Synaptic tagging and capture in a biophysical model
There is wide consensus that synaptic plasticity (prominently long-term potentiation; LTP) is the underlying mechanism for learning and memory storage (cf Nabavi 2014). Open issues include the molecular pathways and networks and structural processes leading to functional and structural changes at th...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2014-06-01
|
| Series: | Frontiers in Systems Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/conf.fnsys.2014.05.00048/full |
| _version_ | 1818305234618810368 |
|---|---|
| author | Benjamin Auffarth |
| author_facet | Benjamin Auffarth |
| author_sort | Benjamin Auffarth |
| collection | DOAJ |
| description | There is wide consensus that synaptic plasticity (prominently long-term potentiation; LTP) is the underlying mechanism for learning and memory storage (cf Nabavi 2014). Open issues include the molecular pathways and networks and structural processes leading to functional and structural changes at the synaptic and dendritic levels in terms of channels and spines. Synaptic tagging and capture (STC; Frey and Morris 1997; Redondo and Morris 2011) is a predominant model for investigating LTP. According to the STC hypothesis, the mechanisms underlying LTP can be separated into independent processes for the generation of plasticity-related products (PRPs) and the setting of a synaptic tag.
We know from many studies that dendritic branches act as computational units, given the availability of ionic mechanisms and local compartmentalization of synaptic interactions (Branco and Hausser 2010; Poirazi et al 2003; Frey, 2001). In order to investigate the effects of dendritic compartmentalization on memory formation, we implemented a model of STC in the NEURON platform, incorporating both mechanisms for short-term plasticity and late LTP (l-LTP). Synapses are confined within spines and include numerous biophysical channels and receptors. Our l-LTP mechanism demonstrates the association of memories to synapses and dendrites. We show that local diffusion leads to increases in synaptic weights for neighboring spines, showing the plausibility of the synaptic clustering in memory storage (Poirazi 2001; Govindarajan 2006).
The first figure shows the dendritic excitatory postsynaptic potential on tetanic stimulation of 2x100Hz. The second figure shows consolidated synaptic plasticity at the stimulated synapse (blue), and two neighboring synapses (green and red). |
| first_indexed | 2024-12-13T06:23:21Z |
| format | Article |
| id | doaj.art-8a274c16ea664efa9a59420bb8f9b1a8 |
| institution | Directory Open Access Journal |
| issn | 1662-5137 |
| language | English |
| last_indexed | 2024-12-13T06:23:21Z |
| publishDate | 2014-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Systems Neuroscience |
| spelling | doaj.art-8a274c16ea664efa9a59420bb8f9b1a82022-12-21T23:56:48ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372014-06-01810.3389/conf.fnsys.2014.05.0004882076Synaptic tagging and capture in a biophysical modelBenjamin Auffarth0IMBB, FORTHThere is wide consensus that synaptic plasticity (prominently long-term potentiation; LTP) is the underlying mechanism for learning and memory storage (cf Nabavi 2014). Open issues include the molecular pathways and networks and structural processes leading to functional and structural changes at the synaptic and dendritic levels in terms of channels and spines. Synaptic tagging and capture (STC; Frey and Morris 1997; Redondo and Morris 2011) is a predominant model for investigating LTP. According to the STC hypothesis, the mechanisms underlying LTP can be separated into independent processes for the generation of plasticity-related products (PRPs) and the setting of a synaptic tag. We know from many studies that dendritic branches act as computational units, given the availability of ionic mechanisms and local compartmentalization of synaptic interactions (Branco and Hausser 2010; Poirazi et al 2003; Frey, 2001). In order to investigate the effects of dendritic compartmentalization on memory formation, we implemented a model of STC in the NEURON platform, incorporating both mechanisms for short-term plasticity and late LTP (l-LTP). Synapses are confined within spines and include numerous biophysical channels and receptors. Our l-LTP mechanism demonstrates the association of memories to synapses and dendrites. We show that local diffusion leads to increases in synaptic weights for neighboring spines, showing the plausibility of the synaptic clustering in memory storage (Poirazi 2001; Govindarajan 2006). The first figure shows the dendritic excitatory postsynaptic potential on tetanic stimulation of 2x100Hz. The second figure shows consolidated synaptic plasticity at the stimulated synapse (blue), and two neighboring synapses (green and red).http://journal.frontiersin.org/Journal/10.3389/conf.fnsys.2014.05.00048/fullDendritesHippocampusNeuronal PlasticityLTPpyramidal neuronfunctional connectivityCA1compartmental modelingCA1 pyramidal neuronLTP (Long Term Potentiation)STP |
| spellingShingle | Benjamin Auffarth Synaptic tagging and capture in a biophysical model Frontiers in Systems Neuroscience Dendrites Hippocampus Neuronal Plasticity LTP pyramidal neuron functional connectivity CA1 compartmental modeling CA1 pyramidal neuron LTP (Long Term Potentiation) STP |
| title | Synaptic tagging and capture in a biophysical model |
| title_full | Synaptic tagging and capture in a biophysical model |
| title_fullStr | Synaptic tagging and capture in a biophysical model |
| title_full_unstemmed | Synaptic tagging and capture in a biophysical model |
| title_short | Synaptic tagging and capture in a biophysical model |
| title_sort | synaptic tagging and capture in a biophysical model |
| topic | Dendrites Hippocampus Neuronal Plasticity LTP pyramidal neuron functional connectivity CA1 compartmental modeling CA1 pyramidal neuron LTP (Long Term Potentiation) STP |
| url | http://journal.frontiersin.org/Journal/10.3389/conf.fnsys.2014.05.00048/full |
| work_keys_str_mv | AT benjaminauffarth synaptictaggingandcaptureinabiophysicalmodel |