面孔神经处理机制的研究及其信息建模
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摘要
面孔作为人们在日常生活中最常见的视觉体验,是个体身份判断和情绪识别最具鉴别性的表征之一。由于面孔在人们生存行为和社会交往中的特殊作用,面孔识别成为行为学,脑科学,认知科学、信息建模研究者所共同关注的一个研究领域。面孔研究具有两方面的理论意义。一方面,人脑是一个非常复杂的生物信息处理系统,研究面孔识别为进一步考察人脑对复杂视觉模式的信息处理模式奠定基础。另一方面,理解面孔的神经处理机制也会为基于计算机的面孔识别系统提供借鉴。就目前而言,虽然来自多学科的研究成果使得对面孔识别的深入探讨成为可能,但未能全面透彻地揭示面孔识别的神经机制,距离该目标仍需要大量的科研努力。
Leopold教授与Webster教授分别与2001年与2004年发现了面孔的身份与表情在高级视皮层可以被适应(adaptation),并产生相应的后效(aftereffect)。此项研究使得研究者可以通过适应范例来揭示面孔在人脑中的神经表征,为面孔研究提供了一项有效的测量手段。本文拟采用适应范例来研究面孔处理机制,并对其进行信息上的建模。由于篇幅和时间所限,无法涉及到面孔识别的所有方面。本文主要关注三个与功能建模相关的基础问题。
首先,本文将研究面孔适应的成因。由于面孔适应是一个研究历史较短的视觉效应,近期的一些研究虽然探讨了适应的类型和时间属性,但其内在机制还没有得到清晰阐释。建模面孔后效需要解决两个基本问题。第一个问题是研究面孔皮层与低级视皮层之间是否存在跨层次适应传递的可能性。由于面孔是由色彩,明暗,形状等基本视觉属性组成,所以在面孔适应发生的同时,低层视觉系统也会被适应并产生后效。如果低层后效会被传递到面孔处理区域,那么,面孔适应可能并非来源于面孔神经系统,而只是低层适应在高级视皮层的汇集。在此种情况下,应用面孔适应范例进行面孔研究是不合理的,因为面孔后效本身并不与面孔处理系统发生直接关联。所以需要首先确定面孔后效与其他低层后效之间的功能关系。第二个问题是确定适应时间对神经元的抑制或激活程度的影响。历史上的研究发现,在不同的时间节点上,适应会对神经元产生不同的抑制或者激活反应。如果明确了神经元的激活属性,则可以通过仿真方法来建立面孔后效的计算模型。针对这两个问题,本文首先通过测量低层色彩视觉刺激和形状刺激在真实面孔上的后效尺寸,评估了低层神经系统对高层面孔系统的适应传递。在确定了后效模型为层次型结构后,通过单维度阈值估值法评估了不同适应时间下神经元的抑制和激活,并根据实验观察为面孔后效建立了抑制锐化模型。通过对该问题的研究,奠定了后续研究的方法学基础。
其次,本文研究表情的神经表征类型。过去20年中,面孔的身份识别和表情识别的研究存在着一定程度上的不平衡。面孔身份识别一般被放在心理物理学,脑功能影像学,和信息建模的研究范畴,这些领域的学者关注面孔信息在大脑中的功能组织和实现方式,并深入地探讨了身份信息的大脑内在神经表征。而表情识别一般由社会心理学的学者进行探讨,他们相对关注表情信息在群体交往中传达的特定社会意义,对于表情的神经表征和编码机制的理解一直囿于经典功能模型,并未能取得实质性的进展。本文探讨了表情在视觉系统中内在神经表征方式。面孔信息可以被划分为组件信息(例如,眼睛,鼻子,嘴巴等基本组件)和空间配置信息(例如,眼睛和嘴巴之间的空间距离)两类。一部分学者提出,表情信息主要通过局部组件如眼睛区域和嘴巴区域进行表达,即只存在局部组件的神经表征。而另一部分学者认为,除了局部组件,空间配置在表情信息感知中也起到一定作用。为了辨析这两种假设,我们首先测量了不同局部组件在完整面孔上的表情后效,确认了局部组件神经表征的存在。然后,在保持局部组件不变的情况下修改了面孔的空间配置,结果表明空间配置的改变显著弱化表情后效,这在一定程度上证明了空间配置神经表征的存在。该发现对表情识别的空间配置模型提供了支持。
最后,我们探讨面孔的身份信息处理通路和表情信息处理通路的功能交互关系。人能够轻易从不同表情中识别出同一个人的面孔(即面孔身份识别),也能够从不同人的面孔上识别出同一种表情(即面孔表情识别),表情识别和身份识别是否独立,互不干扰?对于这个问题,在面孔识别的研究历史上一直存在着争议。经典的面孔认知模型认为表情和身份识别在功能和解剖上是相互独立的信息处理通路,这个假设广泛得到了行为学,脑功能影像学,信息建模学的证据支持。然而,近期的研究却发现在颞叶区的神经元会以不同的延时来响应面孔和身份信息,说明表情处理和身份处理存在着共有神经表征的可能性。本研究采用交互干扰的方式,在改变面孔身份的情况下来测量表情后效,和在改变表情信息的情况下来测量身份后效。实验结果揭示出身份改变会显著影响表情后效,但表情变化对身份后效无显著影响。基于这样一种非对称的影响模式,我们建立了表情信息处理通路与身份信息处理通路之间的单向依赖模型,在一定程度上挑战了经典模型中对面孔身份信息和表情信息并行处理的假设。
综上所述,本文以面孔的神经处理机制与建模为研究课题,通过广泛调研和深入探索,在面孔后效成因,表情识别,表情与身份识别的功能关系三个问题上做出了有益探索。本文对面孔领域的研究主要具有以下的贡献。
研究了低级视皮层和面孔处理皮层的神经适应传递关系。
通过仿真方式建立了面孔后效模型。
一定程度上确认了基于空间配置的表情神经表征的存在。
阐明了面孔身份处理和表情处理之间的功能依赖关系。
The human face is not only a common visual stimulus in the daily life, but also one of most distinguishable features for the human to recognize identity and expression. Due to important ecological role on the human social communication, face perception is extensively studied by the researchers from the multi-disciplines such as behavioristics, brain science, cognitive science and information modeling studies. The better understanding about face perception helps to illuminate the neural mechanism in high-level visual system, and also help to improve the design of the computer-based face recognition system.
