Bayesian simulator-based inference is used to infer the parameters of complex multicompartment models of retinal neurons from two-photon imaging data.

Attractive and repulsive history biases in visual perception occur simultaneously, yet over dissociable timescales, and are explained by efficient encoding and Bayesian decoding of visual information in a stable environment.

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.

The dependence of incentive value attribution on the anticipation of rewards within a given context is explained via a normative Bayesian account of how rewards map to incentive values.

Evidence for neuromodulatory control of flexibility in human neural models.

A Bayesian model of phase angles illustrates a novel approach to the analysis of phase coherence in frequency-tagged experiments.

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.

Circulating immune cells reflect intra-tumoural immunity and can predict response to systemic therapy in head and neck cancer.

A novel Bayesian method of modeling retinotopic maps is more accurate than traditional voxel-wise methods and can be used to automatically derive high-quality maps.

Insecticide-treated net requirements for Africa have been underestimated, but mitigating for inefficiencies in net distributions can produce a cost effective path to universal coverage.