Closed-loop Neural Recording

Closed-Loop Neural Recording is a neural recording technology that integrates real-time signal acquisition, on-the-fly neural data analysis, and immediate feedback-driven stimulation or intervention within a single, continuously operating system, thereby distinguishing itself from open-loop systems by enabling dynamic bidirectional interaction with neural circuits.

22

Publications

1.5K

Citations

118

Authors

53

Institutions

Publications per year

2017–2026

12

Publications

22

1–5 of 22

Authors

118

  1. MP
    Michael P. Flynn

    University of Michigan, United States

    2 publications · 27 citations

    2

    h-index

  2. SB
    Scott Barbay

    University of Kansas Medical Center, United States

    2 publications · 29 citations

    2

    h-index

  3. SB
    Shawn B. Frost

    University of Kansas Medical Center, United States

    2 publications · 29 citations

    2

    h-index

  4. PM
    Pedram Mohseni

    Case Western Reserve University, United States

    2 publications · 29 citations

    2

    h-index

  5. CD
    Caleb Dunham

    University of Kansas Medical Center, United States

    2 publications · 29 citations

    2

    h-index

1–5 of 118

Venues

  1. Journal of Neural Engineering

    4 publications · 752 citations

    4

    h-index

  2. IEEE Journal of Solid-State Circuits

    3 publications · 365 citations

    3

    h-index

  3. 1

    h-index

  4. Circuits Systems and Signal Processing

    CSSP · 1 publications · 15 citations

    1

    h-index

  5. Frontiers in Neural Circuits

    1 publications · 76 citations

    1

    h-index

1–5