The face study is a new branch in the information modeling studies and Neuropsychology. Although the luminous studies from multi-disciplines have accumulated to enable the deeper investigation about visual system, it is still a long way to clarify the complex mechanism of face processing.
In 2001 and 2004, Leopold and Webster have found the face adaptation phenomenon in the human visual system, which provide the researchers an practical experimental paradigm to model the underlying neural mechanism for face perception. In this dissertation, we intend to construct a functional model by means of face adaptation paradigm. As the face perception involves the various aspects of processing, which is too large to be involved in one dissertation, we intend to focus on the below three issues, which are the key knots for establishing a functional model.
Firstly, we studied the mechanism of face aftereffect. The face aftereffect is a relatively new phenomenon. Although several studies have investigated the type and temporal characteristic of adaptation, little is known about the inner mechanism of face aftereffect. It is necessary to solve two problems for modeling the face aftereffect. The first issue is to examine the possibility of adaptation propagation between low-level visual system and high-level visual system. The face consists of the many low-level visual properties such as color, shape, and lamination. These low level visual properties would also generate the adaptation effect when the face is used as an adapting stimulus. If the low-level adaptation effects can be propagated to the face system, the observed "face adaptation effect" may only originate from the low level visual system, rather than the face neural system. In this case, it is not reasonable to use the adaptation as a face research tool, because the adaptation is not really related to the face neural system. Thus, it is clear to be important to examine the relationship between the low-level and high-level adaptations. The second issue is to investigate the facilitation and inhibition effects for neurons with the various adaptation times. Once the facilitation and inhibition characteristic is clarified, it is possible to establish the computational model for face aftereffect by means of simulation technology. For these two issues, we firstly measured the adaptation effect from the color and figure stimuli on the real face. These results were used to evaluate the propagation of adaptation effect from the low-level visual system to the face system. Then, we employed the single dimension threshold method to examine the facilitation and inhibition effects. Based on these results, we developed a computational model for face aftereffect. This study is expected to lay a methodology foundation for the further investigation in the dissertation.
