| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000433053 |
| 005 | | 20200225111704 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781392801055 |
| 035 | |
▼a (MiAaPQ)AAI22592119 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 150 |
| 100 | 1 |
▼a Zhou, Jingyang. |
| 245 | 10 |
▼a Delayed Gain Control Model and Its Application to Cortical Neuronal Dynamics. |
| 260 | |
▼a [S.l.]:
▼b New York University.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 175 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-06, Section: B. |
| 500 | |
▼a Advisor: Winawer, Jonathan. |
| 502 | 1 |
▼a Thesis (Ph.D.)--New York University, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 520 | |
▼a The nervous system extracts meaning from the distribution of light over space and time. Spatial vision has been a highly successful research area, and the spatial receptive field has served as a fundamental and unifying concept that spans perception, computation, and physiology. In particular, it was found that later visual areas become increasingly tolerant to variations in image properties such as object size, location, viewpoint, and so on. This phenomenon is often modeled by a cascade of repeated processing stages in which each stage involves pooling followed by a compressive nonlinearity. One result of this sequence is that stimulus-referred measurements show increasingly large receptive fields and stronger normalization in later processing stages. In this thesis, a similar approach was applied to the temporal domain. Using fMRI and intracranial potentials (ECoG), we develop a population receptive field (pRF) model for temporal sequences of visual stimulation. The model consists of linear summation followed by a time-varying divisive normalization. The same model accurately accounts for both ECoG broadband time courses and fMRI amplitudes. The model parameters reveal several regularities about temporal encoding in cortex. First, higher visual areas accumulate stimulus information over a longer time period than earlier areas, analogous to the hierarchically organized spatial receptive fields. Second, we found that all visual areas sum sub-linearly in time: e.g., the response to a long stimulus is less than the response to two successive brief stimuli. Third, the degree of compression increases in later visual areas, analogous to spatial vision. Finally, based on published data, we show that our model can account for the time course of single units in macaque V1 and multi-units in humans. This suggests that for space and time, cortex uses a similar processing strategy to achieve higher-level and increasingly invariant representations of the visual world. |
| 590 | |
▼a School code: 0146. |
| 650 | 4 |
▼a Neurosciences. |
| 650 | 4 |
▼a Psychology. |
| 690 | |
▼a 0317 |
| 690 | |
▼a 0621 |
| 710 | 20 |
▼a New York University.
▼b Psychology. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-06B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0146 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493216
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |