Instantaneous Cross‐Correlation Analysis of Neural Ensembles with High Temporal Resolution

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.