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Understanding the human brain via its spatio-temporal properties (vision paper)

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Ouri WolfsonAuthors Info & Claims

SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 85 - 88

https://doi.org/10.1145/3274895.3274931

Published: 06 November 2018 Publication History

Abstract

The human brain is probably the most complex object in the universe, and also one of the least understood. For example, how the brain produces the mind and consciousness is a complete mystery. Nevertheless, the brain is amenable to measurements of various kinds that produce lots of data. It is a spatial object residing in the skull; it is also temporal in the sense that neurons communicate by signals that take traverse the brain network over time. In this paper we ask whether spatio-temporal data analysis can contribute to its understanding. Toward this goal we propose several research directions that are inspired by GIS work. However, these are just examples, and other work on moving objects in space or on networks is applicable.

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Cited By

Vijayan A(2023)Deciphering Neural Codes: A Resource Search Network Perspective on Brain ConnectivityProceedings of the 2023 6th International Conference on Algorithms, Computing and Artificial Intelligence10.1145/3639631.3639664(190-194)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3639631.3639664
Margaritella NInácio VKing R(2020)Parameter clustering in Bayesian functional principal component analysis of neuroscientific dataStatistics in Medicine10.1002/sim.876840:1(167-184)Online publication date: 11-Oct-2020
https://doi.org/10.1002/sim.8768
Züfle A(2019)Visions and challenges in GeoAI, ethics, and spatial quantum computingSIGSPATIAL Special10.1145/3377000.337700111:2(2-4)Online publication date: 17-Dec-2019
https://dl.acm.org/doi/10.1145/3377000.3377001

Index Terms

Understanding the human brain via its spatio-temporal properties (vision paper)
1. Applied computing
  1. Life and medical sciences
    1. Bioinformatics
    2. Computational biology

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Published In

cover image ACM Conferences

SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2018

655 pages

ISBN:9781450358897

DOI:10.1145/3274895

General Chairs:
Farnoush Banaei-Kashani
University of Colorado, Denver
,
Erik Hoel
Esri
,
Program Chairs:
Ralf Hartmut Güting
FernUniversität in Hagen, Germany
,
Roberto Tamassia
Brown University
,
Li Xiong
Emory University

Copyright © 2018 ACM.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2018

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SIGSPATIAL '18

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SIGSPATIAL

SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 6 - 9, 2018

Washington, Seattle

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SIGSPATIAL '18 Paper Acceptance Rate 30 of 150 submissions, 20%;

Overall Acceptance Rate 220 of 1,116 submissions, 20%

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Cited By

Vijayan A(2023)Deciphering Neural Codes: A Resource Search Network Perspective on Brain ConnectivityProceedings of the 2023 6th International Conference on Algorithms, Computing and Artificial Intelligence10.1145/3639631.3639664(190-194)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3639631.3639664
Margaritella NInácio VKing R(2020)Parameter clustering in Bayesian functional principal component analysis of neuroscientific dataStatistics in Medicine10.1002/sim.876840:1(167-184)Online publication date: 11-Oct-2020
https://doi.org/10.1002/sim.8768
Züfle A(2019)Visions and challenges in GeoAI, ethics, and spatial quantum computingSIGSPATIAL Special10.1145/3377000.337700111:2(2-4)Online publication date: 17-Dec-2019
https://dl.acm.org/doi/10.1145/3377000.3377001

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