Decoding brain states using backward edge elimination and graph kernels in fMRI connectivity networks

2013 ◽  
Vol 212 (2) ◽  
pp. 259-268 ◽  
Author(s):  
Fatemeh Mokhtari ◽  
Gholam-Ali Hossein-Zadeh
Keyword(s):  
Graph Kernels ◽  
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.

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.

scholarly journals Algorithm selection for software validation based on graph kernels

2020 ◽  
Vol 27 (1-2) ◽  
pp. 153-186
Author(s):  
Cedric Richter ◽  
Eyke Hüllermeier ◽  
Marie-Christine Jakobs ◽  
Heike Wehrheim
Keyword(s):  
Software Validation ◽  
Algorithm Selection ◽  
Graph Kernels ◽  
Selection For

scholarly journals Structural control energy of resting‐state functional brain states reveals less cost‐effective brain dynamics in psychosis vulnerability

2021 ◽  
Vol 42 (7) ◽  
pp. 2181-2200
Author(s):  
Daniela Zöller ◽  
Corrado Sandini ◽  
Marie Schaer ◽  
Stephan Eliez ◽  
Danielle S. Bassett ◽  
...  
Keyword(s):  
Resting State ◽  
Structural Control ◽  
Cost Effective ◽  
Brain Dynamics ◽  
Functional Brain ◽  
Brain States

scholarly journals (Ascorb)ing Pb Neurotoxicity in the Developing Brain

Antioxidants ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1311
Author(s):  
Faraz Ahmad ◽  
Ping Liu
Keyword(s):  
Ascorbic Acid ◽  
Animal Studies ◽  
Redox Homeostasis ◽  
Special Role ◽  
Developmental Exposure ◽  
Brain Functions ◽  
Brain States ◽  
Pb Exposure ◽  
The Brain ◽  
Potent Therapeutic Agent

Lead (Pb) neurotoxicity is a major concern, particularly in children. Developmental exposure to Pb can alter neurodevelopmental trajectory and has permanent neuropathological consequences, including an increased vulnerability to further stressors. Ascorbic acid is among most researched antioxidant nutrients and has a special role in maintaining redox homeostasis in physiological and physio-pathological brain states. Furthermore, because of its capacity to chelate metal ions, ascorbic acid may particularly serve as a potent therapeutic agent in Pb poisoning. The present review first discusses the major consequences of Pb exposure in children and then proceeds to present evidence from human and animal studies for ascorbic acid as an efficient ameliorative supplemental nutrient in Pb poisoning, with a particular focus on developmental Pb neurotoxicity. In doing so, it is hoped that there is a revitalization for further research on understanding the brain functions of this essential, safe, and readily available vitamin in physiological states, as well to justify and establish it as an effective neuroprotective and modulatory factor in the pathologies of the nervous system, including developmental neuropathologies.

Sign in / Sign up

Export Citation Format

Share Document