In the second issue, we investigated the types of neural representation for human expression recognition. In the previous twenties years, there is an imbalance between studies of the facial identity processing and facial expression processing. The facial identity recognition have been studied within the framework in the psychophysics, brain imaging, information modeling fields, where researchers has focused on functional organization and perceptual representation of facial identity. The facial expression recognition has, however, been heavily influenced by the social psychology studies, and consequently, a firm emphasis has been placed on understanding the communicative value of signals of expression rather than their perceptual representation. Hence, the perceptual mechanisms and neural representation underlying facial expression recognition have not been extensively clarified. We intend to study the neural representation for the human expression using the adaptation paradigm. The face generally consists of two types of information, i.e., the local feature and configuration. There are historically inconsistent ideas about the role of features and configuration on the expression perception. The feature model suggests that only local features contribute to the expression perception. The configuration model, however, hold that not only features but also configuration will play an important role in the expression perception. We measured the adaptation effect from the local features such as the eye area and mouth area, and then introduced the SFDC face and inverted face to evaluate the contribution from the configuration. The result suggested the existence of feature based neural representation and configuration based neural representation. This issue has implication on the perceptual representation and mechanism for the expression perception, and on the automatic expression recognition.
Finally, we studied the functional relationship between facial identity processing and expression processing. The human can easily identify the other people's face with the different emotional expressions (face identification), and, on the other hand, can recognize the expression from the different faces (expression recognition). Whether the face identity processing and expression processing are parallel functionally and anatomically? There is a long term debate about this issue in the face-related studies. The classical models hold that expression and face identity are processed by the parallel neural routes; this parallel hypothesis is supported by the some evidences from the behavior science, brain imaging studies, and information modeling studies. Other evidences, however, suggested that there is possibly a functional interaction between two neural routes. We used the visual adaptation to investigate this issue by measuring the expression aftereffect with the identity variance, and measuring the identity aftereffect with the expression variance. The results show that identity change significantly reduced the expression aftereffect, while the expression variance did not influence the identity aftereffect. Based on this asymmetrical interference, we proposed a one-way hierarchical model. This findings challenge the parallel hypothesis for the processing of expression and face identity in the classical models.
