The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

Mathematical and statistical models have played important roles in neuroscience, especially
by describing the electrical activity of neurons recorded individually, or collectively across …

We investigate the ability of the pairwise maximum entropy (PME) model to describe the
spiking activity of large populations of neurons recorded from the visual, auditory, motor, and …

In contrast to their postsynaptic counterparts, the contributions of activity-dependent
cytoskeletal signaling to presynaptic plasticity remain controversial and poorly understood …

Neural responses are highly structured, with population activity restricted to a small subset of
the astronomical range of possible activity patterns. Characterizing these statistical …

Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in
large neural populations. Recent studies have shown that the summed activity of all neurons …

Empirical complex systems are widely assumed to be characterized not only by pairwise
interactions, but also by higher-order (group) interactions that affect collective phenomena …

Identifying network architecture from observed neural activities is crucial in neuroscience
studies. A key requirement is knowledge of the statistical input-output relation of single …

The models in statistical physics such as an Ising model offer a convenient way to
characterize stationary activity of neural populations. Such stationary activity of neurons may …

We propose that correlations among neurons are generically strong enough to organize
neural activity patterns into a discrete set of clusters, which can each be viewed as a …