders

Therapy and prevention for mental health: What if mental diseases are mostly not brain disorders?

2019 ◽  
Vol 42 ◽  
Author(s):  
John P. A. Ioannidis
Keyword(s):  
Mental Health ◽  
Mental Disease ◽  
Brain Disorders ◽  
Social Stressors ◽  
Labor Education ◽  
Mental Diseases ◽  
Long Term Follow Up ◽  
Political Decisions

AbstractNeurobiology-based interventions for mental diseases and searches for useful biomarkers of treatment response have largely failed. Clinical trials should assess interventions related to environmental and social stressors, with long-term follow-up; social rather than biological endpoints; personalized outcomes; and suitable cluster, adaptive, and n-of-1 designs. Labor, education, financial, and other social/political decisions should be evaluated for their impacts on mental disease.

Progressive Brain Disorders in Childhood

2017 ◽  
Author(s):  
Juan Pascual
Keyword(s):  
Brain Disorders

Omgaan met mensen met een visuele beperking in het verpleeghuis

2019 ◽  
Keyword(s):  
Emotional Support ◽  
Vision Loss ◽  
Visual Impairments ◽  
Brain Disorders ◽  
Process Of Care ◽  
Coordinated Care ◽  
Specific Training ◽  
Literature Overview ◽  
Care For Older People

The number of people with vision loss increases; a large part of them is nursing home resident. Although the number of elderly with visual impairments is growing, little special attention is paid to this group. This is however urgently needed. Caregivers need to understand the limitations of visual impairment and how to cope with them. This can lead to better coordinated care. This article presents a literature overview about what conditions are essential for the quality of care for older people with visual impairments caused by eye-diseases (not by brain disorders). The results show that these conditions concern the process of care, communication and emotional support, support when moving, in providing structure, specific training of caregivers, and lighting provision. Practical tips and advice are given that can be used in nursing homes.

scholarly journals Formaldehyde and Brain Disorders: A Meta-Analysis and Bioinformatics Approach

2021 ◽  
Author(s):  
Iemaan Rana ◽  
Linda Rieswijk ◽  
Craig Steinmaus ◽  
Luoping Zhang
Keyword(s):  
Meta Analysis ◽  
Brain Disorders

PROTON MR SPECTROSCOPY IN NEOPLASTIC AND NON-NEOPLASTIC BRAIN DISORDERS

1998 ◽  
Vol 6 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Mauricio Castillo ◽  
Lester Kwock ◽  
James Scatliff ◽  
Suresh K. Mukherji
Keyword(s):  
Mr Spectroscopy ◽  
Brain Disorders ◽  
Proton Mr Spectroscopy

scholarly journals Brain pathology recapitulates physiology: A network meta-analysis

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Thomas J. Vanasse ◽  
Peter T. Fox ◽  
P. Mickle Fox ◽  
Franco Cauda ◽  
Tommaso Costa ◽  
...  
Keyword(s):  
Network Architecture ◽  
Spatial Scales ◽  
Meta Analysis ◽  
Metabolic Cost ◽  
Common Mechanism ◽  
Brain Disorders ◽  
Brain Pathology ◽  
Structural Network ◽  
Meta Analyses ◽  
Function Network

AbstractNetwork architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic ‘cost’ significantly differs along this transdiagnostic/multimodal gradient.

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