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Functional Ultrasound Imaging Platform for Brain Research

Functional Ultrasound Imaging Platform for Brain Research
用于脑研究的功能性超声成像平台
批准号:
465073597
负责人:
金额:
$0.0万
依托单位国家:
德国
项目类别:
Major Research Instrumentation
财政年份:
2021
资助国家:
德国
项目状态:
未结题
起止时间:
2020-12-31 至 --

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英文摘要
How the extraordinary cognitive abilities of humans emerged through evolutionary history is one of the greatest questions in biology. We approach this question by studying the cognitive capabilities and their underlying neural mechanisms in two highly-intelligent, but distantly-related animal species - macaques, a non-human primate and the carrion crow, a corvid. Through meticulous single-unit electrophysiology of particular brain areas and sophisticated behavioral tasks, we have uncovered some neural coding principles that underlie higher brain functions such as number processing, working memory, volitional control of communication, and conscious perception. However, many of these functions are not isolated to lone brain areas and instead rely on the interaction of large networks of connected brain regions. This application proposes to use a promising, innovative technique - functional ultrasound imaging (fUSI) – to visualize neural activity on a brain-wide scale in awake, behaving animals. fUSi offers an attractive set of advantages compared to more traditional imaging techniques such as a large field of view, improved spatio-temporal resolution, and minimal constraints on the animal. For example, fMRI is difficult to perform in mobile-behaving animals and currently lacks fine enough spatial-temporal resolution to capture recurrent activity within small nuclei deep in the brain. Thus, we turn to fUSi, where it is possible to measure the real-time dynamics of brain activation – via neurovascular coupling – in large slices of the brain while animals process information and perform cognitively-demanding tasks. This will allow us an unprecedented glance at how complex cognitive is driven by the relative contributions of various brain structures and their interactions. Beyond insights into large-scale network dynamics, this approach will also help to guide the unbiased selection of brain areas to be further-studied with more local, fine-grained electrophysiological investigations. Together, we are optimistic that experiments made possible by fUSI will allow us to enter a new phase in our quest to understand the workings of intelligent behavior.
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