Smart MEMS recording systems for visual cortical studies
Smart MEMS recording systems for visual cortical studies
批准号:
7345357
负责人:
RICHARD A ANDERSEN
金额:
$74.84万
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-02-15 至 2010-01-31
关键词:
AcuteAlgorithmsAreaCellsChronicClassCommunicationComplexComputersDataDepthDevicesElectrodesElectrolysesFeedbackGoalsHeatingImplantImplanted ElectrodesLongevityManualsMethodsMicroelectrodesMonitorMonkeysMovementNervous system structureNeuronsOutputPerformancePopulationPositioning AttributeProceduresProcessProductivityProsthesisPurposeRattusResearchResearch PersonnelSchemeSignal TransductionStandards of Weights and MeasuresSystemTechnologyTestingTimeTissuesVisualVisual CortexVisual system structureWorkawakebasecell typeconceptdesignimplantationimprovedminiaturizeneural prosthesisnovelprogramsprototyperesearch studyvisual neuroscience
中文摘要
描述(申请人提供):本提案的目的是设计和制造一种智能MEMS设备,用于记录视觉神经系统中的多细胞活动。这种小型化和可植入的微电极阵列系统将自动调整电极的深度,以优化记录性能。该系统的基本原理是改善视觉系统中神经元群体的长期、长期记录,用于科学和神经假体应用。当前具有固定电极几何形状的系统不能被调整以根据产量或单元类型来优化记录。此外,这些系统不能随着时间的推移“跟随”细胞,以克服由于组织相对于电极移动而造成的信号损失。手动系统的缺点是在科学研究中变得无法管理大阵列,而对于用于假体应用的永久植入物则是不可接受的。通过根据记录的信号质量自动确定每个电极的位置,所提出的系统克服了所有这些缺点。
这项研究的第一个目标是开发自动搜索和保存来自神经元的记录信号的算法。初步数据显示,这对清醒、行为正常的猴子和麻醉大鼠的皮层神经元是可能的。第二个目标是开发低散热、可锁定、能量应用最少、能够提供大位移的MEMS致动器。初步研究表明,由其中一位研究人员开发的电解执行器是这一应用的理想选择。目标三将把早期目标中开发的所有组件集成到一个单一系统中。该设备将由一个基于MEMS的多电极阵列组成,该阵列具有独立可移动的电极,以及车载控制、监控和通信电路。虽然这是一项开发技术的提议,但一个潜在的假设是,与固定几何系统相比,该系统将大大改进多单元、慢性记录。这一假设最初将通过麻醉大鼠的皮质记录进行验证,随后将通过表现良好的猴子的视觉皮质区域的记录进行验证。
英文摘要
DESCRIPTION (PROVIDED BY APPLICANT): The purpose of this proposal is to design and build a smart MEMs device for recording multicellular activity in the visual nervous system. This miniaturized and implantable microelectrode array system will automatically adjust the depths of the electrodes to optimize recording performance. The rationale for this system is to improve long term, chronic recording from populations of neurons in the visual system for scientific and neuroprosthetic applications. Current systems with fixed electrode geometries cannot be adjusted to optimize recordings in terms of yield or cell type. Moreover, these systems cannot "follow" cells over time to overcome loss of signal due to movement of the tissue with respect to the electrodes. Manual systems have the drawback of becoming unmanageable for large arrays in scientific studies, and unacceptable for permanent implants for prosthetics applications. The proposed system overcomes all of these drawbacks by automating the position of each electrode based on recorded signal quality.
The first aim of this study is to develop algorithms to automatically search for, and hold, recorded signals from neurons. Preliminary data show that this is possible for cortical neurons recorded from awake, behaving monkeys and anesthetized rats. The second aim is to develop MEMS actuators that have low heat dissipation, are lockable with minimal energy application, and can provide large displacements. Preliminary studies indicate that electrolysis actuators developed by one of the co-investigators are ideal for this application. Aim three will integrate all of the components developed in the earlier aims into a single system. This device will consist of a MEMS-based multielectrode array with independently moveable electrodes, and on-board control, monitoring and communications circuits. Although this is a proposal to develop technology, an underlying hypothesis is that this system will improve multiunit, chronic recordings substantially over what can be achieved with fixed geometry systems. This hypothesis will be tested initially with cortical recordings in anesthetized rats followed by recordings from visual cortical areas in behaving monkeys.
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