Towards Online Detection of Neural Assemblies in Parallel Spike Trains

Neural assemblies are supposed to play an important role in the de- and encoding of information and stimuli in the brain. These groups of neurons are representing information by increased synchronous behavior. Spike trains are abstractions of recordings of the electrical potential emitted by individual neurons. We use a previously developed method to describe a single spike trains behavior and extend this method to distinguish between different neural assemblies. Our algorithm can be extended to work in an online fashion that will allow neurobiologists to verify the spike-time hypothesis and eventually observe neural assemblies in real-time.