Show simple item record

dc.contributor.authorConti, D
dc.contributor.authorDi Nuovo, S
dc.contributor.authorCangelosi, A
dc.contributor.authorDi Nuovo, A
dc.date.accessioned2016-04-08T10:05:30Z
dc.date.available2016-04-08T10:05:30Z
dc.date.issued2016-08
dc.identifier.issn1612-4782
dc.identifier.issn1612-4790
dc.identifier.urihttp://hdl.handle.net/10026.1/4483
dc.description.abstract

In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans.

dc.format.extent321-328
dc.format.mediumPrint-Electronic
dc.languageen
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.subjectUnilateral spatial neglect
dc.subjectEmbodied cognition
dc.subjectCognitive robotics
dc.subjectHemisphere specialization
dc.subjectNeuropsychology
dc.titleLateral specialization in unilateral spatial neglect: a cognitive robotics model
dc.typejournal-article
dc.typeArticle
plymouth.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/27018020
plymouth.issue3
plymouth.volume17
plymouth.publication-statusPublished
plymouth.journalCognitive Processing
dc.identifier.doi10.1007/s10339-016-0761-x
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Institute of Health and Community
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
dc.publisher.placeGermany
dcterms.dateAccepted2016-03-10
dc.identifier.eissn1612-4790
dc.rights.embargoperiodNo embargo
rioxxterms.versionofrecord10.1007/s10339-016-0761-x
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2016-08
rioxxterms.typeJournal Article/Review
plymouth.oa-locationhttp://link.springer.com/article/10.1007/s10339-016-0761-x


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record


All items in PEARL are protected by copyright law.
Author manuscripts deposited to comply with open access mandates are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author.
Theme by 
Atmire NV