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ORCHESTRAS develops a theoretical framework to understand how the brain tracks speech through neural oscillations. It integrates insights from computational neuroscience and artificial intelligence to enhance both our understanding of speech processing and AI language models.
ORCHESTRAS posits a new a theoretical framework for a mechanistic understanding of neural tracking of speech by synthesizing views from both the oscillatory and evoked-like paradigms.
It builds upon work from computational neuroscience on whole-brain modelling together with the emergent field of NeuroAI where artificial neural networks are augmented with neural architectural priors which serves in bringing inductive biases to AI models that allow for faster learning and more efficient inference.…
BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
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