Multiquantal release underlies the distribution of synaptic efficacies in the neocortex

Loebel, Alex; Silberberg, Gilad; Helbig, Daniela; Markram, Henry; Tsodyks, Misha; Richardson, Magnus J. E.

doi:10.3389/neuro.10.027.2009

Cited by 53 publications

(108 citation statements)

References 51 publications

(108 reference statements)

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“…One study reported MVR at L2/3 neurons in V1 at room temperature (Watanabe et al, 2005), which was in contrast with other reports in S1 (Rozov et al, 2001;Koester and Johnston, 2005). Another recent study suggested that MVR occurred at L5 synapses in S1 (Loebel et al, 2009). Here, our data provide strong evidence in favor of MVR at RS-RS connections of L4 in S1 under physiological conditions based on the differential block of Kyn, which clearly indicates that the local glutamate transient changes during the train.…”

Section: Multivesicular Release At Cortical Synapsescontrasting

confidence: 56%

Multivesicular Release Differentiates the Reliability of Synaptic Transmission between the Visual Cortex and the Somatosensory Cortex

Huang¹,

Bao²,

Sakaba³

2010

J. Neurosci.

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Neurons in layer 4 (L4) of the cortex play an important role in transferring signals from thalamus to other layers of the cortex. Understanding the fundamental properties of synaptic transmission between L4 neurons helps us gain a clear picture of how the neuronal network in L4 cooperates to process sensory information. In the present study, we have determined the underlying parameters that govern synaptic strength, such as quantal size, size of readily releasable vesicle pool, and release probability (Pr) of excitatory synaptic connections within L4 of the visual cortex (V1) and the somatosensory cortex (S1) in mice. Although only a single vesicle is released per release site under physiological conditions at V1 synapses, multivesicular release (MVR) is observed at S1 synapses. In addition, we observed a saturation of postsynaptic receptors at S1 synapses. Other synaptic properties are similar in both cortices. Dynamic clamp experiments suggest that higher Pr and MVR at S1 synapses lower the requirement of the number of synaptic inputs to generate postsynaptic action potentials. In addition, the slower decay of synaptic current and the intrinsic membrane properties of the postsynaptic neuron also contribute to the reliable transmission between S1 neurons.

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Section: Multivesicular Release At Cortical Synapsescontrasting

confidence: 56%

Multivesicular Release Differentiates the Reliability of Synaptic Transmission between the Visual Cortex and the Somatosensory Cortex

Huang¹,

Bao²,

Sakaba³

2010

J. Neurosci.

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“…Our model assumes that each synaptic contact hosts exactly one vesicle docking site, in contrast to similar models in which a single contact can dock multiple vesicles (Vere-Jones 1966;Wang 1999;de la Rocha and Parga 2005;Loebel et al 2009). This difference could potentially be resolved by interpreting our parameter M as the total number of release sites at all contacts, but this resolution is only consistent if vesicle release at each site is statistically independent.…”

