News Finding: Because the existing brain patterns likely reflect how the neurons are interconnected, the results suggest that the connectivity among neurons shapes learning.
Paper Finding: These alternative explanations did reveal interesting secondary aspects of the data; they partially explained within-category differences in learnability, albeit in an idiosyncratic manner between the two monkeys (Extended Data Fig.
News Context: The harder-to-learn patterns were different from any of the pre-existing patterns, whereas the easier-to-learn patterns were combinations of pre-existing brain patterns. Because the existing brain patterns likely reflect how the neurons are interconnected, the results suggest that the connectivity among neurons shapes learning. Byron M. Yu, assistant professor of electrical and computer engineering and biomedical engineering at Carnegie Mellon, believes this work demonstrates the utility of BCI for basic scientific studies that will eventually impact people's lives.
Paper Context: We conclude from these analyses that the parsimonious explanation for BCI learning is whether or not the new control space is within the intrinsic manifold. These alternative explanations did reveal interesting secondary aspects of the data; they partially explained within-category differences in learnability, albeit in an idiosyncratic manner between the two monkeys (Extended Data Fig. Although our estimate of the intrinsic manifold can depend on several methodological factors (Extended Data Fig.