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Statistical Machine Learning Methods for the Large-Scale Analysis of Neural Data
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Mena, Gonzalo E. |
| 단체저자명 | Columbia University. Statistics. |
| 서명/저자사항 | Statistical Machine Learning Methods for the Large-Scale Analysis of Neural Data. |
| 발행사항 | [S.l.] : Columbia University., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 197 p. |
| 소장본 주기 | School code: 0054. |
| ISBN | 9780438159853 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Adviser: Liam M. Paninski. |
| 요약 | Modern neurotechnologies enable the recording of neural activity at the scale of entire brains and with single-cell resolution. However, the lack of principled approaches to extract structure from these massive data streams prevent us from fully |
| 요약 | The second part focuses on the simultaneous electrical stimulation and recording of neurons using large electrode arrays. There, identification of neural activity is hindered by stimulation artifacts that are much larger than spikes, and overlap |
| 요약 | The third part is motivated by the problem of inference of neural dynamics in the worm C.elegans: when taking a data-driven approach to this question, e.g., when using whole-brain calcium imaging data, one is faced with the need to match neural |
| 일반주제명 | Statistics. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-11B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14999470 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00025317 | 310 | 가야대학교// | 대출가능 |
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