Title |
Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
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Published in |
Journal of Neurodevelopmental Disorders, May 2017
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DOI | 10.1186/s11689-017-9195-8 |
Pubmed ID | |
Authors |
Michael S. Sidorov, Gina M. Deck, Marjan Dolatshahi, Ronald L. Thibert, Lynne M. Bird, Catherine J. Chu, Benjamin D. Philpot |
Abstract |
Clinicians have qualitatively described rhythmic delta activity as a prominent EEG abnormality in individuals with Angelman syndrome, but this phenotype has yet to be rigorously quantified in the clinical population or validated in a preclinical model. Here, we sought to quantitatively measure delta rhythmicity and evaluate its fidelity as a biomarker. We quantified delta oscillations in mouse and human using parallel spectral analysis methods and measured regional, state-specific, and developmental changes in delta rhythms in a patient population. Delta power was broadly increased and more dynamic in both the Angelman syndrome mouse model, relative to wild-type littermates, and in children with Angelman syndrome, relative to age-matched neurotypical controls. Enhanced delta oscillations in children with Angelman syndrome were present during wakefulness and sleep, were generalized across the neocortex, and were more pronounced at earlier ages. Delta rhythmicity phenotypes can serve as reliable biomarkers for Angelman syndrome in both preclinical and clinical settings. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 4 | 44% |
Unknown | 5 | 56% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 8 | 89% |
Scientists | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 106 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 24 | 23% |
Student > Ph. D. Student | 15 | 14% |
Student > Bachelor | 9 | 8% |
Student > Master | 8 | 8% |
Student > Doctoral Student | 7 | 7% |
Other | 15 | 14% |
Unknown | 28 | 26% |
Readers by discipline | Count | As % |
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Neuroscience | 25 | 24% |
Medicine and Dentistry | 16 | 15% |
Biochemistry, Genetics and Molecular Biology | 11 | 10% |
Agricultural and Biological Sciences | 6 | 6% |
Psychology | 6 | 6% |
Other | 10 | 9% |
Unknown | 32 | 30% |