Neuroimaging distinction between neurological and psychiatric disorders
Nicolas A Crossley1, Jessica Scott1, Ian Ellison-Wright1
1Nicolas A. Crossley, MRCPsych, PhD, Jessica Scott, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London; Ian Ellison-Wright, MRCPsych, Avon and Wiltshire Mental Health Partnership NHS Trust, Salisbury; Andrea Mechelli, PhD, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK.
Neuroimaging reveals distinct brain patterns for neurological and psychiatric disorders. These findings support the biological separation of these two disorder classes, impacting future research and treatment.
Area of Science:
- Neuroimaging
- Neuroscience
- Medical Research
Background:
- The biological basis for distinguishing neurological and psychiatric disorders remains unclear.
- Investigating neuroimaging data can elucidate potential biological differences.
Purpose of the Study:
- To analyze neuroimaging evidence differentiating neurological and psychiatric disorders.
- To compare brain alterations and network involvement in both disorder types.
Main Methods:
- Activation Likelihood Estimation (ALE) meta-analysis of voxel-based morphometry studies.
- Inclusion of 14 neurological and 10 psychiatric disorders with reported grey matter reduction.
- Comparative analysis of regional and network-level brain alterations.
Main Results:
- Neurological disorders showed greater impairment in basal ganglia, insula, sensorimotor, and temporal cortex.
- Psychiatric disorders exhibited greater impairment in cingulate, medial frontal, superior frontal, and occipital cortex.
- Distinct functional networks were affected, with higher within-class similarity for neurological disorders.
Conclusions:
- Neuroimaging data supports neurological and psychiatric disorders as distinct biological classes.
- Significant differences in brain region and network involvement underscore their separation.
- Findings provide a neuroimaging perspective on the classification of these disorders.
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