Interneuronal gamma oscillations in hippocampus via adaptive exponential integrate-and-fire neurons

International audienceFast neuronal oscillations in gamma frequencies are observed in neocortex and hippocampus during essential arousal behaviors. Through a four-variable Hodgkin-Huxley type model, Wang and Buzsáki have numerically demonstrated that such rhythmic activity can emerge from a random network of GABAergic interneurons via minimum synaptic inputs. In this case, the intrinsic neuronal characteristics and network structure act as the main drive of the rhythm. We investigate inhibitory network synchrony with a low complexity, two-variable adap-tive exponential integrate-and-fire (AdEx) model, whose parameters possess strong physiological relevances, and provide a comparison with the two-variable Izhike-vich model and Morris-Lecar model. Despite the simplicity of these three models, AdEx model shares two important results with the previous biophysically detailed Hodgkin-Huxley type model: the minimum number of synaptic input necessary to initiate network gamma-band rhythms remains the same, and this number is weakly dependent on the network size. Meanwhile, Izhikevich and Morris-Lecar neurons demonstrate different results in this study. We further investigate the necessary neuronal, synaptic and connectivity properties, including gap junctions and shunting inhibitions, for AdEx model leading to sparse and random network synchrony in gamma rhythms and nested theta gamma rhythms. These findings suggest a computationally more tractable framework for studying synchronized networks in inducing cerebral gamma band activities

Propofol-induced GABAergic Tonic Inhibition Diminishes α-rhythms and Induces δ-rhythms in neuronal populations

Anaesthetic agents such as propofol are known to have an effect on both synaptic and extra-synaptic receptors. On the one hand, binding of propofol to GABA A synaptic receptors induces a phasic inhibition, as opposed to tonic inhibition which seems mainly induced by binding to extra-synaptic receptors. On the second hand, under aneasthesia, an increase in amount of slow oscillations, mainly delta (0-4Hz), concurrent to a decrease of alpha oscillations (8-12Hz), is observed in EEG recordings of occipital areas in most mammals including humans. The latter observation cannot be explained by sole phasic inhibition. Therefore, we propose to investigate, through numer- ical simulations, the role of tonic inhibition in the increase (in amount) of slow oscillations under propofol anaesthesia. To account for the biological realism of our simulations, the cortical model includes two neuronal populations, one excitatory modeled by Type I Leaky integrate-and-fire neurons, one inhibitory modeled by Type II Morris-Lecar neurons, the stimulations are noisy, and the intrinsic cellular properties heterogeneous. The cells are connected through exponential conductance-based synapses. We show that, in presence of tonic inhibition, 1) the oscillation frequency of the network decreases as well as subthreshold oscillations, inducing delta-rhythms in EEG-like recordings; 2) simulatneously, the amount of alpha-rhythms decreases supporting experimental evidence about the role of tonic inhibition

Tonic inhibition mediates a synchronisation enhancement during propofol anaesthesia in a network of hippocampal interneurons: a modelling study

Neural oscillations are thought to be correlated with the execution of cognitive functions. Indeed, gamma oscillations are often recorded in functionally-coupled brain regions for cooperation during memory tasks, and this rhythmic behaviour is thought to result from synaptic GABAergic interactions between in-terneurons. Interestingly, GABAergic synaptic and ex-trasynaptic receptors have been shown to be the preferred target of the most commonly used anaesthetic agents. We present a in-depth computational study of the action of anaesthesia on neural oscillations by introducing a new mathematical model which takes into account the four main effects of the anaesthetic agent propofol on GABAergic hippocampal interneurons. These are: the action on synaptic GABA A receptors, which includes an amplification and an extension of the duration of the synaptic currents, as well as an increase in current baseline, and the action on extrasynaptic GABA A receptors mediating a tonic inhibitory current. Our results indicate that propofol-mediated tonic inhibition contributes to an unexpected enhancement of synchro-nisation in the activity of a network of hippocampal interneurons. We speculate that this enhanced synchro-nisation could provide a possible mechanism supporting the occurrence of intraoperative awareness and explicit memory formationunder general anaesthesia, by transiently facilitating the communication between brain structures which should supposedly be not allowed to do so when anaesthetised

