For analyzing time-dependent patch-clamp or patch-clamp fluorometry data of ion channels in terms of Markovian models, the superiority of Bayesian filtering with respect to traditional deterministic approaches is demonstrated enabling more reliable quantification of the parameters.

Brain activity is modelled as a function of stimuli that evolve continuously in time, in experimental designs without repeated trials.

The asymptomatic colonization and importation of methicillin-resistant Staphylococcus aureus (MRSA) in hospital settings can be inferred from observed cases using combined model-inference methods and used to inform improved interventions.

Quantitative analysis of cell dynamics over a range of timescales reveals that core PCP is not required to organize large-scale tissue flows but does affect short timescale mechanics.

Neuron ensembles in the medial prefrontal cortex gradually develop codes for relevant, latent variables common across multiple experiences while – apparently independently – losing information about irrelevant, contextual variables unique to each experience.

The retina compensates for rod death and deteriorating cones to retain high-fidelity visual signaling to the brain.

Purkinje cell inputs onto cerebellar nuclei (CbN) neurons have highly variable strengths, which allow them to influence CbN firing in a graded manner, with the largest individual inputs effectively regulating both the rate and spike timing of CbN neuron firing.

The new method and reported findings address a growing interest in neuroscience for research tools that can reliably decompose brain activity at the mesoscopic scale into interpretable components.

GrimAge acceleration may increase the risk of colorectal cancer.

Mnemonic representations in the human anterior-lateral entorhinal cortex change through learning to reflect an experienced temporal event structure and holistic temporal maps relate to memory recall.