title: Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment.
abstract: The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and more specifically on the analysis of the connectivity of a NeuCube model trained with electroencephalography (EEG) data. The case study data used to illustrate this method is EEG data collected from three groups-subjects with opiate addiction, patients undertaking methadone maintenance treatment, and non-drug users/healthy control group. The proposed method classifies more accurately the EEG data than traditional statistical and artificial intelligence (AI) methods and can be used to predict response to treatment and dose-related drug effect. But more importantly, the method can be used to compare functional brain activities of different subjects and the changes of these activities as a result of treatment, which is a step towards a better understanding of both the EEG data and the brain processes that generated it. The method can also be used for a wide range of applications, such as a better understanding of disease progression or aging.
authors.affiliation: Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1010, New Zealand.
authors.forename: Elisa
authors.initials: E
authors.lastname: Capecci
authors.affiliation: Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1010, New Zealand. Electronic address: nkasabov@aut.ac.nz.
authors.forename: Nikola
authors.initials: N
authors.lastname: Kasabov
authors.affiliation: Department of Psychology, Faculty of Health and Environmental Science, Auckland University of Technology, Auckland 1142, New Zealand.
authors.forename: Grace Y
authors.initials: GY
authors.lastname: Wang
mesh_terms: D000328:Adult; D001185:Artificial Intelligence; D001921:Brain / Q000187:drug effects / Q000503:physiopathology*; D001931:Brain Mapping / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008691:Methadone / Q000494:pharmacology / Q000627:therapeutic use; D008959:Models, Neurological; D009294:Narcotics / Q000494:pharmacology / Q000627:therapeutic use; D009415:Nerve Net / Q000187:drug effects / Q000503:physiopathology*; D016571:Neural Networks, Computer; D058850:Opiate Substitution Treatment; D009293:Opioid-Related Disorders / Q000188:drug therapy / Q000503:physiopathology*
chemical_list: D009294:Narcotics; D008691:Methadone
keywords: EEG; Methadone maintenance; NeuCube; Opiates; Response to treatment; Spiking neural networks