簡易檢索 / 詳目顯示

研究生: 黃千恩
Huang, Chian-En
論文名稱: 應用於腦神經傳導物質偵測的矽光子探針與寬動態範圍讀出電路
Silicon Photonic Probe and Wide Dynamic Range Readout Circuit for Neurotransmitter Detection in Brain
指導教授: 陳新
Chen, Hsin
口試委員: 李明昌
Li, Ming-Chang
吳玉威
Wu, Yu-Wei
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電子工程研究所
Institute of Electronics Engineering
論文出版年: 2025
畢業學年度: 113
語文別: 英文
論文頁數: 68
中文關鍵詞: 神經訊號讀取電路矽光子探針光纖光度法
外文關鍵詞: Neural signal readout circuit, Silicon photonic probe, Fiber photometry system
相關次數: 點閱:117下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 光纖光度系統廣泛用於監測大腦中的神經活動;然而,傳統系統通常依賴於體積龐大的光學設備,不容易由實驗動物攜帶。這種限制迫使動物在數據採集期間保持固定位置,可能影響其自然行為並降低神經信號測量的準確性。

    本研究提出了一種新型光纖光度系統,結合矽光子晶片與寬動態範圍讀取電路。矽光子晶片整合了關鍵的光學元件,包括邊緣耦合器、波導、光柵耦合器和PIN光電二極體,能夠實現藍光傳輸進入腦組織以及偵測神經螢光信號。為了設計讀取電路,我們構建了一個二維光電二極體模型,用來估算光電流強度範圍,從飛米安培到奈米安培不等。在此模型的基礎上,讀取電路設計包含電流前置放大器、電流分配器和對數放大器,用於放大及處理由PIN光電二極體生成的寬動態範圍光電流信號。最終,量測結果顯示讀取電路實現了70dB的動態範圍,並將最低可檢測電流降至皮米安培。

    總結來說,這套雙晶片系統成功將光纖光度技術小型化,在動物腦部植入應用方面展現了極大的潛力。此項技術進步使得能夠更精準地監測特定腦區的神經活動,為神經疾病的研究與治療策略發展提供了重要貢獻。


    Fiber photometry systems are widely employed to monitor neural activity in the brain; however, conventional setups often rely on bulky optical equipment, limiting their portability for experimental animals. This constraint confines animals to fixed positions during data collection, potentially influencing their natural behavior and compromising the accuracy of neural signal measurements.

    This research introduces a novel fiber photometry system that integrates silicon photonic chips with wide dynamic range readout circuits. The silicon photonic chip incorporates key optical components, including edge couplers, waveguides, grating couplers, and PIN photodiodes, to facilitate blue-light transmission into brain tissue and the subsequent detection of neuronal fluorescence signals. To inform the design of the readout circuit, a two-dimensional photodiode model was developed to estimate photocurrent intensities ranging from femtoamperes to nanoamperes. Guided by this model, the readout circuit—comprising a current pre-amplifier, current splitter, and logarithmic amplifier—was designed to amplify and process these wide-dynamic-range photocurrent signals generated by the PIN photodiodes. The measurement results indicate that the readout circuit achieves a dynamic range of 70 dB and detect currents as low as the picoampere level.

    In summary, this dual-chip system effectively miniaturizes fiber photometry technology, offering significant potential for brain implantation in animals. This advancement facilitates precise monitoring of neural activity in specific brain regions, paving the way for improved understanding and treatment of neurological disorders.

