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Updated: Jun 23, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Neuropsychological patterns in magnetic resonance imaging-defined subgroups of patients with degenerative dementia
John Listerud1, Chivon Powers, Peachie Moore
1Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104-4283, USA.
Abstract:
We hypothesized that specific neuropsychological deficits were associated with specific patterns of atrophy. A magnetic resonance imaging volumetric study and a neuropsychological protocol were obtained for patients with several frontotemporal lobar dementia phenotypes including a social/dysexecutive (SOC/EXEC, n = 17), progressive nonfluent aphasia (n = 9), semantic dementia (n = 7), corticobasal syndrome (n = 9), and Alzheimer's disease (n = 21). Blinded to testing results, patients were partitioned according to pattern of predominant cortical atrophy; our partitioning algorithm had been derived using seriation, a hierarchical classification technique. Neuropsychological test scores were regressed versus these atrophy patterns as fixed effects using the covariate total atrophy as marker for disease severity. The results showed the model accounted for substantial variance. Furthermore, the "large-scale networks" associated with each neuropsychological test conformed well to the known literature. For example, bilateral prefrontal cortical atrophy was exclusively associated with SOC/EXEC dysfunction. The neuropsychological principle of "double dissociation" was supported not just by such active associations but also by the "silence" of locations not previously implicated by the literature. We conclude that classifying patients with degenerative dementia by specific pattern of cortical atrophy has the potential to predict individual patterns of cognitive deficits.

