CAREER: Scalable, Penetrating Multimodal Neural Interfaces for Adaptive Closed-Loop Neuromodulation
CAREER: Scalable, Penetrating Multimodal Neural Interfaces for Adaptive Closed-Loop Neuromodulation
批准号:
2145412
负责人:
Samantha Santacruz
金额:
$58.28万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-06-01 至 2027-05-31
中文摘要
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英文摘要
In the United States, anxiety disorders are the most prevalent neuropsychiatric illness, defined as an illness of the mind and nervous system, yet standard treatments for these disorders have failed to show a significant reduction in the prevalence or severity of illness. A major challenge is that anxiety disorders develop from disruptions in highly interconnected groups of brain areas, which are referred to as neural circuits, and the appropriate technologies to characterize these neural circuits are lacking. This CAREER project will develop and leverage a neural interface technology to characterize neural circuits impacted by anxiety disorders. Ultimately the work will increase understanding of neural mechanisms underscoring anxiety-related behavior and potentially lead to new treatment options. The research objectives in this proposal are integrated with an educational and outreach plan to increase visibility and training in neuroengineering. Specifically, the plan includes the following activities: establishing a neuroengineering research concentration; experiential learning and mentoring opportunities for women and underrepresented minorities; interactive and remote learning outreach activities; and multidisciplinary training for graduate and undergraduate students. The shortcomings of existing therapies for neuropsychiatric illnesses, such as anxiety, highlight the urgent need to better understand functional interactions in the affected neural circuits. The goal of this CAREER project is to develop a transformative multimodal neural interface fabrication process and design that will pave the way for establishing neural circuit mechanisms of anxiety-related behavior. Existing multimodal neural interfaces typically leverage manual assembly techniques that are not practically scalable and fail to reach brain areas beyond the superficial cortex. These shortcomings will be addressed by two foci. The Engineering Focus will develop microfabrication and microassembly processes for a neural interface design that can be easily optimized to different applications. The advantages of developing these processes include greater device yield, lower variation in fabricated devices, and design scalability to high channel counts. This work also distinguishes itself from the state-of-the-art in its holistic design that leverages a highly biocompatible material that easily integrates with the fabrication pipeline and is appropriate for multimodal functionality. Under the Biological Focus, the deep penetrating neural interface will be used to examine how approach-avoidance choice information is represented and communicated across relevant neural circuitry and implement an electrical neuromodulation paradigm to establish causal circuit mechanisms underlying aberrant changes in anxiety-related behavior. The knowledge gained through this work will provide a fundamentally new strategy to develop scalable multimodal neural interfaces and lay the foundation for neural circuit-level characterizations of any neurological condition – ultimately leading to new neuromodulatory interventions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
“Mind-Reading” Machines
– 读心术 – 机器
DOI:
10.3389/frym.2022.771696
发表时间:
2022
期刊:
Frontiers for Young Minds
影响因子:
--
作者:
[Lu, Hung-Yun, Jeanpierre, Grace M., Mitchell, Jaz, Santacruz, Samantha R.]
通讯作者:
Santacruz, Samantha R.
How Your Sense of Touch Can Change Your Brain
你的触觉如何改变你的大脑
DOI:
10.3389/frym.2022.772919
发表时间:
2022
期刊:
Frontiers for Young Minds
影响因子:
--
作者:
[Stealey, Hannah M., Zhao, Yi, Chang, Yin-Jui, Santacruz, Samantha R.]
通讯作者:
Santacruz, Samantha R.
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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