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Updated: Jan 27, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
Published on: March 10, 2017
Dynamic Causal Modeling of the Relationship between Cognition and Theta-alpha Oscillations in Adults with Down
Sarah Hamburg1,2,3, Richard Rosch4,5, Carla Marie Startin1,2,3
1Division of Psychiatry, Faculty of Brain Sciences, University College London, 149 Tottenham Court Road, London, UK.
Abstract:
Individuals with Down syndrome (DS) show high inter-subject variability in cognitive ability and have an ultra-high risk of developing dementia (90% lifetime prevalence). Elucidating factors underlying variability in cognitive function can inform us about intellectual disability (ID) and may improve our understanding of factors associated with later cognitive decline. Increased neuronal inhibition has been posited to contribute to ID in DS. Combining electroencephalography (EEG) with dynamic causal modeling (DCM) provides a non-invasive method for investigating excitatory/inhibitory mechanisms. Resting-state EEG recordings were obtained from 36 adults with DS with no evidence of cognitive decline. Theta-alpha activity (4-13 Hz) was characterized in relation to general cognitive ability (raw Kaufmann's Brief Intelligence Test second Edition (KBIT-2) score). Higher KBIT-2 was associated with higher frontal alpha peak amplitude and higher theta-alpha band power across distributed regions. Modeling this association with DCM revealed intrinsic self-inhibition was the key network parameter underlying observed differences in 4-13 Hz power in relation to KBIT-2 and age. In particular, intrinsic self-inhibition in right V1 was negatively correlated with KBIT-2. Results suggest intrinsic self-inhibition within the alpha network is associated with individual differences in cognitive ability in adults with DS, and may provide a potential therapeutic target for cognitive enhancement.
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