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Algorithm Separates Intrinsic Brain Patterns from Sensory Inputs

Algorithm Separates Intrinsic Brain Patterns from Sensory Inputs
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New algorithm disentangles intrinsic brain patterns from sensory inputs

New algorithm disentangles intrinsic brain patterns from sensory inputs
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New algorithm disentangles intrinsic brain pa

<p><a href="https://viterbi.usc.edu/directory/faculty/Shanechi/Maryam" target=" blank">Maryam Shanechi</a>, Dean&rsquo;s Professor of Electrical and Computer Engineering and founding director of the USC Center for Neurotechnology, and her team have developed a new machine learning method that reveals surprisingly consistent intrinsic brain patterns across different subjects by disentangling these patterns from the effect of visual inputs.</p>

Breaking Ground in Neurotechnologies: New AI Algorithm Unleashes Advanced Real-Time Decoding Capabilities

Maryam Shanechi, Dean’s Professor of Electrical and Computer Engineering and Founding Director of the USC Center for Neurotechnology, and her PhD students have developed a new, advanced deep-learning method for brain signals that can perform real-tim

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