Topic
Synaptic gating
About: Synaptic gating is a research topic. Over the lifetime, 14 publications have been published within this topic receiving 237 citations.
Papers
2 Sep 2021
TL;DR: The results show that optimal range of glutamate and GABA neurotransmitter concentrations subserve as the dynamic working point of the brain, that is, the state of heightened metastability observed in empirical blood-oxygen-level-dependent signals.
Abstract: Previous computational models have related spontaneous resting-state brain activity with local excitatory-inhibitory balance in neuronal populations. However, how underlying neurotransmitter kinetics associated with E-I balance govern resting-state spontaneous brain dynamics remains unknown. Understanding the mechanisms by virtue of which fluctuations in neurotransmitter concentrations, a hallmark of a variety of clinical conditions, relate to functional brain activity is of critical importance. We propose a multiscale dynamic mean field (MDMF) model-a system of coupled differential equations for capturing the synaptic gating dynamics in excitatory and inhibitory neural populations as a function of neurotransmitter kinetics. Individual brain regions are modeled as population of MDMF and are connected by realistic connection topologies estimated from diffusion tensor imaging data. First, MDMF successfully predicts resting-state functional connectivity. Second, our results show that optimal range of glutamate and GABA neurotransmitter concentrations subserve as the dynamic working point of the brain, that is, the state of heightened metastability observed in empirical blood-oxygen-level-dependent signals. Third, for predictive validity the network measures of segregation (modularity and clustering coefficient) and integration (global efficiency and characteristic path length) from existing healthy and pathological brain network studies could be captured by simulated functional connectivity from an MDMF model.
37 citations
TL;DR: The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neurons model could be a valuable tool in simulations where behavioral plasticity is required.
16 citations
TL;DR: Using standardized voltage and synaptic gating variable waveforms associated with a spike, it is demonstrated that the functional architecture of a small network of model neurons can be established.
Abstract: Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.
8 citations
TL;DR: In this article, the contribution of parvalbumin interneurons to basal and input driven sustained synaptic inhibition in GCs and semilunar granule cells (SGCs), a sparse morphologically distinct dentate projection neuron subtype are investigated.
Abstract: Strong inhibitory synaptic gating of dentate gyrus granule cells (GCs), attributed largely to fast-spiking parvalbumin interneurons (PV-INs), is essential to maintain sparse network activity needed for dentate dependent behaviors. However, the contribution of PV-INs to basal and input driven sustained synaptic inhibition in GCs and semilunar granule cells (SGCs), a sparse morphologically distinct dentate projection neuron subtype are currently unknown. We find that although basal inhibitory postsynaptic currents (IPSCs) are more frequent in SGCs and optical activation of PV-INs elicited IPSCs in both GCs and SGCs, optical suppression of PV-INs failed to reduce IPSC frequency in either cell type. Amplitude and kinetics of IPSCs evoked by perforant path activation were not different between GCs and SGCs. However, the robust increase in sustained polysynaptic IPSCs elicited by paired afferent stimulation was lower in SGCs than in simultaneously recorded GCs. Optical suppression of PV-IN selectively reduced sustained IPSCs in SGCs but not in GCs. These results demonstrate that PV-INs, while contributing minimally to basal synaptic inhibition in both GCs and SGCs in slices, mediate sustained feedback inhibition selectively in SGCs. The temporally selective blunting of activity-driven sustained inhibitory gating of SGCs could support their preferential and persistent recruitment during behavioral tasks.
5 citations
Dissertation•
1 May 2010
TL;DR: A difference is discovered in the results of the two spiny dendrite models which suggests that the form of spine connectivity is important and it is shown that both models have the capacity to act as a robust filter and that a branched structure can perform logic computations.
Abstract: The dendritic tree provides the surface area for synaptic connections between the 100 billion neurons in the brain. 90% of excitatory synapses are made onto dendritic spines which are constantly changing shape and strength. This adaptation is believed to be an important factor in learning, memory and computations within the dendritic tree. The environment in which the neuron sits is inherently noisy due to the activity in nearby neurons and the stochastic nature of synaptic gating. Therefore the effects of noise is a very important aspect in any realistic model. This work provides a comprehensive study of two spiny dendrite models driven by different forms of noise in the spine dynamics or in the membrane voltage. We investigate the effect of the noise on signal propagation along the dendrite and how any correlation in the noise may affect this behaviour. We discover a difference in the results of the two models which suggests that the form of spine connectivity is important. We also show that both models have the capacity to act as a robust filter and that a branched structure can perform logic computations.
4 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 2 |
| 2019 | 1 |
| 2018 | 1 |
| 2016 | 1 |
| 2014 | 2 |
| 2013 | 1 |