Simultaneous recording from large numbers of neurons is a prerequisite for understanding their cooperative behavior. Various recording techniques and spike separation methods are being used toward this goal. However, the error rates involved in spike separation have not yet been quantified. We studied the separation reliability of "tetrode" (4-wire electrode)-recorded spikes by monitoring simultaneously from the same cell intracellularly with a glass pipette and extracellularly with a tetrode. With manual spike sorting, we found a trade-off between Type I and Type II errors, with errors typically ranging from 0 to 30% depending on the amplitude and firing pattern of the cell, the similarity of the waveshapes of neighboring neurons, and the experience of the operator. Performance using only a single wire was markedly lower, indicating the advantages of multiple-site monitoring techniques over single-wire recordings. For tetrode recordings, error rates were increased by burst activity and during periods of cellular synchrony. The lowest possible separation error rates were estimated by a search for the best ellipsoidal cluster shape. Human operator performance was significantly below the estimated optimum. Investigation of error distributions indicated that suboptimal performance was caused by inability of the operators to mark cluster boundaries accurately in a high-dimensional feature space. We therefore hypothesized that automatic spike-sorting algorithms have the potential to significantly lower error rates. Implementation of a semi-automatic classification system confirms this suggestion, reducing errors close to the estimated optimum, in the range 0-8%.

Multichannel tetrode array recording in awake behaving animals provides a powerful method to record the activity of large numbers of neurons. The power of this method could be extended if further information concerning the intracellular state of the neurons could be extracted from the extracellularly recorded signals. Toward this end, we have simultaneously recorded intracellular and extracellular signals from hippocampal CA1 pyramidal cells and interneurons in the anesthetized rat. We found that several intracellular parameters can be deduced from extracellular spike waveforms. The width of the intracellular action potential is defined precisely by distinct points on the extracellular spike. Amplitude changes of the intracellular action potential are reflected by changes in the amplitude of the initial negative phase of the extracellular spike, and these amplitude changes are dependent on the state of the network. In addition, intracellular recordings from dendrites with simultaneous extracellular recordings from the soma indicate that, on average, action potentials are initiated in the perisomatic region and propagate to the dendrites at 1.68 m/s. Finally we determined that a tetrode in hippocampal area CA1 theoretically should be able to record electrical signals from approximately 1, 000 neurons. Of these, 60-100 neurons should generate spikes of sufficient amplitude to be detectable from the noise and to allow for their separation using current spatial clustering methods. This theoretical maximum is in contrast to the approximately six units that are usually detected per tetrode. From this, we conclude that a large percentage of hippocampal CA1 pyramidal cells are silent in any given behavioral condition.

Although extracellular unit recording is typically used for the detection of spike occurrences, it also has the theoretical ability to report about what are typically considered intracellular features of the action potential. We address this theoretical ability by developing a model system that captures features of experimentally recorded simultaneous intracellular and extracellular recordings of CA1 pyramidal neurons. We use the line source approximation method of Holt and Koch to model the extracellular action potential (EAP) voltage resulting from the spiking activity of individual neurons. We compare the simultaneous intracellular and extracellular recordings of CA1 pyramidal neurons recorded in vivo with model predictions for the same cells reconstructed and simulated with compartmental models. The model accurately reproduces both the waveform and the amplitude of the EAPs, although it was difficult to achieve simultaneous good matches on both the intracellular and extracellular waveforms. This suggests that accounting for the EAP waveform provides a considerable constraint on the overall model. The developed model explains how and why the waveform varies with electrode position relative to the recorded cell. Interestingly, each cell's dendritic morphology had very little impact on the EAP waveform. The model also demonstrates that the varied composition of ionic currents in different cells is reflected in the features of the EAP.

No abstract

Brain systems communicate by means of neuronal oscillations at multiple temporal and spatial scales. In anesthetized rats, we find that neocortical "slow" oscillation engages neurons in prefrontal, somatosensory, entorhinal, and subicular cortices into synchronous transitions between UP and DOWN states, with a corresponding bimodal distribution of their membrane potential. The membrane potential of hippocampal granule cells and CA3 and CA1 pyramidal cells lacked bimodality, yet it was influenced by the slow oscillation in a region-specific manner. Furthermore, in both anesthetized and naturally sleeping rats, the cortical UP states resulted in increased activity of dentate and most CA1 neurons, as well as the highest probability of ripple events. Yet, the CA3-CA1 network could self-organize into gamma bursts and occasional ripples during the DOWN state. Thus, neo/paleocortical and hippocampal networks periodically reset, self-organize, and temporally coordinate their cell assemblies via the slow oscillation.

Processing of neuronal information depends on interactions between the anatomical connectivity and cellular properties of single cells. We examined how these computational building blocks work together in the intact rat hippocampus. Single spikes in dentate granule cells, controlled intracellularly, generally failed to discharge either interneurons or CA3 pyramidal cells. In contrast, trains of spikes effectively discharged both CA3 cell types. Increasing the discharge rate of the granule cell increased the discharge probability of its target neuron and decreased the delay between the onset of a granule cell train and evoked firing in postsynaptic targets. Thus, we conclude that the granule cell to CA3 synapses are 'conditional detonators,' dependent on granule cell firing pattern. In addition, we suggest that information in single granule cells is converted into a temporal delay code in target CA3 pyramidal cells and interneurons. These data demonstrate how a neural circuit of the CNS may process information.

The formation and recall of sensory, motor, and cognitive representations require coordinated fast communication among multiple cortical areas. Interareal projections are mainly mediated by glutamatergic pyramidal cell projections; only few long-range GABAergic connections have been reported. Using in vivo recording and labeling of single cells and retrograde axonal tracing, we demonstrate novel long-range GABAergic projection neurons in the rat hippocampus: (1) somatostatin-and predominantly mGluR1␣-positive neurons in stratum oriens project to the subiculum, other cortical areas, and the medial septum; (2) neurons in stratum oriens, including somatostatin-negative ones; and (3) trilaminar cells project to the subiculum and/or other cortical areas but not the septum. These three populations strongly increase their firing during sharp wave-associated ripple oscillations, communicating this network state to the septotemporal system. Finally, a large population of somatostatin-negative GABAergic cells in stratum radiatum project to the molecular layers of the subiculum, presubiculum, retrosplenial cortex, and indusium griseum and fire rhythmically at high rates during theta oscillations but do not increase their firing during ripples. The GABAergic projection axons have a larger diameter and thicker myelin sheet than those of CA1 pyramidal cells. Therefore, rhythmic IPSCs are likely to precede the arrival of excitation in cortical areas (e.g., subiculum) that receive both glutamatergic and GABAergic projections from the CA1 area. Other areas, including the retrosplenial cortex, receive only rhythmic GABAergic CA1 input. We conclude that direct GABAergic projections from the hippocampus to other cortical areas and the septum contribute to coordinating oscillatory timing across structures.

According to the temporal coding hypothesis, neurons encode information by the exact timing of spikes. An example of temporal coding is the hippocampal phase precession phenomenon, in which the timing of pyramidal cell spikes relative to the theta rhythm shows a unidirectional forward precession during spatial behaviour. Here we show that phase precession occurs in both spatial and non-spatial behaviours. We found that spike phase correlated with instantaneous discharge rate, and processed unidirectionally at high rates, regardless of behaviour. The spatial phase precession phenomenon is therefore a manifestation of a more fundamental principle governing the timing of pyramidal cell discharge. We suggest that intrinsic properties of pyramidal cells have a key role in determining spike times, and that the interplay between the magnitude of dendritic excitation and rhythmic inhibition of the somatic region is responsible for the phase assignment of spikes.