A central goal of neuroscience is to understand the representations formed by brain activity
patterns and their connection to behaviour. The classic approach is to investigate how …

How interactions between neurons relate to tuned neural responses is a longstanding
question in systems neuroscience. Here we use statistical modeling and simultaneous multi …

Measuring neuronal tuning curves has been instrumental for many discoveries in
neuroscience but requires a priori assumptions regarding the identity of the encoded …

Many sensory and motor variables are encoded in the nervous system by the activities of
large populations of neurons with bell-shaped tuning curves. Extracting information from …

The firing rates of individual neurons displaying mixed selectivity are modulated by multiple
task variables. When mixed selectivity is nonlinear, it confers an advantage by generating a …

Neurons often respond to diverse combinations of task-relevant variables. This form of
mixed selectivity plays an important computational role which is related to the dimensionality …

The two basic processes underlying perceptual decisions—how neural responses encode
stimuli, and how they inform behavioral choices—have mainly been studied separately …

Tuning curves are widely used to characterize the responses of sensory neurons to external
stimuli, but there is an ongoing debate as to their role in sensory processing. Commonly, it is …

Sensory and motor variables are typically represented by a population of broadly tuned
neurons. A coarser representation with broader tuning can often improve coding accuracy …

In systems neuroscience, neural activity that represents movements or sensory stimuli is
often characterized by spatial tuning curves that may change in response to training …