Modeling of evoked field potentials in hippocampal CA1 area describes their dependence on NMDA and GABA receptors

The glutamatergic synapse: a complex machinery for information processing

Being the most abundant synaptic type, the glutamatergic synapse is responsible for the larger part of the brain's information processing. Despite the conceptual simplicity of the basic mechanism of synaptic transmission, the glutamatergic synapse shows a large variation in the response to the presynaptic release of the neurotransmitter. This variability is observed not only among different synapses but also in the same single synapse. The synaptic response variability is due to several mechanisms of control of the information transferred among the neurons and suggests that the glutamatergic synapse is not a simple bridge for the transfer of information but plays an important role in its elaboration and management. The control of the synaptic information is operated at pre, post, and extrasynaptic sites in a sort of cooperation between the pre and postsynaptic neurons which also involves the activity of other neurons. The interaction between the different mechanisms of control is extremely complicated and its complete functionality is far from being fully understood. The present review, although not exhaustively, is intended to outline the most important of these mechanisms and their complexity, the understanding of which will be among the most intriguing challenges of future neuroscience.

Simplest relationship between local field potential and intracellular signals in layered neural tissue

The relationship between the extracellularly measured electric field potential resulting from synaptic activity in an ensemble of neurons and intracellular signals in these neurons is an important but still open question. Based on a model neuron with a cylindrical dendrite and lumped soma, we derive a formula that substantiates a proportionality between the local field potential and the total somatic transmembrane current that emerges from the difference between the somatic and dendritic membrane potentials. The formula is tested by intra- and extracellular recordings of evoked synaptic responses in hippocampal slices. Additionally, the contribution of different membrane currents to the field potential is demonstrated in a two-population mean-field model. Our formalism, which allows for a simple estimation of unknown dendritic currents directly from somatic measurements, provides an interpretation of the local field potential in terms of intracellularly measurable synaptic signals. It is also applicable to the study of cortical activity using two-compartment neuronal population models.

A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement.

Cannabinoids alter spontaneous firing, bursting, and cell synchrony of hippocampal principal cells

Both natural and synthetic cannabinoid receptor (e.g., CB1) agonists such as Δ(9)-THC, WIN 55,212-2 (WIN-2), and HU-210 disrupt spatial cognition presumably through the inhibition of synchrony of hippocampal ensemble firing to task-related events. Although the CB1 receptor agonist CP 55,940 also disrupts the synchronous firing of hippocampal neurons, it does not seem to affect the average firing rate. This difference is not readily explained by the chemical structure and pharmacology of the different compounds thus warranting a more detailed examination into (i) how other cannabinoids affect the spontaneous firing, bursting, and cell synchrony of hippocampal principal cells located in CA3 and CA1 subfields, and (ii) whether these effects are indeed mediated through CB1 receptors, which will be explored by the selective antagonist AM-251. Male Long-Evans rats surgically implanted with multielectrode arrays to hippocampal CA3 and CA1 were anesthetized and principal cells discharging at 0.25-6.0 Hz were isolated and "tracked" following the systemic administration of Tween-80, Δ(9)-THC (1 or 3 mg/kg) or WIN-2 (1 mg/kg) or HU-210 (100 μg/kg), and 1.5 mg/kg AM-281. All cannabinoids except for 1 mg/kg Δ(9) -THC reliably reduced average firing rates and altered "burst" characteristics, which were reversible with AM-281 for Δ(9)-THC and WIN-2 but not for HU-210. In addition, all cannabinoids disrupted intrasubfield and intersubfield ensemble synchrony of pyramidal cells, which is an effect insensitive to AM-281 and thus unlikely to be CB1 mediated. We consider these cannabinoid effects on spike timing and firing/bursting of principal hippocampal neurons carried by CB1 and non-CB1 receptors to be physiological underpinnings of the cognitive impairments inherent to cannabinoid exposure.

