Inhibition dominates in shaping spontaneous CA3 hippocampal network activities in vitro

Transient effect of mossy fiber stimulation on spatial firing of CA3 neurons

Strong hippocampal mossy fiber synapses are thought to function as detonators, imposing "teaching" signals onto CA3 neurons during new memory formation. For an empirical test of this long-standing view, we examined effects of optogenetically stimulating mossy fibers on spatial firing of CA3 neurons in freely-moving mice. We found that spatially restricted mossy fiber stimulation drives novel place-specific firing in some CA3 pyramidal neurons. Such neurons comprise only a minority, however, and many more CA3 neurons showed inhibited spatial firing during mossy fiber stimulation. Also, changes in spatial firing induced by mossy fiber stimulation, both activated and inhibited, reverted immediately upon stimulation termination, leaving CA3 place fields unaltered. Our results do not support the traditional view that mossy fibers impose teaching signals onto CA3 network, and show robustness of established CA3 spatial representations.

Disrupted Co-activation of Interneurons and Hippocampal Network after Focal Kainate Lesion

GABAergic interneurons are known to control activity balance in physiological conditions and to coordinate hippocampal networks during cognitive tasks. In temporal lobe epilepsy interneuron loss and consecutive network imbalance could favor pathological hypersynchronous epileptic discharges. We tested this hypothesis in mice by in vivo unilateral epileptogenic hippocampal kainate lesion followed by in vitro recording of extracellular potentials and patch-clamp from GFP-expressing interneurons in CA3, in an optimized recording chamber. Slices from lesioned mice displayed, in addition to control synchronous events, larger epileptiform discharges. Despite some ipsi/contralateral and layer variation, interneuron density tended to decrease, average soma size to increase. Their membrane resistance decreased, capacitance increased and contralateral interneuron required higher current intensity to fire action potentials. Examination of synchronous discharges of control and larger amplitudes, revealed that interneurons were biased to fire predominantly with the largest population discharges. Altogether, these observations suggest that the overall effect of reactive cell loss, hypertrophy and reduced contralateral excitability corresponds to interneuron activity tuning to fire with larger population discharges. Such cellular and network mechanisms may contribute to a runaway path toward epilepsy.

Single CA3 pyramidal cells trigger sharp waves in vitro by exciting interneurones

KEY POINTS

The CA3 hippocampal region generates sharp waves (SPW), a population activity associated with neuronal representations. The synaptic mechanisms responsible for the generation of these events still require clarification. Using slices maintained in an interface chamber, we found that the firing of single CA3 pyramidal cells triggers SPW like events at short latencies, similar to those for the induction of firing in interneurons. Multi-electrode records from the CA3 stratum pyramidale showed that pyramidal cells triggered events consisting of putative interneuron spikes followed by field IPSPs. SPW fields consisted of a repetition of these events at intervals of 4-8 ms. Although many properties of induced and spontaneous SPWs were similar, the triggered events tended to be initiated close to the stimulated cell. These data show that the initiation of SPWs in vitro is mediated via pyramidal cell synapses that excite interneurons. They do not indicate why interneuron firing is repeated during a SPW.

ABSTRACT

Sharp waves (SPWs) are a hippocampal population activity that has been linked to neuronal representations. We show that SPWs in the CA3 region of rat hippocampal slices can be triggered by the firing of single pyramidal cells. Single action potentials in almost one-third of pyramidal cells initiated SPWs at latencies of 2-5 ms with probabilities of 0.07-0.76. Initiating pyramidal cells evoked field IPSPs (fIPSPs) at similar latencies when SPWs were not initiated. Similar spatial profiles for fIPSPs and middle components of SPWs suggested that SPW fields reflect repeated fIPSPs. Multiple extracellular records showed that the initiated SPWs tended to start near the stimulated pyramidal cell, whereas spontaneous SPWs could emerge at multiple sites. Single pyramidal cells could initiate two to six field IPSPs with distinct amplitude distributions, typically preceeded by a short-duration extracellular action potential. Comparison of these initiated fields with spontaneously occurring inhibitory field motifs allowed us to identify firing in different interneurones during the spread of SPWs. Propagation away from an initiating pyramidal cell was typically associated with the recruitment of interneurones and field IPSPs that were not activated by the stimulated pyramidal cell. SPW fields initiated by single cells were less variable than spontaneous events, suggesting that more stereotyped neuronal ensembles were activated, although neither the spatial profiles of fields, nor the identities of interneurone firing were identical for initiated events. The effects of single pyramidal cell on network events are thus mediated by different sequences of interneurone firing.

