Behaviordependent states of the hippocampal network affect functional clustering of neurons

Local versus distant coherence of hippocampal CA1 pyramidal cells was investigated in the behaving rat. Temporal crosscorrelation of pyramidal cells revealed a significantly stronger relationship among local (Ͻ140 m) pyramidal neurons compared with distant (Ͼ300 m) neurons during non-thetaassociated immobility and sleep but not during thetaassociated running and walking. In contrast, cross-correlation between local pyramidal cell-interneuron pairs was significantly stronger than between distant pairs during theta oscillations but were similar during non-theta-associated behaviors. We suggest that network state-dependent functional clustering of neuronal activity emerges because of the differential contribution of the main excitatory inputs, the perforant path, and Schaffer collaterals during theta and non-theta behaviors. Key words: pyramidal cell; interneuron; sleep; synchrony; theta; sharp waves Neighboring and distant hippocampal "place" cells have been postulated to have the same probability for representing the same part of the environment (O' Keefe and Nadel, 1978; Functional clustering of actively spiking neurons depends primarily on the configuration of the inputs. In various networks states, different sets of afferents may drive the same neuronal population, giving rise to state-dependent firing relationship among the cells. The two major network patterns of the hippocampus are theta oscillation in the awake, exploring rat and during REM sleep and non-theta state associated with consummatory behaviors and slow wave sleep (SWS) MATERIALS AND METHODS T welve male rats of the L ong-Evans strain (300 -500 gm) were implanted with eight individually movable tetrodes. The tetrodes were inserted into the CA1 pyramidal layer with 300 m center spacings. Before implantation, the rats were trained to run continuously in a running wheel (29.5 cm in diameter) for water reinforcement available in an adjacent box (C zurkó et al., 1999). After amplification (10,000ϫ) and band-pass filtering (1 Hz to 5 kHz) field potentials and extracellular action potentials were digitized continuously at a 20 kHz rate with a DataMax system (16-bit resolution; RC Electronics, Santa Barbara, CA). Interneurons and pyramidal cells were separated by a multidimensional clustering method using the principal components of the detected spikes To quantif y coactivation of neurons, first a cross-correlogram between cell pairs was computed. Each bar of the histogram was divided by the bin width and by the total length of recording. This normalized the cross-correlogram (i.e., when two units are not correlated, the height of the bar is equal to the product of firing rate[unit 1] and firing rate[unit 2]; in square Hertz). Next, the cross-correlogram was f urther divided by the firing rates of unit 1 and unit 2. This produced cross-correlograms that were independent of firing rate of the units. The summed center bins of the cross-correlograms (100 msec) were used for examining the relationship between coactivity of local (i.e., neurons isolated from the same tetrode) versus distal (neurons recorded from different tetrodes) neuron pairs. After completion of the experiments, the rats were deeply anesthetized and perf used. The brains were sectioned and stained with the cresyl violet method to verif y electrode placements