Can we predict who will respond more to neurofeedback with resting state EEG?

Autor:	Fehim Arman, Mert Gurkan, Gunet Eroglu, Selim Balcisoy, Barış Ekici, Mujdat Cetin
Rok vydání:	2018
Předmět:	Correlation Theta rhythm medicine.diagnostic_test Multi sensory Resting state eeg medicine Cognition Neurofeedback Electroencephalography Psychology Neuroscience Left dorsolateral prefrontal cortex
Zdroj:	2018 Medical Technologies National Congress (TIPTEKNO).
Popis:	AutoTrainBrain is a neurofeedback and multi sensory learning-based mobile phone software application, designed at Sabanci University with the aim of improving the cognitive functions of dyslexic children. We investigated whether we can predict who will respond more to neurofeedback applied by AutoTrainBrain by analyzing the resting state EEG brain data. Based on our analysis of the EEG data collected, we observed that the power amplitudes across resting states in the theta band over the left Dorsolateral Prefrontal Cortex (DLPFC) (electrode: FC5) predicts who will respond more to neurofeedback with AutoTrainBrain (Pearson correlation coeff: 0.78, P
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::04680ef52d3d7552b5a824d6e856ca41 https://doi.org/10.1109/tiptekno.2018.8596857 Zobrazit plný text záznamu