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Neural Recording System

Explore the significance and enhancement of neural network recording systems in mapping the brain, with solutions for better performance in medical research, mental health, and more. Dive into amplifier design improvements for efficient signal processing.

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Neural Recording System

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  1. Neural Recording System By: Ivana Duvnjak Stephen Kilpatrick Dawit Fsiha

  2. Outline • What is a Neural Network Recording System? • Why are they important? • How can they be improved? • Some possible solutions • Analysis of some solutions • Conclusions

  3. Brain sends electrical signals - Neurons Sent through axons Electrical Signals processed by synapses Mapping the brain Neural Network Recoding Systems

  4. Applications • Medical Research • Mental Performance • Mental Illness • Sleep Disorders • Etc.

  5. Electrode Amplifier Multiplexer Transmitter Receiver Subsystems

  6. Block Diagram of System DATA Electrode Amplifier Amplifier Electrode Tx Rx Electrode Amplifier POWER MUX

  7. Possible Improvements • Areas to improve in the neural recording system • Electrodes • Amplifier • Multiplexer • Transmitter • Receiver

  8. Neural LNA Amplifier • Functions • Power dissipation must kept low • Must reject noise ( flicker noise) • Amplifying a weak signal received from the electrodes • Must reject the DC offset created at the electrodes-Tissue interface

  9. Neural Amplifier Requirements • Power dissipation • Bandwidth requirement • Gain • Stability • Overall size

  10. Amplifier Solutions: Design I Neural Amplifier Circuit OTA Design

  11. Amplifier Solutions: Design II Neural Amplifier Circuit OTA Design

  12. Design I: Simulation Results • 10 pW power consumption • 39.974dB gain • Low-cutoff frequency: 0.4Hz • High-cutoff frequency: 7.852kHz • Area: 0.16mm2 • Stable

  13. Design II: Simulation Results • 11.5 pW power consumption • 40.362dB gain • Low-cutoff frequency: 83.114Hz • High-cutoff frequency: 32.526kHz • Area: 0.091mm2 • Stable

  14. Comparison of Designs Table 1. Summary of simulation results for the neural amplifiers

  15. Conclusions • Both designs meet the requirements of: • Power consumption • Stability • Size • DC offset rejection • Design I is significantly better, due to the more desirable bandwidth requirements.

  16. Implementation

  17. References

  18. Exit(0); Questions?

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