Temporally delayed linear modelling provides a domain-general linear framework for sequence detection and statistical testing, and is able to detect replays in both human neuroimaging and animal electrophysiology.
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.
An oscillating computational model combined with a predictive internal linguistic model can track naturally timed speech in which pseudo-rhythmicity is related to the predictability of words within their sentence context.
In vivo quantitative analysis of multi-shell diffusion MRI reveals novel insights into microstructure of human insular cortex and its functional circuits associated with the salience network and cognitive control.
Hybrid brain network models predict neurophysiological processes that link structural and functional empirical data across scales and modalities in order to better understand neural information processing and its relation to brain function.
A very large number of place-field maps can be robustly learned by association of external cues with the grid-driven response, however plasticity in the grid-cell inputs renders the place-cell responses volatile.