NDLI: On how to efficiently accelerate brain network analysis on FPGA-based computing system

Content Provider	IEEE Xplore Digital Library
Author	Gnemmi, G. Crippa, M. Durelli, G. Cattaneo, R. Pallotta, G. Santambrogio, M.D.
Copyright Year	2015
Description	Author affiliation: Dipt. di Elettron., Inf. e Biomed., Politec. di Milano, Milan, Italy (Gnemmi, G.; Crippa, M.; Durelli, G.; Cattaneo, R.; Pallotta, G.; Santambrogio, M.D.)
Abstract	The ability to map neural networks is of fundamental importance for the understanding of the plasticity of neural connections, their behavior and organization, as well as the clinical implications related to neurological conditions. Being able to quickly and accurately model and map neural interconnections through Brain Networks (BNs) is critical for the study and modeling of neurodegenerative diseases such as Alzheimer's disease and Essential Tremor. However, both the construction and the analysis of BNs require massive amounts of computing resources. Currently, it is conceivable to analyze only few hundred of neural nodes in reasonable time. In this paper, we focus on the development of an hardware accelerator for the analysis of autofluorescence of mitochondria, the clinical technique used to derive BNs. Our results are state of the art for the construction and analysis of BNs, providing the community, both academic and industrial, a fundamental tool to enable further development in this field.
Starting Page	1
Ending Page	6
File Size	2223623
Page Count	6
File Format	PDF
e-ISBN	9781467394062
DOI	10.1109/ReConFig.2015.7393330
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-07
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Neurons Integrated circuit interconnections Brain modeling Real-time systems Yttrium Biological neural networks
Content Type	Text
Resource Type	Article

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