Computational modeling of cognitive and neuroscience data is an insightful and powerful tool, but has many potential pitfalls that can be avoided by following simple guidelines.

A computational model of fission yeast mitosis can interrogate mechanisms required for successful mitosis, the origin of spindle length fluctuations, and spindle force balance during assembly.

A comprehensive, data-driven and interpretable nonlinear computational modeling framework based on deep neural networks uncovers different nonlinear transformations of speech signal in the human auditory cortex.

Computational modeling reveals the mechanisms by which a diverse group of neurons in the brainstem generates rhythmic breathing in mammals.

Organization of commissural and long propriospinal neuronal pathways defines gait expression in quadrupeds.

A new computational model of brainstem control of locomotor speed and gait was developed to reproduce and explain recent experimental data and propose predictions for subsequent experimental testing.

Computational modeling and analysis of mouse neural population data finds that the excitation/inhibition imbalance theory of brain disorders is too limited to account for key changes in neural activity statistics.

Theoretical ideas have a rich history in many areas of biology, and new theories and mathematical models have much to offer in the future.

Cell cycle gating enables a temporal compartmentalization of negative vs positive feedback control processes, leading to differential responses to repetitive interferon stimulations.

Human Neocortical Neurosolver is a new user-friendly software tool for researchers to develop and test hypotheses on cellular/circuit origins of human MEG/EEG signals using a biophysical model.