Sophisticated decision-making mechanisms and complex experimental paradigms can be modeled, simulated, and fit to empirical response time data, using a flexible and efficient computational modeling framework.

Embryo-wide quantitative analysis of BMP signaling in zebrafish embryos, combined with a mathematical model-based computational screen, challenges the prevailing model of an antagonist counter-gradient shaping the gastrula BMP morphogen gradient and supports an antagonist sink with BMP diffusion mechanism.

Realistic reaction-diffusion signaling networks that include cell-autonomous factors can robustly form self-organizing spatial patterns for any combination of diffusion coefficients without requiring differential diffusivity.

The powerful computational operation of sequence recognition on behavioral timescales of approximately 1 s may emerge from synaptic activity-triggered build-up of biochemical waves in short 20 micron zones on dendrites.

Statistical analysis of evidence-based decisions reveals new insights into the source of behavioral variability.

C. elegans foraging efficiently approximate maximally informative search strategies that involve abrupt switching between different types of behaviors.

Alpha oscillations represent an intermediate stage of evidence accumulation that is influenced by self-regulation in value-based decision making.

Regulatory success operates by goal-consistent increases and decreases of distinct attribute representations in generic neural hubs and in domain-specific brain regions, explaining when and why regulatory success generalizes across domains and contexts.

Diffusivity, extracellular interactions of Nodal ligands with the receptors and inhibitors, and selective ligand destruction collectively shape the Nodal morphogen gradient.

A simple model reveals the roles of colony geometry and diffusion rate in allowing microbes to cooperate by sharing public goods.