No abstract

One of the fundamental difficulties in neural assembly studies is the lack of an effective, high resolution measure of the spatio-temporal structure in spike trains obtained from a single realization. In this chapter a systematic approach to estimate the cross-correlation (CC) of spike trains, over time and in only one realization, is proposed. The solution lies in an alternate definition of cross-correlation which suggests that, rather than time averaging as is current practice, we should use ensemble averaging. This observation suggests a natural instantaneous CC estimator as required for high temporal resolution and real-time ensemble analysis and decoding. Results are shown in simulated datasets and neural activity of rat motor cortical neurons during a behavioral task.