Synchronous firing and higher-order interactions in neuron pool
Neural Computation
How precise is neuronal synchronization?
Neural Computation
Messages of oscillatory correlograms: A spike train model
Neural Computation
Model this! seven empirical phenomena missing in the models of cortical oscillatory dynamics
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Temporal coding: competition for coherence and new perspectives on assembly formation
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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The analysis of neuronal information involves the detection of spatiotemporal relations between neuronal discharges. We propose a method that is based on the positions (phase offsets) of the central peaks obtained from pairwise cross-correlation histograms. Data complexity is reduced to a one-dimensional representation by using redundancies in the measured phase offsets such that each unit is assigned a “preferred firing time” relative to the other units in the group. We propose two procedures to examine the applicability of this method to experimental data sets. In addition, we propose methods that help the investigation of dynamical changes in the preferred firing times of the units. All methods are applied to a sample data set obtained from cat visual cortex.