Training in Methods of Computational Neuroscience
Training in Methods of Computational Neuroscience
批准号:
7658931
负责人:
WILLIAM S. REZNIKOFF
金额:
$17.65万
依托单位国家:
美国
项目类别:
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-08-22 至 2010-09-19
关键词:
AlgorithmsAnimalsAreaArtsBasal GangliaBasic ScienceBiologicalBiologyBooksBostonClinicalCognitionCognitive ScienceCollaborationsComputational TechniqueComputer HardwareDeep Brain StimulationDisciplineDiseaseEducationEducational CurriculumEducational process of instructingEngineeringEpilepsyEquationExerciseFacultyFosteringFundingGoalsGrantHandHealthHumanInformation TheoryInstructionLaboratoriesLeadLearningMarinesMathematicsMemory DisordersMethodsModelingMotivationNamesNeurologicNeurosciencesParkinson DiseasePhysicsPlayPoliciesPopulationPostdoctoral FellowPrincipal InvestigatorRecruitment ActivityRequest for ProposalsRespirationRoboticsScientistSeriesSleep DisordersStudent SelectionsStudentsSudden infant death syndromeSystemTechniquesTrainingTraining ProgramsUniversitiesUpper armVisitWorkabstractingaddictionanalytical toolcomputational neurosciencecomputer sciencecomputerized toolsinsightinterestlecturerlecturesmultidisciplinaryneural prosthesispre-clinicalprogramsrelating to nervous systemresearch studysimulationsuccesstheories
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): In this proposal we request continuation of support for the Methods in Computational Neuroscience Course offered annually at the Marine Biological Laboratory since 1988. The goal of this course is to train 24 advanced students and post-doctoral fellows per year in the fundamental issues in computational neuroscience, providing them with analytical tools to assist in their studies. The course has several unique features, which would be hard if not impossible to duplicate in a university setting. First, it continues to attract and educate students from a broad range of established disciplines that impact on neuroscience, including biology, cognitive science, computer science, mathematics, physics and engineering. Secondly, as a means to providing a coherent and relatively complete perspective on the growing field of computational neuroscience, students are exposed to a large visiting faculty, drawn from leaders in the field, as well as, receiving instruction and guidance from the course directors, resident faculty and course assistants. It is unlikely that such a combination of faculty could be convened for a similar course in a university setting. Finally, the course provides students with access to state-of-art computational techniques and computer hardware essential in the simulation of neural systems from a detailed cellular through more abstract systems level. The course is an intensive 4-week lecture/laboratory series. The first three weeks consist of daily formal lectures, along with tutorials and lab exercises. Each week is devoted to a clear theme, ranging from the basics (Week 1) to networks (Week 2) to learning and cognition (Week 3). Week Four is devoted exclusively to student projects. We aim to show students how combined experimental and theoretical approaches can lead to breakthroughs and make them familiar with the analytic methods and computational tools that they will need for success.
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