Crosscorrelation analysis of simultaneously recorded activity of pairs of neurons is a common tool to infer functional neural connectivity. The adequacy of crosscorrelation procedures to detect and estimate neural connectivity has been investigated by means of computer simulations of small networks composed of fairly realistic modelneurons. If the mean interval of neural firings is much larger than the duration of postsynaptic potentials, which will be the case in many central brain areas excitatory connections are easier to detect than inhibitory ones. On the other hand, inhibitory connections are revealed better if the mean firing interval is much smaller than post-synaptic potential duration. In general the effects of external stimuli and the effects of neural connectivity do not add linearly. Furthermore, neurons may exhibit a certain degree of timelock to the stimulus. For these reasons the commonly applied "shift predictor" procedure to separate stimulus and neural effects appears to be of limited value. In case of parallel direct and indirect neural pathways between two neurons crosscorrelation analysis does not estimate the direct connection but instead an effective connectivity, which reflects the combined influences of the parallel pathways.

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With a dual-electrode configuration separable few-unit activity was recorded both on one electrode as well as on two electrodes in the auditory midbrain of the grassfrog to a large variety of stimuli. Activity recorded on one electrode was separated by a pattern recognition technique through the use of features of the action potential waveform. Functional connections between units were established on basis of cross-correlation histograms of pairs of simultaneously recorded units. A hierarchical scheme was adopted to describe the various manifestations of neural correlation. If a peak or trough was observed in the simultaneous cross-correlation histogram, irrespective of stimulus conditions, this was called neural synchrony. If this peak or trough was not equal to its shift predictor estimating the stimulus contribution, neural correlation was considered to be present. About 60% of the pairs exhibited neural synchrony, mostly due to shared stimulus influences, independent of mutual distance of units. About 15% of the unit pairs showed neural correlation indicating a functional neural connection. Neural correlation was observed only in units with a distance smaller than 300 micron. The majority (approximately 85%) of the cases showing neural correlation could be ascribed to neural shared input. Unidirectional excitation was observed only in unit pairs recorded on the same electrode. Unidirectional inhibition could not be demonstrated. The dependency of occurrence of neural correlation on unit distance has implications for models of the functional organization of the auditory midbrain. About half of the neurally correlated pairs showed stimulus dependencies of their functional connections. Together with the observed lack of stimulus invariance of single-unit spectrotemporal sensitivities this indicates a dynamic stimulus dependency of functional neuronal organization in the auditory midbrain of the grassfrog. Neuron pairs with a large overlap of their spectrotemporal sensitivities on average had neurally correlated activities more often than pairs with a smaller amount of overlap. In comparison to single-unit coding, ensemble coding by populations of neurons may show an enhanced selectivity to stimulus characteristics.

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