Duplication of a spontaneously active neuron in Aplysia: electrical coupling and effects of a phosphodiesterase inhibitor.

An abdominal ganglion from an Aplysia californica is described, in which cell R15 has anomalously duplicated. The two cells exhibited a high degree of electrical coupling, assuring functional synchrony of output in the cells, which are characterized by a complex firing pattern. Exposure of this ganglion to the phosphodiesterase inhibitor IBMX caused a more altered firing rhythm in one of the cells, as well as an enhanced inhibitory component associated with the coupling potentials between cells, resulting in a loss of synchrony between the two cells.     

Firing coincidences between neighboring retinal ganglion cells: inside information or epiphenomenon?

Retinal ganglion cells often fire impulses in synchrony; is this synchronization an irrelevant by-product of processing shared inputs, or does it encode information? We examined the rate of occurrence of coincident impulses from pairs of ganglion cells responding to stimuli that varied along several dimensions. We find that coincidences convey little if any additional information about simple static stimuli beyond what could be determined from the firing rates of the two cells considered separately. In fact, at least one of the separate cells generally provided a better information channel than the coincidence rate, implying that under these conditions ganglion cells do not employ a strategy of encoding by coincidences.     

Properties of a symmetric pair of serotonin-containing neurones in the cerebral ganglia of Planorbis.

1. There is a bilaterally symmetric pair of large serotonin-containing neurones in the cerebral ganglia of Planorbis corneus. 2. In some animals these neurones are connected by a non-rectifying electrotonic synapse, and fire in synchrony even at prolonged high frequency. In other animals the neurones are not coupled, and fire independently except when driven by common input. Occasionally the coupling is weak. 3. Both coupled and non-coupled serotonin neurones have processes in the major nerve trunks of both buccal ganglia. 4. Synapses are made with many neurones in the buccal ganglia. The serotonin neurones can initiate firing in several motoneurones and thus produce movements of the buccal mass. 5. During spontaneous feeding cycles the input and firing pattern of the serotonin neurones do not bear any obvious relation to the movements of the buccal mass. 6. The data suggest that the serotonin neurones are modulatory cells, altering the level of excitability of buccal ganglion neurones.     

Distribution of correlated spiking events in a population-based approach for Integrate-and-Fire networks

Randomly connected populations of spiking neurons display a rich variety of dynamics. However, much of the current modeling and theoretical work has focused on two dynamical extremes: on one hand homogeneous dynamics characterized by weak correlations between neurons, and on the other hand total synchrony characterized by large populations firing in unison. In this paper we address the conceptual issue of how to mathematically characterize the partially synchronous “multiple firing events” (MFEs) which manifest in between these two dynamical extremes. We further develop a geometric method for obtaining the distribution of magnitudes of these MFEs by recasting the cascading firing event process as a first-passage time problem, and deriving an analytical approximation of the first passage time density valid for large neuron populations. Thus, we establish a direct link between the voltage distributions of excitatory and inhibitory neurons and the number of neurons firing in an MFE that can be easily integrated into population–based computational methods, thereby bridging the gap between homogeneous firing regimes and total synchrony.     

See globally, spike locally: oscillations in a retinal model encode large visual features

We show that coherent oscillations among neighboring ganglion cells in a retinal model encode global topological properties, such as size, that cannot be deduced unambiguously from their local, time-averaged firing rates. Whereas ganglion cells may fire similar numbers of spikes in response to both small and large spots, only large spots evoke coherent high frequency oscillations, potentially allowing downstream neurons to infer global stimulus properties from their local afferents. To determine whether such information might be extracted over physiologically realistic spatial and temporal scales, we analyzed artificial spike trains whose oscillatory correlations were similar to those measured experimentally. Oscillatory power in the upper gamma band, extracted on single-trials from multi-unit spike trains, supported good to excellent size discrimination between small and large spots, with performance improving as the number of cells and/or duration of the analysis window was increased. By using Poisson distributed spikes to normalize the firing rate across stimulus conditions, we further found that coincidence detection, or synchrony, yielded substantially poorer performance on identical size discrimination tasks. To determine whether size encoding depended on contiguity independent of object shape, we examined the total oscillatory activity across the entire model retina in response to random binary images. As the ON-pixel probability crossed the percolation threshold, which marks the sudden emergence of large connected clusters, the total gamma-band activity exhibited a sharp transition, a phenomena that may be experimentally observable. Finally, a reanalysis of previously published oscillatory responses from cat ganglion cells revealed size encoding consistent with that predicted by the retinal model.     

