Conditional Spike Transmission Mediated by Electrical Coupling Ensures Millisecond Precision-Correlated Activity among Interneurons In Vivo

Many GABAergic interneurons are electrically coupled and in vitro can display correlated activity with millisecond precision. However, the mechanisms underlying correlated activity between interneurons in vivo are unknown. Using dual patch-clamp recordings in vivo, we reveal that in the presence of spontaneous background synaptic activity, electrically coupled cerebellar Golgi cells exhibit robust millisecond precision-correlated activity which is enhanced by sensory stimulation. This precisely correlated activity results from the cooperative action of two mechanisms. First, electrical coupling ensures slow subthreshold membrane potential correlations by equalizing membrane potential fluctuations, such that coupled neurons tend to approach action potential threshold together. Second, fast spike-triggered spikelets transmitted through gap junctions conditionally trigger postjunctional spikes, depending on both neurons being close to threshold. Electrical coupling therefore controls the temporal precision and degree of both spontaneous and sensory-evoked correlated activity between interneurons, by the cooperative effects of shared synaptic depolarization and spikelet transmission

Consistency and diversity of spike dynamics in the neurons of bed nucleus of Stria Terminalis of the rat: a dynamic clamp study

Neurons display a high degree of variability and diversity in the expression and regulation of their voltage-dependent ionic channels. Under low level of synaptic background a number of physiologically distinct cell types can be identified in most brain areas that display different responses to standard forms of intracellular current stimulation. Nevertheless, it is not well understood how biophysically different neurons process synaptic inputs in natural conditions, i.e., when experiencing intense synaptic bombardment in vivo. While distinct cell types might process synaptic inputs into different patterns of action potentials representing specific "motifs'' of network activity, standard methods of electrophysiology are not well suited to resolve such questions. In the current paper we performed dynamic clamp experiments with simulated synaptic inputs that were presented to three types of neurons in the juxtacapsular bed nucleus of stria terminalis (jcBNST) of the rat. Our analysis on the temporal structure of firing showed that the three types of jcBNST neurons did not produce qualitatively different spike responses under identical patterns of input. However, we observed consistent, cell type dependent variations in the fine structure of firing, at the level of single spikes. At the millisecond resolution structure of firing we found high degree of diversity across the entire spectrum of neurons irrespective of their type. Additionally, we identified a new cell type with intrinsic oscillatory properties that produced a rhythmic and regular firing under synaptic stimulation that distinguishes it from the previously described jcBNST cell types. Our findings suggest a sophisticated, cell type dependent regulation of spike dynamics of neurons when experiencing a complex synaptic background. The high degree of their dynamical diversity has implications to their cooperative dynamics and synchronization

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file

Homeostatic Scaling of Excitability in Recurrent Neural Networks

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity

Ih-mediated depolarization enhances the temporal precision of neuronal integration

Feed-forward inhibition mediated by ionotropic GABAA receptors contributes to the temporal precision of neuronal signal integration. These receptors exert their inhibitory effect by shunting excitatory currents and by hyperpolarizing neurons. The relative roles of these mechanisms in neuronal computations are, however, incompletely understood. In this study, we show that by depolarizing the resting membrane potential relative to the reversal potential for GABAA receptors, the hyperpolarization-activated mixed cation current (Ih) maintains a voltage gradient for fast synaptic inhibition in hippocampal pyramidal cells. Pharmacological or genetic ablation of Ih broadens the depolarizing phase of afferent synaptic waveforms by hyperpolarizing the resting membrane potential. This increases the integration time window for action potential generation. These results indicate that the hyperpolarizing component of GABAA receptor-mediated inhibition has an important role in maintaining the temporal fidelity of coincidence detection and suggest a previously unrecognized mechanism by which Ih modulates information processing in the hippocampus

Hyperpolarization-Activated Current (Ih) in Ganglion-Cell Photoreceptors

Intrinsically photosensitive retinal ganglion cells (ipRGCs) express the photopigment melanopsin and serve as the primary retinal drivers of non-image-forming visual functions such as circadian photoentrainment, the pupillary light reflex, and suppression of melatonin production in the pineal. Past electrophysiological studies of these cells have focused on their intrinsic photosensitivity and synaptic inputs. Much less is known about their voltage-gated channels and how these might shape their output to non-image-forming visual centers. Here, we show that rat ipRGCs retrolabeled from the suprachiasmatic nucleus (SCN) express a hyperpolarization-activated inwardly-rectifying current (Ih). This current is blocked by the known Ih blockers ZD7288 and extracellular cesium. As in other systems, including other retinal ganglion cells, Ih in ipRGCs is characterized by slow kinetics and a slightly greater permeability for K+ than for Na+. Unlike in other systems, however, Ih in ipRGCs apparently does not actively contribute to resting membrane potential. We also explore non-specific effects of the common Ih blocker ZD7288 on rebound depolarization and evoked spiking and discuss possible functional roles of Ih in non-image-forming vision. This study is the first to characterize Ih in a well-defined population of retinal ganglion cells, namely SCN-projecting ipRGCs

Population diversity and function of hyperpolarization-activated current in olfactory bulb mitral cells

Although neurons are known to exhibit a broad array of intrinsic properties that impact critically on the computations they perform, very few studies have quantified such biophysical diversity and its functional consequences. Using in vivo and in vitro whole-cell recordings here we show that mitral cells are extremely heterogeneous in their expression of a rebound depolarization (sag) at hyperpolarized potentials that is mediated by a ZD7288-sensitive current with properties typical of hyperpolarization-activated cyclic nucleotide gated (HCN) channels. The variability in sag expression reflects a functionally diverse population of mitral cells. For example, those cells with large amplitude sag exhibit more membrane noise, a lower rheobase and fire action potentials more regularly than cells where sag is absent. Thus, cell-to-cell variability in sag potential amplitude reflects diversity in the integrative properties of mitral cells that ensures a broad dynamic range for odor representation across these principal neurons

Gene Expression in Human Hippocampus from Cocaine Abusers Identifies Genes which Regulate Extracellular Matrix Remodeling

The chronic effects of cocaine abuse on brain structure and function are blamed for the inability of most addicts to remain abstinent. Part of the difficulty in preventing relapse is the persisting memory of the intense euphoria or cocaine “rush”. Most abused drugs and alcohol induce neuroplastic changes in brain pathways subserving emotion and cognition. Such changes may account for the consolidation and structural reconfiguration of synaptic connections with exposure to cocaine. Adaptive hippocampal plasticity could be related to specific patterns of gene expression with chronic cocaine abuse. Here, we compare gene expression profiles in the human hippocampus from cocaine addicts and age-matched drug-free control subjects. Cocaine abusers had 151 gene transcripts upregulated, while 91 gene transcripts were downregulated. Topping the list of cocaine-regulated transcripts was RECK in the human hippocampus (FC = 2.0; p<0.05). RECK is a membrane-anchored MMP inhibitor that is implicated in the coordinated regulation of extracellular matrix integrity and angiogenesis. In keeping with elevated RECK expression, active MMP9 protein levels were decreased in the hippocampus from cocaine abusers. Pathway analysis identified other genes regulated by cocaine that code for proteins involved in the remodeling of the cytomatrix and synaptic connections and the inhibition of blood vessel proliferation (PCDH8, LAMB1, ITGB6, CTGF and EphB4). The observed microarray phenotype in the human hippocampus identified RECK and other region-specific genes that may promote long-lasting structural changes with repeated cocaine abuse. Extracellular matrix remodeling in the hippocampus may be a persisting effect of chronic abuse that contributes to the compulsive and relapsing nature of cocaine addiction