Self-repair in a bidirectionally coupled astrocyte-neuron (AN) system based on retrograde signaling

Abstract

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 (PR) synapses; the enhancement of the transmission PR of a healthy neighboring synapse by retrograde signaling can enhance the transmission PR of the “faulty” synapse (repair). Our model of self-repair is based on recent research showing that retrograde signaling via astrocytes can increase the PR of neurotransmitter release at damaged or low transmission PR 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 PR. 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.

Biophysically based computational models of astrocyte ~ neuron coupling and their functional significance

“…In the paper by Wade et al (2012) it is shown that retrograde signaling via astrocytes may underpin self-repair in the brain. Their model of self-repair is based on recent research showing that retrograde signaling mediated by astrocytes increases the probability of neurotransmitter release at damaged or low transmission probability synapses.…”

From in silico astrocyte cell models to neuron-astrocyte network models: A review

“…Neuron-astrocyte network models have also been devised to study the potential role of astrocytes on network robustness. When the communication between synapses fail for example due to neurodegenerative diseases, astrocytes could modulate IP3 diffusion via gap junctions to maintain Ca2+ oscillations and subsequently the global endocannabinoid-mediated synaptic potentiation signal in a syncytia (Perea and Araque 2005;Wade et al 2012). After introducing B-STDP learning rule into the model, which combines spike-timingdependent plasticity and Bienenstock, Cooper, and Munro learning rules, the firing rate of neurons with damaged synapses recovers over time (Naeem et al, 2015).…”

Fault-Tolerant Learning in Spiking Astrocyte-Neural Networks on FPGAs

“…Interneuron-astrocyte signaling dynamically affects excitatory neurotransmission. Astrocytes, by the action of retrograde signaling [12], regulates transmission of spikes between two layers of the network (A * in Figure 1). For example, under low f pre , the interneuron-astrocyte interaction leads to an inhibitory effect representing a low transmission probability (P R) with the associated neuron.…”

“…The Bienenstock, Cooper, and Munro (BCM) synaptic modification rule modulates the postsynaptic activity if it deviates from the required response [9], [10]. In this paper, we use a self-repairing learning rule [11] that uses evidence [12] to explain how the STDP and BCM learning rules co-exist to give a learning function that is under the control of postsynaptic neuron activity.…”