Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

Synchrony in Networks of Type 2 Interneurons Is More Robust to Noise with Hyperpolarizing Inhibition Compared to Shunting Inhibition in Both the Stochastic Population Oscillator and the Coupled Oscillator Regimes

Synchronization in the gamma band (25-150 Hz) is mediated by PV+ inhibitory interneurons, and evidence is accumulating for the essential role of gamma oscillations in cognition. Oscillations can arise in inhibitory networks via synaptic interactions between individual oscillatory neurons (mean-driven) or via strong recurrent inhibition that destabilizes the stationary background firing rate in the fluctuation-driven balanced state, causing an oscillation in the population firing rate. Previous theoretical work focused on model neurons with Hodgkin's Type 1 excitability (integrators) connected by current-based synapses. Here we show that networks comprised of simple Type 2 oscillators (resonators) exhibit a supercritical Hopf bifurcation between synchrony and asynchrony and a gradual transition via cycle skipping from coupled oscillators to stochastic population oscillator (SPO), as previously shown for Type 1. We extended our analysis to homogeneous networks with conductance rather than current based synapses and found that networks with hyperpolarizing inhibitory synapses were more robust to noise than those with shunting synapses, both in the coupled oscillator and SPO regime. Assuming that reversal potentials are uniformly distributed between shunting and hyperpolarized values, as observed in one experimental study, converting synapses to purely hyperpolarizing favored synchrony in all cases, whereas conversion to purely shunting synapses made synchrony less robust except at very high conductance strengths. In mature neurons the synaptic reversal potential is controlled by chloride cotransporters that control the intracellular concentrations of chloride and bicarbonate ions, suggesting these transporters as a potential therapeutic target to enhance gamma synchrony and cognition.

Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair

Due to its complex and multifaceted nature, developing effective treatments for epilepsy is still a major challenge. To deal with this complexity we introduce the concept of degeneracy to the field of epilepsy research: the ability of disparate elements to cause an analogous function or malfunction. Here, we review examples of epilepsy-related degeneracy at multiple levels of brain organisation, ranging from the cellular to the network and systems level. Based on these insights, we outline new multiscale and population modelling approaches to disentangle the complex web of interactions underlying epilepsy and to design personalised multitarget therapies.

Non-monotonic effects of GABAergic synaptic inputs on neuronal firing

GABA is generally known as the principal inhibitory neurotransmitter in the nervous system, usually acting by hyperpolarizing membrane potential. However, GABAergic currents sometimes exhibit non-inhibitory effects, depending on the brain region, developmental stage or pathological condition. Here, we investigate the diverse effects of GABA on the firing rate of several single neuron models, using both analytical calculations and numerical simulations. We find that GABAergic synaptic conductance and output firing rate exhibit three qualitatively different regimes as a function of GABA reversal potential, EGABA: monotonically decreasing for sufficiently low EGABA (inhibitory), monotonically increasing for EGABA above firing threshold (excitatory); and a non-monotonic region for intermediate values of EGABA. In the non-monotonic regime, small GABA conductances have an excitatory effect while large GABA conductances show an inhibitory effect. We provide a phase diagram of different GABAergic effects as a function of GABA reversal potential and glutamate conductance. We find that noisy inputs increase the range of EGABA for which the non-monotonic effect can be observed. We also construct a micro-circuit model of striatum to explain observed effects of GABAergic fast spiking interneurons on spiny projection neurons, including non-monotonicity, as well as the heterogeneity of the effects. Our work provides a mechanistic explanation of paradoxical effects of GABAergic synaptic inputs, with implications for understanding the effects of GABA in neural computation and development.

Effects of brain-derived neurotrophic factor and noise on transitions in temporal lobe epilepsy in a hippocampal network

Brain-derived neurotrophic factor (BDNF) has recently been implicated in the modulation of receptor activation leading to dynamic state transitions in temporal lobe epilepsy (TLE). In addition, the crucial role of neuronal noise in these transitions has been studied in electrophysiological experiments. However, the precise role of these factors during seizure generation in TLE is not known. Building on a previously proposed model of an epileptogenic hippocampal network, we included the actions of BDNF-regulated receptors and intrinsic noise. We found that the effects of both BDNF and noise can increase the activation of N-methyl-D-aspartate receptors leading to excessive C a 2 + flux, which induces abnormal fast spiking and bursting. Our results indicate that the combined effects have a strong influence on the seizure-generating network, resulting in higher firing frequency and amplitude. As correlations between firing increase, the synchronization of the entire network increases, a marker of the ictogenic transitions from normal to seizures-like dynamics. Our work on the effects of BDNF dynamics in a noisy environment might lead to an improved model-based understanding of the pathological mechanisms in TLE.

Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells

In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G_i-max) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G_i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G_i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G_i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

Immunostaining of Biocytin-filled and Processed Sections for Neurochemical Markers

Electrophysiological recordings of cells using the patch clamp technique have allowed for the identification of different neuronal types based on firing patterns. The inclusion of biocytin/neurobiotin in the recording electrode permits post-hoc recovery of morphological details, which are necessary to determine the dendritic arborization and the regions targeted by the axons of the recorded neurons. However, given the presence of morphologically similar neurons with distinct neurochemical identities and functions, immunohistochemical staining for cell-type-specific proteins is essential to definitively identify neurons. To maintain network connectivity, brain sections for physiological recordings are prepared at a thickness of 300 µm or greater. However, this thickness often hinders immunohistological postprocessing due to issues with antibody penetration, necessitating the resectioning of the tissue. Resectioning of slices is a challenging art, often resulting in the loss of tissue and morphology of the cells from which electrophysiological data was obtained, rendering the data unusable. Since recovery of morphology would limit data loss and guide in the selection of neuronal markers, we have adopted a strategy of recovering cell morphology first, followed by secondary immunostaining. We introduce a practical approach to biocytin filling during physiological recordings and subsequent serial immunostaining for the recovery of morphology, followed by the restaining of sections to determine the neurochemical identity. We report that sections that were filled with biocytin, fixed with paraformaldehyde (PFA), stained, and coverslipped can be removed and restained with a second primary antibody days later. This restaining involves the removal of the coverslip, the washing of sections in a buffer solution, and the incubation of primary and secondary antibodies to reveal the neurochemical identity. The method is advantageous for eliminating data loss due to an inability to recover morphology and for narrowing down the neurochemical markers to be tested based on morphology.

Dentate cannabinoid-sensitive interneurons undergo unique and selective strengthening of mutual synaptic inhibition in experimental epilepsy

Altered inhibition is a salient feature of hippocampal network reorganization in epilepsy. Hippocampal pyramidal cells and dentate granule cells show specific reduction in cannabinoid receptor type 1 (CB1R)-sensitive GABAergic inputs in experimental epilepsy. In the dentate gyrus, CB1Rs regulate synaptic release from accommodating interneurons (AC-INs) with adapting firing characteristics and axonal projections in the molecular layer, but not from fast-spiking basket cells (FS-BCs). However, it is not known whether the intrinsic physiology and synaptic inhibition of AC-INs responsible for CB1R-sensitive inhibition is altered in epilepsy. Using the pilocarpine-induced status epilepticus (SE) model of epilepsy, we find that the basic physiological characteristics of AC-INs in epileptic rats are not different from age-matched controls. In paired interneuronal recordings, the amplitude of unitary inhibitory synaptic currents (uIPSCs) between AC-INs doubled after SE. Non-stationary noise analysis revealed that the post-SE strengthening of synapses between AC-INs resulted from an increase in postsynaptic receptors. Baseline synaptic release and CB1R antagonist enhancement of release at synapses between AC-INs were not different between control and post-SE rats. Additionally, uIPSC amplitude in FS-BCs to AC-INs pairs was unchanged after SE indicating input-specific microcircuit alterations in inhibitory inputs to AC-INs. At the network level, AC-INs showed no reduction in spontaneous and miniature inhibitory synaptic current (sIPSC or mIPSC) frequency or amplitude after SE. However, AC-IN mIPSC amplitude was persistently enhanced in post-SE and epileptic rats. CB1R agonist reduced the amplitude and suppressed a greater proportion of sIPSCs in AC-INs from post-SE and epileptic rats demonstrating a novel, cell-type specific increase in CB1R-sensitive inhibition of AC-INs after SE. This unique post-SE strengthening of inhibition between AC-INs could lead to activity-dependent suppression of AC-IN firing and compromise dentate CB1R-sensitive inhibition in epilepsy.