Network models predict that reduced excitatory fluctuations can give rise to hippocampal network hyper-excitability in MeCP2-null mice

Rett syndrome is a severe pediatric neurological disorder caused by loss of function mutations within the gene encoding methyl CpG-binding protein 2 (MeCP2). Although MeCP2 is expressed near ubiquitously, the primary pathophysiology of Rett syndrome stems from impairments of nervous system function. One alteration within different regions of the MeCP2-deficient brain is the presence of hyper-excitable network responses. In the hippocampus, such responses exist despite there being an overall decrease in spontaneous excitatory drive within the network. In this study, we generated and used mathematical, neuronal network models to resolve this apparent paradox. We did this by taking advantage of previous mathematical modelling insights that indicated that decreased excitatory fluctuations, but not mean excitatory drive, more critically explain observed changes in hippocampal network oscillations from MeCP2-null mouse slices. Importantly, reduced excitatory fluctuations could also bring about hyper-excitable responses in our network models. Therefore, these results indicate that diminished excitatory fluctuations may be responsible for the hyper-excitable state of MeCP2-deficient hippocampal circuitry.

Modeling oscillatory dynamics in brain microcircuits as a way to help uncover neurological disease mechanisms: a proposal

There is an undisputed need and requirement for theoretical and computational studies in Neuroscience today. Furthermore, it is clear that oscillatory dynamical output from brain networks is representative of various behavioural states, and it is becoming clear that one could consider these outputs as measures of normal and pathological brain states. Although mathematical modeling of oscillatory dynamics in the context of neurological disease exists, it is a highly challenging endeavour because of the many levels of organization in the nervous system. This challenge is coupled with the increasing knowledge of cellular specificity and network dysfunction that is associated with disease. Recently, whole hippocampus in vitro preparations from control animals have been shown to spontaneously express oscillatory activities. In addition, when using preparations derived from animal models of disease, these activities show particular alterations. These preparations present an opportunity to address challenges involved with using models to gain insight because of easier access to simultaneous cellular and network measurements, and pharmacological modulations. We propose that by developing and using models with direct links to experiment at multiple levels, which at least include cellular and microcircuit, a cycling can be set up and used to help us determine critical mechanisms underlying neurological disease. We illustrate our proposal using our previously developed inhibitory network models in the context of these whole hippocampus preparations and show the importance of having direct links at multiple levels.

Bifurcations of large networks of two-dimensional integrate and fire neurons

Recently, a class of two-dimensional integrate and fire models has been used to faithfully model spiking neurons. This class includes the Izhikevich model, the adaptive exponential integrate and fire model, and the quartic integrate and fire model. The bifurcation types for the individual neurons have been thoroughly analyzed by Touboul (SIAM J Appl Math 68(4):1045-1079, 2008). However, when the models are coupled together to form networks, the networks can display bifurcations that an uncoupled oscillator cannot. For example, the networks can transition from firing with a constant rate to burst firing. This paper introduces a technique to reduce a full network of this class of neurons to a mean field model, in the form of a system of switching ordinary differential equations. The reduction uses population density methods and a quasi-steady state approximation to arrive at the mean field system. Reduced models are derived for networks with different topologies and different model neurons with biologically derived parameters. The mean field equations are able to qualitatively and quantitatively describe the bifurcations that the full networks display. Extensions and higher order approximations are discussed.

Inhibitory networks of fast-spiking interneurons generate slow population activities due to excitatory fluctuations and network multistability

Slow population activities (SPAs) exist in the brain and have frequencies below ~5 Hz. Despite SPAs being prominent in several cortical areas and serving many putative functions, their mechanisms are not well understood. We studied a specific type of in vitro GABAergic, inhibition-based SPA exhibited by C57BL/6 murine hippocampus. We used a multipronged approach consisting of experiment, simulation, and mathematical analyses to uncover mechanisms responsible for hippocampal SPAs. Our results show that hippocampal SPAs are an emergent phenomenon in which the "slowness" of the network is due to interactions between synaptic and cellular characteristics of individual fast-spiking, inhibitory interneurons. Our simulations quantify characteristics underlying hippocampal SPAs. In particular, for hippocampal SPAs to occur, we predict that individual fast-spiking interneurons should have frequency-current (f-I) curves that exhibit a suitably sized kink where the slope of the curve decreases more abruptly in the gamma frequency range with increasing current. We also predict that these interneurons should be well connected with one another. Our mathematical analyses show that the combination of synaptic and intrinsic conditions, as predicted by our simulations, promotes network multistability. Population slow timescales occur when excitatory fluctuations drive the network between different stable network firing states. Since many of the parameters we use are extracted from experiments and subsequent measurements of experimental f-I curves of fast-spiking interneurons exhibit characteristics as predicted, we propose that our network models capture a fundamental operating mechanism in biological hippocampal networks.