Richmond Crisostomo: Activity-Dependent Neuronal Growth and Migration: The Role of Inhibition in Network Development in Silico
| When |
May 14, 2024
from 05:15 PM to 05:45 PM |
|---|---|
| Where | Freiburg, Hansastr. 9a, Lecture Hall |
| Contact Name | Fiona Siegfried |
| Contact Phone | 0761 203 9549 |
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Abstract
The human brain's organization relies on interconnected clusters with high intrinsic connectivity. During early development, basic functional units form through modular connectivity structures. With neuronal activity regulating its dynamical self-organization, neurons establish synaptic connections by extending neurite fields to nearby neurons or migrating towards regions that provide connectivity and activity. The resulting pattern of overlaps determine local and long-range connectivity as well as spatiotemporal activity. In principle, synaptic connections and neuronal positioning are orchestrated by a homeostatic control loop, stabilizing activity towards a specific target level.
Associated morphological and functional differentiation of such networks are regulated by activity-dependent structural plasticity, suggesting opposing influences of excitatory and inhibitory signals on this process of which specific mechanisms remain poorly understood. This motivates investigation into the synergistic effect of excitatory and inhibitory neurons on the structural differentiation of the network. Of particular interest is the role of maturing inhibition in promoting network modularity and stability; both are beneficial for neural computation.
Our ongoing work focuses on the impact of excitatory-inhibitory interaction on the structure of developing networks. Utilizing computational models, we disentangle interactions among growth, migration, and inhibition -- elucidating their role in shaping connectivity and activity in abstracted neuronal networks. Preliminary simulations with asymmetric interactions between excitatory and inhibitory neurons indicate that inhibition may be crucially involved in the shaping of network architecture.