State-dependent changes of connectivity patterns and functional brain network topology in Autism Spectrum Disorder

Anatomical and functional brain studies have converged to the hypothesis that Autism Spectrum Disorders (ASD) are associated with atypical connectivity. Using a modified resting-state paradigm to drive subjects' attention, we provide evidence of a very marked interaction between ASD brain functional connectivity and cognitive state. We show that functional connectivity changes in opposite ways in ASD and typicals as attention shifts from external world towards one's body generated information. Furthermore, ASD subject alter more markedly than typicals their connectivity across cognitive states. Using differences in brain connectivity across conditions, we classified ASD subjects at a performance around 80% while classification based on the connectivity patterns in any given cognitive state were close to chance. Connectivity between the Anterior Insula and dorsal-anterior Cingulate Cortex showed the highest classification accuracy and its strength increased with ASD severity. These results pave the path for diagnosis of mental pathologies based on functional brain networks obtained from a library of mental states

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 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.Fil: Barttfeld, Pablo. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Wicker, Bruno. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Cukier, Sebastián. Universidad de Buenos Aires; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Navarta, Silvana Elisa. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Lew, Sergio Eduardo. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Sigman, Mariano. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentin

Large-scale network analysis reflects big-world characteristics in ASD

No abstrac