Pynapple advances data analysis in systems neuroscience with a versatile, open-source framework that uses common objects to handle diverse data streams, ensuring reliable and reproducible analysis while maintaining long-term backward compatibility.

A novel method and software provides researchers with the capability to rapidly, flexibly, and robustly perform Bayesian parameter estimation of theoretically meaningful models in cognitive neuroscience that were heretofore intractable.

Building on simple unsupervised matrix factorization techniques, the seqNMF algorithm successfully recovers neural sequences in a wide range of simulated and real datasets.

Self-citation rates differed by geographic region, seniority, gender, and field, which may ultimately affect the perceived influence of authors in these subgroups in neuroscience literature.

Circular analyses of knowledge are a common, serious, but often manageable problem in systems and network neuroscience.

The InsectBrain Database is a novel, freely available software tool designed to accelerate research in the field of insect neuroscience and to improve implementation of open data concepts.

Measurement precision offers a comprehensive perspective on good scientific practices to improve reproducibility of research results by providing means to optimize design and analysis parameters (e.g. sample size, trial count, or sample heterogeneity) in accordance with the researcher’s goals.

Effectively connected neurons self-organize forming networks with a small-world architecture composed of modules, with most likely few and nearby neurons, integrated by more topologically important and high firing rate neurons.