Nonlinear directed information flow estimation for fNIRS brain network analysis based on the modified multivariate transfer entropy

2022 ◽  
Vol 74 ◽  
pp. 103422
Author(s):  
Yalin Wang ◽  
Chen Chen ◽  
Wei Chen
Keyword(s):  
Network Analysis ◽  
Information Flow ◽  
Brain Network ◽  
Transfer Entropy ◽  
Flow Estimation ◽  
Directed Information

scholarly journals Can Transfer Entropy Infer Information Flow in Neuronal Circuits for Cognitive Processing?

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 385 ◽  
Author(s):  
Ali Tehrani-Saleh ◽  
Christoph Adami
Keyword(s):  
Cognitive Processing ◽  
Information Flow ◽  
Cognitive Task ◽  
Evolutionary Process ◽  
Logic Gates ◽  
Ground Truth ◽  
Transfer Entropy ◽  
Causal Connection ◽  
Directed Information ◽  
Flow Of Information

How cognitive neural systems process information is largely unknown, in part because of how difficult it is to accurately follow the flow of information from sensors via neurons to actuators. Measuring the flow of information is different from measuring correlations between firing neurons, for which several measures are available, foremost among them the Shannon information, which is an undirected measure. Several information-theoretic notions of “directed information” have been used to successfully detect the flow of information in some systems, in particular in the neuroscience community. However, recent work has shown that directed information measures such as transfer entropy can sometimes inadequately estimate information flow, or even fail to identify manifest directed influences, especially if neurons contribute in a cryptographic manner to influence the effector neuron. Because it is unclear how often such cryptic influences emerge in cognitive systems, the usefulness of transfer entropy measures to reconstruct information flow is unknown. Here, we test how often cryptographic logic emerges in an evolutionary process that generates artificial neural circuits for two fundamental cognitive tasks (motion detection and sound localization). Besides counting the frequency of problematic logic gates, we also test whether transfer entropy applied to an activity time-series recorded from behaving digital brains can infer information flow, compared to a ground-truth model of direct influence constructed from connectivity and circuit logic. Our results suggest that transfer entropy will sometimes fail to infer directed information when it exists, and sometimes suggest a causal connection when there is none. However, the extent of incorrect inference strongly depends on the cognitive task considered. These results emphasize the importance of understanding the fundamental logic processes that contribute to information flow in cognitive processing, and quantifying their relevance in any given nervous system.

scholarly journals Measuring the Non-linear Directed Information Flow in Schizophrenia by Multivariate Transfer Entropy

2020 ◽  
Vol 13 ◽  
Author(s):  
Dennis Joe Harmah ◽  
Cunbo Li ◽  
Fali Li ◽  
Yuanyuan Liao ◽  
Jiuju Wang ◽  
...  
Keyword(s):  
Information Flow ◽  
Transfer Entropy ◽  
Non Linear ◽  
Directed Information

A survey of brain network analysis by electroencephalographic signals

2021 ◽  
Author(s):  
Cuihua Luo ◽  
Fali Li ◽  
Peiyang Li ◽  
Chanlin Yi ◽  
Chunbo Li ◽  
...  
Keyword(s):  
Network Analysis ◽  
Brain Network ◽  
Electroencephalographic Signals

scholarly journals Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects

2017 ◽  
Vol 14 (4) ◽  
pp. 046002 ◽  
Author(s):  
Bin Hu ◽  
Qunxi Dong ◽  
Yanrong Hao ◽  
Qinglin Zhao ◽  
Jian Shen ◽  
...  
Keyword(s):  
Network Analysis ◽  
Resting State ◽  
Brain Network ◽  
Eeg Data

Directed Network Analysis Using Transfer Entropy Component Analysis

2018 ◽  
pp. 491-500
Author(s):  
Meihong Wu ◽  
Yangbin Zeng ◽  
Zhihong Zhang ◽  
Haiyun Hong ◽  
Zhuobin Xu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Component Analysis ◽  
Transfer Entropy ◽  
Directed Network ◽  
Entropy Component

scholarly journals Integrative Structural Brain Network Analysis in Diffusion Tensor Imaging

2017 ◽  
Vol 7 (6) ◽  
pp. 331-346 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Network Analysis ◽  
Diffusion Tensor ◽  
Brain Network ◽  
Structural Brain Network ◽  
Structural Brain

scholarly journals Applying transfer entropy approach to investigate the information flow among ASEAN stock markets

2020 ◽  
Vol 4 (1) ◽  
pp. First
Author(s):  
Tran Thi Tuan Anh
Keyword(s):  
Information Flow ◽  
Stock Markets ◽  
Investment Strategy ◽  
The Philippines ◽  
Transfer Entropy ◽  
The Other ◽  
Information Flows ◽  
Research Results ◽  
Region Data ◽  
Asean Countries

This paper uses transfer entropy to measure and identify the information flows between stock markets in the ASEAN region. Data on daily closing stock indices, including Vietnam, the Philippines, Malaysia, Indonesia, Thailand, and Singapore, are collected for the period from March 2012 to October 2019 to calculate these transfer entropies. The research results of this article can be considered in two aspects: one is, how information flow originating from one market will be accepted by other markets and secondly, information flow that markets receive. From the perspective of incoming transfer entropy, Vietnam is the country most affected by information from the other ASEAN markets while Indonesia and Malaysia are the least affected. In terms of outgoing entropy, Thailand is the largest source of information flow to the ASEAN markets. Malaysia and the Philippines are the two countries that receive minor information impact from other countries. The research also reveals that the Singapore stock market is rather separate from the other ASEAN countries. The research results also imply that, for investors and policymakers, defining the information flows among ASEAN stock markets can help to predict market movements, thereby developing a suitable investment strategy or establishing appropriate management policies.

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