Characterizing synaptic conductance fluctuations in cortical neurons and their influence on spike generation

Cortical neurons are subject to sustained and irregular synaptic activity which causes important fluctuations of the membrane potential (Vm). We review here different methods to characterize this activity and its impact on spike generation. The simplified, fluctuating point-conductance model of synaptic activity provides the starting point of a variety of methods for the analysis of intracellular Vm recordings. In this model, the synaptic excitatory and inhibitory conductances are described by Gaussian-distributed stochastic variables, or colored conductance noise. The matching of experimentally recorded Vm distributions to an invertible theoretical expression derived from the model allows the extraction of parameters characterizing the synaptic conductance distributions. This analysis can be complemented by the matching of experimental Vm power spectral densities (PSDs) to a theoretical template, even though the unexpected scaling properties of experimental PSDs limit the precision of this latter approach. Building on this stochastic characterization of synaptic activity, we also propose methods to qualitatively and quantitatively evaluate spike-triggered averages of synaptic time-courses preceding spikes. This analysis points to an essential role for synaptic conductance variance in determining spike times. The presented methods are evaluated using controlled conductance injection in cortical neurons in vitro with the dynamic-clamp technique. We review their applications to the analysis of in vivo intracellular recordings in cat association cortex, which suggest a predominant role for inhibition in determining both sub- and supra-threshold dynamics of cortical neurons embedded in active networks.Comment: 9 figures, Journal of Neuroscience Methods (in press, 2008

Gain modulation of synaptic inputs by network state in auditory cortex in vivo

The cortical network recurrent circuitry generates spontaneous activity organized into Up (active) and Down (quiescent) states during slow-wave sleep or anesthesia. These different states of cortical activation gain modulate synaptic transmission. However, the reported modulation that Up states impose on synaptic inputs is disparate in the literature, including both increases and decreases of responsiveness. Here, we tested the hypothesis that such disparate observations may depend on the intensity of the stimulation. By means of intracellular recordings, we studied synaptic transmission during Up and Down states in rat auditory cortex in vivo. Synaptic potentials were evoked either by auditory or electrical (thalamocortical, intracortical) stimulation while randomly varying the intensity of the stimulus. Synaptic potentials evoked by the same stimulus intensity were compared in Up/Down states. Up states had a scaling effect on the stimulus-evoked synaptic responses: the amplitude of weaker responses was potentiated whereas that of larger responses was maintained or decreased with respect to the amplitude during Down states. We used a computational model to explore the potential mechanisms explaining this nontrivial stimulus–response relationship. During Up/Down states, there is different excitability in the network and the neuronal conductance varies. We demonstrate that the competition between presynaptic recruitment and the changing conductance might be the central mechanism explaining the experimentally observed stimulus–response relationships. We conclude that the effect that cortical network activation has on synaptic transmission is not constant but contingent on the strength of the stimulation, with a larger modulation for stimuli involving both thalamic and cortical networks.Fil: Reig, Ramon. Institut d'Investigacions Biomèdiques August Pi i Sunyer; España. Karolinska Huddinge Hospital. Karolinska Institutet; SueciaFil: Zerlaut, Yann. Centre National de la Recherche Scientifique; Francia. Unité de Neurosciences, Information et Complexité; FranciaFil: Vergara, Ramiro Oscar. Institut d'Investigacions Biomèdiques August Pi i Sunyer; España. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Acústica y Percepción Sonora; ArgentinaFil: Destexhe, Alain. Centre National de la Recherche Scientifique; Francia. Unité de Neurosciences, Information et Complexité; FranciaFil: Sánchez Vives, María V.. Institut d'Investigacions Biomèdiques August Pi i Sunyer; España. Institució Catalana de Recerca i Estudis Avancats; Españ

