Neuroimaging and eating disorders.

Guido K W Frank
Author Information
  1. Guido K W Frank: Eating Disorders Center for Treatment and Research, University of California San Diego, San Diego, California, USA.

Abstract

PURPOSE OF REVIEW: Eating disorders are severe psychiatric disorders with a suspected complex biopsychosocial cause. The purpose of this review is to synthesize the recent literature on brain imaging in eating disorders.
RECENT FINDINGS: Food restriction as well as binge eating and purging behaviors are associated with lower regional brain volumes or cortical thickness, but those changes largely return to normal with normalization of weight and eating behavior. Computational modeling has started to identify patterns of structural and functional imaging data that classify eating disorder subtypes, which could be used in the future, diagnostically and to better understand disorder-specific psychopathology. The prediction error model, a computational approach to assess dopamine-related brain reward function, helped support a brain-based model for anorexia nervosa. In that model, the conscious motivation to restrict conflicts with body signals that stimulate eating. This conflict causes anxiety and drives a vicious cycle of food restriction.
SUMMARY: Novel brain research supports the notion that eating disorders have distinct neurobiological underpinnings. This new knowledge can be used to describe disease models to patients and develop novel treatments.

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Grants

  1. R01 MH096777/NIMH NIH HHS
  2. R01 MH103436/NIMH NIH HHS
  3. T32 HD041697/NICHD NIH HHS

MeSH Term

Brain
Computational Biology
Dopamine
Feeding Behavior
Feeding and Eating Disorders
Humans
Motivation
Neurobiology
Neuroimaging
Reward

Chemicals

Dopamine

Word Cloud

Created with Highcharts 10.0.0eatingdisordersbrainmodelimagingrestrictionusedPURPOSEOFREVIEW:EatingseverepsychiatricsuspectedcomplexbiopsychosocialcausepurposereviewsynthesizerecentliteratureRECENTFINDINGS:FoodwellbingepurgingbehaviorsassociatedlowerregionalvolumescorticalthicknesschangeslargelyreturnnormalnormalizationweightbehaviorComputationalmodelingstartedidentifypatternsstructuralfunctionaldataclassifydisordersubtypesfuturediagnosticallybetterunderstanddisorder-specificpsychopathologypredictionerrorcomputationalapproachassessdopamine-relatedrewardfunctionhelpedsupportbrain-basedanorexianervosaconsciousmotivationrestrictconflictsbodysignalsstimulateconflictcausesanxietydrivesviciouscyclefoodSUMMARY:NovelresearchsupportsnotiondistinctneurobiologicalunderpinningsnewknowledgecandescribediseasemodelspatientsdevelopnoveltreatmentsNeuroimaging

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