Contrasting roles of axonal (pyramidal cell) and dendritic (interneuron) electrical coupling in the generation of neuronal network oscillations

Electrical coupling between pyramidal cell axons, and between interneuron dendrites, have both been described in the hippocampus. What are the functional roles of the two types of coupling? Interneuron gap junctions enhance synchrony of γ oscillations (25-70 Hz) in isolated interneuron networks and also in networks containing both interneurons and principal cells, as shown in mice with a knockout of the neuronal (primarily interneuronal) connexin36. We have recently shown that pharmacological gap junction blockade abolishes kainate-induced γ oscillations in connexin36 knockout mice; without such gap junction blockade, γ oscillations do occur in the knockout mice, albeit at reduced power compared with wild-type mice. As interneuronal dendritic electrical coupling is almost absent in the knockout mice, these pharmacological data indicate a role of axonal electrical coupling in generating the γ oscillations. We construct a network model of an experimental γ oscillation, known to be regulated by both types of electrical coupling. In our model, axonal electrical coupling is required for the γ oscillation to occur at all; interneuron dendritic gap junctions exert a modulatory effect

Zero-lag long-range synchronization via dynamical relaying

We show that simultaneous synchronization between two delay-coupled oscillators can be achieved by relaying the dynamics via a third mediating element, which surprisingly lags behind the synchronized outer elements. The zero-lag synchronization thus obtained is robust over a considerable parameter range. We substantiate our claims with experimental and numerical evidence of these synchronization solutions in a chain of three coupled semiconductor lasers with long inter-element coupling delays. The generality of the mechanism is validated in a neuronal model with the same coupling architecture. Thus, our results show that synchronized dynamical states can occur over long distances through relaying, without restriction by the amount of delay.Comment: 10 pages, 4 figure

A γ-β frequency transition generated by inter-areal communication in the hippocampus in vitro

Gamma oscillations are generated in area CA3 of the hippocampus both in vitro and in vivo (Fisahn et al., 1998; Csicsvari et al., 2003). Here we present experimental and network simulation data to elucidate the mechanism of the generation of CA3-driven gamma and beta oscillations in area CA1. (1) The frequency of area CA1 output generated by gamma input from area CA3 was dependent on the degree of recruitment of CA1 principal cells. Passive involvement of area CA1 principal cells resulted in a gamma frequency oscillation. Active involvement of CA1 principal cells transformed this gamma oscillation into one at beta frequencies. (2) This beta oscillation in area CA1 was dependent on CA1 recurrent excitation. (3) It was also dependent on the temporal relationship between feedforward excitation of CA1 interneurons (by CA3 output) and feedback excitation of CA1 interneurons (by CA1 output). That is, the network beta oscillation in area CA1 depended on doublet firing of certain interneurons driven by area CA3. (4) The interneuron doublet rate during beta corresponded to whether or not dendrites are oriented horizontally or vertically: Interneurons with vertically oriented dendrites (eg. basket cells and - to a lesser extent - bistratified cells, all receiving input from CA3) fired considerably more doublets than interneurons with horizontally oriented dendrites (horizontal alveus cells or olm cells) which are not contacted by area CA3 and hardly ever fired doublets during beta. Taken together the findings demonstrate that different interneurons can serve different purposes during a given network oscillation, that single interneuron subtypes can mediate multiple network frequencies, and that the frequency of output from a cortical region serves to signal the degree of principal cell recruitment

A γ-β frequency transition generated by inter-areal communication in the hippocampus in vitro

Gamma oscillations are generated in area CA3 of the hippocampus both in vitro and in vivo (Fisahn et al., 1998; Csicsvari et al., 2003). Here we present experimental and network simulation data to elucidate the mechanism of the generation of CA3-driven gamma and beta oscillations in area CA1. (1) The frequency of area CA1 output generated by gamma input from area CA3 was dependent on the degree of recruitment of CA1 principal cells. Passive involvement of area CA1 principal cells resulted in a gamma frequency oscillation. Active involvement of CA1 principal cells transformed this gamma oscillation into one at beta frequencies. (2) This beta oscillation in area CA1 was dependent on CA1 recurrent excitation. (3) It was also dependent on the temporal relationship between feedforward excitation of CA1 interneurons (by CA3 output) and feedback excitation of CA1 interneurons (by CA1 output). That is, the network beta oscillation in area CA1 depended on doublet firing of certain interneurons driven by area CA3. (4) The interneuron doublet rate during beta corresponded to whether or not dendrites are oriented horizontally or vertically: Interneurons with vertically oriented dendrites (eg. basket cells and - to a lesser extent - bistratified cells, all receiving input from CA3) fired considerably more doublets than interneurons with horizontally oriented dendrites (horizontal alveus cells or olm cells) which are not contacted by area CA3 and hardly ever fired doublets during beta. Taken together the findings demonstrate that different interneurons can serve different purposes during a given network oscillation, that single interneuron subtypes can mediate multiple network frequencies, and that the frequency of output from a cortical region serves to signal the degree of principal cell recruitment

Axonal gap junctions between principal neurons: a novel source of network oscillations, and perhaps epileptogenesis

