3d-SPADE: Significance evaluation of spatio-temporal patterns of various temporal extents.

The Spike Pattern Detection and Evaluation (SPADE) analysis is a method to find reoccurring spike patterns in parallel spike train data, and to determine their statistical significance. Here we introduce an extension of the original statistical testing procedure which explicitly accounts for the temporal duration of the patterns. The extension improves the performance in the presence of patterns with different durations, as here demonstrated by application to various synthetic data.

Methods for identification of spike patterns in massively parallel spike trains.

Temporally, precise correlations between simultaneously recorded neurons have been interpreted as signatures of cell assemblies, i.e., groups of neurons that form processing units.

Synchronous Spike Patterns in Macaque Motor Cortex during an Instructed-Delay Reach-to-Grasp Task.

Unlabelled: The computational role of spike time synchronization at millisecond precision among neurons in the cerebral cortex is hotly debated. Studies performed on data of limited size provided experimental evidence that low-order correlations occur in relation to behavior. Advances in electrophysiological technology to record from hundreds of neurons simultaneously provide the opportunity to observe coordinated spiking activity of larger populations of cells.

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains.

With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing.

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining.

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing.

An incubating diseased-predator ecoepidemic model.

We present a model for transmissible diseases spreading among predators in a predator-prey system. Upon successful contact, a susceptible individual becomes infected but is not yet able to spread the disease further. After an incubation period, the diseased individual becomes infectious.