A Spiking Neural Network Builder for Systematic Data-to-Model Workflow.

In building biological neural network models, it is crucial to efficiently convert diverse anatomical and physiological data into parameters of neurons and synapses and to systematically estimate unknown parameters in reference to experimental observations. Web-based tools for systematic model building can improve the transparency and reproducibility of computational models and can facilitate collaborative model building, validation, and evolution. Here, we present a framework to support collaborative data-driven development of spiking neural network (SNN) models based on the Entity-Relationship (ER) data description commonly used in large-scale business software development.

Characterization of cephalic and non-cephalic sensory cell types provides insight into joint photo- and mechanoreceptor evolution.

Rhabdomeric opsins (r-opsins) are light sensors in cephalic eye photoreceptors, but also function in additional sensory organs. This has prompted questions on the evolutionary relationship of these cell types, and if ancient r-opsins were non-photosensory. A molecular profiling approach in the marine bristleworm revealed shared and distinct features of cephalic and non-cephalic -expressing cells.