Robert Pröpper

TL;DR: The results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step.

TL;DR: This work proposes here a language-independent object model, named “Neo,” suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations, and develops an open source implementation in the Python programming language that should become the standard basis for Python tools in neurophysiology.

TL;DR: It is shown that high spike sorting performance of in vivo recordings, including overlapping spikes, can be achieved with a recently developed filter-based template matching procedure and that overlapping spikes can be identified and assigned to individual neurons to study synchronous activity in local groups of neurons.

TL;DR: Spyke Viewer is an open source application designed to help researchers analyze data from electrophysiological recordings or neural simulations and provides a graphical data browser and supports finding and selecting relevant subsets of the data.