VBM signatures of abnormal eating behaviours in frontotemporal lobar degeneration

Jennifer L. Whitwell, Elizabeth L. Sampson, Clement T. Loy, Jane E. Warren, Martin N. Rossor, Nick C. Fox, Jason D. Warren

Research output: Contribution to journalArticlepeer-review

103 Scopus citations


The brain bases of specific human behaviours in health and disease are not well established. In this voxel-based morphometric (VBM) study we demonstrate neuroanatomical signatures of different abnormalities of eating behaviour (pathological sweet tooth and increased food consumption, or hyperphagia) in individuals with frontotemporal lobar degeneration (FTLD). Sixteen male patients with FTLD were assessed using the Manchester and Oxford Universities Scale for the Psychopathological Assessment of Dementia and classified according to the presence or absence of abnormal eating behaviours. Volumetric brain magnetic resonance imaging was performed in all patients and in a group of nine healthy age-matched male controls and grey matter changes were assessed using an optimised VBM protocol. Compared with healthy controls, the FTLD group had a typical pattern of extensive bilateral grey matter loss predominantly involving the frontal and temporal lobes. Within the FTLD group, grey matter changes associated with different abnormal behaviours were assessed independently using a covariate-only model. The development of pathological sweet tooth was associated with grey matter loss in a distributed brain network including bilateral posterolateral orbitofrontal cortex (Brodmann areas 12/47) and right anterior insula. Hyperphagia was associated with more focal grey matter loss in anterolateral OFC bilaterally (Brodmann area 11). In accord with emerging evidence in humans and other species, our findings implicate distinct components of a multi-component brain network in the control of specific aspects of eating behaviour.

Original languageEnglish (US)
Pages (from-to)207-213
Number of pages7
Issue number1
StatePublished - Mar 2007

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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