Spatial and temporal correlations of spike trains in frog retinal ganglion cells

For a neuron, firing activity can be in synchrony with that of others, which results in spatial correlation; on the other hand, spike events within each individual spike train may also correlate with each other, which results in temporal correlation. In order to investigate the relationship between these two phenomena, population neurons’ activities of frog retinal ganglion cells in response to binary pseudo-random checker-board flickering were recorded via a multi-electrode recording system. The spatial correlation index (SCI) and temporal correlation index (TCI) were calculated for the investigated neurons. Statistical results showed that, for a single neuron, the SCI and TCI values were highly related—a neuron with a high SCI value generally had a high TCI value, and these two indices were both associated with burst activities in spike train of the investigated neuron. These results may suggest that spatial and temporal correlations of single neuron’s spiking activities could be mutually modulated; and that burst activities could play a role in the modulation. We also applied models to test the contribution of spatial and temporal correlations for visual information processing. We show that a model considering spatial and temporal correlations could predict spikes more accurately than a model does not include any correlation.     

The morphology and coupling of Aplysia bag cells within the abdominal ganglion and in cell culture

The bag cells in the abdominal ganglion of Aplysia californica control egg-laying behavior by releasing a polypeptide (ELH) during an afterdischarge of synchronous action potentials. We have used intracellular injection of Lucifer Yellow to study the morphology and interconnections of the bag cells. These neurosecretory cells are typically multipolar and their processes extend in all directions out from the bag cell clusters into the surrounding connective tissue, where they branch in a complex manner. In some of the dye injection experiments, dye transfer from the injected cell to neighboring cells was observed. Freeze fracture of the bag cell clusters and their surrounding connective tissue revealed numerous gap junctions on bag cell processes within the clusters as well as on more distal processes. We have also examined the morphology and coupling between bag cells in primary culture. As in the intact ganglion, bag cells in culture were found to be multipolar. All pairs of bag cells whose somata or processes had formed contacts in culture were electrically coupled. The strongest coupling was observed between pairs of cells whose somata appeared closely apposed. In these cases transfer of Lucifer Yellow between cells could also be observed. It is therefore likely that the synchrony of bag cell action potentials during a bag cell afterdischarge is a result of coupling between individual cells in the bag cell cluster.     

Establishing a Statistical Link between Network Oscillations and Neural Synchrony

Pairs of active neurons frequently fire action potentials or “spikes” nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons’ fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron’s firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony.     

Dynamic Range of Vertebrate Retina Ganglion Cells: Importance of Active Dendrites and Coupling by Electrical Synapses

The vertebrate retina has a very high dynamic range. This is due to the concerted action of its diverse cell types. Ganglion cells, which are the output cells of the retina, have to preserve this high dynamic range to convey it to higher brain areas. Experimental evidence shows that the firing response of ganglion cells is strongly correlated with their total dendritic area and only weakly correlated with their dendritic branching complexity. On the other hand, theoretical studies with simple neuron models claim that active and large dendritic trees enhance the dynamic range of single neurons. Theoretical models also claim that electrical coupling between ganglion cells via gap junctions enhances their collective dynamic range. In this work we use morphologically reconstructed multi-compartmental ganglion cell models to perform two studies. In the first study we investigate the relationship between single ganglion cell dynamic range and number of dendritic branches/total dendritic area for both active and passive dendrites. Our results support the claim that large and active dendrites enhance the dynamic range of a single ganglion cell and show that total dendritic area has stronger correlation with dynamic range than with number of dendritic branches. In the second study we investigate the dynamic range of a square array of ganglion cells with passive or active dendritic trees coupled with each other via dendrodendritic gap junctions. Our results suggest that electrical coupling between active dendritic trees enhances the dynamic range of the ganglion cell array in comparison with both the uncoupled case and the coupled case with cells with passive dendrites. The results from our detailed computational modeling studies suggest that the key properties of the ganglion cells that endow them with a large dynamic range are large and active dendritic trees and electrical coupling via gap junctions.     

