Heterogeneous Release Properties of Visualized Individual Hippocampal Synapses

Murthy, Venkatesh N.; Sejnowski, Terrence J.; Stevens, Charles F.

doi:10.1016/s0896-6273(00)80301-3

Cited by 540 publications

(609 citation statements)

References 27 publications

Supporting

Mentioning

538

Contrasting

Order By: Relevance

“…There is experimental evidence to support both possibilities. It has been shown in hippocampal neuron cultures that the release properties of individual synapses made by a single neuron vary significantly (Murthy et al, 1997). Additionally, at frog neuromuscular junctions, some active zones within a terminal have a high release probability whereas others in the same terminal do not (Bennett and Lavidis, 1989).…”

Section: Discussionmentioning

confidence: 99%

Heterogeneity in Synaptic Vesicle Release at Neuromuscular Synapses of Mice Expressing SynaptopHluorin

Wyatt

Balice-Gordon²

2008

J. Neurosci.

View full text Add to dashboard Cite

Mammalian neuromuscular junctions are useful model synapses to study the relationship between synaptic structure and function, although these have rarely been studied together at the same synapses. To do this, we generated transgenic lines of mice in which the thy1.2 promoter drives expression of synaptopHluorin (spH) as a means of optically measuring synaptic vesicle distribution and release. SpH is colocalized with other synaptic vesicle proteins in presynaptic terminals and does not alter normal synaptic function. Nerve stimulation leads to readily detectable and reproducible fluorescence changes in motor axon terminals that vary with stimulus frequency and, when compared with electrophysiological recordings, are reliable indicators of neurotransmitter release. Measurements of fluorescence intensity changes reveal a surprising amount of heterogeneity in synaptic vesicle release throughout individual presynaptic motor axon terminals. Some discrete terminal regions consistently displayed a greater rate and extent of release than others, regardless of stimulation frequency. The amount of release at a particular site is highly correlated to the relative abundance of synaptic vesicles there, indicating that a relatively constant fraction of the total vesicular pool, ϳ30%, is released in response to activity. These studies reveal previously unknown relationships between synaptic structure and function at mammalian neuromuscular junctions and demonstrate the usefulness of spH expressing mice as a tool for studying neuromuscular synapses in adults, as well as during development and diseases that affect neuromuscular synaptic function.

show abstract

Section: Discussionmentioning

confidence: 99%

Heterogeneity in Synaptic Vesicle Release at Neuromuscular Synapses of Mice Expressing SynaptopHluorin

Wyatt

Balice-Gordon²

2008

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…For this figure, the dynamics described in the previous paragraph were applied to AMPA and GABA conductances, with separate P T values for each. Based on experimental reports (Murthy et al, 1997), we chose P T ϭ 0.15. Figure 12, a and b, corresponds to a balanced postsynaptic neuron, and Figure 12, c and d, corresponds to an unbalanced one, with the same sets of parameters used before.…”

Section: Impact Of Other Factors Contributing To Input Variancementioning

confidence: 99%

Impact of Correlated Synaptic Input on Output Firing Rate and Variability in Simple Neuronal Models

2000

Self Cite

View full text Add to dashboard Cite

Cortical neurons are typically driven by thousands of synaptic inputs. The arrival of a spike from one input may or may not be correlated with the arrival of other spikes from different inputs. How does this interdependence alter the probability that the postsynaptic neuron will fire? We constructed a simple random walk model in which the membrane potential of a target neuron fluctuates stochastically, driven by excitatory and inhibitory spikes arriving at random times. An analytic expression was derived for the mean output firing rate as a function of the firing rates and pairwise correlations of the inputs. This stochastic model made three quantitative predictions. (1) Correlations between pairs of excitatory or inhibitory inputs increase the fluctuations in synaptic drive, whereas correlations between excitatory-inhibitory pairs decrease them. (2) When excitation and inhibition are fully balanced (the mean net synaptic drive is zero), firing is caused by the fluctuations only. (3) In the balanced case, firing is irregular. These theoretical predictions were in excellent agreement with simulations of an integrate-and-fire neuron that included multiple conductances and received hundreds of synaptic inputs. The results show that, in the balanced regime, weak correlations caused by signals shared among inputs may have a multiplicative effect on the input-output rate curve of a postsynaptic neuron, i.e. they may regulate its gain; in the unbalanced regime, correlations may increase firing probability mainly around threshold, when output rate is low; and in all cases correlations are expected to increase the variability of the output spike train. Key words: random-walk; integrate-and-fire; computer simulation; spike synchrony; oscillations; cross-correlation; balanced inhibition; cerebral cortexThe output of a typical cortical neuron depends on the activity of a large number of synaptic inputs-several thousands of them, as estimated by anatomical techniques (White, 1989; Braitenberg and Shüz, 1997). What kind of response should be expected from a postsynaptic neuron driven by so many inputs? Answering this question in detail requires a deep understanding of dendritic integration, synaptic function, and spike generation mechanisms; but, given the large numbers commonly involved, as a first approximation it is natural to cast the problem in statistical terms. The strategy then is to compute the output responses of a model neuron (or their statistics), given a set of driving inputs with known statistical properties. These inputs may be either independent or temporally correlated. In the latter case, spikes from different input neurons arrive close together in time more often or less often than expected by chance.In general, the situation with independent inputs is easier to analyze, and for many applications it is probably a good approximation. However, there are at least three reasons why the effects of correlations on single cells should be fully characterized. First, correlations in spike counts have indeed been o...

