Title |
Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity
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Published in |
BMC Medicine, February 2013
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DOI | 10.1186/1741-7015-11-54 |
Pubmed ID | |
Authors |
Jurriaan M Peters, Maxime Taquet, Clemente Vega, Shafali S Jeste, Iván Sánchez Fernández, Jacqueline Tan, Charles A Nelson, Mustafa Sahin, Simon K Warfield |
Abstract |
Graph theory has been recently introduced to characterize complex brain networks, making it highly suitable to investigate altered connectivity in neurologic disorders. A current model proposes autism spectrum disorder (ASD) as a developmental disconnection syndrome, supported by converging evidence in both non-syndromic and syndromic ASD. However, the effects of abnormal connectivity on network properties have not been well studied, particularly in syndromic ASD. To close this gap, brain functional networks of electroencephalographic (EEG) connectivity were studied through graph measures in patients with Tuberous Sclerosis Complex (TSC), a disorder with a high prevalence of ASD, as well as in patients with non-syndromic ASD. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 7 | 33% |
Canada | 2 | 10% |
United Kingdom | 2 | 10% |
United States | 2 | 10% |
India | 1 | 5% |
Belgium | 1 | 5% |
Singapore | 1 | 5% |
Unknown | 5 | 24% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 16 | 76% |
Scientists | 3 | 14% |
Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | <1% |
Netherlands | 2 | <1% |
United Kingdom | 2 | <1% |
Malaysia | 1 | <1% |
Germany | 1 | <1% |
Korea, Republic of | 1 | <1% |
Italy | 1 | <1% |
Brazil | 1 | <1% |
Switzerland | 1 | <1% |
Other | 4 | 1% |
Unknown | 354 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 77 | 21% |
Researcher | 60 | 16% |
Student > Master | 47 | 13% |
Student > Bachelor | 31 | 8% |
Professor | 20 | 5% |
Other | 79 | 21% |
Unknown | 57 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 63 | 17% |
Psychology | 61 | 16% |
Medicine and Dentistry | 59 | 16% |
Engineering | 32 | 9% |
Agricultural and Biological Sciences | 24 | 6% |
Other | 59 | 16% |
Unknown | 73 | 20% |