scholarly journals Cortical Temperature Change: A Tool for Modulating Brain States?

eNeuro ◽  
2016 ◽  
Vol 3 (3) ◽  
pp. ENEURO.0096-16.2016 ◽  
Author(s):  
Miriam Schwalm ◽  
Curtis Easton
Keyword(s):  
Temperature Change ◽  
Cortical Temperature ◽  
Brain States

Spectral and Topographic Microstructure of Brain Alpha Activity During Drowsiness at Sleep Onset and REM Sleep

2000 ◽  
Vol 14 (3) ◽  
pp. 151-158 ◽  
Author(s):  
José Luis Cantero ◽  
Mercedes Atienza
Keyword(s):  
Rem Sleep ◽  
Spectral Component ◽  
Sleep Onset ◽  
Quantitative Information ◽  
Maximum Energy ◽  
Alpha Activity ◽  
The Other ◽  
Classification Algorithms ◽  
Microstructural Properties ◽  
Brain States

Abstract High-resolution frequency methods were used to describe the spectral and topographic microstructure of human spontaneous alpha activity in the drowsiness (DR) period at sleep onset and during REM sleep. Electroencephalographic (EEG), electrooculographic (EOG), and electromyographic (EMG) measurements were obtained during sleep in 10 healthy volunteer subjects. Spectral microstructure of alpha activity during DR showed a significant maximum power with respect to REM-alpha bursts for the components in the 9.7-10.9 Hz range, whereas REM-alpha bursts reached their maximum statistical differentiation from the sleep onset alpha activity at the components between 7.8 and 8.6 Hz. Furthermore, the maximum energy over occipital regions appeared in a different spectral component in each brain activation state, namely, 10.1 Hz in drowsiness and 8.6 Hz in REM sleep. These results provide quantitative information for differentiating the drowsiness alpha activity and REM-alpha by studying their microstructural properties. On the other hand, these data suggest that the spectral microstructure of alpha activity during sleep onset and REM sleep could be a useful index to implement in automatic classification algorithms in order to improve the differentiation between the two brain states.

Concealment and Exposure of PV Modules Failures with Temperature Change

2019 ◽  
Vol 139 (9) ◽  
pp. 584-591
Author(s):  
Takumi Takashima ◽  
Kazuaki Ikeda
Keyword(s):  
Temperature Change ◽  
Pv Modules

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

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