This review integrates computational approaches to provide a unified view on how data analysis methods, biophysical mechanistic models and machine learning approaches can help to uncover the origins a...

Value-guided decisions are a cornerstone of cognition, yet the underlying circuit-level mechanisms remain elusive. We used reinforcement learning to t…

Value-guided decisions are at the core of reinforcement learning and neuroeconomics, yet the basic computations they require remain poorly understood at the mechanistic level. For instance, how does t...

Value-guided decisions are at the core of reinforcement learning and neuroeconomics, yet the basic computations they require remain poorly understood at the mechanistic level. For instance, how does t...

Sensory adaptation dynamically changes neural responses as a function of previous stimuli, profoundly impacting perception. The response changes induced by adaptation have been characterized in detail...

Examination of the neural activity in the basolateral amygdala and ventral CA1 of mice during tasks or rest following exposure to social stress reveals signatures of resilience and susceptibility to s...

Statistical physics provides tools for analyzing high-dimensional problems in machine learning and theoretical neuroscience. These calculations, particularly those using the replica method, often invo...