High-resolution CMOS-based biosensor for assessing hippocampal circuit dynamics in experience-dependent plasticity

Emery, Brett; Hu, Xin; Khanzada, Shahrukh; Kempermann, Gerd; Amin, Hayder

doi:10.1016/j.bios.2023.115471

Cited by 9 publications

(42 citation statements)

References 84 publications

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“…Extracellular neural activity was recorded using HD-MEAs crafted from complementary-metal-oxide-semiconductor (CMOS) technology, coupled with a bespoke acquisition system (3Brain AG, Switzerland). The CMOS chip featured 4096 electrodes organized in a 64×64 array with a pitch of 42 μm, creating an active sensing area of approximately 7 mm 2 , an ideal dimension for comprehensive recordings from both hippocampal-entorhinal cortex and olfactory bulb (OB) tissues at 14 kHz/electrode sampling frequency (10,11). The on-chip amplification circuit allowed band-pass filtering from 1 Hz to 5 kHz, sufficient to record slow and fast neural activity.…”

Section: Methodsmentioning

confidence: 99%

“…Event detection for LFPs and multi-unit spiking activity (MUA) was conducted using commercial software (3Brain AG), where data was first refined by applying a low-pass filter (1– 100 Hz) for LFPs and a band-pass filter (300–3500 Hz) for MUA. Following the filtering, events were detected using hard thresholding alongside precise timing spike detection (PTSD) algorithms, respectively (10,11). This sequence ensured that the frequency components suitable for describing LFPs and spikes were accurately isolated before event detection, improving the specificity and accuracy of the detected events.…”

Section: Methodsmentioning

confidence: 99%

“…HD-MEAs significantly enhance brain slice studies, merging ex vivo biosensing precision with brain tissue complexity. This approach allows for detailed exploration of electrical spiking activity and rhythmic dynamics of local field potentials (LFPs) under controlled conditions, thus enabling researchers to investigate environmental factors, apply pharmacological agents, or introduce genetic modifications to elucidate their effects on neural activity (10,11,14,(16)(17)(18). Despite advancements in these electrophysiological technologies, capturing the full spectrum of neural patterns within these complex networks remains challenging.…”

Section: Introductionmentioning

confidence: 99%

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DENOISING: Dynamic Enhancement and Noise Overcoming in Multimodal Neural Observations via High-density CMOS-based Biosensors

Hu,

Emery,

Khanzada

et al. 2024

Preprint

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Large-scale multimodal neural recordings on high-density biosensing microelectrode arrays (HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity across various brain networks. However, the fidelity of these recordings is frequently compromised by pervasive noise, which obscures meaningful neural information and complicates data analysis. To address this challenge, we introduce DENOISING, a versatile data-derived computational engine engineered to adjust thresholds adaptively based on large-scale extracellular signal characteristics and noise levels. This facilitates the separation of signal and noise components without reliance on specific data transformations. Uniquely capable of handling a diverse array of noise types (electrical, mechanical, and environmental) and multidimensional neural signals, including stationary and non-stationary oscillatory local field potential (LFP) and spiking activity, DENOISING presents an adaptable solution applicable across different recording modalities and brain networks. Applying DENOISING to large-scale neural recordings from mice hippocampal and olfactory bulb networks yielded enhanced signal-to-noise ratio (SNR) of LFP and spike firing patterns compared to those computed from raw data. Comparative analysis with existing state-of-the-art denoising methods, employing SNR and root mean square noise (RMS), underscores DENOISING’s performance in improving data quality and reliability. Through experimental and computational approaches, we validate that DENOISING improves signal clarity and data interpretation by effectively mitigating independent noise in spatiotemporally structured multimodal datasets, thus unlocking new dimensions in understanding neural connectivity and functional dynamics.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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DENOISING: Dynamic Enhancement and Noise Overcoming in Multimodal Neural Observations via High-density CMOS-based Biosensors

