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    This study introduces a novel CMOS neuromorphic circuit inspired by astrocyte signaling for self-repairing brain functions. The circuit effectively compensates for damaged synapses, paving the way for advanced neuro-inspired computing systems.

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    Area of Science:

    • Neuroscience
    • Electrical Engineering
    • Computer Science

    Background:

    • The brain possesses self-repairing capabilities for damaged synapses.
    • Astrocyte retrograde signaling modulates synaptic transmission and aids in neural repair.
    • Bidirectional astrocyte-neuron collaboration is crucial for the brain's self-repair mechanisms.

    Purpose of the Study:

    • To propose a CMOS neuromorphic circuit with self-repairing capabilities.
    • To design an analog integrated circuit based on astrocyte signaling.
    • To investigate the circuit's ability to compensate for damaged synapses.

    Main Methods:

    • Developed a computational model of the brain's self-repair process.
    • Designed a novel analog integrated circuit using 180-nm CMOS technology.
    • Employed astrocyte signaling principles to achieve fault tolerance.

    Main Results:

    • The proposed analog circuit successfully compensates for damaged synapses.
    • The circuit modifies voltage signals of healthy synapses to recompense for faults.
    • Demonstrated functionality across a wide range of frequencies.

    Conclusions:

    • The developed neuromorphic circuit exhibits self-repairing capabilities.
    • This fault-tolerant circuit is a promising candidate for future silicon neuronal systems.
    • Potential applications include neurorobotic and neuro-inspired circuits.