Connectomics to Semantomics: Addressing the Brain's Big Data Challenge1
| Autor: | David Dalmazzo, Alberto Betella, Paul F. M. J. Verschure, Xerxes D. Arsiwalla, Riccardo Zucca, Santiago Brandi, Pedro Omedas, Enrique Martinez |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Connectomics
business.industry Computer science Big data Virtual Reality Brain Connectomics Human brain Visualization Visual processing medicine.anatomical_structure Connectome medicine Data Mining General Earth and Planetary Sciences Artificial intelligence business Neuroscience General Environmental Science |
| Zdroj: | INNS Conference on Big Data |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2015.07.278 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|