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Psychogenic seizures and frontal disconnection: EEG synchronisation study
, Article Journal of Neurology, Neurosurgery and Psychiatry ; Volume 82, Issue 5 , 2011 , Pages 505-511 ; 00223050 (ISSN) ; Jalili, M ; Frackowiak, R. S ; Rossetti, A. O ; Sharif University of Technology
2011
Abstract
Objective Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. Methods The authors analysed the whole-head...
Quantitative Structure - Retention Relationship study of benzodiazepines using adaptive neuro fuzzy inference system as feature selection method
, Article QSAR and Combinatorial Science ; Volume 27, Issue 4 , 2008 , Pages 407-416 ; 1611020X (ISSN) ; Kyani, A ; Afsari Mamaghani, S ; Ghadiri Bidhendi, A ; Sharif University of Technology
2008
Abstract
A Quantitative Structure-Retention Relationship (QSRR) study of 32 benzodiazepines is performed in this work. Two feature selection methods of Adaptive Neuro Fuzzy Inference System (ANFIS) and a stepwise regression approach adopted for the Multiple Linear Regressions (MLR) were used to predict the Liquid Chromatography-Mass Spectrometry (LC-MS) Retention Time (RT) of these compounds on a Xterra MS C-18 stationary phase. ANFIS and MLR methods were used as variable selection tools and a neural network was employed for predicting the RTs. Tbree descriptors of 3D-MoRSE-signal 06/weighted by atomic polarizabilities (Mor06p), Radial Distribution Function-1.0/weighted by atomic van der Waals...
Properties of functional brain networks correlate frequency of psychogenic non-epileptic seizures
, Article Frontiers in Human Neuroscience ; Issue DEC , 2012 ; 16625161 (ISSN) ; Joudaki, A ; Jalili, M ; Rossetti, A. O ; Frackowiak, R. S ; Knyazeva, M. G ; Sharif University of Technology
Frontiers Media S. A
2012
Abstract
Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a...