Nervous system variability and robustness from cellular feedback control

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• Tim O'Leary
• Tuesday 01 July 2014, 16:00-17:00
• Cambridge University Engineering Department, CBL Rm #438 (http://learning.eng.cam.ac.uk/Public/Directions).

If you have a question about this talk, please contact Guillaume Hennequin.

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A fundamental question in neuroscience is how neurons develop, control, and maintain their electrical signaling properties. The signaling components in individual neurons (ion channels and receptors) are continually assembled and degraded, yet an appropriate balance of these components is critical to nervous system function. From experiments we know that neurons employ feedback control to regulate ion channel and receptor turnover but the details and constraints of this process are poorly understood. In this talk I will introduce some recent modelling work that has tied together experimental data with long-standing questions about the inherent variability of ion channel expression in neurons that have well-defined electrical properties. I will show how a simple yet robust and flexible model of homeostatic regulation can be derived from generic assumptions about the molecular biology underlying channel expression. The model can generate diverse self-regulating cell types and both synaptic as well as intrinsic conductances can be regulated to make a self-assembling central pattern generator network; thus network-level homeostasis can emerge from cell-autonomous regulation rules. Additionally, I will demonstrate that homeostatic regulation critically depends on the complement of ion channels expressed in cells: in some cases loss of specific ion channels can be completely compensated, in others the homeostatic mechanisms itself can cause pathological loss of function. Finally, time permitting, I will show how regulation mechanisms can be tuned to make neurons robust to global perturbations to the biophysical properties of ion channels caused by temperature fluctuations.

This talk is part of the Computational Neuroscience series.

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