Stability of two cluster solutions in pulse coupled networks of neural oscillators

Phase response curves (PRCs) have been widely used to study synchronization in neural circuits comprised of pacemaking neurons. They describe how the timing of the next spike in a given spontaneously firing neuron is affected by the phase at which an input from another neuron is received. Here we study two reciprocally coupled clusters of pulse coupled oscillatory neurons. The neurons within each cluster are presumed to be identical and identically pulse coupled, but not necessarily identical to those in the other cluster. We investigate a two cluster solution in which all oscillators are synchronized within each cluster, but in which the two clusters are phase locked at nonzero phase with each other. Intuitively, one might expect this solution to be stable only when synchrony within each isolated cluster is stable, but this is not the case. We prove rigorously the stability of the two cluster solution and show how reciprocal coupling can stabilize synchrony within clusters that cannot synchronize in isolation. These stability results for the two cluster solution suggest a mechanism by which reciprocal coupling between brain regions can induce local synchronization via the network feedback loop.     

Estimating the Strength and Direction of Functional Coupling in the Lamprey Spinal Cord

A method of estimating coupling strength between two neural oscillators based on their spikes trains (Kiemel and Cohen, J. Comput. Neurosci. 5: 267–284, 1998) is tested using simulated data and then applied to experimental data from the central pattern generator (CPG) for swimming in the lamprey. The method is tested using a model of two connectionist oscillators and a model of two endogenously bursting cells. For both models, the method provides useful estimates of the relative strength of coupling in each direction, as well as estimates of total strength. The method is applied to pairs of motor-nerve recordings from isolated 50-segment pieces of spinal cords from adult silver lampreys (Ichthyomyzon unicuspus). The strength and direction of coupling is estimated under control conditions and conditions in which intersegmental coupling between the two recording locations is weakened by hemisections of the spinal cords and/or chambers containing an inhibitory solution that blocks firing in postsynaptic cells. The relevance of these measures in constraining models of the CPG is discussed.     

Gap junctions with amacrine cells provide a feedback pathway for ganglion cells within the retina.

In primates, one type of retinal ganglion cell, the parasol cell, makes gap junctions with amacrine cells, the inhibitory, local circuit neurons. To study the effects of these gap junctions, we developed a linear, mathematical model of the retinal circuitry providing input to parasol cells. Electrophysiological studies have indicated that gap junctions do not enlarge the receptive field centres of parasol cells, but our results suggest that they make other contributions to their light responses. According to our model, the coupled amacrine cells enhance the responses of parasol cells to luminance contrast by disinhibition. We also show how a mixed chemical and electrical synapse between two sets of amacrine cells presynaptic to the parasol cells might make the responses of parasol cells more transient and, therefore, more sensitive to motion. Finally, we show how coupling via amacrine cells can synchronize the firing of parasol cells. An action potential in a model parasol cell can excite neighbouring parasol cells, but only when the coupled amacrine cells also fire action potentials. Passive conduction was ineffective due to low-pass temporal filtering. Inhibition from the axons of the coupled amacrine cells also produced oscillations that might synchronize the firing of more distant ganglion cells.     

