Toward Quieting the Brain: Cluster Analysis of Cat Neural Network Models Reveals Promising Anti-seizure Strategies
Chronic brain disease such as epilepsy involve disturbances of the brain’s electrical activity. Finding new and better ways to connect them is the dream of millions of patients, their physicians and researchers
Connections in the brain are known as neural networks. These networks work together and were separated into four separate categories for this study involving researchers from Brazil, Scotland and Germany who created a computer model of a cat’s brain to study how to control or avert seizure-like electrical patterns. These four separate categories, or cognitive regions, they studied, include visual, cognitive auditory, somatosensory-motor and frontolimbic. “We investigated the destruction of synchronization in a realistic neural network model whose connecting architecture is formed by a cluster of sub-network, and we found the most significant and interesting aspect to be the verification that the efficiency of synchronization suppression by delayed feedback control is higher and more efficient than for the two other methods: external time-periodic driving and activation of selected neurons. And importantly, the delayed feedback control is an intervention that does not damage the neurons,” said Antonio M. Batista, PhD, the team leader of the study from the Department of Mathematics and Statistics at State University of Ponta Grossa, Brazil. To read more on this study, click here.
Microsurgery Course Zurich
March 29-April 1, 2017; Zurich, Switzerland
12th World Congress on Brain Injury
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2017 National Neuroscience Review
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