A theory of Gap Junction Plasticity
by Mr. Eyal Fishel
Dept. Of Physics, Ben-Gurion University Of The Negev
at Biological and soft-matter physics
Thu, 04 Jun 2020, 12:00
ZOOM meeting ID: 919-198-85007 Password: 2q35r3
Rhythms in the brain have been reported in relation with a wide range of cognitive tasks. Moreover, changes and modifications to the normal rhythmic activity have been linked to pathologies and mental disorders. Although the functional role of rhythmic activity in the brain is yet undecided, it is clear that rhythmic activity is abundant in the brain. Numerous theoretical studies investigated the underlying mechanisms for rhythmic activity. However, all these studies require a certain degree of fine tuning of parameters (such as the strengths of synaptic connectivity) to generate the desired rhythmic activity. This raises the question:
What possible mechanism can regulate network parameters in order to stabilize a specific rhythm?
It was suggested that a synaptic learning rule, known as spike-timing-dependent-plasticity, can provide such a mechanism. However, synaptic connectivity is not the only means of neuronal interaction. Gap junctions, intercellular channels permitting a bi-directional flow of ionic currents across paired cells, have been shown to facilitate synchronized neural activities. Moreover, it has been claimed that Gap junctions have an important role in governing rhythmic activity. Recently, experimental studies demonstrated that similar to synaptic connectivity, Gap junctions also undergo activity-dependent plasticity.
Here we study the hypothesis that Gap junction plasticity may (also) serve as a mechanism for stabilizing and regulating the desired rhythmic activity in the brain. We propose that Gap junction undergo activity dependent plastic changes that take into account the temporal and causal relations and suggest a learning rule that generalizes synaptic spike-timing dependent plasticity. We then study under what conditions does our hypothesized gap junction plasticity rule stabilize the resultant oscillations? How do the features characterizing the plasticity rule govern the rhythmic activities?
We address these questions in the framework of a modelling study. We investigate Gap junction plasticity in a model of reciprocally connected neuronal network via Gap junctions. Analyzing the rhythmic activity as function of the Gap junction couplings provides the phase diagram of the system. Assuming Gap junction plasticity occurs at a slower timescale than the rhythmic activity we use the separation of timescales and develop the Gap junction plasticity dynamics in the limit of slow learning. Thus, Gap junction plasticity induces a flow on the phase diagram of the system. Next, we analyze, analytically and numerically under what conditions can Gap junction plasticity stabilize a specific rhythmic activity, and if so, what features of the Gap junction plasticity rule govern the resultant rhythmic activity. Thus, our theory demonstrates that in principle Gap junction plasticity can provide the stabilizing mechanism for rhythmic activity. The constraints on the plasticity rule obtained from our theory, provide further predictions for the validity of our theory.
Join URL: https://zoom.us/j/91919885007?pwd=WVRtRjlqQ1lDZkJ1cmJGbEcwSW4wZz09
Created on 23-02-2020 by Granek, Rony (rgranek)
Updaded on 16-06-2020 by Granek, Rony (rgranek)