Reactivation, Replay, and Preplay: How It Might All Fit Together

Sequential activation of neurons that occurs during “offline” states, such as sleep or awake rest, is correlated with neural sequences recorded during preceding exploration phases. This so-called reactivation, or replay, has been observed in a number of different brain regions such as the striatum, prefrontal cortex, primary visual cortex and, most prominently, the hippocampus. Reactivation largely co-occurs together with hippocampal sharp-waves/ripples, brief high-frequency bursts in the local field potential. Here, we first review the mounting evidence for the hypothesis that reactivation is the neural mechanism for memory consolidation during sleep. We then discuss recent results that suggest that offline sequential activity in the waking state might not be simple repetitions of previously experienced sequences. Some offline sequential activity occurs before animals are exposed to a novel environment for the first time, and some sequences activated offline correspond to trajectories never experienced by the animal. We propose a conceptual framework for the dynamics of offline sequential activity that can parsimoniously describe a broad spectrum of experimental results. These results point to a potentially broader role of offline sequential activity in cognitive functions such as maintenance of spatial representation, learning, or planning

Effects of tonic inhibition on a cortical neuronal population: implications for general anesthesia under propofol

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Study of GABAergic extra-synaptic tonic inhibition in single neurons and neural populations by traversing neural scales: application to propofol-induced anaesthesia

International audienceAnaesthetic agents are known to affect extra-synaptic GABAergic recep- tors, which induce tonic inhibitory currents. Since these receptors are very sensitive to small concentrations of agents, they are supposed to play an important role in the underlying neural mechanism of general anaesthesia. Moreover anaethetic agents modulate the encephalographic activity (EEG) of patients and hence show an ef- fect on neural populations. To understand better the tonic inhibition effect in single neurons on neural populations and hence how it affects the EEG, the work consid- ers single neurons and neural populations in a steady-state and studies numerically and analytically the modulation of its firing rate and nonlinear gain with respect to different levels of tonic inhibition. We consider populations of both type-I (Leaky Integrate-and-Fire model) and type-II (Morris-Lecar model) neurons. The work re- veals a strong subtractive and divisive effect of tonic inhibition in type-I neurons, i.e. a shift of the firing rate to higher excitation levels accompanied by a change of the nonlinear gain. Tonic inhibition shortens the excitation window of type-II neu- rons and their populations while retaining the nonlinear gain. To bridge the single neuron description to the population description analytically, a recently proposed sta- tistical approach is employed which allows to derive new analytical expressions for the population firing rate for type-I neurons. In addition, the work derives a novel transfer function for type-I neurons as considered in neural mass models and studies briefly the interaction of synaptic and extra-synaptic inhibition. The gained results are interpreted in the context of recent experimental findings under propofol-induced anaesthesia

Modelling the effects of propofol on neuronal synchronization in network of interneurons

International audiencePropofol is a chemical agent commonly used as an intravenous general anesthetic. At the cellular level, this short-acting ananesthetic positively modulates GABAergic inhibitory activity by targeting GABA-A receptors [1]. This type of receptors are widespread in the brain and can be present both within synaptic clefts, as well as on extrasynaptic locations along the dendrites and neuron membrane where they are responsible for tonic inhibition. At the macroscopic level of SEEG (deep Stereographic-Electro Encephalogram) or EEG (Electro Encephalogram) recordings, one observes, with certain doses of propofol, a paradoxical excitation phenomenon [2] the generation mechanisms of which are not clearly understood. In this study, we suggest a potential mechanism for the appearance of paradoxical excitation occurring under propofol-induced general anaesthesia. We show, with a model network of Hodgkin-Huxley neurons, that tonic inhibition – induced by the binding of propofol to extra-synaptic receptors – together with an increase of the synaptic time constant within an certain range [3] can account for the phenomenon of paradoxical excitation. However, changes in the gain (or conductance) of the synaptic inhibition do not correspond to a sudden increase in neuronal population firing rate nor synchrony as described in the experiments [3]. The action of propofol on extrasynaptic GABAergic receptors was modelled by varying the conductance g ton of a tonic current in the form $I ton = g ton (V − E ton)$ as described in [4]. Figure 1 shows the evolution of the neuronal population firing rate and the coherence (or synchrony) of the network activity as the tonic inhibition and the synaptic conductance vary. The plots are given for different values of the synaptic time constants. The increase of these three variables, synaptic time constant and conductance, and tonic conductance reflect an increase in propofol doses

