A central question in neuroscience is how interactions between neurons give rise to
behavior. In many electrophysiological experiments, the activity of a set of neurons is …

Statistical dependencies in the responses of sensory neurons govern both the amount of
stimulus information conveyed and the means by which downstream neurons can extract it …

Neural spike train analysis is an important task in computational neuroscience which aims to
understand neural mechanisms and gain insights into neural circuits. With the advancement …

One of the central problems in systems neuroscience is to understand how neural spike
trains convey sensory information. Decoding methods, which provide an explicit means for …

Deducing the structure of neural circuits is one of the central problems of modern
neuroscience. Recently-introduced calcium fluorescent imaging methods permit …

Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster
than visual responses, has been reported in many studies. Two candidate mechanisms of …

Current multielectrode techniques enable the simultaneous recording of spikes from
hundreds of neurons. To study neural plasticity and network structure it is desirable to infer …

Plasticity is a crucial component of normal brain function and a critical mechanism for
recovery from injury. In vitro, associative pairing of presynaptic spiking and stimulus-induced …

Inferring connectivity in neuronal networks remains a key challenge in statistical
neuroscience. The “common input” problem presents a major roadblock: it is difficult to …

We describe a class of models that predict how the instantaneous firing rate of a neuron
depends on a dynamic stimulus. The models utilize a learnt pointwise nonlinear transform of …