Discovering Spike Patterns in Neuronal Responses

Fellous, Tiesinga, Thomas and Sejnowski
J of Neuroscience, 24(12):2989-3001, 2004

When a cortical neuron is repeatedly injected with the same fluctuating current stimulus (frozen noise) the timing of the spikes is highly precise from trial to trial and the spike pattern appears to be unique. We show here that the same repeated stimulus can produce more than one reliable temporal pattern of spikes. A new method is introduced to find these patterns in raw multitrial data and is tested on surrogate data sets. Using it, multiple coexisting spike patterns were discovered in pyramidal cells recorded from rat prefrontal cortex in vitro, in data obtained in vivo from the middle temporal area of the monkey (Buracas et al., 1998) and from the cat lateral geniculate nucleus (Reinagel and Reid, 2002). The spike patterns lasted from a few tens of milliseconds in vitro to several seconds in vivo. We conclude that the prestimulus history of a neuron may influence the precise timing of the spikes in response to a stimulus over a wide range of time scales.

Full Paper

This page contains data code and instructions for clustering surrogate datasets that contain 2,3 or 5 'hidden' spike patterns. These datasets are in Matlab (.mat) format.



2 Clusters (100 files, ~20 MB zip file)
3 Clusters (100 files, ~30 MB zip file)
5 Clusters (100 files, ~48 MB zip file)

Typical Results

Code (Matlab)

See also :


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