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.

doi:http://dx.doi.org/10.1016/j.procs.2015.07.278

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

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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

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.