To conclude, this dissertation takes the face neural processing mechanism and its information modeling as research topic. Based on the extensive experimental measurements, we made the investigations on these issues, i.e.,1) cross-level adaptation effect propagation,2) the function relationship between facial identity processing and expression processing,3) the type of neural representation for expression. The dissertation has the below theoretical implications on the face studies.
Found the adaptation propagation between low-level system and face system.
Established the functional model for face aftereffect by means of simulation.
Confirmed the configuration based neural representation for the expression.
Clarified the functional relationship between facial identity processing and expression processing.
Leopold教授与Webster教授分别与2001年与2004年发现了面孔的身份与表情在高级视皮层可以被适应(adaptation),并产生相应的后效(aftereffect)。此项研究使得研究者可以通过适应范例来揭示面孔在人脑中的神经表征,为面孔研究提供了一项有效的测量手段。本文拟采用适应范例来研究面孔处理机制,并对其进行信息上的建模。由于篇幅和时间所限,无法涉及到面孔识别的所有方面。本文主要关注三个与功能建模相关的基础问题。
首先,本文将研究面孔适应的成因。由于面孔适应是一个研究历史较短的视觉效应,近期的一些研究虽然探讨了适应的类型和时间属性,但其内在机制还没有得到清晰阐释。建模面孔后效需要解决两个基本问题。第一个问题是研究面孔皮层与低级视皮层之间是否存在跨层次适应传递的可能性。由于面孔是由色彩,明暗,形状等基本视觉属性组成,所以在面孔适应发生的同时,低层视觉系统也会被适应并产生后效。如果低层后效会被传递到面孔处理区域,那么,面孔适应可能并非来源于面孔神经系统,而只是低层适应在高级视皮层的汇集。在此种情况下,应用面孔适应范例进行面孔研究是不合理的,因为面孔后效本身并不与面孔处理系统发生直接关联。所以需要首先确定面孔后效与其他低层后效之间的功能关系。第二个问题是确定适应时间对神经元的抑制或激活程度的影响。历史上的研究发现,在不同的时间节点上,适应会对神经元产生不同的抑制或者激活反应。如果明确了神经元的激活属性,则可以通过仿真方法来建立面孔后效的计算模型。针对这两个问题,本文首先通过测量低层色彩视觉刺激和形状刺激在真实面孔上的后效尺寸,评估了低层神经系统对高层面孔系统的适应传递。在确定了后效模型为层次型结构后,通过单维度阈值估值法评估了不同适应时间下神经元的抑制和激活,并根据实验观察为面孔后效建立了抑制锐化模型。通过对该问题的研究,奠定了后续研究的方法学基础。
其次,本文研究表情的神经表征类型。过去20年中,面孔的身份识别和表情识别的研究存在着一定程度上的不平衡。面孔身份识别一般被放在心理物理学,脑功能影像学,和信息建模的研究范畴,这些领域的学者关注面孔信息在大脑中的功能组织和实现方式,并深入地探讨了身份信息的大脑内在神经表征。而表情识别一般由社会心理学的学者进行探讨,他们相对关注表情信息在群体交往中传达的特定社会意义,对于表情的神经表征和编码机制的理解一直囿于经典功能模型,并未能取得实质性的进展。本文探讨了表情在视觉系统中内在神经表征方式。面孔信息可以被划分为组件信息(例如,眼睛,鼻子,嘴巴等基本组件)和空间配置信息(例如,眼睛和嘴巴之间的空间距离)两类。一部分学者提出,表情信息主要通过局部组件如眼睛区域和嘴巴区域进行表达,即只存在局部组件的神经表征。而另一部分学者认为,除了局部组件,空间配置在表情信息感知中也起到一定作用。为了辨析这两种假设,我们首先测量了不同局部组件在完整面孔上的表情后效,确认了局部组件神经表征的存在。然后,在保持局部组件不变的情况下修改了面孔的空间配置,结果表明空间配置的改变显著弱化表情后效,这在一定程度上证明了空间配置神经表征的存在。该发现对表情识别的空间配置模型提供了支持。
最后,我们探讨面孔的身份信息处理通路和表情信息处理通路的功能交互关系。人能够轻易从不同表情中识别出同一个人的面孔(即面孔身份识别),也能够从不同人的面孔上识别出同一种表情(即面孔表情识别),表情识别和身份识别是否独立,互不干扰?对于这个问题,在面孔识别的研究历史上一直存在着争议。经典的面孔认知模型认为表情和身份识别在功能和解剖上是相互独立的信息处理通路,这个假设广泛得到了行为学,脑功能影像学,信息建模学的证据支持。然而,近期的研究却发现在颞叶区的神经元会以不同的延时来响应面孔和身份信息,说明表情处理和身份处理存在着共有神经表征的可能性。本研究采用交互干扰的方式,在改变面孔身份的情况下来测量表情后效,和在改变表情信息的情况下来测量身份后效。实验结果揭示出身份改变会显著影响表情后效,但表情变化对身份后效无显著影响。基于这样一种非对称的影响模式,我们建立了表情信息处理通路与身份信息处理通路之间的单向依赖模型,在一定程度上挑战了经典模型中对面孔身份信息和表情信息并行处理的假设。
综上所述,本文以面孔的神经处理机制与建模为研究课题,通过广泛调研和深入探索,在面孔后效成因,表情识别,表情与身份识别的功能关系三个问题上做出了有益探索。本文对面孔领域的研究主要具有以下的贡献。
研究了低级视皮层和面孔处理皮层的神经适应传递关系。
通过仿真方式建立了面孔后效模型。
一定程度上确认了基于空间配置的表情神经表征的存在。
阐明了面孔身份处理和表情处理之间的功能依赖关系。
The human face is not only a common visual stimulus in the daily life, but also one of most distinguishable features for the human to recognize identity and expression. Due to important ecological role on the human social communication, face perception is extensively studied by the researchers from the multi-disciplines such as behavioristics, brain science, cognitive science and information modeling studies. The better understanding about face perception helps to illuminate the neural mechanism in high-level visual system, and also help to improve the design of the computer-based face recognition system.
The face study is a new branch in the information modeling studies and Neuropsychology. Although the luminous studies from multi-disciplines have accumulated to enable the deeper investigation about visual system, it is still a long way to clarify the complex mechanism of face processing.
