What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective-Reference-Cited by-同舟云学术

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What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective

Published:2020-02-27 Issue: Volume:14 Page:
ISSN:1662-5145
Container-title:Frontiers in Integrative Neuroscience
language:
Short-container-title:Front. Integr. Neurosci.

Author:

Fu Di,Weber Cornelius,Yang Guochun,Kerzel Matthias,Nan Weizhi,Barros Pablo,Wu Haiyan,Liu Xun,Wermter Stefan

Funder

National Natural Science Foundation of China

Publisher

Frontiers Media SA

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience,Sensory Systems

Reference200 articles.

1. Task-modulated “what” and “where” pathways in human auditory cortex;Ahveninen;Proc. Natl. Acad. Sci. U.S.A.,2006

2. “What” and “where” in the human auditory system;Alain;Proc. Natl. Acad. Sci. U.S.A.,2001

3. The ventriloquist effect results from near-optimal bimodal integration;Alais;Curr. Biol.,2004

4. Value-driven attentional capture;Anderson;Proc. Natl. Acad. Sci. U.S.A.,2011

5. Top-down versus bottom-up attentional control: a failed theoretical dichotomy;Awh;Trends Cogn. Sci.,2012

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