The ongoing exponential rise in recording capacity calls for new approaches for analysing
and interpreting neural data. Effective dimensionality has emerged as an important property …

The cerebellar cortex is an important system for relating neural circuits and learning. Its
promise reflects the longstanding idea that it contains simple, repeated circuit modules with …

Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural
activity across the brain. To understand the nature and function of these signals, we need …

Neurophysiology has long progressed through exploratory experiments and chance
discoveries. Anecdotes abound of researchers listening to spikes in real time and noticing …

Recent work has argued that large-scale neural recordings are often well described by
patterns of coactivation across neurons. Yet the view that neural variability is constrained to …

The cerebellum is thought to help detect and correct errors between intended and executed
commands, and is critical for social behaviours, cognition and emotion,,–. Computations for …

Sensory areas are spontaneously active in the absence of sensory stimuli. This
spontaneous activity has long been studied; however, its functional role remains largely …

In classical cerebellar learning, Purkinje cells (PkCs) associate climbing fiber (CF) error
signals with predictive granule cells (GrCs) that were active just prior (∼ 150 ms). The …

Simultaneous recordings from hundreds or thousands of neurons are becoming routine
because of innovations in instrumentation, molecular tools, and data processing software …

An influential framework within systems neuroscience posits that neural computations can
be understood in terms of low-dimensional dynamics in recurrent circuits. A number of …