Interregional synaptic competition in neurons with multiple STDP-inducing signals

Ilan, Lital Bar; Gidon, Albert; Segev, Idan

doi:10.1152/jn.00612.2010

Cited by 17 publications

(16 citation statements)

References 67 publications

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“…But they may fail to provide greater insights into the mechanism underlying AP initiation than the experiments upon which they are based, since they include so many extraneous details. There are also theoretical studies using simple two-compartment models to describe the Ca 2+ activity of dendrites for pyramidal cell383940414243. However, none of them has provided a satisfied interpretation of how dendritic Ca 2+ spike participates in the initiating dynamics of somatic/axonal APs.…”

Section: Discussionmentioning

confidence: 99%

“…There are also studies that use two compartments to model pyramidal neurons with dendritic Ca 2+ channel. Such simple point-neuron models have been adopted to study their firing patterns383940, spike-timing predictions41, spike timing-dependent plasticity42, and spike-frequency adaptation43. However, it has attracted little attention about the somatic/axonal AP initiation associated with dendritic Ca 2+ spike.…”

mentioning

confidence: 99%

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Action potential initiation in a two-compartment model of pyramidal neuron mediated by dendritic Ca2+ spike

Wang

Wei

et al. 2017

Sci Rep

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Dendritic Ca2+ spike endows cortical pyramidal cell with powerful ability of synaptic integration, which is critical for neuronal computation. Here we propose a two-compartment conductance-based model to investigate how the Ca2+ activity of apical dendrite participates in the action potential (AP) initiation to affect the firing properties of pyramidal neurons. We have shown that the apical input with sufficient intensity triggers a dendritic Ca2+ spike, which significantly boosts dendritic inputs as it propagates to soma. Such event instantaneously shifts the limit cycle attractor of the neuron and results in a burst of APs, which makes its firing rate reach a plateau steady-state level. Delivering current to two chambers simultaneously increases the level of neuronal excitability and decreases the threshold of input-output relation. Here the back-propagating APs facilitate the initiation of dendritic Ca2+ spike and evoke BAC firing. These findings indicate that the proposed model is capable of reproducing in vitro experimental observations. By determining spike initiating dynamics, we have provided a fundamental link between dendritic Ca2+ spike and output APs, which could contribute to mechanically interpreting how dendritic Ca2+ activity participates in the simple computations of pyramidal neuron.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Action potential initiation in a two-compartment model of pyramidal neuron mediated by dendritic Ca2+ spike

Wang

Wei

et al. 2017

Sci Rep

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“…This can be achieved by local diffusion of the individual thresholds, with an underlying topographical organization added. Our model offers a possible framework for detailed compartmental description of different integrative subfields underlying distinct STDP-based operations in which the validating postsynaptic signal can be either the sodium spike or the local calcium spike boosted by backpropagation of the action potential in the distal dendrite (Frégnac, 1999;Bar Ilan et al, 2011). STDP models have been developed along these lines showing the emergence of spatially distinct clusters of synaptic "engrams" on the dendrites (Iannella et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

Stable Learning in Stochastic Network States

et al. 2012

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The mammalian cerebral cortex is characterized in vivo by irregular spontaneous activity, but how this ongoing dynamics affects signal processing and learning remains unknown. The associative plasticity rules demonstrated in vitro, mostly in silent networks, are based on the detection of correlations between presynaptic and postsynaptic activity and hence are sensitive to spontaneous activity and spurious correlations. Therefore, they cannot operate in realistic network states. Here, we present a new class of spike-timing-dependent plasticity learning rules with local floating plasticity thresholds, the slow dynamics of which account for metaplasticity. This novel algorithm is shown to both correctly predict homeostasis in synaptic weights and solve the problem of asymptotic stable learning in noisy states. It is shown to naturally encompass many other known types of learning rule, unifying them into a single coherent framework. The mixed presynaptic and postsynaptic dependency of the floating plasticity threshold is justified by a cascade of known molecular pathways, which leads to experimentally testable predictions.

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“…This means that the emerging connectivity can reflect the stimulating input properties despite the constraint of being located on different dendritic branches. A future step consists in incorporating more physiological details in our model (e.g., compartmental neuron model as in [4]) to verify that our results still hold. Eventually, we aim to understand how the diversity of STDP and PSP properties observed in the biology contributes to the computational power of neurons in terms of spike processing.…”

mentioning

confidence: 93%

“…A previous study [4] used additive (weight-independent) STDP with a realistic neuron model in order to examine the competition between basal and apical synapses. It was found in this configuration that, in most cases, either basal or apical synapses take over, and a balance between them is difficult to obtain.…”

mentioning

confidence: 99%