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Brain Topography

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01.03.2016 | Original Paper

Long-Range Reduced Predictive Information Transfers of Autistic Youths in EEG Sensor-Space During Face Processing

verfasst von: Ali Khadem, Gholam-Ali Hossein-Zadeh, Anahita Khorrami

Erschienen in: Brain Topography | Ausgabe 2/2016

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Abstract

The majority of previous functional/effective connectivity studies conducted on the autistic patients converged to the underconnectivity theory of ASD: “long-range underconnectivity and sometimes short-rang overconnectivity”. However, to the best of our knowledge the total (linear and nonlinear) predictive information transfers (PITs) of autistic patients have not been investigated yet. Also, EEG data have rarely been used for exploring the information processing deficits in autistic subjects. This study is aimed at comparing the total (linear and nonlinear) PITs of autistic and typically developing healthy youths during human face processing by using EEG data. The ERPs of 12 autistic youths and 19 age-matched healthy control (HC) subjects were recorded while they were watching upright and inverted human face images. The PITs among EEG channels were quantified using two measures separately: transfer entropy with self-prediction optimality (TE_SPO), and modified transfer entropy with self-prediction optimality (MTE_SPO). Afterwards, the directed differential connectivity graphs (dDCGs) were constructed to characterize the significant changes in the estimated PITs of autistic subjects compared with HC ones. By using both TE_SPO and MTE_SPO, long-range reduction of PITs of ASD group during face processing was revealed (particularly from frontal channels to right temporal channels). Also, it seemed the orientation of face images (upright or upside down) did not modulate the binary pattern of PIT-based dDCGs, significantly. Moreover, compared with TE_SPO, the results of MTE_SPO were more compatible with the underconnectivity theory of ASD in the sense that MTE_SPO showed no long-range increase in PIT. It is also noteworthy that to the best of our knowledge it is the first time that a version of MTE is applied for patients (here ASD) and it is also its first use for EEG data analysis.

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Titel: Long-Range Reduced Predictive Information Transfers of Autistic Youths in EEG Sensor-Space During Face Processing
verfasst von: Ali Khadem
Gholam-Ali Hossein-Zadeh
Anahita Khorrami
Publikationsdatum: 01.03.2016
Verlag: Springer US
Erschienen in: Brain Topography / Ausgabe 2/2016
Print ISSN: 0896-0267
Elektronische ISSN: 1573-6792
DOI: https://doi.org/10.1007/s10548-015-0452-4

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