Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
The mf-GrC relay provides the case of a synapse at which elementary neurotransmission mechanisms are particularly well understood allowing a precise investigation of synaptic plasticity. An interesting consequence is that a presynaptic mechanism of LTP cou ...
Synaptic transmission in the neocortex is dynamic, such that the magnitude of the postsynaptic response changes with the history of the presynaptic activity. Therefore each response carries information about the temporal structure of the preceding presynap ...
Maximization of information transmission by a spiking-neuron model predicts changes of synaptic connections that depend on timing of pre- and postsynaptic spikes and on the postsynaptic membrane potential. Under the assumption of Poisson firing statistics, ...
Single-particle electron microscopy (EM) combined with biochemical measurements revealed the molecular shape of SAP97 and a monomer-dimer transition that depended on the N-terminal L27 domain. Overexpression of SAP97 drove GluR1 to synapses, potentiated AM ...
The impact was examined of exposing rats to two life experiences of a very different nature (stress and learning) on synaptic structures in hippocampal area CA3. Rats were subjected to either (i) chronic restraint stress for 21 days, and/or (ii) spatial tr ...
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabilistic optimality criterion. Our approach allows us to obtain quantitative res ...
The short-term plasticity of synaptic transmission between excitatory neurons within a barrel of layer 4 rat somatosensory neocortex was investigated. Action potentials in presynaptic neurons at frequencies ranging from 1 to 100 Hz evoked depressing postsy ...
Several formulations of correlation-based Hebbian learning are reviewed. On the presynaptic side, activity is described either by a firing rate or by presynaptic spike arrival. The state of the postsynaptic neuron can be described by its membrane potential ...
We derive an optimal learning rule in the sense of mutual information maximization for a spiking neuron model. Under the assumption of small fluctuations of the input, we find a spike-timing dependent plasticity (STDP) function which depends on the time co ...
In this thesis, we studied two systems important for synaptic plasticity, one presynaptic and another postsynaptic. The protein complex composed of VAMP 2, SNAP-25 and syntaxin 1 (SNARE complex) is essential for docking and fusion of neurotransmitter-fille ...