Highlights•Relating network connectivity to dynamics poses a serious theoretical
challenge.•Network science concepts may have limited relevance in a neuroscience …

Recent advances in neuroscience have enabled the exploration of brain structure at the
level of individual synaptic connections. These connectomics datasets continue to grow in …

We hypothesized that the heterogeneous architecture of biological neural networks provides
a substrate to regulate the well-known tradeoff between robustness and efficiency, thereby …

A basic—yet nontrivial—function which neocortical circuitry must satisfy is the ability to
maintain stable spiking activity over time. Stable neocortical activity is asynchronous, critical …

Neurons in a neural circuit exhibit astonishing diversity in terms of the numbers and targets
of their synaptic connections and the statistics of their spiking activity. We hypothesize that …

In this paper we develop a novel mathematical formalism for the modeling of neural
information networks endowed with additional structure in the form of assignments of …

The architecture of a neural network constrains the potential dynamics that can emerge.
Some architectures may only allow for a single dynamic regime, while others display a great …

This is a brief overview of an ongoing research project, involving topological models of
neural information networks and the development of new versions of associated information …

Through the use of biofidelic spiking neural network models (SNNs), this work offers
mechanistic insights into the relationship between neocortical structure, dynamics, and …

Neuroscience discoveries and machine learning tools have evolved hand to hand to provide
a clearer picture of what intelligent computation is all about. Computations is more and more …