Disentangling astroglial physiology with a realistic cell model in silico

Electrically non-excitable astroglia take up neurotransmitters, buffer extracellular K+ and generate Ca2+ signals that release molecular regulators of neural circuitry. The underlying machinery remains enigmatic, mainly because the sponge-like astrocyte morphology has been difficult to access experimentally or explore theoretically. Here, we systematically incorporate multi-scale, tri-dimensional astroglial architecture into a realistic multi-compartmental cell model, which we constrain by empirical tests and integrate into the NEURON computational biophysical environment. This approach is implemented as a flexible astrocyte-model builder ASTRO. As a proof-of-concept, we explore an in silico astrocyte to evaluate basic cell physiology features inaccessible experimentally. Our simulations suggest that currents generated by glutamate transporters or K+ channels have negligible distant effects on membrane voltage and that individual astrocytes can successfully handle extracellular K+ hotspots. We show how intracellular Ca2+ buffers affect Ca2+ waves and why the classical Ca2+ sparks-and-puffs mechanism is theoretically compatible with common readouts of astroglial Ca2+ imaging

Strength and dendritic organization of thalamocortical synapses onto excitatory layer 4 neurons

The thalamus is a potent driver of cortical activity, even though cortical synapses onto layer 4 (L4) neurons outnumber thalamic synapses ten to one. Previous in vitro studies have suggested that enhanced efficacy of thalamocortical (TC) relative to corticocortical (CC) synapses explains the effectiveness of the thalamus. We investigated possible key anatomical and physiological differences between these inputs onto excitatory L4 neurons in vivo. We developed a high-throughput light microscopy method, validated by electron microscopy, to completely map the locations of synapses across an entire dendritic tree. This demonstrated that TC synapses are slightly more proximal to the soma than CC synapses, but detailed compartmental modeling predicted that dendritic filtering does not appreciably favor one synaptic class over another. Measurements of synaptic strength in intact animals revealed that both TC and CC synapses are weak and approximately equivalent. We conclude that thalamic potency relies, not on enhanced TC strength, but on coincident activation of converging inputs

Stochastic Ion Channel Gating in Dendritic Neurons: Morphology Dependence and Probabilistic Synaptic Activation of Dendritic Spikes

Neuronal activity is mediated through changes in the probability of stochastic transitions between open and closed states of ion channels. While differences in morphology define neuronal cell types and may underlie neurological disorders, very little is known about influences of stochastic ion channel gating in neurons with complex morphology. We introduce and validate new computational tools that enable efficient generation and simulation of models containing stochastic ion channels distributed across dendritic and axonal membranes. Comparison of five morphologically distinct neuronal cell types reveals that when all simulated neurons contain identical densities of stochastic ion channels, the amplitude of stochastic membrane potential fluctuations differs between cell types and depends on sub-cellular location. For typical neurons, the amplitude of membrane potential fluctuations depends on channel kinetics as well as open probability. Using a detailed model of a hippocampal CA1 pyramidal neuron, we show that when intrinsic ion channels gate stochastically, the probability of initiation of dendritic or somatic spikes by dendritic synaptic input varies continuously between zero and one, whereas when ion channels gate deterministically, the probability is either zero or one. At physiological firing rates, stochastic gating of dendritic ion channels almost completely accounts for probabilistic somatic and dendritic spikes generated by the fully stochastic model. These results suggest that the consequences of stochastic ion channel gating differ globally between neuronal cell-types and locally between neuronal compartments. Whereas dendritic neurons are often assumed to behave deterministically, our simulations suggest that a direct consequence of stochastic gating of intrinsic ion channels is that spike output may instead be a probabilistic function of patterns of synaptic input to dendrites

Action Potential Monitoring Using Neuronanorobots: Neuroelectric Nanosensors

Neuronanorobotics, a key future medical technology that can enable the preservation of human brain information, requires appropriate nanosensors. Action potentials encode the most resource-intensive functional brain data. This paper presents a theoretical design for electrical nanosensors intended for use in neuronanorobots to provide non-destructive, in vivo, continuous, real-time, single-spike monitoring of action potentials initiated and processed within the ~86 × 109 neurons of the human brain as intermediated through the ~2.4 × 1014 human brain synapses. The proposed ~3375 nm3 FET-based neuroelectric nanosensors could detect action potentials with a temporal resolution of at least 0.1 ms, enough for waveform characterization even at the highest human neuron firing rates of 800 Hz.The principal author (NRBM) thanks the “Fundação para a Ciência e Tecnologia” (FCT) for their financial support of this work (grant SFRH/BD/69660/2010).info:eu-repo/semantics/publishedVersio