European Journal of NeuroscienceNeurosciencePeer-reviewed journal article
Temporal dynamics of cognitive flexibility in adolescents with anorexia nervosa: a high density EEG study
Cristina BerchioiD, Lucie Clémentine Annen, Ynès Bouamoud, Nadia MicaliiD
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- 11
- FWCI
- 3.20
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- top 9%
Abstract
Cognitive rigidity is a core symptom of anorexia nervosa (AN) and is associated with treatment resistance. Nevertheless, studies on the neural basis of cognitive flexibility (CF) in adolescent AN are rare. The aim of this study was to investigate temporal brain dynamics of CF in adolescents with AN and their tendency to experience anxiety. To address this aim, participants performed a Dimensional Change Card Sorting task during high-density EEG recording. Transient state and stable traits of anxiety were measured with the State-Trait Anxiety Inventory. Data were collected on 22 girls with AN, and 23 healthy controls (HC) (aged 12-20 years old). Evoked potentials were investigated using microstates analysis. Effects of trait and state anxiety on microstates parameters were investigated performing correlations across groups and in the AN group only. Adolescents with AN did not differ from HC with respect to behavioral switching cost, despite a greater overall accuracy. Adolescents with AN showed altered visual orienting processes (N100 micro-state), and earlier attentional processing to task switching (P300b microstate) when compared to HC. Reduced activation in a network involving the pre-central cortex, the cerebellum, and the posterior cingulate was identified in adolescents with AN. Trait and state anxiety were correlated with atypical AN microstates across groups. The present findings suggest CF manifests with inefficient behavioral and neural strategies in adolescents with AN, at early stages in the illness. Additionally, this study provides evidence that transient and stable tendencies to experience anxiety could represent a vulnerability to developing CF impairments in adolescent AN.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
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