We examined whether excitation and inhibition are balanced in hippocampal cortical networks. Extracellular field and single-unit activity were recorded by multiple tetrodes and multisite silicon probes to reveal the timing of the activity of hippocampal CA1 pyramidal cells and classes of interneurons during theta waves and sharp wave burst (SPW)-associated field ripples. The somatic and dendritic inhibition of pyramidal cells was deduced from the activity of interneurons in the pyramidal layer [int(p)] and in the alveus and st. oriens [int(a/o)], respectively. Int(p) and int(a/o) discharged an average of 60 and 20 degrees before the population discharge of pyramidal cells during the theta cycle, respectively. SPW ripples were associated with a 2.5-fold net increase of excitation. The discharge frequency of int(a/o) increased, decreased ("anti-SPW" cells), or did not change ("SPW-independent" cells) during SPW, suggesting that not all interneurons are innervated by pyramidal cells. Int(p) either fired together with (unimodal cells) or both before and after (bimodal cells) the pyramidal cell burst. During fast-ripple oscillation, the activity of interneurons in both the int(p) and int(a/o) groups lagged the maximum discharge probability of pyramidal neurons by 1-2 msec. Network state changes, as reflected by field activity, covaried with changes in the spike train dynamics of single cells and their interactions. Summed activity of parallel-recorded interneurons, but not of pyramidal cells, reliably predicted theta cycles, whereas the reverse was true for the ripple cycles of SPWs. We suggest that network-driven excitability changes provide temporal windows of opportunity for single pyramidal cells to suppress, enable, or facilitate selective synaptic inputs.

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%.

Most neuronal interactions in the cortex occur within local circuits. Because principal cells and GABAergic interneurons contribute differently to cortical operations, their experimental identification and separation is of utmost important. We used 64-site two-dimensional silicon probes for high-density recording of local neurons in layer 5 of the somatosensory and prefrontal cortices of the rat. Multiple-site monitoring of units allowed for the determination of their two-dimensional spatial position in the brain. Of the approximately 60,000 cell pairs recorded, 0.2% showed robust short-term interactions. Units with significant, short-latency (<3 ms) peaks following their action potentials in their cross-correlograms were characterized as putative excitatory (pyramidal) cells. Units with significant suppression of spiking of their partners were regarded as putative GABAergic interneurons. A portion of the putative interneurons was reciprocally connected with pyramidal cells. Neurons physiologically identified as inhibitory and excitatory cells were used as templates for classification of all recorded neurons. Of the several parameters tested, the duration of the unfiltered (1 Hz to 5 kHz) spike provided the most reliable clustering of the population. High-density parallel recordings of neuronal activity, determination of their physical location and their classification into pyramidal and interneuron classes provide the necessary tools for local circuit analysis.

Neurons can produce action potentials with high temporal precision. A fundamental issue is whether, and how, this capability is used in information processing. According to the 'cell assembly' hypothesis, transient synchrony of anatomically distributed groups of neurons underlies processing of both external sensory input and internal cognitive mechanisms. Accordingly, neuron populations should be arranged into groups whose synchrony exceeds that predicted by common modulation by sensory input. Here we find that the spike times of hippocampal pyramidal cells can be predicted more accurately by using the spike times of simultaneously recorded neurons in addition to the animals location in space. This improvement remained when the spatial prediction was refined with a spatially dependent theta phase modulation. The time window in which spike times are best predicted from simultaneous peer activity is 10-30 ms, suggesting that cell assemblies are synchronized at this timescale. Because this temporal window matches the membrane time constant of pyramidal neurons, the period of the hippocampal gamma oscillation and the time window for synaptic plasticity, we propose that cooperative activity at this timescale is optimal for information transmission and storage in cortical circuits.

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.

Transfer of neuronal patterns from the CA3 to CA1 region was studied by simultaneous recording of neuronal ensembles in the behaving rat. A nonlinear interaction among pyramidal neurons was observed during sharp wave (SPW)-related population bursts, with stronger synchrony associated with more widespread spatial coherence. SPW bursts emerged in the CA3a-b subregions and spread to CA3c before invading the CA1 area. Synchronous discharge of >10% of the CA3 within a 100 ms window was required to exert a detectable influence on CA1 pyramidal cells. Activity of some CA3 pyramidal neurons differentially predicted the ripple-related discharge of circumscribed groups of CA1 pyramidal cells. We suggest that, in SPW behavioral state, the coherent discharge of a small group of CA3 cells is the primary cause of spiking activity in CA1 pyramidal neurons.

Spike transmission probability between pyramidal cells and interneurons in the CA1 pyramidal layer was investigated in the behaving rat by the simultaneous recording of neuronal ensembles. Population synchrony was strongest during sharp wave (SPW) bursts. However, the increase was three times larger for pyramidal cells than for interneurons. The contribution of single pyramidal cells to the discharge of interneurons was often large (up to 0.6 probability), as assessed by the presence of significant (<3 ms) peaks in the cross-correlogram. Complex-spike bursts were more effective than single spikes. Single cell contribution was higher between SPW bursts than during SPWs or theta activity. Hence, single pyramidal cells can reliably discharge interneurons, and the probability of spike transmission is behavior dependent.

The glymphatic system is a brain-wide clearance pathway; its impairment contributes to the accumulation of amyloid-β. Influx of cerebrospinal fluid (CSF) depends upon the expression and perivascular localization of the astroglial water channel aquaporin-4 (AQP4). Prompted by a recent failure to find an effect of Aqp4 knock-out (KO) on CSF and interstitial fluid (ISF) tracer transport, five groups re-examined the importance of AQP4 in glymphatic transport. We concur that CSF influx is higher in wild-type mice than in four different Aqp4 KO lines and in one line that lacks perivascular AQP4 (Snta1 KO). Meta-analysis of all studies demonstrated a significant decrease in tracer transport in KO mice and rats compared to controls. Meta-regression indicated that anesthesia, age, and tracer delivery explain the opposing results. We also report that intrastriatal injections suppress glymphatic function. This validates the role of AQP4 and shows that glymphatic studies must avoid the use of invasive procedures.