    Contents Abstract I Abstract (Chinese) II Acknowledgments (Chinese) III Contents IV Chapter 1 Introduction 1 1.1 Fiber Photometry System . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Advanced Fiber Photometry System . . . . . . . . . . . . . . . . . . . 3 1.3 Silicon Photonic Probe and Wide Dynamic Range Readout Circuit . . 5 Chapter 2 Silicon Photonic Probe 7 2.1 Probe Structure and Light Propagation . . . . . . . . . . . . . . . . . 9 2.2 Grating Coupler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.3 PIN Photodiode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 PIN Photodiode Model Contruction . . . . . . . . . . . . . . . 14 2.3.2 PIN Photodiode Simulation Result . . . . . . . . . . . . . . . . 15 2.4 Layout of Silicon Photonic Probe . . . . . . . . . . . . . . . . . . . . 17 Chapter 3 Wide-Dynamic-Range Readout Circuit 19 3.1 Minimum Detectable Current Range . . . . . . . . . . . . . . . . . . . 22 3.2 Logarithmic Amplifier . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.2.1 DC Analysis of Logarithmic Amplifier . . . . . . . . . . . . . . 24 3.2.2 AC Analysis of Logarithmic Amplifier . . . . . . . . . . . . . . 27 3.3 Translinear Current Pre-Amplifier . . . . . . . . . . . . . . . . . . . . 29 3.3.1 Translinear Principle . . . . . . . . . . . . . . . . . . . . . . . 29 IV 3.3.2 Design and Simulation of Translinear Circuit . . . . . . . . . . 31 3.4 Current Splitter 1 for Biasing Current . . . . . . . . . . . . . . . . . . 33 3.4.1 Operation principle . . . . . . . . . . . . . . . . . . . . . . . . 33 3.4.2 DC Analysis of Current Splitter 1 . . . . . . . . . . . . . . . . 35 3.5 Current Splitter 2 for Built-in Test . . . . . . . . . . . . . . . . . . . . 38 3.5.1 Operation Principle . . . . . . . . . . . . . . . . . . . . . . . . 38 3.6 Post Simulation Result . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.6.1 Whole System Iin to Vout Curve . . . . . . . . . . . . . . . . . 40 3.6.2 Current Pre-amplifier Amplification ratio . . . . . . . . . . . . 41 3.6.3 Current Splitter 1 Circuit . . . . . . . . . . . . . . . . . . . . . 46 3.6.4 Current Splitter 2 Circuit . . . . . . . . . . . . . . . . . . . . . 47 3.7 Layout of Readout Circuit . . . . . . . . . . . . . . . . . . . . . . . . 48 3.8 PIN of Readout Circuit . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Chapter 4 Measurement 51 4.1 Silicon Photonic Probe . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.1.1 Grating and Edge Coupler Measurement Result . . . . . . . . 53 4.1.2 PIN Photodioe Measurement Result . . . . . . . . . . . . . . . 56 4.2 Wide Dynamic Range Readout Circuit . . . . . . . . . . . . . . . . . 58 4.2.1 PCB Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 4.2.2 Readout Circuit Measurement Result . . . . . . . . . . . . . . 59 4.3 Performance Summary . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Chapter 5 Conclusion 64 Bibliography 66

