.png){kind=icon}
返回
.png){kind=icon}
.png){kind=icon}
摘要
En 中文
Brain activity takes place in three spatial-plus time dimensions. This rather obvious claim has been recently questioned by papers that, taking into account the big data outburst and novel available computational tools, are starting to unveil a more intricate state of affairs. Indeed, various brain activities and their correlated mental functions can be assessed in terms of trajectories embedded in phase spaces of dimensions higher than the canonical ones. In this review, I show how further dimensions may not just represent a convenient methodological tool that allows a better mathematical treatment of otherwise elusive cortical activities, but may also reflect genuine functional or anatomical relationships among real nervous functions. I then describe how to extract hidden multidimensional information from real or artificial neurodata series, and make clear how our mind dilutes, rather than concentrates as currently believed, inputs coming from the environment. Finally, I argue that the principle the higher the dimension, the greater the information may explain the occurrence of mental activities and elucidate the mechanisms of human diseases associated with dimensionality reduction. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Central nervous system
Big data
Neural networks
Topology
Phase space
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
14.3
论文数:
1.9K
被引数:
2.5K
机构
引用论文
Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy.png)
EPILEPSIA.png)
OAAI
EPILEPSIAIF6.6
OAAI.png){kind=icon}
分享.png){kind=icon}
收藏The hubs of the human connectome are generally implicated in the anatomy of brain disordersBRAIN
OAAI
BRAINIF11.7
OAAI分享收藏
查看更多内容