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    This study introduces a novel digital processor for analyzing neural signal phase synchronization. Its low-power, compact design is ideal for neural prosthetics and brain activity mapping.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Digital Signal Processing

    Background:

    • Neural signal analysis is crucial for understanding brain function and treating neurological disorders.
    • Accurate phase synchronization measurement is key for assessing neural connectivity.

    Purpose of the Study:

    • To present an integer-based digital processor for calculating phase synchronization between neural signals.
    • To demonstrate a low-power and compact hardware solution for neural signal processing.

    Main Methods:

    • Developed an integer-based digital processor utilizing elementary digital blocks (registers, counters, adders).
    • The processor measures time periods between consecutive minima of neural signals.
    • Fabricated the processor using a 0.18-μm CMOS process.

    Main Results:

    • The processor achieves phase synchronization calculation with high efficiency.
    • Achieved a small chip area of 0.05 mm².
    • Demonstrated ultra-low power consumption of 15 nW at 0.5 V supply and 1024 S/s input rate.

    Conclusions:

    • The developed processor offers a highly efficient, low-area, and low-power solution for neural signal phase synchronization.
    • This technology is suitable for integration into closed-loop neural prostheses for epilepsy treatment.
    • Enables advanced assessment of neural assembly activity and functional connectivity maps.