I am interested in stochastic modeling and statistical analysis of temporal coordination in neurophysiological recordings, with a focus on spiking activity.To this end, we develop stochastic spike-train models for the description, measurement and statistical analysis of spiking patterns in single and parallel spike trains, such as phase relations, oscillatory and synchronous activity, higher-order correlations or bursting. We also derive statistical analysis techniques for the identification of nonstationarity and develop tools for a combined analysis of discrete and continuous processes. Our approaches are data driven, and all models and analysis techniques are motivated by empirical analyses of experimental data in close interdisciplinary cooperation.
Schiemann J, Klose V, Schlaudraff F, Bingmer M, Seino S, Magill P J, Schneider G, Liss B, Roeper J (2012). K-ATP channels control in vivo burst firing of dopamine neurons in the medial substantia nigra and novelty-induced behavior. Nat Neurosci 15:1272-80.
Bingmer M, Schiemann J, Roeper J, Schneider G (2011). Measuring burstiness and regularity in oscillatory spike trains. J Neurosci Methods 201: 426-437.
Schneider G (2008). Messages of oscillatory correlograms - a spike train model. Neural Computation 20 (5): 1211-1238.
Schneider G, Havenith MN, Nikolic D (2006). Spatio-temporal structure in large neuronal networks detected from cross correlation. Neural Computation 18(10): 2387-2413.
Schneider G, Nikolic D (2006). Detection and assessment of near-zero delays in neuronal spiking activity. J Neurosci Methods:97-106.