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The hippocampus, which is known as the center for learning and memory, is a remarkable neural structure that displays a variety of synchronous oscillations under physiological or pathophysiological conditions, such as theta rhythms, ripples, and epileptic seizures. Epileptic seizures, in particular, are caused by the enormous synchronous and rhythmic firing of hippocampal neurons (2-5 Hz) and can last for up to several minutes in temporal lobe epilepsy. Electrically induced seizure-like afterdischarges are an excellent experimental system for elucidating the network mechanisms underlying the neuronal synchronization and rhythm generation of these epileptic seizures in extremely hyperactive hippocampal networks. In this paper, we review the key findings of recent in vitro studies on the seizure-like afterdischarge in a local neuronal network in the rat hippocampal CA1 area. During the afterdischarge, GABAergic synaptic transmissions become transiently depolarizing and even excitatory as chloride rapidly accumulates post-synaptically through the GABAA receptors on hippocampal pyramidal cells. This transient GABAergic excitation is enhanced by glutamate release and extracellular potassium accumulation. Dual whole-cell patch-clamp recordings from a variety of interneurons and their neighboring pyramidal cells revealed that interneurons located in the stratum oriens and stratum pyramidale, including basket, chandelier, and bistratified cells, exhibited prominent firing activity that was phase-locked to the afterdischarge responses in the pyramidal cells. Thus, neuronal synchronization during the afterdischarge is achieved by synergistic excitations of glutamatergic pyramidal cells and GABAergic interneurons. Our observations also suggest that local circuits in the stratum oriens and stratum pyramidale may be responsible for rhythmic excitation during the seizure-like afterdischarge; however the detailed mechanism underlying this rhythmic excitation is not yet fully understood.

The hippocampus, which is a part of the old brain, has been considered responsible for the formation of episodic memory. Atrophy of the hippocampus can lead to Alzheimer disease. Alzheimer disease is a problem of the society. It is also expected to pose a serious problem in future societies composed of large numbers of elderly people. Therefore, it has become the focus of considerable attention. Motivated by the rehabilitation process of Alzheimer's patients, we mathematically studied the coding scheme in the hippocampus. We show that a mathematical model for CA3 exhibits successive recalls of memories which follow the emergent chaotic dynamics, where chaotic dynamics means ordered but comple and unpredictable neural activity. We also show that a network consisting of two-compartment model neurons for CA1 produces Cantor sets, by which the input time series of CA1 can be hierarchically encoded. We called this coding scheme Cantor coding. Predictions obtained from the model study have been partially verified by experiments using rat hippocampal slices.

The neuronal network is a computing system that transforms input to output. This computation involves complex nonlinear processes that are carried out with polysynaptic feedforward and feedback microcircuitry. Thus it cannot be assessed by isolating responses of single neurons or by averaging multineuronal responses. To solve this problem, functional multineuron calcium imaging (fMCI) is a promising option. This is a large-scale recording technique that simultaneously monitors the spatiotemporal patterns of spikes emitted by hundreds of neurons with single-cell resolution. Here, we review the availability and actual applications of fMCI. Using fMCI, we attempt to understand the manner in which information is processed in the hippocampal networks. The hippocampus receives information from the cortex; relays it through the dentate gyrus (DG), Cornu Ammonis (CA) 3, and then CA1; and sends it back to the cortex. We placed 2 stimulation electrodes (Stim A and Stim B) in the DG granule cell layer of cultured hippocampal networks and monitored the firing activity of a population of CA1 pyramidal neurons. In this experimental design, the hippocampal polysynaptic network is regarded as a huge arithmetic operator that converts DG inputs to CA1 outputs. We found that the hippocampal polysynaptic network functions as a complex parallel and distributed processing system.