Neuronal networks possess the impressive ability to process even extremely
complex and extensive information efficiently. An in-depth comprehension
about the underlying mechanisms and communication paradigms between the
neurons would render numerous innovations in several areas possible. To
gain such an understanding it is necessary to investigate the signals
inside a neuronal network. To this end, powerful methods for signal
analysis are required. In this paper several concepts are introduced, which
permit the detection of electrical neuronal activity. For assigning the
recorded signals to specific neurons, a new, reliable technique is
developed. In addition a procedure is presented, that allows such
associations even in multichannel systems. The proposed methods are based
on the automatic extraction of relevant signal parameters by means of
multivariate data decomposition and the subsequent clustering of the
determined features.