A big-world network in ASD: Dynamical connectivity analysis reflects a deficit in long-range connections and an excess of short-range connections
Over the last years, increasing evidence has fuelled the hypothesis that Autism Spectrum Disorder (ASD) is a condition of altered brain functional connectivity. The great majority of these empirical studies relies on functional magnetic resonance imaging (fMRI) which has a relatively poor temporal r...
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2011
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| 008 | 190411s2011 xx ||||fo|||| 00| 0 eng|d | ||
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| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 030 | |a NUPSA | ||
| 100 | 1 | |a Barttfeld, P. | |
| 245 | 1 | 2 | |a A big-world network in ASD: Dynamical connectivity analysis reflects a deficit in long-range connections and an excess of short-range connections |
| 260 | |c 2011 | ||
| 270 | 1 | 0 | |m Barttfeld, P.; Integrative Neuroscience Laboratory, Physics Department, University of Buenos Aires, Ciudad Universitaria, Pabellón 1, Buenos Aires, Argentina; email: pbarttfeld@fi.uba.ar |
| 506 | |2 openaire |e Política editorial | ||
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| 520 | 3 | |a Over the last years, increasing evidence has fuelled the hypothesis that Autism Spectrum Disorder (ASD) is a condition of altered brain functional connectivity. The great majority of these empirical studies relies on functional magnetic resonance imaging (fMRI) which has a relatively poor temporal resolution. Only a handful of studies has examined networks emerging from dynamic coherence at the millisecond resolution and there are no investigations of coherence at the lowest frequencies in the power spectrum-which has recently been shown to reflect long-range cortico-cortical connections. Here we used electroencephalography (EEG) to assess dynamic brain connectivity in ASD focusing in the low-frequency (delta) range. We found that connectivity patterns were distinct in ASD and control populations and reflected a double dissociation: ASD subjects lacked long-range connections, with a most prominent deficit in fronto-occipital connections. Conversely, individuals with ASD showed increased short-range connections in lateral-frontal electrodes. This effect between categories showed a consistent parametric dependency: as ASD severity increased, short-range coherence was more pronounced and long-range coherence decreased. Theoretical arguments have been proposed arguing that distinct patterns of connectivity may result in networks with different efficiency in transmission of information. We show that the networks in ASD subjects have less Clustering coefficient, greater Characteristic Path Length than controls - indicating that the topology of the network departs from small-world behaviour - and greater modularity. Together these results show that delta-band coherence reveal qualitative and quantitative aspects associated with ASD pathology. © 2010 Elsevier Ltd. |l eng | |
| 536 | |a Detalles de la financiación: Conseil National de la Recherche Scientifique | ||
| 536 | |a Detalles de la financiación: MS and PB are supported by the Human Frontiers Science Program. BW is supported by the CNRS. The authors want to thank Iñaki Landerreche for providing help with the code to calculate SL, and Dr. Ernesto Wahlberg and Dr. Hernán Amartino for helping with patient recruitment. Appendix A | ||
| 593 | |a Integrative Neuroscience Laboratory, Physics Department, University of Buenos Aires, Buenos Aires, Argentina | ||
| 593 | |a Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia, Buenos Aires, Argentina | ||
| 593 | |a Mediterranean Institute of Cognitive Neurosciences, Centre National de la Recherche Scientifique, Université de la Méditerranée, 31 Chemin Joseph Aiguier, 13402 Marseille Cedex 20, France | ||
| 593 | |a Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad of Buenos Aires, Argentina | ||
| 690 | 1 | 0 | |a AUTISM SPECTRUM DISORDER |
| 690 | 1 | 0 | |a DELTA BAND EEG |
| 690 | 1 | 0 | |a FUNCTIONAL CONNECTIVITY |
| 690 | 1 | 0 | |a RESTING STATE |
| 690 | 1 | 0 | |a SMALL WORLD METRICS |
| 690 | 1 | 0 | |a ADOLESCENT |
| 690 | 1 | 0 | |a ADULT |
| 690 | 1 | 0 | |a ARTICLE |
| 690 | 1 | 0 | |a AUTISM |
| 690 | 1 | 0 | |a BRAIN FUNCTION |
| 690 | 1 | 0 | |a CALCULATION |
| 690 | 1 | 0 | |a CLINICAL ARTICLE |
| 690 | 1 | 0 | |a CONTROLLED STUDY |
| 690 | 1 | 0 | |a DISEASE SEVERITY |
| 690 | 1 | 0 | |a ELECTROENCEPHALOGRAPHY |
| 690 | 1 | 0 | |a FEMALE |
| 690 | 1 | 0 | |a FRONTAL LOBE |
| 690 | 1 | 0 | |a FUNCTIONAL ASSESSMENT |
| 690 | 1 | 0 | |a FUNCTIONAL MAGNETIC RESONANCE IMAGING |
| 690 | 1 | 0 | |a HUMAN |
| 690 | 1 | 0 | |a MALE |
| 690 | 1 | 0 | |a OCCIPITAL CORTEX |
| 690 | 1 | 0 | |a ADOLESCENT |
| 690 | 1 | 0 | |a ADULT |
| 690 | 1 | 0 | |a ASPERGER SYNDROME |
| 690 | 1 | 0 | |a AUTISTIC DISORDER |
| 690 | 1 | 0 | |a BRAIN MAPPING |
| 690 | 1 | 0 | |a CEREBRAL CORTEX |
| 690 | 1 | 0 | |a DELTA RHYTHM |
| 690 | 1 | 0 | |a ELECTROENCEPHALOGRAPHY |
| 690 | 1 | 0 | |a FEMALE |
| 690 | 1 | 0 | |a HUMANS |
| 690 | 1 | 0 | |a MALE |
| 690 | 1 | 0 | |a NERVE NET |
| 690 | 1 | 0 | |a NEURAL PATHWAYS |
| 690 | 1 | 0 | |a YOUNG ADULT |
| 700 | 1 | |a Wicker, B. | |
| 700 | 1 | |a Cukier, S. | |
| 700 | 1 | |a Navarta, S. | |
| 700 | 1 | |a Lew, S. | |
| 700 | 1 | |a Sigman, M. | |
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