Here, we present a simplified, biophysically inspired network model that incorporates multiple plasticity processes and explains linking of information at three different levels: (a) learning of a single associative memory (b) rescuing of a weak memory when paired with a strong one and (c) linking of multiple memories across time. By dissecting synaptic from intrinsic plasticity and neuron-wide from dendritically restricted protein capture, the model reveals a simple, unifying principle: Linked memories share synaptic clusters within the dendrites of overlapping populations of neurons
Model Type: Realistic Network
Cell Type(s): Abstract integrate-and-fire leaky neuron with dendritic subunits
Model Concept(s): Active Dendrites
Simulation Environment: C or C++ program; C or C++ program (web link to model)
Implementer(s): Kastellakis, George [gkastel at gmail.com]
References:
Kastellakis G, Silva AJ, Poirazi P. (2016). Linking Memories across Time via Neuronal and Dendritic Overlaps in Model Neurons with Active Dendrites. Cell reports. 17 [PubMed]