    Bibliography
    [1] S. Ayub, L. J. Gentet, R. Fi´ath, M. Schwaerzle, M. Borel, F. David, P. Barth´o,
    I. Ulbert, O. Paul, and P. Ruther. “Hybrid intracerebral probe with integrated
    bare LED chips for optogenetic studies”. In: Biomedical Microdevices 19 (2017),
    pp. 1–12.
    [2] A. Basu, R. W. Robucci, and P. E. Hasler. “A low-power, compact, adaptive
    logarithmic transimpedance amplifier operating over seven decades of current”.
    In: IEEE Transactions on Circuits and Systems I: Regular Papers 54.10 (2007),
    pp. 2167–2177.
    [3] A. Burton, S. N. Obaid, A. V´azquez-Guardado, M. B. Schmit, T. Stuart, L. Cai,
    Z. Chen, I. Kandela, C. R. Haney, E. A. Waters, et al. “Wireless, battery-free
    subdermally implantable photometry systems for chronic recording of neural
    dynamics”. In: Proceedings of the National Academy of Sciences 117.6 (2020),
    pp. 2835–2845.
    [4] T. Delbr¨uck and A. V. Schaik. “Bias current generators with wide dynamic
    range”. In: Analog Integrated Circuits and Signal Processing 43 (2005), pp. 247–
    268.
    [5] G. Di Patrizio Stanchieri, A. De Marcellis, G. Battisti, M. Faccio, E. Palange,
    and U. Guler. “A 1.8 V low-power low-noise high tunable gain TIA for CMOS
    integrated optoelectronic biomedical applications”. In: Electronics 11.8 (2022),
    p. 1271.
    [6] E. Genco, K. Van Oosterhout, M. Timmermans, and M. Fattori. “A High-Gain
    Low-Noise Transimpedance Amplifier based on Active-Feedback Network”. In:
    2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI).
    IEEE. 2023, pp. 166–171.
    [7] M. Ghioni, F. Zappa, V. P. Kesan, and J. Warnock. “A VLSI-compatible high-
    speed silicon photodetector for optical data link applications”. In: IEEE Trans-
    actions on Electron Devices 43.7 (1996), pp. 1054–1060.
    [8] Q. Guo, J. Zhou, Q. Feng, R. Lin, H. Gong, Q. Luo, S. Zeng, M. Luo, and L. Fu.
    “Multi-channel fiber photometry for population neuronal activity recording”.
    In: Biomedical optics express 6.10 (2015), pp. 3919–3931.
    66
    [9] M. N. Khiarak, E. Martianova, C. Bories, S. Martel, C. D. Proulx, Y. De Kon-
    inck, and B. Gosselin. “A Wireless Fiber Photometry System Based on a High-
    Precision CMOS Biosensor With Embedded Continuous-Time
    \
    Sigma\Delta M odulation”. In: IEEE transactions on biomedical circuits and sys-
    tems 12.3 (2018), pp. 495–509.
    [10] T.-i. Kim, J. G. McCall, Y. H. Jung, X. Huang, E. R. Siuda, Y. Li, J. Song,
    Y. M. Song, H. A. Pao, R.-H. Kim, et al. “Injectable, cellular-scale optoelec-
    tronics with applications for wireless optogenetics”. In: Science 340.6129 (2013),
    pp. 211–216.
    [11] S. Kumar et al. “A review of transimpedance amplifiers used in biomedical
    applications”. In: 2021 5th International Conference on Computing Methodologies
    and Communication (ICCMC). IEEE. 2021, pp. 1314–1321.
    [12] Y. Li, X. Liu, X. Li, S. Wang, H. Ye, L. Zhang, Y. Li, S. Sun, B. Chen, Y.
    Ma, et al. “Surface illuminated interdigitated Ge-on-Si photodetector with high
    responsivity”. In: Optics Express 29.11 (2021), pp. 16346–16361.
    [13] B. Linares-Barranco and T. Serrano-Gotarredona. “On the design and charac-
    terization of femtoampere current-mode circuits”. In: IEEE journal of solid-state
    circuits 38.8 (2003), pp. 1353–1363.
    [14] X. Liu, J. Li, W. Mao, Z. Chen, Z. Chen, P. Wan, and H. Yu. “A Charge
    Balanced Neural Stimulator Silicon Chip for Human-Machine Interface”. In:
    Frontiers in Electronics 2 (2021), p. 773812.
    [15] Y. Ma, Z. Ma, Z. Liang, T. Neuberger, and N. Zhang. “Global brain signal in
    awake rats”. In: Brain Structure and Function 225 (2020), pp. 227–240.
    [16] J.-H. Noh. “Frequency-response analysis and design rules for capacitive feed-
    back transimpedance amplifier”. In: IEEE Transactions on Instrumentation and
    Measurement 69.12 (2020), pp. 9408–9416.
    [17] M. Rafati, S. R. Qasemi, and A. Alvandpour. “A Dynamic Range Extension
    Technique for Pseudo-Resistive Transimpedance Amplifiers Based on Two-Step
    Conversion”. In: 2022 IEEE Nordic Circuits and Systems Conference (NorCAS).
    IEEE. 2022, pp. 1–5.
    [18] W. D. Sacher, F.-D. Chen, H. Moradi-Chameh, X. Luo, A. Fomenko, P. Shah,
    T. Lordello, X. Liu, I. F. Almog, J. N. Straguzzi, et al. “Implantable photonic
    neural probes for light-sheet fluorescence brain imaging”. In: Neurophotonics 8.2
    (2021), p. 025003.
    67
    [19] E. H. Simpson, T. Akam, T. Patriarchi, M. Blanco-Pozo, L. M. Burgeno, A.
    Mohebi, S. J. Cragg, and M. E. Walton. “Lights, fiber, action! A primer on in
    vivo fiber photometry”. In: Neuron 112.5 (2024), pp. 718–739.
    [20] Y. Sych, M. Chernysheva, L. T. Sumanovski, and F. Helmchen. “High-density
    multi-fiber photometry for studying large-scale brain circuit dynamics”. In: Na-
    ture methods 16.6 (2019), pp. 553–560.
    [21] A. J. Taal, I. Uguz, S. Hillebrandt, C.-K. Moon, V. Andino-Pavlovsky, J. Choi,
    C. Keum, K. Deisseroth, M. C. Gather, and K. L. Shepard. “Optogenetic stim-
    ulation probes with single-neuron resolution based on organic LEDs monolith-
    ically integrated on CMOS”. In: Nature Electronics 6.9 (2023), pp. 669–679.
    [22] R. Vargas-Bernal, A. Sarmiento-Reyes, and F. Serdijn. “Identifying translinear
    loops in the circuit topology”. In: 2000 IEEE International Symposium on Circuits
    and Systems (ISCAS). Vol. 2. IEEE. 2000, pp. 585–588.
    [23] Y. Zhang, M. R´ozsa, Y. Liang, D. Bushey, Z. Wei, J. Zheng, D. Reep, G. J.
    Broussard, A. Tsang, G. Tsegaye, et al. “Fast and sensitive GCaMP calcium
    indicators for imaging neural populations”. In: Nature 615.7954 (2023), pp. 884–
    891.

    QR CODE