Self-repair in a Bidirectionally Coupled Astrocyte-Neuron (AN) System based on Retrograde Signaling - Wade, John; McDaid, Liam J.; Harkin, Jim; Crunelli, Vincenzo; Kelso, Scott (Frontiers in Computational Neuroscience, 2012)
In this paper we demonstrate that retrograde signaling via astrocytes may underpin self-repair in the brain. Faults manifest themselves in silent or near silent neurons caused by low transmission probability synapses; the enhancement of the transmission probability of a healthy neighbouring synapse by retrograde signaling can enhance the transmission probability of the “faulty” synapse (repair). Our model of self-repair is based on recent research showing that retrograde signaling via astrocytes can increase the probability of neurotransmitter release at damaged or low transmission probability synapses. The model demonstrates that astrocytes are capable of bidirectional communication with neurons which leads to modulation of synaptic activity, and that indirect signaling through retrograde messengers such as endocannabinoids leads to modulation of synaptic transmission probability. Although our model operates at the level of cells, it provides a new research direction on brain-like self-repair which can be extended to networks of astrocytes and neurons. It also provides a biologically inspired basis for developing highly adaptive, distributed computing systems that can, at fine levels of granularity, fault detect, diagnose and self-repair autonomously, without the traditional constraint of a central fault detect/repair unit.