Special Issue "Entropy Applications in Electroencephalography"
Deadline for manuscript submissions: 25 November 2023 | Viewed by 2610
Interests: neuroscience; dynorphin expression in dorsal spinal cord circuits; cortical processing of sensory inputs; mental measurements of time
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Synchronous activities, namely, excitation and inhibition of cortical neurons, are recorded by electroencephalograms (EEGs). Since some of the superficial cortical neurons are responsible for corticocortical connections, synchronization largely represents the flow of information between synchronized cortical circuits. Furthermore, during an interaction of the brain with the environment, there is the activation of cortical neurons due to sensory stimulation and movements, manipulating the environment. If the measurement of cortical activities is blind to external interactions, then these activities will represent an increase in entropy, a measurement of randomness. Past studies have shown that different measures of entropy in EEG patterns are reduced in deep anesthetic states, which suggests that high entropy is critical for the brain’s interaction with the environment. Note that a decrease in entropy, a measure of randomness or uncertainty, can result from an increase in mutual information, a correlation measure. A decrease in entropy represents a gain of knowledge. Accordingly, higher levels of entropy can provide greater knowledge. Since neurons in the brain are activated as a result of external tasks, it is the increased probability of the coactivation of circuits or neurons which represents an increase in mutual information about its interactions with physical surroundings.
While an increase in the amplitude of EEG waves suggests an increased probability of coactivation of pairs of neurons in synchronized areas of the brain, consistent with an increase in mutual information, it mostly represents the knowledge of the connections between circuits, only partly contributing to the knowledge of the external physical world. However, in desynchronized cortical states, the interaction of the brain with the physical environment increases the probability of coactivation of unique sets of pairs of neurons that are not surprising if given the knowledge about the interactions between the brain and external surroundings. Thus, an increase in mutual information, and a corresponding gain in knowledge, resulting directly from an interaction of the brain with physical surroundings, will provide the basis for the knowledge underlying perception and volition.
In this Special Issue, we invite contributions that will shed light on how the changes in the measurements of entropy in EEG recordings can be related to cognitive functions of the brain, such as perception and voluntary motor control. We hope to learn how EEG can be analyzed to understand changes in the levels of cognitive functioning during various stages of anesthesia and disease states, such as Parkinson’s and Alzheimer’s diseases and schizophrenia.
Dr. Daya Shankar Gupta
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