Banca de QUALIFICAÇÃO: FRANCISCO LEANDRO PONTES CARLOS

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : FRANCISCO LEANDRO PONTES CARLOS
DATE: 15/09/2023
TIME: 09:00
LOCAL: Instituto de Física UFAL
TITLE:

Entropy and statistical complexity to characterize data from
Electroencephalogram (EEG) in humans during a decision-making task

KEY WORDS:

computational neuroscience, data analysis , complex systems

PAGES: 70
BIG AREA: Ciências Exatas e da Terra
AREA: Física
SUBÁREA: Física Geral
SPECIALTY: Física Estatística e Termodinâmica
SUMMARY:

Understanding the functional connectivity of the brain, and how it processes information and perceives the world, is one of the main goals of neuroscience. To study these
questions, one can analyze the brain through time series generated by electrical signals between neurons, obtained during different cognitive processes, and thus statistically characterize the properties of these signals. In this
work, we analyzed electroencephalogram (EEG) data in humans during a Go/No-Go visual task in the light of information theory quantifiers. Here, we adopt the methodology of
Bandt-Pompe symbolization to determine a probability distribution function and calculate complexity and entropy for different time windows along the cognitive task.
Using these information theory quantifiers, it was possible to show that the Go/No-Go trials
can be distinguished in complexity-entropy plane in different time windows and EEG channels.
Thus, our results show that these quantifiers can be a good tool for
analyzing and differentiating brain signals in different cognitive activities. Furthermore, using the approach of temporal multiscale, one can estimate the most important time scales for information processing in the brain.

BANKING MEMBERS:
Presidente - 1339771 - UESLEN ROCHA SILVA
Interno(a) - 1247925 - ANIELLE CHRISTINE ALMEIDA SILVA
Externo(a) à Instituição - NIVALDO ANTONIO PORTELA DE VASCONCELOS - UFPE