Functional Reduction in Cannabinoid-Sensitive Heterotypic Inhibition of Dentate Basket Cells in Epilepsy: Impact on Network Rhythms

Strong perisomatic inhibition by fast-spiking basket cells (FS-BCs) regulates dentate throughput. Homotypic FS-BC interconnections that support gamma oscillations, and heterotypic inputs from diverse groups of interneurons that receive extensive neurochemical regulation, together, shape FS-BC activity patterns. However, whether seizures precipitate functional changes in inhibitory networks and contribute to abnormal network activity in epilepsy is not known. In the first recordings from dentate interneuronal pairs in a model of temporal lobe epilepsy, we demonstrate that status epilepticus (SE) selectively compromises GABA release at synapses from dentate accommodating interneurons (AC-INs) to FS-BCs, while efficacy of homotypic FS-BC synapses is unaltered. The functional decrease in heterotypic cannabinoid receptor type 1 (CB₁R)-sensitive inhibition of FS-BCs resulted from enhanced baseline GABA_B-mediated suppression of synaptic release after SE. The frequency of CB₁R-sensitive inhibitory synaptic events in FS-BCs was depressed early after SE induction and remained reduced in epileptic rats. In biologically based simulations of heterogeneous inhibitory networks and excitatory-inhibitory cell networks, experimentally identified decrease in reliability of AC-IN to FS-BCs synaptic release reduced theta power and theta-gamma coupling and enhanced gamma coherence. Thus, the experimentally identified functional reduction in heterotypic inhibition of FS-BCs can contribute to compromised network oscillations in epilepsy and could precipitate memory and cognitive co-morbidities.

Homeostatic regulation of KCC2 activity by the zinc receptor mZnR/GPR39 during seizures

The aim of this study was to investigate the role of the synaptic metabotropic zinc receptor mZnR/GPR39 in physiological adaptation to epileptic seizures. We previously demonstrated that synaptic activation of mZnR/GPR39 enhances inhibitory drive in the hippocampus by upregulating neuronal K(+)/Cl(-) co-transporter 2 (KCC2) activity. Here, we first show that mZnR/GPR39 knockout (KO) adult mice have dramatically enhanced susceptibility to seizures triggered by a single intraperitoneal injection of kainic acid, when compared to wild type (WT) littermates. Kainate also substantially enhances seizure-associated gamma oscillatory activity in juvenile mZnR/GPR39 KO hippocampal slices, a phenomenon that can be reproduced in WT tissue by extracellular Zn(2+) chelation. Importantly, kainate-induced synaptic Zn(2+) release enhances surface expression and transport activity of KCC2 in WT, but not mZnR/GPR39 KO hippocampal neurons. Kainate-dependent upregulation of KCC2 requires mZnR/GPR39 activation of the Gαq/phospholipase C/extracellular regulated kinase (ERK1/2) signaling cascade. We suggest that mZnR/GPR39-dependent upregulation of KCC2 activity provides homeostatic adaptation to an excitotoxic stimulus by increasing inhibition. As such, mZnR/GPR39 may provide a novel pharmacological target for dampening epileptic seizure activity.

Dentate total molecular layer interneurons mediate cannabinoid-sensitive inhibition

Activity of the dentate gyrus, which gates information flow to the hippocampus, is under tight inhibitory regulation by interneurons with distinctive axonal projections, intrinsic and synaptic characteristics and neurochemical identities. Total molecular layer cells (TML-Cs), a class of morphologically distinct GABAergic neurons with axonal projections across the molecular layer, are among the most frequent interneuronal type in the dentate subgranular region. However, little is known about their synaptic and neurochemical properties. We demonstrate that synapses from morphologically identified TML-Cs to dentate interneurons are characterized by low release probability, facilitating short-term dynamics and asynchronous release. TML-Cs consistently show somatic and axonal labeling for the cannabinoid receptor type 1 (CB₁R) yet fail to express cholecystokinin (CCK) indicating their distinctive neurochemical identity. In paired recordings, the release probability at synapses between TML-Cs was increased by the CB₁R antagonist AM251, demonstrating baseline endocannabinoid regulation of TML-C synapses. Apart from defining the synaptic and neurochemical features of TML-Cs, our findings reveal the morphological identity of a class of dentate CB₁R-positive neurons that do not express CCK. Our findings indicate that TML-Cs can mediate cannabinoid sensitive feed-forward and feedback inhibition of dentate perforant path inputs. © 2015 The Authors Hippocampus Published by Wiley Periodicals, Inc.

