CRCNS: Collaborative Research: Characterizing Bayesian Surprise in Humans and Monkeys

CRCNS：合作研究：描述人类和猴子的贝叶斯惊讶

• 批准号: 0515261
• 负责人: Laurent Itti
• 金额: $ 46.75万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0515261&HistoricalAwards=false
• 关键词: CRCNS; Collaborative; Research; Characterizing; Bayesian

The concept of surprise is central to sensory processing, adaptation and learning, attention, and decision making. Yet, no widely-accepted mathematical theory currently exists to quantitatively characterize surprise elicited by a stimulus or event, for observers that range from single neurons to complex natural or engineered systems. This project develops a formal Bayesian definition of surprise that is the only consistent formulation under minimal axiomatic assumptions. Surprise quantifies how data affects natural or artificial observers, by measuring the difference between posterior and prior beliefs of the observers. Preliminary human eye-tracking experiments demonstrated that participants gaze towards surprising image regions, significantly more than expected by chance, while watching complex videoclips including TV and video games. What are the underlyingneural mechanisms responsible for this behavior? This cross-disciplinary proposal addresses this question as follows:- Theory and modeling, to investigate how surprise relates to previous notions of saliency and novelty, and may advantageously complement Shannon information when analyzing neural function and behavior.- Monkey electrophysiology with simple surprising stimuli, to investigate how single-neurons along the sensorimotor processing stream (primary visual cortex, frontal eye fields, superior colliculus) may be modulated by surprise.- Parallel human/monkey psychophysics/electrophysiology, to investigate, in natural situations and with more complex stimuli including TV programs, whether stimuli which attract human and monkey attention may carry more Bayesian surprise.The theory of surprise developed here is applicable across different modalities, datatypes, tasks, and abstraction levels. It has potential for impacting science and engineering, and especially education in computer science, mathematics, information theory, statistics, psychology and biology. The research involves undergraduate, graduate, and postdoctoral trainees in a collaboration between a theory lab (Baldi), a modeling and psychophysics lab (Itti), and a monkey electrophysiology lab (Munoz).

惊讶的概念是感觉处理、适应和学习、注意力和决策的核心。然而，对于从单个神经元到复杂的自然或工程系统的观察者来说，目前还没有被广泛接受的数学理论来定量描述由刺激或事件引起的惊讶。这个项目开发了一个正式的贝叶斯惊喜定义，这是在最小公理假设下唯一一致的公式。通过测量观察者的后验信念和先验信念之间的差异，惊喜量化了数据对自然或人造观察者的影响。初步的人类眼睛跟踪实验表明，参与者在观看包括电视和视频游戏在内的复杂视频片段时，会盯着令人惊讶的图像区域，这比预期的要多得多。导致这种行为的神经机制是什么？这项跨学科的建议解决了这个问题如下：-理论和建模，调查惊奇如何与先前的显著和新奇的概念相关，并且在分析神经功能和行为时可以有利地补充香农信息。-猴子电生理学，用简单的惊喜刺激，研究感觉运动处理流(初级视觉皮质，额眼区域，上丘)上的单个神经元如何受到惊喜的调制。-平行的人/猴心理物理学/电生理学，研究在自然情况下，以及在包括电视节目在内的更复杂的刺激下，吸引人类和猴子注意的刺激是否会带来更多的贝叶斯惊喜。这里发展的惊讶理论适用于不同的形态、数据类型任务和抽象级别。它有可能影响科学和工程，特别是计算机科学、数学、信息论、统计学、心理学和生物学方面的教育。这项研究涉及理论实验室(Baldi)、建模和心理物理实验室(ITTI)和猴子电生理学实验室(Munoz)合作的本科生、研究生和博士后实习生。