Bidirectional Hybrid Electrical-Acoustic Minimally Invasive Implants for Large-Scale Neural Recording and Modulation

用于大规模神经记录和调制的双向混合电声微创植入物

• 批准号: 9766303
• 负责人: Mehdi Kiani
• 金额: $ 19.72万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9766303
• 关键词: Acoustics; Animals; Biological; Brain; Brain region; Chemicals; Cicatrix; Cognitive; Complex; Data; Development; Devices; Disease; Electrocorticogram; Electrodes; Electromagnetics; Electrophysiology (science); Emotions; Esthesia; Failure; Fiber Optics; Film; Focused Ultrasound; Frequencies; Future; Geometry; Goals; Human; Hybrids; Image; Implant; Injury; Knowledge; Light; Link; Liquid substance; Measures; Methods; Modality; Monitor; Motor; Neurons; Optics; Pattern; Penetration; Performance; Pharmacology; Resolution; Safety; Sensory; Signal Transduction; Site; Specificity; Structure; Surface; System; Technology; Telemetry; Testing; Thick; Thinness; Time; Tissue imaging; Tissues; Transducers; Ultrasonic Transducer; Ultrasonics; Ultrasonography; Validation; Wireless Technology; biomaterial compatibility; brain parenchyma; data exchange; density; design; failure Implantation; flexibility; hemodynamics; image guided; imaging capabilities; implantation; millimeter; millisecond; minimally invasive; nervous system disorder; neural stimulation; neuroregulation; neurotechnology; operation; parylene C; prevent; relating to nervous system; research and development; response; spatiotemporal; technology development; tool

Project Summary: Dynamic mapping of complex brain circuits by monitoring and modulating brain activity at large scale will enhance our understanding of brain functions, such as sensation, thought, emotion, and action. This knowledge will ultimately help to better treat and prevent neurological disorders. Real-time interfacing with the brain also has the potential to enhance our perceptual, motor, and cognitive capabilities, as well as to restore sensory and motor functions lost through injuries or diseases. Despite decades of research and development of neurotechnologies for the brain, unfortunately monitoring and modulation of brain activity with high spatiotemporal resolution at large scale is still one of the grand challenges in the 21st century. Currently, neuromodulation can be achieved with different modalities from pharmacological and chemical methods, which lack specificity, to electrical, electromagnetic, optical, and acoustic methods with higher specificity. Similarly, neural activity can be monitored with different indirect (through imaging hemodynamic changes) or direct (electrophysiology recording) methods with various spatiotemporal resolution and spatial coverage. Unfortunately, available non-invasive tools for brain interfacing suffer from poor spatiotemporal resolution. Implantable methods are extremely invasive, requiring penetration of devices (e.g. electrodes, optic fibers) into the brain parenchyma with scar tissue formation, long-term damage, and biological responses that can result in implantation failure over time. More importantly, current implantable methods can only be applied to hundreds of neurons out of ~85 billion neurons in the human brain. We propose a new paradigm for large-scale neural interfacing by developing a new bidirectional neural- interface platform in that a network of minimally invasive, hybrid electrical-acoustic implants are distributed over the brain surface. These implants will 1) be small (millimeter scale), light, free-floating, addressable, and wireless, 2) simultaneously provide high-density electrophysiology recording (µECOG) and ultrasonic stimulation with high spatiotemporal resolution of several micrometers and milliseconds, 3) stimulate different distributed regions of the brain parenchyma through focusing an ultrasonic beam by an array of thin-film ultrasonic transducers (without penetration into the brain parenchyma), and 4) acoustically guide both µECOG recording and ultrasonic stimulation by imaging neural structure under the implant.

项目总结:

项目成果

32 Element Piezoelectric Micromachined Ultrasound Transducer (PMUT) Phased Array for Neuromodulation.

• DOI: 10.1109/ojuffc.2022.3196823
• 发表时间: 2022
• 期刊: IEEE open journal of ultrasonics, ferroelectrics, and frequency control
• 作者: Tipsawat, Pannawit;Ilham, Sheikh Jawad;Yang, Jung In;Kashani, Zeinab;Kiani, Mehdi;Trolier-McKinstry, Susan
• 通讯作者: Trolier-McKinstry, Susan