Flexible connectivity under physiological constraints
Year: 2019
Type: conference-paper
Abstract: Physiological constraints define allowed configurations of synaptic weights for neural circuits. How this affects circuit function remains little understood. We examine the hypothesis that neural circuits may be structured to make constraints flexible: to allow many configurations of synaptic weights. The size of these allowed weight spaces depends on the number of inputs to a neuron: its connectivity degree. We predict degree distributions that optimize simple constraints on a neuron’s total synaptic weight. We also find the degrees of connectivity that maximize the number of allowed synaptic weight configurations. To test these predictions, we examine reconstructions of the mushroom bodies from the first instar larva and the adult Drosophila melanogaster. Overall, flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring.
Authors: Gabriel Ocker, Michael Buice
Institution: Allen Institute for Brain Science
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W2970793603