Connectomics to semantomics: addressing the brain's big data challenge

Arsiwalla, Xerxes D.; Dalmazzo, David; Zucca, Riccardo; Betella, Alberto; Brandi Hernández, Santiago; Martínez Bueno, Enrique; Omedas, Pedro; Verschure, Paul F. M. J.

Connectomics to semantomics: addressing the brain's big data challenge

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dc.contributor.author Arsiwalla, Xerxes D.
dc.contributor.author Dalmazzo, David
dc.contributor.author Zucca, Riccardo
dc.contributor.author Betella, Alberto
dc.contributor.author Brandi Hernández, Santiago
dc.contributor.author Martínez Bueno, Enrique
dc.contributor.author Omedas, Pedro
dc.contributor.author Verschure, Paul F. M. J.
dc.date.accessioned 2025-11-12T13:57:04Z
dc.date.available 2025-11-12T13:57:04Z
dc.date.issued 2015
dc.date.updated 2025-11-12T13:57:03Z
dc.description.abstract Can semantic corpora be coupled to dynamical simulations in such a way so as to extract new associations from the data that were hitherto unapparent? We attempt to do this within neuroscience as an application domain, by introducing the notion of the semantome and coupling it to the connectome of the human brain network. This is implemented using BrainX3, a virtual reality simulation cum data mining platform that can be used for visualization, analysis and feature extraction of neuroscience data. We use this system to explore anatomical, functional and symptomatic semantics associated to simulated neuronal activity of a healthy brain, one with stroke and one perturbed by transcranial magnetic stimulation. In particular, we find that parietal and occipital lesions in stroke affect the visual processing pathway leading to symptoms such as visual neglect, depression and photo-sensitivity seizures. Integrating semantomics with connectomics thus generates hypotheses about symptoms, functions and brain activity that supplement existing tools for diagnosis of mental illness. Our results suggest a new approach to big data with potential applications to other domains.
dc.description.sponsorship We thank Olaf Sporns and Chris Honey for sharing the DSI data. Research supported by CEEDS (FP7-ICT-2009-5) & CDAC (ERC-2013-ADG 341196) projects.
dc.format.mimetype application/pdf
dc.identifier.citation Arsiwalla XD, Dalmazzo D, Zucca R, Betella A, Brandi S, Martinez E, Omedas P, Verschure P. Connectomics to semantomics: addressing the brain's big data challenge. Procedia Comput Sci. 2015;53:48-55. DOI: 10.1016/j.procs.2015.07.278
dc.identifier.doi http://dx.doi.org/10.1016/j.procs.2015.07.278
dc.identifier.issn 1877-0509
dc.identifier.uri http://hdl.handle.net/10230/71867
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof Procedia Computer Science. 2015;53:48-55
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/341196
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/258749
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.keyword Brain connectomics
dc.subject.keyword Data mining
dc.subject.keyword Virtual reality
dc.title Connectomics to semantomics: addressing the brain's big data challenge
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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