Inhibitory synchrony as a mechanism for attentional gain modulation

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there can be an increase in the coherence between spikes and the local field potential (LFP) in the gamma-frequency range (30-50 Hz). The hypothesis explored here is that these observed effects of attention could be a consequence of changes in the synchrony of local interneuron networks. We performed computer simulations of a Hodgkin-Huxley type neuron driven by a constant depolarizing current, I, representing visual stimulation and a modulatory inhibitory input representing the effects of attention via local interneuron networks. We observed that the neuron's firing rate and the coherence of its output spike train with the synaptic inputs was modulated by the degree of synchrony of the inhibitory inputs. When inhibitory synchrony increased, the coherence of spiking model neurons with the synaptic input increased, but the firing rate either increased or remained the same. The mean number of synchronous inhibitory inputs was a key determinant of the shape of the firing rate versus current (f-I) curves. For a large number of inhibitory inputs (approximately 50), the f-I curve saturated for large I and an increase in input synchrony resulted in a shift of sensitivity-the model neuron responded to weaker inputs I. For a small number (approximately 10), the f-I curves were non-saturating and an increase in input synchrony led to an increase in the gain of the response-the firing rate in response to the same input was multiplied by an approximately constant factor. The firing rate modulation with inhibitory synchrony was highest when the input network oscillated in the gamma frequency range. Thus, the observed changes in firing rate and coherence of neurons in the visual cortex could be controlled by top-down inputs that regulated the coherence in the activity of a local inhibitory network discharging at gamma frequencies.     

Electrical coupling between pyramidal cells in adult cortical regions

Recently, intense interest has focussed on electrical coupling between interneurones in cortical regions and their contributions towards oscillatory network activity. Despite mounting circumstantial evidence that pyramidal cells are also coupled, the paucity of direct evidence has made this controversial. Dual intracellular recordings from pairs of cortical and hippocampal pyramids demonstrated strong, but sparse coupling. Approximately 70% of CA1 pyramids close to the stratum radiatum border were coupled to another pyramid, but only to one or two of their very closest neighbours. On average 25% of the steady state and 10% of the peak action potential voltage change in one cell transferred to the other, supporting synchrony and promoting burst firing. The very high incidence of convergent inputs from coupled pyramids onto single targets provided additional evidence that ‘spikelets’ reflected full action potentials in a coupled cell, since the EPSPs activated by APs and by ‘spikelets’ had significantly different amplitude distributions. Audrey Mercer and Peter Bannister made equal contributions to this study     

Physiological characteristics and reflex activation of DUM (octopaminergic) neurons of locust metathoracic ganglion

Intracellular recordings were made from single or pairs of somata of the dorsal unpaired median (DUM) neurons of the metathoracic ganglion of the locust Schistocerca gregaria and the grasshopper Romalea microptera, during reflex actions, direct electric excitation and orthodromic and antidromic neural stimulation. Some, possibly all, of these neurons are unique, identifiable individuals in regard to their targets, which are specific peripheral muscles. Their physiological properties and the ways they are activated synaptically are, however, similar. Large, overshooting action potentials, comprising three components, occur. The first component in time is small and represents an excitatory synaptic potential for orthodromic stimulation or an axon spike (AS) for antidromic stimulation, electrotonically conducted into the soma. The second component is larger, being an electrotonically conducted integrating segment spike (ISS). The final component is the soma spike (SS). Neither AS nor ISS have a late positive phase, but there is a large, prolonged one for SS. The latter, combined with rapid accommodation, determine a low maximum firing rate for the neurons. Most nerves entering the ganglion make excitatory inputs onto each DUM neuron, which is readily driven to spike by electric excitation of either connective. There is a great deal of spontaneous excitatory synaptic input to each DUM neuron and a high proportion of it is common. Although there is no detectable electrical coupling between the cells, there is about 30% synchronous firing, apparently due to the common inputs; independent excitation and inhibition also occur. All sensory modalities tested have inputs to the neurons, which tend to fire constantly at a low rate (1 per 3–4 sec). In reflex actions, DUM neurons tend to fire before motor output occurs. It is suggested that the cells will be found to have many functions serving a general role comparable to that achieved by the release of adrenaline in vertebrates.     

