This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods.

The cellular generation and spatial distribution of gamma frequency (40– 100 Hz) activity was examined in the hippocampus of the awake rat. Field potentials and unit activity were recorded by multiple site silicon probes (5- and 16-site shanks) and wire electrode arrays. Gamma waves were highly coherent along the long axis of the dentate hilus, but average coherence decreased rapidly in the CA3 and CA1 directions. Analysis of short epochs revealed large fluctuations in coherence values between the dentate and CA1 gamma waves. Current source density analysis revealed large sinks and sources in the dentate gyrus with spatial distribution similar to the dipoles evoked by stimulation of the perforant path. The frequency changes of gamma and theta waves positively correlated (40–100 Hz and 5–10 Hz, respectively). Putative interneurons in the dentate gyrus discharged at gamma frequency and were phase-locked to the ascending part of the gamma waves recorded from the hilus. Following bilateral lesion of the entorhinal cortex the power and frequency of hilar gamma activity significantly decreased or disappeared. Instead, a large amplitude but slower gamma pattern (25–50 Hz) emerged in the CA3-CA1 network. We suggest that gamma oscillation emerges from an interaction between intrinsic oscillatory properties of interneurons and the network properties of the dentate gyrus. We also hypothesize that under physiological conditions the hilar gamma oscillation may be entrained by the entorhinal rhythm and that gamma oscillation in the CA3-CA1 circuitry is suppressed by either the hilar region or the entorhinal cortex.

Sharp wave bursts, induced by a cooperative discharge of CA3 pyramidal cells, are the most synchronous physiological pattern in the hippocampus. In conjunction with sharp wave bursts, CA1 pyramidal cells display a high-frequency (200 Hz) network oscillation (ripple). In the present study extracellular field and unit activity was recorded simultaneously from 16 closely spaces sites in the awake rat and the intracellular activity of CA1 pyramidal cells during the network oscillation was studied under anesthesia. Current source density analysis of the high-frequency oscillation revealed circumscribed sinks and sources in the vicinity of the pyramidal layer. Single pyramidal cells discharged at a low frequency but were phase locked to the negative peak of the locally derived field oscillation. Approximately 10% of the simultaneously recorded pyramidal cells fired during a given oscillatory event. Putative interneurons increased their discharge rates during the field ripples severalfold and often maintained a 200 Hz frequency during the oscillatory event. Under urethane and ketamine anesthesia the frequency of ripples was slower (100-I 20 Hz) than in the awake rat (160-200 Hz). Halothane anesthesia prevented the occurrence of high-frequency field oscillations in the CA1 region. Both the amplitude (l-4 mV) and phase of the intracellular ripple, but not its frequency, were voltage dependent. The amplitude of intracellular ripple was smallest between-70 and-60 mV. The phase of intracellular oscillation relative to the extracellular ripple reversed when the membrane was hyperpolarized more than-60 mV. A histologically verified CA1 basket cell increased its firing rate during the network oscillation and discharged at the frequency of the extracellular ripple. These findings indicate that the intracellularly re

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Information in neuronal networks may be represented by the spatiotemporal patterns of spikes. Here we examined the temporal coordination of pyramidal cell spikes in the rat hippocampus during slow-wave sleep. In addition, rats were trained to run in a defined position in space (running wheel) to activate a selected group of pyramidal cells. A template-matching method and a joint probability map method were used for sequence search. Repeating spike sequences in excess of chance occurrence were examined by comparing the number of repeating sequences in the original spike trains and in surrogate trains after Monte Carlo shuffling of the spikes. Four different shuffling procedures were used to control for the population dynamics of hippocampal neurons. Repeating spike sequences in the recorded cell assemblies were present in both the awake and sleeping animal in excess of what might be predicted by random variations. Spike sequences observed during wheel running were "replayed" at a faster timescale during single sharp-wave bursts of slow-wave sleep. We hypothesize that the endogenously expressed spike sequences during sleep reflect reactivation of the circuitry modified by previous experience. Reactivation of acquired sequences may serve to consolidate information.