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model

The pathophysiological interpretation of EEG signals recorded with depth electrodes [i.e., local field potentials (LFPs)] during interictal (between seizures) or ictal (during seizures) periods is fundamental in the presurgical evaluation of patients with drug-resistant epilepsy. Our objective was to explain specific shape features of interictal spikes in the hippocampus (observed in LFPs) in terms of cell- and network-related parameters of neuronal circuits that generate these events. We developed a neural network model based on "minimal" but biologically relevant neuron models interconnected through GABAergic and glutamatergic synapses that reproduce the main physiological features of the CA1 subfield. Simulated LFPs were obtained by solving the forward problem (dipole theory) from networks including a large number ( approximately 3000) of cells. Insertion of appropriate parameters allowed the model to simulate events that closely resemble actual epileptic spikes. Moreover, the shape of the early fast component ("spike'') and the late slow component ("negative wave'') was linked to the relative contribution of glutamatergic and GABAergic synaptic currents in pyramidal cells. In addition, the model provides insights about the sensitivity of electrode localization with respect to recorded tissue volume and about the relationship between the LFP and the intracellular activity of principal cells and interneurons represented in the network.

Simulation of sleep spindles and spike and wave discharges using a novel method for the calculation of field potentials in rats

We suggest a new method for calculation of extracellular field potentials generated by a large population of pyramidal cells (PCs), using a single PC compartmental model. Similar methods described earlier use the assumption that the intracellular potential or current distributions of the cells within the population are much alike as a result of simultaneous activation at about the same longitudinal location (i.e., all the PCs in the population are located on the same level and are ideally synchronized). However, the degree of synchronization of natural firing even during synchronized rhythmic discharges in the cortex is not as high. We introduce the possibility to vary the degree of synchronization of the PCs' activity in the population, thus taking into account disperse timing of cortical pyramidal cells' firing. The temporal variability in cell firing is described by a Gaussian distribution, the width of which defines the degree of synchronization/desynchronization. In addition, the suggested method allows for certain spatial spread of PCs in the population along longitudinal axis of the PCs. The method was applied to test the assumption that the transition from sleep spindles to rhythmic spike and wave discharges (SWDs) observed in absence epilepsy may occur due to an increase in pyramidal cells' firing synchronization. We show that in case of weak synchronization of PC firing in the population, the shape of field potential during rhythmic thalamic input is similar to the oscillations during a sleep spindle, while at stronger synchronization of PCs, it looks much more as a SWD, with clear expressed spikes and waves. This suggests that in large population of pyramidal cells the changes in the degree of synchronization of cell firing may explain the changes in the shape of field potential from spindle oscillations to SWDs and vice versa.

Model-based source localization of extracellular action potentials

A new model-based analysis method was set up for revealing information encrypted in extracellular spatial potential patterns of neocortical action potentials. Spikes were measured by extracellular linear multiple microelectrode in vivo cat's primary auditory cortex and were analyzed based on current source density (CSD) distribution models. Validity of the monopole and other point source approximations were tested on the measured potential patterns by numerical fitting. We have found, that point source models could not provide accurate description of the measured patterns. We introduced a new model of the CSD distribution on a spiking cell, called counter-current model (CCM). This new model was shown to provide better description of the spatial current distribution of the cell during the initial negative deflection of the extracellular action potential, from the onset of the spike to the negative peak. The new model was tested on simulated extracellular potentials. We proved numerically, that all the parameters of the model could be determined accurately based on measurements. Thus, fitting of the CCM allowed extraction of these parameters from the measurements. Due to model fitting, CSD could be calculated with much higher accuracy as done with the traditional method because distance dependence of the spatial potential patterns was explicitly taken into consideration in our method. Average CSD distribution of the neocortical action potentials was calculated and spatial decay constant of the dendritic trees was determined by applying our new method.

A computer model of field potential responses for the study of short-term plasticity in hippocampus

Activity-dependent synaptic plasticity has important implications for network function. The previously developed model of the hippocampal CA1 area, which contained pyramidal cells (PC) and two types of interneurons involved in feed-forward and recurrent inhibition, respectively, and received synaptic inputs from CA3 neurons via the Schaffer collaterals, was enhanced by incorporating dynamic synaptic connections capable of changing their weights depending on presynaptic activation history. The model output was presented as field potentials, which were compared with those derived experimentally. The parameters of Schaffer collateral-PC excitatory model synapse were determined, with which the model successfully reproduced the complicated dynamics of train-stimulation sequential potentiation/depression observed in experimentally recorded field responses. It was found that the model better reproduces the time course of experimental field potentials if the inhibitory synapses on PC are also made dynamic, with expressed properties of frequency-dependent depression. This finding supports experimental evidence that these synapses are subject to activity-dependent depression. The model field potentials in response to various randomly generated and real (derived from recorded CA3 unit activity) long stimulating trains were calculated, illustrating that short-term plasticity with the observed characteristics could play specific roles in frequency processing in hippocampus and thus providing a new tool for the theoretical study of activity-dependent synaptic plasticity.

A model synapse that incorporates the properties of short- and long-term synaptic plasticity

We propose a general computer model of a synapse, which incorporates mechanisms responsible for the realization of both short- and long-term synaptic plasticity-the two forms of experimentally observed plasticity that seem to be very significant for the performance of neuronal networks. The model consists of a presynaptic part based on the earlier 'double barrier synapse' model, and a postsynaptic compartment which is connected to the presynaptic terminal via a feedback, the sign and magnitude of which depend on postsynaptic Ca(2+) concentration. The feedback increases or decreases the amount of neurotransmitter which is in a ready for release state. The model adequately reproduced the phenomena of short- and long-term plasticity observed experimentally in hippocampal slices for CA3-CA1 synapses. The proposed model may be used in the investigation of certain real synapses to estimate their physiological parameters, and in the construction of realistic neuronal networks.

NMDA and AMPA receptors contribute to the nicotinic cholinergic excitation of CA1 interneurons in the rat hippocampus

In the hippocampus, glutamatergic inputs to pyramidal neurons and interneurons are modulated by alpha7* and alpha3beta4* nicotinic acetylcholine receptors (nAChRs), respectively, present in glutamatergic neurons. This study examines how nicotinic AMPA, and NMDA receptor nAChR activities are integrated to regulate the excitability of CA1 stratum radiatum (SR) interneurons in rat hippocampal slices. At resting membrane potentials and in the presence of extracellular Mg2+ (1 mM), nicotinic agonists triggered in SR interneurons excitatory postsynaptic currents (EPSCs) that had two components: one mediated by AMPA receptors, and the other by NMDA receptors. As previously shown, nicotinic agonist-triggered EPSCs resulted from glutamate released by activation of alpha3beta4* nAChRs in glutamatergic neurons/fibers synapsing directly onto the neurons under study. The finding that CNQX caused more inhibition of nicotinic agonist-triggered EPSCs than expected from the blockade of postsynaptic AMPA receptors indicated that this nicotinic response also depended on the AMPA receptor activity in the glutamatergic neurons synapsing onto the interneuron under study. Nicotinic agonists always triggered action potentials in CA1 SR interneurons. In most interneurons, these action potentials resulted from activation of somatodendritic AMPA receptors and alpha7* nAChRs. In interneurons expressing somatodendritic alpha4beta2* nAChRs, activation of these receptors caused sufficient membrane depolarization to remove the Mg2+-induced block of somatodendritic NMDA receptors; in these neurons, nicotinic agonist-triggered action potentials were partially dependent on NMDA receptor activation. Removing extracellular Mg2+ or clamping the neuron at positive membrane potentials revealed the existence of a tonic NMDA current in SR interneurons that was unaffected by nAChR activation or inhibition. Thus integration of the activities of nAChRs, NMDA, and AMPA receptors in different compartments of CA1 neurons contributes to the excitability of CA1 SR interneurons.