Sigalas, E and Li, J and Bezerianos, A and Antonopoulos, CG (2018) Emergence of Chimera-like States in Prefrontal-Cortex Macaque Intracranial Recordings. In: UNSPECIFIED, ? - ?.
|
Text
antonopoulos.pdf - Accepted Version Download (634kB) | Preview |
Abstract
© 2018 IEEE. Neural synchronization plays a crucial role in cognitive functions and in performing tasks as it facilitates the transmission of information among the various brain subregions, and thus their communication. In this paper, we use an approach for analyzing and quantifying the emergence of synchronization patterns used previously in the study of data from toy dynamical models, in neurophysiological signals from a macaque monkey and particularly, from prefrontal-cortex intracranial recordings. Specifically, we study the emergence of synchronization patterns in neural ensembles recorded in the macaque brain while the monkey is performing the same delayed saccade task successfully for a number of times. We quantify the emergence of chimera-like states, metastability and coalition entropy in the recordings coming from intracranial arrays implanted in the macaque's brain. Our results show the emergence of spatio-Temporal co-existing patterns of synchronized and desynchronized behavior, termed chimera-like states with small metastability during the stage where the target and the distractor appears on the screen and when the go cue appears on the screen for the monkey to report, namely the two most crucial stages of the trials to be termed successful. Finally, we perform a statistical hypothesis test on the calculated quantities over the successful trials and demonstrate that our findings are statistically significant in the sense that they cannot be attributed to randomness.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Additional Information: | Published proceedings: 2018 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2018 |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of Faculty of Science and Health > Mathematical Sciences, Department of |
Depositing User: | Elements |
Date Deposited: | 14 Sep 2018 12:57 |
Last Modified: | 07 May 2019 18:15 |
URI: | http://repository.essex.ac.uk/id/eprint/22973 |
Actions (login required)
![]() |
View Item |