To understand complex biological systems requires the integration of experimental and
computational research—in other words a systems biology approach. Computational …

The adoption of powerful software tools and computational methods from the software
industry by the scientific research community has resulted in a renewed interest in …

Establishing how neural function emerges from network properties is a fundamental problem
in neuroscience. Here, to better understand the relationship between the structure and the …

A central goal of artificial intelligence in high-stakes decision-making applications is to
design a single algorithm that simultaneously expresses generalizability by learning …

We introduce a new class of time-continuous recurrent neural network models. Instead of
declaring a learning system's dynamics by implicit nonlinearities, we construct networks of …

Caenorhabditis elegans explores its environment by interrupting its forward movement with
occasional turns and reversals. Turns and reversals occur at stable frequencies but irregular …

There is increasing interest in topological analysis of brain networks as complex systems,
with researchers often using neuroimaging to represent the large-scale organization of …

We present an optogenetic illumination system capable of real-time light delivery with high
spatial resolution to specified targets in freely moving Caenorhabditis elegans. A tracking …

The Caenorhabditis elegans gene eat-4 affects multiple glutamatergic neurotransmission
pathways. We find that eat-4 encodes a protein similar in sequence to a mammalian brain …

A neural network can sustain and switch between different activity patterns to execute
multiple behaviors. By monitoring the decision making for directional locomotion through …