Synchronization phenomena in large populations of interacting elements are the subject of
intense research efforts in physical, biological, chemical, and social systems. A successful …

Large-scale neural recordings have established that the transformation of sensory stimuli
into motor outputs relies on low-dimensional dynamics at the population level, while …

Spin glasses are magnetic materials. Statistical mechanics, a subfield of physics, has been a
powerful tool to theoretically analyze various unique properties of spin glasses. This book is …

Gene expression has a stochastic component because of the single-molecule nature of the
gene and the small number of copies of individual DNA-binding proteins in the cell. We …

This paper summarizes associative memory models and sparse representation of memory in
these models. Important properties of the associative memory models are their storage …

Hopfield networks are artificial neural networks which store memory patterns on the states of
their neurons by choosing recurrent connection weights and update rules such that the …

A fundamental problem in neuroscience is understanding how working memory—the ability
to store information at intermediate timescales, like tens of seconds—is implemented in …

Conventional neural network models for temporal association generally do not work well in
the absence of synchronizing neurons. This is because their dynamical properties are …

The connectivity structure of neural networks has significant implications for neural
information processing, and much experimental effort has been made to clarify the structure …

How cortical neurons process information crucially depends on how their local circuits are
organized. Spontaneous synchronous neuronal activity propagating through neocortical …