Stability conditions of Hopfield ring networks with discontinuous piecewise-affine activation functions

International audienceRing networks, a particular form of Hopfield neural networks, can be used in computational neurosciences in order to model the activity of place cells or head-direction cells. The behaviour of these models is highly dependent on their recurrent synaptic connectivity matrix and on individual neurons' activation function, which must be chosen appropriately to obtain physiologically meaningful conclusions. In this article, we propose some simpler ways to tune this synaptic connectivity matrix compared to existing literature so as to achieve stability in a ring attractor network with a piece-wise affine activation functions, and we link these results to the possible stable states the network can converge to

Mathematical modelling of ICAN-mediated persistent firing in hippocampal neurons

International audiencePersistent neural activity has been the focus of neuroscientific research since it was first associated with complex cognitive behaviours. In particular, persistent firing has long been thought to be the neural mechanisms underlying short-term memory encoding and storage [1]. This activity is often elicited by short transient stimuli that have to be retained in memory for long delay periods, in the order of several seconds, after the original stimulus disappeared. In this scenario, the brain stores information for future execution of action depending on that information.Persistent activity elicited in a recurrent network comprising strong excitation in the local circuit has been extensively described in the literature (for a review see [2]). However, recent findings have shown that memory can also be encoded in brain regions which do not display such recurrent connection topology, including the CA1 hippocampal area [3]. Emerging studies are pointing towards intrinsic neural mechanisms independent of synaptic connections, as a complementary mechanism for the maintenance of persistent activity in the hippocampus [4]. These include various cytoplasmic currents flowing through the membrane, characterised by slow ion channel kinetics, and particular neurotransmitter modulation. Our work investigates persistent firing activity in networks of hippocampal neurons, elicited by leveraging intrinsic currents rather than network dynamics.Building on previous findings [5], we model a hippocampal pyramidal neuron using the Hodgkin-Huxley model, with low-threshold Ca2+ currents governing the inward flow of calcium ions in the cell membrane. The intracellular calcium concentration mediates the opening of calcium-activated non-specific (CAN) ion channels [6], which causes an increase in the ionic flow through the cell membrane. Therefore the CAN channels equip the neuron with an after-spike depolarisation mechanism, which enables it to emit action potentials in the absence of external stimulation. Given a transient 250ms 200pA current injection, the neuron is capable of eliciting and maintaining persistent activity with a firing rate of 6Hz for long delay periods (~30s). Moreover, this behaviour is in accord with that displayed in neural recordings of hippocampal slice preparations [4]. Connecting these persistent firing neurons in a network comprising strong local excitation yields a wide range of behaviours depending on the interaction between CAN and synaptic currents. Indeed, our network model is capable of displaying rhythmic behaviour in the form of short synchronised bursts with intra-burst frequencies of 20-40Hz and inter-burst frequencies of 3Hz. These results hint towards a possible mechanism for the generation of memory-related oscillatory activity in the hippocampus

A detailed anatomical and mathematical model of the hippocampal formation for the generation of sharp-wave ripples and theta-nested gamma oscillations

International audienceThe mechanisms underlying the broad variety of oscillatory rhythms measured in the hippocampus during the sleep-wake cycle are not yet fully understood. In this article, we propose a computational model of the hippocampal formation based on a realistic topology and synaptic connectivity, and we analyze the effect of different changes on the network, namely the variation of synaptic conductances, the variations of the CAN channel conductance and the variation of inputs. By using a detailed simulation of intracerebral recordings, we show that this model is able to reproduce both the theta-nested gamma oscillations that are seen in awake brains and the sharp-wave ripple complexes measured during slow-wave sleep. The results of our simulations support the idea that the functional connectivity of the hippocampus, modulated by the sleep-wake variations in Acetylcholine concentration, is a key factor in controlling its rhythms