Toll-like receptor 4 enhancement of non-NMDA synaptic currents increases dentate excitability after brain injury

Concussive brain injury results in neuronal degeneration, microglial activation and enhanced excitability in the hippocampal dentate gyrus, increasing the risk for epilepsy and memory dysfunction. Endogenous molecules released during injury can activate innate immune responses including toll-like receptor 4 (TLR4). Recent studies indicate that immune mediators can modulate neuronal excitability. Since non-specific agents that reduce TLR4 signaling can limit post-traumatic neuropathology, we examined whether TLR4 signaling contributes to early changes in dentate excitability after brain injury. Concussive brain injury caused a transient increase in hippocampal TLR4 expression within 4h, which peaked at 24h. Post-injury increase in TLR4 expression in the dentate gyrus was primarily neuronal and persisted for one week. Acute, in vitro treatment with TLR4 ligands caused bidirectional modulation of dentate excitability in control and brain-injured rats, with a reversal in the direction of modulation after brain injury. TLR4 antagonists decreased, and agonist increased, afferent-evoked dentate excitability one week after brain injury. NMDA receptor antagonist did not occlude the ability of LPS-RS, a TLR4 antagonist, to decrease post-traumatic dentate excitability. LPS-RS failed to modulate granule cell NMDA EPSCs but decreased perforant path-evoked non-NMDA EPSC peak amplitude and charge transfer in both granule cells and mossy cells. Our findings indicate an active role for TLR4 signaling in early post-traumatic dentate hyperexcitability. The novel TLR4 modulation of non-NMDA glutamatergic currents, identified herein, could represent a general mechanism by which immune activation influences neuronal excitability in neurological disorders that recruit sterile inflammatory responses.

Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

Gamma frequency oscillations have been proposed to contribute to memory formation and retrieval. Fast-spiking basket cells (FS-BCs) are known to underlie development of gamma oscillations. Fast, high amplitude GABA synapses and gap junctions have been suggested to contribute to gamma oscillations in FS-BC networks. Recently, we identified that, apart from GABAergic synapses, FS-BCs in the hippocampal dentate gyrus have GABAergic currents mediated by extrasynaptic receptors. Our experimental studies demonstrated two specific changes in FS-BC GABA currents following experimental seizures [Yu et al., J. Neurophysiol. 109, 1746 (2013)]: increase in the magnitude of extrasynaptic (tonic) GABA currents and a depolarizing shift in GABA reversal potential (E(GABA)). Here, we use homogeneous networks of a biophysically based model of FS-BCs to examine how the presence of extrasynaptic GABA conductance (g(GABA-extra)) and experimentally identified, seizure-induced changes in g(GABA-extra) and E(GABA) influence network activity. Networks of FS-BCs interconnected by fast GABAergic synapses developed synchronous firing in the dentate gamma frequency range (40-100 Hz). Systematic investigation revealed that the biologically realistic range of 30 to 40 connections between FS-BCs resulted in greater coherence in the gamma frequency range when networks were activated by Poisson-distributed dendritic synaptic inputs rather than by homogeneous somatic current injections, which were balanced for FS-BC firing frequency in unconnected networks. Distance-dependent conduction delay enhanced coherence in networks with 30-40 FS-BC interconnections while inclusion of gap junctional conductance had a modest effect on coherence. In networks activated by somatic current injections resulting in heterogeneous FS-BC firing, increasing g(GABA-extra) reduced the frequency and coherence of FS-BC firing when E(GABA) was shunting (-74 mV), but failed to alter average FS-BC frequency when E(GABA) was depolarizing (-54 mV). When FS-BCs were activated by biologically based dendritic synaptic inputs, enhancing g(GABA-extra) reduced the frequency and coherence of FS-BC firing when E(GABA) was shunting and increased average FS-BC firing when E(GABA) was depolarizing. Shifting E(GABA) from shunting to depolarizing potentials consistently increased network frequency to and above high gamma frequencies (>80 Hz). Since gamma oscillations may contribute to learning and memory processing [Fell et al., Nat. Neurosci. 4, 1259 (2001); Jutras et al., J. Neurosci. 29, 12521 (2009); Wang, Physiol. Rev. 90, 1195 (2010)], our demonstration that network oscillations are modulated by extrasynaptic inhibition in FS-BCs suggests that neuroactive compounds that act on extrasynaptic GABA receptors could impact memory formation by modulating hippocampal gamma oscillations. The simulation results indicate that the depolarized FS-BC GABA reversal, observed after experimental seizures, together with enhanced spillover extrasynaptic GABA currents are likely to promote generation of focal high frequency activity associated with epileptic networks.

Introduction to focus issue: rhythms and dynamic transitions in neurological disease: modeling, computation, and experiment

Rhythmic neuronal oscillations across a broad range of frequencies, as well as spatiotemporal phenomena, such as waves and bumps, have been observed in various areas of the brain and proposed as critical to brain function. While there is a long and distinguished history of studying rhythms in nerve cells and neuronal networks in healthy organisms, the association and analysis of rhythms to diseases are more recent developments. Indeed, it is now thought that certain aspects of diseases of the nervous system, such as epilepsy, schizophrenia, Parkinson's, and sleep disorders, are associated with transitions or disruptions of neurological rhythms. This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases.