An emotional recognition architecture based on human brain structure

Taylor, JG; Fragopanagos, N; Cowie, R; Douglas-Cowie, E; Fotinea, S-E; Kollias, S

dc.contributor.author	Taylor, JG	en
dc.contributor.author	Fragopanagos, N	en
dc.contributor.author	Cowie, R	en
dc.contributor.author	Douglas-Cowie, E	en
dc.contributor.author	Fotinea, S-E	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:18:38Z
dc.date.available	2014-03-01T01:18:38Z
dc.date.issued	2003	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15124
dc.subject	Body of Knowledge	en
dc.subject	Brain Imaging	en
dc.subject	Emotion Recognition	en
dc.subject	Engine Control	en
dc.subject	Human Brain	en
dc.subject	Single Cell	en
dc.title	An emotional recognition architecture based on human brain structure	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/3-540-44989-2_135	en
heal.identifier.secondary	http://dx.doi.org/10.1007/3-540-44989-2_135	en
heal.publicationDate	2003	en
heal.abstract	Emotional experience has two distinct components in human beings: 'automatic' and 'attended'. The former of these is based more heavily on the ventral and limbic areas of the brain; the attention part is concerned with cognitive aspects of experience, and involves more dorsal components. A rapidly increasing body of knowledge on these two separate components of human experience is being developed through brain imaging, single cell recording and deficit analyses under emotional as compared to neutral inputs. We start by summarizing this data. We then incorporate the data into a recently developed engineering control model of attention and motor responses. The crucial extension of this model involves a ventral/limbic brain network building representations of salience and valence. A simulation of a simple paradigm is used to demonstrate the considerable dissociation possible between the cognitive and emotional components. The system is further extended by inclusion of the attention-based CODAM model of consciousness. This allows us to relate 'emotions' to 'feelings' and delineate expected architectures for the construction of artificial emotional recognition systems. © Springer-Verlag Berlin Heidelberg 2003.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/3-540-44989-2_135	en
dc.identifier.volume	2714	en
dc.identifier.spage	1133	en
dc.identifier.epage	1140	en