课题基金 / 基金详情

CAREER: Infomechanics - The interdependence of animal information acquisition and mechanics

CAREER: Infomechanics - The interdependence of animal information acquisition and mechanics
职业:信息力学 - 动物信息获取和力学的相互依赖
批准号:
0846032
负责人:
Malcolm MacIver
金额:
$125.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-15 至 2015-06-30

项目摘要

项目成果

Malcolm MacIver的其他基金

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中文摘要
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英文摘要
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).While the nervous system operates with information, the mechanics of the body and the environment in which it is embedded constitute a world of forces. Work on the mechanics of the body and on the nervous system is rarely undertaken in a joint fashion, in part because of the difficulty of comparing these quantities. A theoretical umbrella under which neural information acquisition can be related to mechanics is currently lacking; there is no science of infomechanics. This project will use the model system of weakly electric fish to push forward an understanding of the linkages between obtaining sensory information and movement mechanics. It has recently been shown that, unlike most forward-biased animals which sense objects ahead better than in other directions, electric fish are able to sense in all directions. Complementing this unique sensory capacity is a motor system which allows them reach locations all around the body quickly. The very high degree of coupling between sensation and movement in these animals makes them ideal for elucidating the principles connecting mechanics to sensory processing. The kinematics and dynamics of this unique motor system will be studied through use of a highly stereotyped refuge-tracking behavior and work on an advanced electric fish robot. The neural basis of sensory-guided movement will be examined through a study of the encoding of locomotor signals in the brain. Finally, a robotic model of a closed-loop sensory tracking behavior present in fish will be used to test hypotheses of how the processing of object features is connected with movement control. This work will result in the training of one postdoctoral associate and several graduate students in interdisciplinary research spanning behavior, neurobiology, robotics, and fluid dynamics.
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