We hypothesized in 1998 that gap junctions might be located between the axons of principal hippocampal neurons, based on the shape of spikelets (fast prepotentials), occurring during gap junction-mediated very fast (to approximately 200 Hz) network oscillations in vitro. More recent electrophysiological, pharmacological and dye-coupling data indicate that axonal gap junctions exist; so far, they appear to be located about 100 microm from the soma, in CA1 pyramidal neurons. Computer modeling and theory predict that axonal gap junctions can lead to very fast network oscillations under three conditions: a) there are spontaneous axonal action potentials; b) the number of gap junctions in the network is neither too low (not less than to approximately 1.5 per cell on average), nor too high (not more than to approximately 3 per cell on average); c) action potentials can cross from axon to axon via gap junctions. Simulated oscillations resemble biological ones, but condition (c) remains to be demonstrated directly. Axonal network oscillations can, in turn, induce oscillatory activity in larger neuronal networks, by a variety of mechanisms. Axonal networks appear to underlie in vivo ripples (to approximately 200 Hz field potential oscillations superimposed on physiological sharp waves), to drive gamma (30-70 Hz) oscillations that appear in the presence of carbachol, and to initiate certain types of ictal discharge. If axonal gap junctions are important for seizure initiation in humans, there could be practical consequences for antiepileptic therapy: at least one gap junction-blocking compound, carbenoxolone, is already in clinical use (for treatment of ulcer disease), and it crosses the blood-brain barrier

GABA-enhanced collective behavior in neuronal axons underlies persistent gamma-frequency oscillations

Gamma (30–80 Hz) oscillations occur in mammalian electroencephalogram in a manner that indicates cognitive relevance. In vitro models of gamma oscillations demonstrate two forms of oscillation: one occurring transiently and driven by discrete afferent input and the second occurring persistently in response to activation of excitatory metabotropic receptors. The mechanism underlying persistent gamma oscillations has been suggested to involve gap-junctional communication between axons of principal neurons, but the precise relationship between this neuronal activity and the gamma oscillation has remained elusive. Here we demonstrate that gamma oscillations coexist with high-frequency oscillations (>90 Hz). High-frequency oscillations can be generated in the axonal plexus even when it is physically isolated from pyramidal cell bodies. They were enhanced in networks by nonsomatic -aminobutyric acid type A (GABAA) receptor activation, were modulated by perisomatic GABAA receptor-mediated synaptic input to principal cells, and provided the phasic input to interneurons required to generate persistent gamma-frequency oscillations. The data suggest that high-frequency oscillations occurred as a consequence of random activity within the axonal plexus. Interneurons provide a mechanism by which this random activity is both amplified and organized into a coherent network rhythm

A role for fast rhythmic bursting neurons in cortical gamma oscillations in vitro

Basic cellular and network mechanisms underlying gamma frequency oscillations (30–80 Hz) have been well characterized in the hippocampus and associated structures. In these regions, gamma rhythms are seen as an emergent property of networks of principal cells and fast-spiking interneurons. In contrast, in the neocortex a number of elegant studies have shown that specific types of principal neuron exist that are capable of generating powerful gamma frequency outputs on the basis of their intrinsic conductances alone. These fast rhythmic bursting (FRB) neurons (sometimes referred to as "chattering" cells) are activated by sensory stimuli and generate multiple action potentials per gamma period. Here, we demonstrate that FRB neurons may function by providing a large-scale input to an axon plexus consisting of gap-junctionally connected axons from both FRB neurons and their anatomically similar counterparts regular spiking neurons. The resulting network gamma oscillation shares all of the properties of gamma oscillations generated in the hippocampus but with the additional critical dependence on multiple spiking in FRB cells

Genetically altered AMPA-type glutamate receptor kinetics in interneurons disrupt long-range synchrony of gamma oscillation

Gamma oscillations synchronized between distant neuronal populations may be critical for binding together brain regions devoted to common processing tasks. Network modeling predicts that such synchrony depends in part on the fast time course of excitatory postsynaptic potentials (EPSPs) in interneurons, and that even moderate slowing of this time course will disrupt synchrony. We generated mice with slowed interneuron EPSPs by gene targeting, in which the gene encoding the 67-kDa form of glutamic acid decarboxylase (GAD67) was altered to drive expression of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptor subunit GluR-B. GluR-B is a determinant of the relatively slow EPSPs in excitatory neurons and is normally expressed at low levels in γ-aminobutyric acid (GABA)ergic interneurons, but at high levels in the GAD-GluR-B mice. In both wild-type and GAD-GluR-B mice, tetanic stimuli evoked gamma oscillations that were indistinguishable in local field potential recordings. Remarkably, however, oscillation synchrony between spatially separated sites was severely disrupted in the mutant, in association with changes in interneuron firing patterns. The congruence between mouse and model suggests that the rapid time course of AMPA receptor-mediated EPSPs in interneurons might serve to allow gamma oscillations to synchronize over distance

From sensorimotor learning to memory cells in prefrontal and temporal association cortex: A neurocomputational study of disembodiment

Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in “embodied” sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to “disembodiment” (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and “disembodied” working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the “where” question of cortical working memory in terms of distributed APCs and their inner structure, which is, in part, determined by neuroanatomical structure. As the neurocomputational model provides a mechanistic explanation of how memory-related “disembodied” neuronal activity emerges in “embodied” APCs, it may be key to solving aspects of the embodiment debate and eventually to a better understanding of cognitive brain functions