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Area of Science:

  • Bioelectronic Sensors
  • Neuroscience
  • Materials Science

Background:

  • Conventional silicon bioelectronic sensors are rigid and energy-intensive.
  • Organic electrochemical neuron (OECN)-based sensors show promise but face limitations in firing rate, energy efficiency, and scalability.

Purpose of the Study:

  • To present a novel OECN-based sensor for rapid and energy-efficient neural signal detection.
  • To enable real-time closed-loop neurostimulation applications.
  • To overcome limitations of existing bioelectronic interfaces.

Main Methods:

  • Development of an event-driven OECN-based sensor.
  • Characterization of sensor response time and firing rate capabilities.
  • Integration with microelectrodes for closed-loop neuromodulation.
  • In vivo testing for suppression of pathological oscillations.

Main Results:

  • The OECN sensor achieves response times within ~1 ms and generates voltage pulses up to 1.1 kHz.
  • The sensor operates at an ultra-low energy consumption of ~40 pJ per spike.
  • Accurate detection of hippocampal interictal epileptiform discharges was demonstrated.
  • Successful in vivo closed-loop neuromodulation to suppress pathological sleep spindle oscillations was achieved.

Conclusions:

  • The developed OECN-based sensors offer rapid, energy-efficient neural signal detection.
  • These sensors are suitable for closed-loop neurostimulation and neuromodulation.
  • The technology presents a promising next-generation solution for implantable bioelectronics in energy-constrained environments.