Using phase resetting to predict 1:1 and 2:2 locking in two neuron networks in which firing order is not always preserved

Our goal is to understand how nearly synchronous modes arise in heterogenous networks of neurons. In heterogenous networks, instead of exact synchrony, nearly synchronous modes arise, which include both 1:1 and 2:2 phase-locked modes. Existence and stability criteria for 2:2 phase-locked modes in reciprocally coupled two neuron circuits were derived based on the open loop phase resetting curve (PRC) without the assumption of weak coupling. The PRC for each component neuron was generated using the change in synaptic conductance produced by a presynaptic action potential as the perturbation. Separate derivations were required for modes in which the firing order is preserved and for those in which it alternates. Networks composed of two model neurons coupled by reciprocal inhibition were examined to test the predictions. The parameter regimes in which both types of nearly synchronous modes are exhibited were accurately predicted both qualitatively and quantitatively provided that the synaptic time constant is short with respect to the period and that the effect of second order resetting is considered. In contrast, PRC methods based on weak coupling could not predict 2:2 modes and did not predict the 1:1 modes with the level of accuracy achieved by the strong coupling methods. The strong coupling prediction methods provide insight into what manipulations promote near-synchrony in a two neuron network and may also have predictive value for larger networks, which can also manifest changes in firing order. We also identify a novel route by which synchrony is lost in mildly heterogenous networks.     

Activity pattern of suboesophageal ganglion cells innervating the salivary glands of the locust Locusta migratoria

The salivary gland of the locust, Locusta migratoria, is innervated from the suboesophageal ganglion by two neurones, SN1 and SN2 which innervate the gland via the salivary gland nerve (nerve 7B of the suboesophageal ganglion). In addition, like most other peripheral nerves of the head, this nerve carries on its outer surface axons and neurohaemal terminal ramifications of the so called satellite nervous system, established by a group of neurosecretory cells also located in the suboesophageal ganglion. These superficial collaterals ramify over the nerve from its origin in the head to its terminals within the gland in the thoracic segments.Nerve 7B was recorded chronically in freely moving locusts. Both salivary neurones are active during and shortly before feeding, as defined by continuous rhythmic activity of the mandibular closer muscle (M9). The activity of the salivary neurones, particularly that of SN2, thus resembles that of the satellite neurones as described recently. While SN2 ceases firing at the end of a feeding bout, SN1 continues firing for a short period. Also, SN1 fires short bursts of impulses for a few minutes following the end of a feeding bout. Similar bursts also occur at random intervals during the long-lasting phases between feeding events.Abbreviations SN1 salivary neurone 1 - SN2 salivary neurone 2 - M9 mandibular closer muscle - DUM dorsal unpaired median - LMN labral median nerve     

Short conduction delays cause inhibition rather than excitation to favor synchrony in hybrid neuronal networks of the entorhinal cortex

How stable synchrony in neuronal networks is sustained in the presence of conduction delays is an open question. The Dynamic Clamp was used to measure phase resetting curves (PRCs) for entorhinal cortical cells, and then to construct networks of two such neurons. PRCs were in general Type I (all advances or all delays) or weakly type II with a small region at early phases with the opposite type of resetting. We used previously developed theoretical methods based on PRCs under the assumption of pulsatile coupling to predict the delays that synchronize these hybrid circuits. For excitatory coupling, synchrony was predicted and observed only with no delay and for delays greater than half a network period that cause each neuron to receive an input late in its firing cycle and almost immediately fire an action potential. Synchronization for these long delays was surprisingly tight and robust to the noise and heterogeneity inherent in a biological system. In contrast to excitatory coupling, inhibitory coupling led to antiphase for no delay, very short delays and delays close to a network period, but to near-synchrony for a wide range of relatively short delays. PRC-based methods show that conduction delays can stabilize synchrony in several ways, including neutralizing a discontinuity introduced by strong inhibition, favoring synchrony in the case of noisy bistability, and avoiding an initial destabilizing region of a weakly type II PRC. PRCs can identify optimal conduction delays favoring synchronization at a given frequency, and also predict robustness to noise and heterogeneity.