{"title":"An adaptive Network-Oriented cognitive model for Major Depression and its treatment","authors":"Marcia A. van der Poel, Jan Treur","doi":"10.1016/j.bica.2018.10.001","DOIUrl":null,"url":null,"abstract":"<div><p><span>This paper presents an adaptive neurologically inspired cognitive model for Major Depressive Disorder. It is based on an (adaptive) temporal-causal network modelling<span> approach incorporating a dynamic perspective on mental states and causal relations. The adaptive network model addresses how a Deep Brain Stimulation treatment used for this disorder can work by a </span></span>Hebbian learning effect.</p></div>","PeriodicalId":48756,"journal":{"name":"Biologically Inspired Cognitive Architectures","volume":"26 ","pages":"Pages 159-165"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bica.2018.10.001","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biologically Inspired Cognitive Architectures","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212683X18301348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Psychology","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents an adaptive neurologically inspired cognitive model for Major Depressive Disorder. It is based on an (adaptive) temporal-causal network modelling approach incorporating a dynamic perspective on mental states and causal relations. The adaptive network model addresses how a Deep Brain Stimulation treatment used for this disorder can work by a Hebbian learning effect.
期刊介绍：
Announcing the merge of Biologically Inspired Cognitive Architectures with Cognitive Systems Research.
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.
The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.
Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
