Analyzing multidimensional neural activity via CNN-UM
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - Trang 243-250
Tóm tắt
In this paper we show that CNN-UM is an excellent tool for analyzing time series of multidimensional binary signals. The developed algorithm is dedicated to process electrophysiological multi-neuron recordings: our aim is to find specific multidimensional activity patterns, which may reflect higher order functional cell-assemblies. The analysis consists of two parts: the occurrences of different patterns are first counted, then the statistical significance of each occurrence frequency is calculated separately.
Từ khóa
#Multidimensional systems #Neurons #Frequency synchronization #Cellular neural networks #Electrodes #Physics #Neurophysiology #Signal analysis #Time series analysis #ElectrophysiologyTài liệu tham khảo
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