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Development of a large area high resolution micro ECoG electrode array

Development of a large area high resolution micro ECoG electrode array
大面积高分辨率微ECoG电极阵列的开发
批准号:
9274056
负责人:
Oliver Graudejus
金额:
$18.94万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-05-15 至 2018-10-31

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中文摘要
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英文摘要
 DESCRIPTION (provided by applicant): This work is directed at the development of a microelectrode array for electrocorticography (ECoG) that allows the recording and stimulation of neural activity on the surface of the brain over a large area at high spatial resolution. Existig technologies either allow the recording of neural activity (i) over a large brain area at low spatil resolution (standard commercial ECoGs), or (ii) over a small brain area at high spatial resolution (so called µECoGs). BMSEED aims to produce large-area-high-resolution µECoG electrode arrays (lahrµECoGs). Conventional ECoG electrode arrays are placed on the surface of the brain, and are used as a less invasive alternative to penetrating microelectrodes, which are inserted into the brain tissue. They are used (i) in neuroscience research to explore the fundamentals of how the brain operates, (ii) in brain-machine-interfaces (BMIs) to record neural activity to drive a neuroprosthesis for amputees or to move a computer cursor for the paralyzed, and (iii) for monitoring neural activity during epilepsy surgery to identify the regions of the corex that generate seizures, which subsequently are removed. These applications would benefit from BMSEED's lahrµECoG because it would provide more accurate localization of the recorded signals (i.e., normal neural activity as well as seizures) over a large area, thus improving brain research, making BMIs more robust, and improving clinical outcomes in epilepsy surgery by providing the neurosurgeon with more accurate localization of seizure activity. In all ECOGs, each recording electrode requires one wire to electrically connect to the data acquisition system without intersecting (i.e., without shorting) with other wires. This becomes increasingly difficult as the density and total number of electrodes increases. BMSEED's lahrµECoG solves this problem by routing the lead wires on multiple levels. In addition, our proprietary technology to produce mechanically robust microelectrodes using microfabrication techniques allows us to reduce the thickness, thus the stiffness, of the device, making the implant more compliant. Importantly, BMSEED's lahrµECoG consists entirely of materials that are suitable for implantation in humans, thus simplifying the FDA approval process. The first specific aim is to optimize the profile of the slope between different levels to provide a reliable electrical connection, and to fabricate and electromechanically characterize prototypes of the lahrµECoG. The second aim is to demonstrate the biocompatibility and capabilities of the prototypes. To that end, a lahrµECoG will be chronically implanted in five cats, and neural recording and micro-stimulation data will be obtained for at least two months. At the end of phase I, BMSEED will have (i) developed the capability to produce multi-level metallization and prototypes of lahrµECoGs, and (ii) characterized their capabilities in a cat model. In phase II, BMSEED will extend the lahrµECoGs development to multi-level metallization on larger, clinically relevant substrate sizes. Our customers will initially be research laboratories, and, after FDA approval, biomedical companies for BMI applications and hospitals for clinical applications.
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A physiologically relevant pre-clinical drug screening platform for Alzheimer's Disease and Traumatic Brain Injury with integrated stretchable microelectrodes
  • 批准号:
    10482284
  • 项目类别:
  • 资助金额:
    $45.0万
  • 财政年份:
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  • 依托单位:
The first adaptable, 3D-formfitting microelectrode array for organoid-based models of neurological and neurodegenerative diseases
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  • 财政年份:
    2021
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    Oliver Graudejus
  • 依托单位:
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  • 批准号:
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Lab-To-Marketplace: Commercialization of a stretchable microelectrode array
  • 批准号:
    10192345
  • 项目类别:
  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
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