Frances K. Skinner

The role of gap junctions in seizures

Electrotonic synaptic communication between neurons via gap junctions (gjs) is increasingly recognized as an important synchronizing mechanism in the brain. At the same time, the biology of central nervous system (CNS) gjs is being unravelled. The pathogenesis of the abnormal neuronal synchrony underlying seizures, formerly thought to be based mainly on chemical synaptic transmission, now includes a role for gap junctional communication. This concept has been strengthened by evidence from several in vitro seizure models, in which pharmacological manipulations of gap junctional communication predictably affect the generation of seizures: blockers diminishing seizures and enhancers increasing the seizures. Evidence for interneurons, coupled in part by gjs, generating synchronous neural network activity including seizures, is presented. Also neuromodelling studies, which have enhanced our ability to understand the functional role that gap junctional communication plays in the generation and maintenance of neural synchrony and seizures, are presented. Gap junctional communication appears to be a promising target for the development of future anticonvulsant therapy.

Somatodendritic Kv7/KCNQ/M Channels Control Interspike Interval in Hippocampal Interneurons

The M-current (IM), comprised of Kv7 channels, is a voltage-activated K+ conductance that plays a key role in the control of cell excitability. In hippocampal principal cells, IM controls action potential (AP) accommodation and contributes to the medium-duration afterhyperpolarization, but the role of IM in control of interneuron excitability remains unclear. Here, we investigated IM in hippocampal stratum oriens (SO) interneurons, both from wild-type and transgenic mice in which green fluorescent protein (GFP) was expressed in somatostatin-containing interneurons. Somatodendritic expression of Kv7.2 or Kv7.3 subunits was colocalized in a subset of GFP+ SO interneurons, corresponding to oriens-lacunosum moleculare (O-LM) cells. Under voltage clamp (VC) conditions at −30 mV, the Kv7 channel antagonists linopirdine/XE-991 abolished the IM amplitude present during relaxation from −30 to −50 mV and reduced the holding current (Ihold). In addition, 0.5 mm tetraethylammonium reduced IM, suggesting that IM was composed of Kv7.2-containing channels. In contrast, the Kv7 channel opener retigabine increased IM amplitude and Ihold. When strongly depolarized in VC, the linopirdine-sensitive outward current activated rapidly and comprised up to 20% of the total current. In current-clamp recordings from GFP+ SO cells, linopirdine induced depolarization and increased AP frequency, whereas retigabine induced hyperpolarization and arrested firing. In multicompartment O-LM interneuron models that incorporated IM, somatodendritic placement of Kv7 channels best reproduced experimentally measured IM. The models suggest that Kv3- and Kv7-mediated channels both rapidly activate during single APs; however, Kv3 channels control rapid repolarization of the AP, whereas Kv7 channels primarily control the interspike interval.

Intersegmental coordination in invertebrates and vertebrates

How does the CNS coordinate muscle contractions between different body segments during normal locomotion? Work on several preparations has shown that this coordination relies on excitability gradients and on differences between ascending and descending intersegmental coupling. Abstract models involving chains of coupled oscillators have defined properties of coordinating circuits that would permit them to establish a constant intersegmental phase in the face of changing periods. Analyses that combine computational and experimental strategies have led to new insights into the cellular organization of intersegmental coordinating circuits and the neural control of swimming in lamprey, tadpole, crayfish and leech.

Active dendrites and spike propagation in multicompartment models of oriens-lacunosum/moleculare hippocampal interneurons

It is well known that interneurons are heterogeneous in their morphologies, biophysical properties, pharmacological sensitivities and electrophysiological responses, but it is unknown how best to understand this diversity. Given their critical roles in shaping brain output, it is important to try to understand the functionality of their computational characteristics. To do this, we focus on specific interneuron subtypes. In particular, it has recently been shown that long‐term potentiation is induced specifically on oriens‐lacunosum/moleculare (O‐LM) interneurons in hippocampus CA1 and that the same cells contain the highest density of dendritic sodium and potassium conductances measured to date. We have created multi‐compartment models of an O‐LM hippocampal interneuron using passive properties, channel kinetics, densities and distributions specific to this cell type, and explored its signalling characteristics. We found that spike initiation depends on both location and amount of input, as well as the intrinsic properties of the interneuron. Distal synaptic input always produces strong back‐propagating spikes whereas proximal input could produce both forward‐ and back‐propagating spikes depending on the input strength. We speculate that the highly active dendrites of these interneurons endow them with a specialized function within the hippocampal circuitry by allowing them to regulate direct and indirect signalling pathways within the hippocampus.

Intersegmental coordination of limb movements during locomotion: mathematical models predict circuits that drive swimmeret beating.

