Multivariate decoding methods were developed originally as tools to enable accurate
predictions in real-world applications. The realization that these methods can also be …

Inhibitory neurons, although relatively few in number, exert powerful control over brain
circuits. They stabilize network activity in the face of strong feedback excitation and actively …

Computational strategies used by the brain strongly depend on the amount of information
that can be stored in population activity, which in turn strongly depends on the pattern of …

Prefrontal persistent activity during the delay of spatial working memory tasks is thought to
maintain spatial location in memory. A'bump attractor'computational model can account for …

Neuronal responses of sensory cortex are highly variable, and this variability is correlated
across neurons. To assess how variability reflects factors shared across a neuronal …

Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise
variability, transient overshoots and oscillations, that have so far escaped a common …

Trial-to-trial variability is a reflection of the circuitry and cellular physiology that make up a
neuronal network. A pervasive yet puzzling feature of cortical circuits is that despite their …

Correlated variability in cortical activity is ubiquitously quenched following stimulus onset, in
a stimulus-dependent manner. These modulations have been attributed to circuit dynamics …

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship,
termed choice probability (CP), can arise from sensory variability biasing behaviour and …

The ability to discriminate between similar sensory stimuli relies on the amount of
information encoded in sensory neuronal populations. Such information can be substantially …