show abstract

“…These properties may result in a differential susceptibility of a synapse to the retrograde signal, resulting in the observed correlation between the degree of depression at the back-propagation site and the initial amplitude of the postsynaptic currents at that site. Indeed, synapses with different release probability show different degrees of short-term plasticity 36 .…”

Section: Potential Cellular Mechanismsmentioning

confidence: 99%

Propagation of activity-dependent synaptic depression in simple neural networks

Fitzsimonds

Song

Poo

1997

Nature

169

125

View full text Add to dashboard Cite

Triple whole-cell recordings from simple networks of cultured hippocampal neurons show that induction of long-term depression at glutamatergic synapses is accompanied by a back propagation of depression to input synapses on the dendrite of the presynaptic neuron. The depression also propagates laterally to divergent outputs of the presynaptic neuron and to convergent inputs on the postsynaptic neuron. There is no forward propagation of depression to the output of the postsynaptic neuron and no presynaptic propagation accompanying long-term depression at GABAergic synapses. Activity-induced synaptic modification is therefore not restricted to the activated synapse, but selectively propagates throughout the neural network.The development and plasticity of the nervous system involve activity-dependent modification of synaptic connections 1-3 . Longterm potentiation (LTP) and long-term depression (LTD) of central synapses induced by repetitive activity in various regions of the brain have been implicated as the cellular mechanisms that underlie learning and memory [4][5][6][7] . These modifications are known to be input-specific, so only activated pathways are affected. But within the vicinity of activated pathways, other non-activated synapses also become modified, leading to more distributed synaptic modifications within a neural network. For example, LTP generated at one synaptic input to a CA1 hippocampal neuron was found to spread to adjacent synapses on the same or on a different postsynaptic neuron [8][9][10][11] and to result in LTD in more distant neurons 12,13 . Such spread of synaptic modification appears to depend on membranepermeable or secreted factors released by the activated synapse, and the extent of influence on other synapses depends on their physical proximity. On the other hand, the spread of synaptic modification can also be mediated by signalling within the neuron. On the postsynaptic side, LTP at one synaptic input can result in heterosynaptic modification of other convergent inputs [14][15][16][17][18][19] . On the presynaptic side, changes may spread through the cytoplasm to other divergent outputs. In Xenopus nerve-muscle cultures, LTD induced at one neuromuscular synapse can propagate to other synapses made by the same neuron onto other myocytes, apparently by signalling within the neuronal cytoplasm 20 . A similar presynaptic cytoplasmic mechanism may also account for the spread of shortterm depression of inhibitory synapses observed in cerebellar slices 21 .Here we find that induction of LTD at glutamatergic synapses within small networks of cultured hippocampal neurons is accompanied by a retrograde spread of depression to synapses on the dendrites of the presynaptic neurons (back propagation). The depression also spreads laterally to synapses made by divergent outputs of the presynaptic neuron (presynaptic lateral propagation) or to convergent inputs on the postsynaptic neurons (postsynaptic lateral propagation). In contrast, there was no forward propagation of depression to output s...

show abstract

Heterogeneous Release Properties of Visualized Individual Hippocampal Synapses

Cited by 540 publications

References 27 publications

Heterogeneity in Synaptic Vesicle Release at Neuromuscular Synapses of Mice Expressing SynaptopHluorin

Heterogeneity in Synaptic Vesicle Release at Neuromuscular Synapses of Mice Expressing SynaptopHluorin

Impact of Correlated Synaptic Input on Output Firing Rate and Variability in Simple Neuronal Models

Propagation of activity-dependent synaptic depression in simple neural networks

Contact Info

Product

Resources

About