Normal locomotion in arthropods and vertebrates is a complex behavior, and the neural mechanisms that coordinate their limbs during locomotion at different speeds are unknown. The neural modules that drive cyclic movements of swimmerets respond to changes in excitation by changing the period of the motor pattern. As period changes, however, both intersegmental phase differences and the relative durations of bursts of impulses in different sets of motor neurons are preserved. To investigate these phenomena, we constructed a cellular model of the local pattern-generating circuit that drives each swimmeret. We then constructed alternative intersegmental circuits that might coordinate these local circuits. The structures of both the model of the local circuit and the alternative models of the coordinating circuit were based on and constrained by previous experimental results on pattern-generating neurons and coordinating interneurons. To evaluate the relative merits of these alternatives, we compared their dynamics with the performance of the real circuit when the level of excitation was changed. Many of the alternative coordinating circuits failed. One coordinating circuit, however, did effectively match the performance of the real system as period changed from 1 to 3.2 Hz. With this coordinating circuit, both the intersegmental phase differences and the relative durations of activity within each of the local modules fell within the ranges characteristic of the normal motor pattern and did not change significantly as period changed. These results predict a mechanism of coordination and a pattern of intersegmental connections in the CNS that is amenable to experimental test.

Spontaneous rhythmic field potentials of isolated mouse hippocampal–subicular–entorhinal cortices in vitro

The rodent hippocampal circuit is capable of exhibiting in vitro spontaneous rhythmic field potentials (SRFPs) of 1–4 Hz that originate from the CA3 area and spread to the CA1 area. These SRFPs are largely correlated with GABA‐A IPSPs in pyramidal neurons and repetitive discharges in inhibitory interneurons. As such, their generation is thought to result from cooperative network activities involving both pyramidal neurons and GABAergic interneurons. Considering that the hippocampus, subiculum and entorhinal cortex function as an integrated system crucial for memory and cognition, it is of interest to know whether similar SRFPs occur in hippocampal output structures (that is, the subiculum and entorhinal cortex), and if so, to understand the cellular basis of these subicular and entorhinal SRFPs as well as their temporal relation to hippocampal SRFPs. We explored these issues in the present study using thick hippocampal–subicular–entorhinal cortical slices prepared from adult mice. SRFPs were found to spread from the CA1 area to the subicular and entorhinal cortical areas. Subicular and entorhinal cortical SRFPs were correlated with mixed IPSPs/EPSPs in local pyramidal neurons, and their generation was dependent upon the activities of GABA‐A and AMPA glutamate receptors. In addition, the isolated subicular circuit could elicit SRFPs independent of CA3 inputs. We hypothesize that the SRFPs represent a basal oscillatory activity of the hippocampal–subicular–entorhinal cortices and that the subiculum functions as both a relay and an amplifier, spreading the SRFPs from the hippocampus to the entorhinal cortex.

Two-Cell to N-Cell Heterogeneous, Inhibitory Networks: Precise Linking of Multistable and Coherent Properties

Inhibitory networks are now recognized as being the controllers of several brain rhythms. However, experimental work with inhibitory cells is technically difficult not only because of their smaller percentage of the neuronal population, but also because of their diverse properties. As such, inhibitory network models with tight links to the experimental data are needed to understand their contributions to population rhythms. However, mathematical analyses of network models with more than two cells is challenging when the cellular models involve biophysical details. We use bifurcation analyses and simulations to show that two-cell analyses can quantitatively predict N-cell (N = 20, 50, 100) network dynamics for heterogeneous, inhibitory networks. Interestingly, multistable states in the two-cell system are manifest as different and distinct coherent network patterns in the N-cell networks for the same parameter sets.

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.

Network bursting using experimentally constrained single compartment CA3 hippocampal neuron models with adaptation

The hippocampus is a brain structure critical for memory functioning. Its network dynamics include several patterns such as sharp waves that are generated in the CA3 region. To understand how population outputs are generated, models need to consider aspects of network size, cellular and synaptic characteristics and context, which are necessarily ‘balanced’ in appropriate ways to produce particular outputs. Thick slice hippocampal preparations spontaneously produce sharp waves that are initiated in CA3 regions and depend on the right balance of glutamatergic activities. As a step toward developing network models that can explain important balances in the generation of hippocampal output, we develop models of CA3 pyramidal cells. Our models are single compartment in nature, use an Izhikevich-type structure and involve parameter values that are specifically designed to encompass CA3 intrinsic properties. Importantly, they incorporate spike frequency adaptation characteristics that are directly comparable to those measured experimentally. Excitatory networks using these model cells are able to produce bursting suggesting that the amount of spike frequency adaptation expressed in the biological cells is an essential contributor to network bursting, and as such, may be important for sharp wave generation. The network bursting mechanism is numerically dissected showing the critical balance between adaptation and excitatory drive. The compact nature of our models allows large network simulations to be efficiently computed. This, together with the linkage of our models to cellular characteristics, will allow us to develop an understanding of population output of CA3 hippocampus with direct biological comparisons.

Theory, models and biology

Theoretical ideas have a rich history in many areas of biology, and new theories and mathematical models have much to offer in the future.