Aug 2026· Journal of Neuroscience· Vol 46· 0 citations· 93 references
Medicine
Abstract
Evidence implicates the cerebellum in motor learning and performance and relatively simple sensorimotor associations such as classical conditioning. However, little is known about how Purkinje cells encode more complex associations, such as arbitrary stimulus–response mappings. To address this, we recorded from Crus I/II Purkinje cells while two male macaques learned to associate novel fractal cues with left- or right-hand bar release. Here we show that as learning progresses, the simple spike activity of individual neurons becomes more selective for stimulus–response associations, with selectivity for left or right association developing closer to the appearance of visual stimuli. Initially, most neurons respond to both associations, irrespective of the identity of the stimulus and the associated movement, but as learning advances, more neurons distinguish between specific stimulus-hand associations. Moreover, complex spikes, which respond after the appearance of the stimuli, decrease their activity as the monkeys learn the task, suggesting that climbing-fiber activity encodes higher-order sensorimotor associations beyond mere error signaling. Using a linear decoder, we found that in early learning stages, the visual stimulus can be decoded only when the choice can also be decoded. As learning progresses, the visual stimulus is decoded earlier than the choice. A simple model can replicate the observed Purkinje cell signals in both the early and late learning stages.
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
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This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.
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Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
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MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
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