Hu,

Emery,

Khanzada

et al. 2024

Preprint

Self Cite

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“…Therefore, cell proliferation is determined by the MEA’s area covered with adherent cells, assuming a loss in cell adhesion due to the cytotoxic anti-cancer drug 5-FU ( Akalovich et al, 2021 ; Fohlen et al, 2021 ). Our MEA comprises both subcellular resolution ( Hierlemann et al, 2011 ; Viswam et al, 2018 ; Ell, Zeitler, et al, 2023 ) and cellular network studies ( Amin et al, 2017 ; Viswam et al, 2017 ; Angotzi et al, 2018 ; Abbott et al, 2022 ; Cojocaru et al, 2022 ; Emery et al, 2022 ; 2023 ). To relate electrical imaging to optical imaging, CAN-based images were overlaid with brightfield microscopy images.…”

Section: Introductionmentioning

confidence: 99%

Assessment of chemotherapeutic effects on cancer cells using adhesion noise spectroscopy

Ell,

Bui,

Kigili

et al. 2024

Front. Bioeng. Biotechnol.

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With cancer as one of the leading causes of death worldwide, there is a need for the development of accurate, cost-effective, easy-to-use, and fast drug-testing assays. While the NCI 60 cell-line screening as the gold standard is based on a colorimetric assay, monitoring cells electrically constitutes a label-free and non-invasive tool to assess the cytotoxic effects of a chemotherapeutic treatment on cancer cells. For decades, impedance-based cellular assays extensively investigated various cell characteristics affected by drug treatment but lack spatiotemporal resolution. With progress in microelectrode fabrication, high-density Complementary Metal Oxide Semiconductor (CMOS)-based microelectrode arrays (MEAs) with subcellular resolution and time-continuous recording capability emerged as a potent alternative. In this article, we present a new cell adhesion noise (CAN)-based electrical imaging technique to expand CMOS MEA cell-biology applications: CAN spectroscopy enables drug screening quantification with single-cell spatial resolution. The chemotherapeutic agent 5-Fluorouracil exerts a cytotoxic effect on colorectal cancer (CRC) cells hampering cell proliferation and lowering cell viability. For proof-of-concept, we found sufficient accuracy and reproducibility for CAN spectroscopy compared to a commercially available standard colorimetric biological assay. This label-free, non-invasive, and fast electrical imaging technique complements standardized cancer screening methods with significant advances over established impedance-based approaches.

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“…Among the various types of widely researched biosensors, electrochemical platforms are intensely investigated for commercialization due to their compatibility with microelectronic circuitry and manufacturing techniques. [9][10][11][12] The amperometric glucose monitor developed by Leland Clark Jr in 1962 13 evolved into three landmark technologies-enzyme electrode glucose test, glucose test strip, and the continuous glucose monitor-commercialized in 1970, 14 1987, 15 and 2017, 16 which have inspired the electrochemical biosensors research for over seventy years (Fig. 1).…”

mentioning

confidence: 99%

Editors’ Choice—Challenges and Opportunities for Developing Electrochemical Biosensors with Commercialization Potential in the Point-of-Care Diagnostics Market

Akhlaghi,

Kaur,

Adhikari

et al. 2024

ECS Sens. Plus

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There is a plethora of electrochemical biosensors developed for ultrasensitive detection of clinically-relevant biomarkers. However, many of these systems lose their performance in heterogeneous clinical samples and are too complex to be operated by end users at the point-of-care (POC), prohibiting their commercial success. Integration of biosensors with sample processing technology addresses both of these challenges; however, it adds to the manufacturing complexity and the overall cost of these systems. Herein, we review the different components of a biosensor and avenues for creating fully-integrated systems. In the context of integration, we focus on discussing the trade-offs between sensing performance, cost, and scalable manufacturing to guide the readers toward designing new electrochemical biosensors with commercialization potential.

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High-resolution CMOS-based biosensor for assessing hippocampal circuit dynamics in experience-dependent plasticity

Cited by 9 publications

References 84 publications

DENOISING: Dynamic Enhancement and Noise Overcoming in Multimodal Neural Observations via High-density CMOS-based Biosensors

DENOISING: Dynamic Enhancement and Noise Overcoming in Multimodal Neural Observations via High-density CMOS-based Biosensors

Assessment of chemotherapeutic effects on cancer cells using adhesion noise spectroscopy

Editors’ Choice—Challenges and Opportunities for Developing Electrochemical Biosensors with Commercialization Potential in the Point-of-Care Diagnostics Market

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