News

How do brains—biological or artificial—respond and adapt to an ever-changing environment? In a recent meeting, experts from various fields of neuroscience and artificial intelligence met to discuss internal world models in brains and machines, arguing for an interdisciplinary approach to gain deeper insights into the underlying mechanisms.

In this study, we introduce the architecture, the integrated building blocks, and the post-CMOS processes required to realize a NeuroBus , and we characterize the prototyped direct digitizing neural recorder front-end as well as polyimide-based ECoG brain interface.

In this study, we introduce a novel class of Latent (Markov) Variable Inverse Q-learning algorithms for characterizing animal behavior during complex decision-making tasks.

To study behavioral flexibility in freely-moving mice, we developed a versatile, low-cost, open-source behavioral setup, called FreiBox, allowing us to investigate the neuronal correlates of licking-based behavioral flexibility.

This study proposes an unitary concept that, leveraging a cross-species definition of prefrontal regions, explains how prefrontal ensembles adaptively regulate and efficiently coordinate multiple processes in distinct cognitive behaviors.

This study provides mechanistic insights into the interactions between the rostral forelimb area (RFA) and the caudal forelimb area (CFA). Specifically, we provide evidence for a differential impact of RFA on CFA depending on the task phase and the targeted CFA layers.

Our results resolve long-standing questions about the dynamical structure of cortical activity associated with movement, and illuminate the dynamical perturbation experiments needed to understand how neural circuits throughout the brain generate complex behavior.

We demonstrate cross-subject and cross-session generalization in a decoding task through alignments of low-dimensional neural manifolds, providing evidence of a conserved neuronal code.