A comprehensive battery of behavioral, electrophysiological and functional MRI techniques has allowed the development of a data-driven conceptual model of the tinnitus-hyperacusis network.
Machine learning models of coordinated hippocampal ensemble activity during sharp wave ripple activity encode structure that mirrors the place cell map expressed during exploration, and enable a new paradigm for analyzing and understanding this offline activity.
Prospective navigational goals are represented by single neuron firing rates and firing relative to slow oscillatory phase (phase coding) in the human medial temporal lobe.
OCT4 and SOX2 display partially independent activity to regulate chromatin accessibility, and highly dynamic activity of OCT4 is required throughout the cell cycle to maintain pluripotency enhancer accessibility.
A combination of signal processing and machine learning form a new approach to classify oscillatory coupling in single cycles without averaging over time and to capture cycle-by-cycle changes in coupling.
A novel methodological framework for cross-frequency coupling and spike-field coherence in multichannel (LFP, EEG, MEG) electrophysiology data reveals new manifestations of coupling dynamics.
Ten popular spike sorting codes are reproducibly benchmarked for accuracy on electrophysiology datasets from eleven laboratories with interactive web-based exploration of thousands of ground-truth units.
