PMID- 26780815
OWN - NLM
STAT- MEDLINE
DCOM- 20170712
LR  - 20171122
IS  - 1558-0210 (Electronic)
IS  - 1534-4320 (Linking)
VI  - 24
IP  - 10
DP  - 2016 Oct
TI  - Revealing Cross-Frequency Causal Interactions During a Mental Arithmetic Task 
      Through Symbolic Transfer Entropy: A Novel Vector-Quantization Approach.
PG  - 1017-1028
AB  - Working memory (WM) is a distributed cognitive process that employs communication 
      between prefrontal cortex and posterior brain regions in the form of 
      cross-frequency coupling between theta ( theta) and high-alpha ( alpha2) brain waves. A 
      novel method for deriving causal interactions between brain waves of different 
      frequencies is essential for a better understanding of the neural dynamics of 
      such complex cognitive process. Here, we proposed a novel method to estimate 
      transfer entropy ( TE) through a symbolization scheme, which is based on 
      neural-gas algorithm (NG) and encodes a bivariate time series in the form of two 
      symbolic sequences. Given the symbolic sequences, the delay symbolic transfer 
      entropy ( dSTE(NG)) is defined. Our approach is akin to standard symbolic 
      transfer entropy ( STE) that incorporates the ordinal pattern (OP) symbolization 
      technique. We assessed the proposed method in a WM-invoked paradigm that included 
      a mental arithmetic task at various levels of difficulty. Effective interactions 
      between Frontal(theta) ( F(theta) ) and [Formula: see text] ( PO(alpha2)) brain waves were 
      detected in multichannel EEG recordings from 16 subjects. Compared with 
      conventional methods, our technique was less sensitive to noise and demonstrated 
      improved computational efficiency in quantifying the dominating direction of 
      effective connectivity between brain waves of different spectral content. 
      Moreover, we discovered an efferent F(theta) connectivity pattern and an afferent 
      PO(alpha2) one, in all the levels of the task. Further statistical analysis revealed 
      an increasing dSTE(NG) strength following the task's difficulty.
FAU - Dimitriadis, Stavros
AU  - Dimitriadis S
FAU - Sun, Yu
AU  - Sun Y
FAU - Laskaris, Nikolaos
AU  - Laskaris N
FAU - Thakor, Nitish
AU  - Thakor N
FAU - Bezerianos, Anastasios
AU  - Bezerianos A
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20160118
PL  - United States
TA  - IEEE Trans Neural Syst Rehabil Eng
JT  - IEEE transactions on neural systems and rehabilitation engineering : a 
      publication of the IEEE Engineering in Medicine and Biology Society
JID - 101097023
SB  - IM
MH  - Adult
MH  - Brain Waves/*physiology
MH  - Causality
MH  - Cerebral Cortex/*physiology
MH  - Cognition/*physiology
MH  - Computer Simulation
MH  - Concept Formation/physiology
MH  - Connectome/methods
MH  - Electroencephalography/methods
MH  - Entropy
MH  - Female
MH  - Humans
MH  - Male
MH  - *Mathematical Concepts
MH  - Memory, Short-Term/*physiology
MH  - *Models, Neurological
MH  - Models, Statistical
MH  - Task Performance and Analysis
MH  - Young Adult
EDAT- 2016/01/19 06:00
MHDA- 2017/07/14 06:00
CRDT- 2016/01/19 06:00
PHST- 2016/01/19 06:00 [pubmed]
PHST- 2017/07/14 06:00 [medline]
PHST- 2016/01/19 06:00 [entrez]
AID - 10.1109/TNSRE.2016.2516107 [doi]
PST - ppublish
SO  - IEEE Trans Neural Syst Rehabil Eng. 2016 Oct;24(10):1017-1028. doi: 
      10.1109/TNSRE.2016.2516107. Epub 2016 Jan 18.