11:30 AM - SB04.08.04
Closed-Loop Biomimetic Synapse for Neuromorphic Network Design
Ugo Bruno1,Daniela Rana1,Francesca Santoro1
Italian Institute of Technology1
As conventional silicon based computing techniques are reaching their limits in terms of energy consumption and density, neuromorphic platforms are emerging as new computational paradigm, with the ultimate goal of replicating the efficiency of the brain in terms of parallel computation. Among the plethora of the available materials and structures, organic electrochemical transistors (OECTs) have emerged for their natural ionic-to-electronic signal transduction, biocompatibility and possibility of operating in aqueous environment. In particular, PEDOT:PSS based OECTs have been exploited to recapitulate neurotransmitter-mediated synaptic plasticity, in which the oxidation of a neurotransmitter modulates the doping state of the transistor, resulting in a change in device conductivity, de facto emulating the synaptic conditioning naturally occurring in biological synapses.
While successfully recapitulating spike-dependent plasticity, this approach still lacks the self-regulation mechanisms naturally found in neuronal networks: when the post-synaptic neuron is engaged in the neurotransmitter-mediated communication, receptor recycling occurs, while astrocytes provide a feedback onto the presynaptic terminal, to reduce or increase the release of such neurotransmitter. Moreover, the PEDOT:PSS-based neuromorphic transistor, if used as a building block of an artificial network, would lead to a continuous de-doping of the devices, ultimately leading to the exhaustion of the network dynamics, because of the unidirectional modulation of the synaptic weight.
Taking inspiration from the nigrostriatal DA pathway, in which the endogenously generated H2O2 activates K+ channels, inhibiting DA neuron firing, a closed-loop synapse is proposed, in which the bidirectional modulation of the synaptic weight is shown. In particular, the output current of the device closes a feedback loop, allowing for a controller to drive a microfluidic system. As a result, an influx of dopamine (DA), and its subsequent oxidation, is used to cause the de-doping of both OECT gate and channel, while the inverse reaction can be induced by the introduction of hydrogen peroxide (H2O2).
The presence of the control system proposed here introduces the astrocytes-like effect of presynaptic input regulation, naturally found in neural networks. This enables for synaptic weight control while avoiding the uncontrolled doping/de-doping of the PEDOT:PSS.
Ultimately, this platform paves the way for the creation of biomimetic complex systems. A network of artificial neurons can be designed in which the output depends on the presence of a neurotransmitter while each node can still be individually controlled, to induce and study topology-dependent dynamics propagation across the network.
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