Section: Discussionmentioning

confidence: 99%

Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations

Rosenbaum

Rubin

Doiron

2013

Journal of Neurophysiology

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Rosenbaum R, Rubin JE, Doiron B. Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations. J Neurophysiol 109: 475-484, 2013. First published October 31, 2012 doi:10.1152/jn.00733.2012.-Correlated neuronal activity is an important feature in many neural codes, a neural correlate of a variety of cognitive states, as well as a signature of several disease states in the nervous system. The cellular and circuit mechanics of neural correlations is a vibrant area of research. Synapses throughout the cortex exhibit a form of short-term depression where increased presynaptic firing rates deplete neurotransmitter vesicles, which transiently reduces synaptic efficacy. The release and recovery of these vesicles are inherently stochastic, and this stochasticity introduces variability into the conductance elicited by depressing synapses. The impact of spiking and subthreshold membrane dynamics on the transfer of neuronal correlations has been studied intensively, but an investigation of the impact of short-term synaptic depression and stochastic vesicle dynamics on correlation transfer is lacking. We find that short-term synaptic depression and stochastic vesicle dynamics can substantially reduce correlations, shape the timescale over which these correlations occur, and alter the dependence of spiking correlations on firing rate. Our results show that short-term depression and stochastic vesicle dynamics need to be taken into account when modeling correlations in neuronal populations. Synaptic neurotransmitter vesicles are released probabilistically in response to a presynaptic spike, and released vesicles are recovered stochastically over a timescale of several hundred milliseconds (Vere-Jones 1966;Wang 1999;Fuhrmann et al. 2002;Goldman 2004;Rosenbaum et al. 2012). The depletion of neurotransmitter vesicles by trains of presynaptic action potentials gives rise to a form of short-term synaptic depression that is pervasive in the cortex (Zucker and Regehr 2002). We find that when two postsynaptic neurons receive correlated input through depressing synapses, the correlation between the synaptic conductances across the neurons' membranes, as well as the neurons' spike trains, are drastically smaller than the correlations predicted by a nondepressing, static synapse model. This reduction in correlation is especially prevalent at higher presynaptic firing rates that more effectively deplete neurotransmitter vesicles. Coupled with the fact that cellular dynamics suppress correlations at low firing rates (de la Rocha et al. 2007), these results show that a population of neurons with depressing synapses exhibit small correlations over a broad range of firing rates, even when their inputs are strongly correlated. Our conclusions reveal an important, yet often ignored, mechanism that promotes asynchronous spiking activity in densely connected neuronal populations. METHODSWe begin by describing the statistical measures used to quantify correlations in this study. We then describe the presyn...

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“…Initial applications relied on conducting experiments under a variety of conditions, in particular varying the extracellular Ca 2+ concentration to alter the vesicle release probability (Foster and Regehr, 2004; Birò et al, 2005). Brémaud et al (2007) and Loebel et al (2009) increased the practicality of the method by using short-term vesicle depletion to vary the effective release probability under a single experimental condition. Their analyses showed that multiquantal release underlies the wide range of EPSP amplitudes observed (Song et al, 2005; Lefort et al, 2009) and that, in general, it is not the case that the number of distinct anatomical contacts equals the maximum number of readily-releasable vesicles as was put forward by the single-vesicle hypothesis (Kuno, 1971; Korn et al, 1981).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Inference of Synaptic Quantal Parameters from Correlated Vesicle Release

Bird

Wall

Richardson

2016

Front. Comput. Neurosci.

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Synaptic transmission is both history-dependent and stochastic, resulting in varying responses to presentations of the same presynaptic stimulus. This complicates attempts to infer synaptic parameters and has led to the proposal of a number of different strategies for their quantification. Recently Bayesian approaches have been applied to make more efficient use of the data collected in paired intracellular recordings. Methods have been developed that either provide a complete model of the distribution of amplitudes for isolated responses or approximate the amplitude distributions of a train of post-synaptic potentials, with correct short-term synaptic dynamics but neglecting correlations. In both cases the methods provided significantly improved inference of model parameters as compared to existing mean-variance fitting approaches. However, for synapses with high release probability, low vesicle number or relatively low restock rate and for data in which only one or few repeats of the same pattern are available, correlations between serial events can allow for the extraction of significantly more information from experiment: a more complete Bayesian approach would take this into account also. This has not been possible previously because of the technical difficulty in calculating the likelihood of amplitudes seen in correlated post-synaptic potential trains; however, recent theoretical advances have now rendered the likelihood calculation tractable for a broad class of synaptic dynamics models. Here we present a compact mathematical form for the likelihood in terms of a matrix product and demonstrate how marginals of the posterior provide information on covariance of parameter distributions. The associated computer code for Bayesian parameter inference for a variety of models of synaptic dynamics is provided in the Supplementary Material allowing for quantal and dynamical parameters to be readily inferred from experimental data sets.

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Multiquantal release underlies the distribution of synaptic efficacies in the neocortex

Cited by 53 publications

References 51 publications

Multivesicular Release Differentiates the Reliability of Synaptic Transmission between the Visual Cortex and the Somatosensory Cortex

Multivesicular Release Differentiates the Reliability of Synaptic Transmission between the Visual Cortex and the Somatosensory Cortex

Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations

Bayesian Inference of Synaptic Quantal Parameters from Correlated Vesicle Release

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