https://scholars.lib.ntu.edu.tw/handle/123456789/625588
標題: | Inference, attention, and decision in a bayesian neural architecture | 作者: | ANGELA YU-CHEN LIN Dayan P. |
公開日期: | 2005 | 來源出版物: | Advances in Neural Information Processing Systems | 摘要: | We study the synthesis of neural coding, selective attention and perceptual decision making. A hierarchical neural architecture is proposed, which implements Bayesian integration of noisy sensory input and topdown attentional priors, leading to sound perceptual discrimination. The model offers an explicit explanation for the experimentally observed modulation that prior information in one stimulus feature (location) can have on an independent feature (orientation). The network's intermediate levels of representation instantiate known physiological properties of visual cortical neurons. The model also illustrates a possible reconciliation of cortical and neuromodulatory representations of uncertainty. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898963841&partnerID=40&md5=ca8eaec767594ec7e7da8abfdbe34ae1 https://scholars.lib.ntu.edu.tw/handle/123456789/625588 |
ISSN: | 10495258 | SDG/關鍵字: | Neural networks; Bayesian integration; Intermediate level; Neural architectures; Perceptual decision making; Physiological properties; Prior information; Selective attention; Visual cortical neurons; Network architecture |
顯示於: | 環境工程學研究所 |
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