In 2001 and 2004, Leopold and Webster have found the face adaptation phenomenon in the human visual system, which provide the researchers an practical experimental paradigm to model the underlying neural mechanism for face perception. In this dissertation, we intend to construct a functional model by means of face adaptation paradigm. As the face perception involves the various aspects of processing, which is too large to be involved in one dissertation, we intend to focus on the below three issues, which are the key knots for establishing a functional model.
Firstly, we studied the mechanism of face aftereffect. The face aftereffect is a relatively new phenomenon. Although several studies have investigated the type and temporal characteristic of adaptation, little is known about the inner mechanism of face aftereffect. It is necessary to solve two problems for modeling the face aftereffect. The first issue is to examine the possibility of adaptation propagation between low-level visual system and high-level visual system. The face consists of the many low-level visual properties such as color, shape, and lamination. These low level visual properties would also generate the adaptation effect when the face is used as an adapting stimulus. If the low-level adaptation effects can be propagated to the face system, the observed "face adaptation effect" may only originate from the low level visual system, rather than the face neural system. In this case, it is not reasonable to use the adaptation as a face research tool, because the adaptation is not really related to the face neural system. Thus, it is clear to be important to examine the relationship between the low-level and high-level adaptations. The second issue is to investigate the facilitation and inhibition effects for neurons with the various adaptation times. Once the facilitation and inhibition characteristic is clarified, it is possible to establish the computational model for face aftereffect by means of simulation technology. For these two issues, we firstly measured the adaptation effect from the color and figure stimuli on the real face. These results were used to evaluate the propagation of adaptation effect from the low-level visual system to the face system. Then, we employed the single dimension threshold method to examine the facilitation and inhibition effects. Based on these results, we developed a computational model for face aftereffect. This study is expected to lay a methodology foundation for the further investigation in the dissertation.
In the second issue, we investigated the types of neural representation for human expression recognition. In the previous twenties years, there is an imbalance between studies of the facial identity processing and facial expression processing. The facial identity recognition have been studied within the framework in the psychophysics, brain imaging, information modeling fields, where researchers has focused on functional organization and perceptual representation of facial identity. The facial expression recognition has, however, been heavily influenced by the social psychology studies, and consequently, a firm emphasis has been placed on understanding the communicative value of signals of expression rather than their perceptual representation. Hence, the perceptual mechanisms and neural representation underlying facial expression recognition have not been extensively clarified. We intend to study the neural representation for the human expression using the adaptation paradigm. The face generally consists of two types of information, i.e., the local feature and configuration. There are historically inconsistent ideas about the role of features and configuration on the expression perception. The feature model suggests that only local features contribute to the expression perception. The configuration model, however, hold that not only features but also configuration will play an important role in the expression perception. We measured the adaptation effect from the local features such as the eye area and mouth area, and then introduced the SFDC face and inverted face to evaluate the contribution from the configuration. The result suggested the existence of feature based neural representation and configuration based neural representation. This issue has implication on the perceptual representation and mechanism for the expression perception, and on the automatic expression recognition.
Finally, we studied the functional relationship between facial identity processing and expression processing. The human can easily identify the other people's face with the different emotional expressions (face identification), and, on the other hand, can recognize the expression from the different faces (expression recognition). Whether the face identity processing and expression processing are parallel functionally and anatomically? There is a long term debate about this issue in the face-related studies. The classical models hold that expression and face identity are processed by the parallel neural routes; this parallel hypothesis is supported by the some evidences from the behavior science, brain imaging studies, and information modeling studies. Other evidences, however, suggested that there is possibly a functional interaction between two neural routes. We used the visual adaptation to investigate this issue by measuring the expression aftereffect with the identity variance, and measuring the identity aftereffect with the expression variance. The results show that identity change significantly reduced the expression aftereffect, while the expression variance did not influence the identity aftereffect. Based on this asymmetrical interference, we proposed a one-way hierarchical model. This findings challenge the parallel hypothesis for the processing of expression and face identity in the classical models.
To conclude, this dissertation takes the face neural processing mechanism and its information modeling as research topic. Based on the extensive experimental measurements, we made the investigations on these issues, i.e.,1) cross-level adaptation effect propagation,2) the function relationship between facial identity processing and expression processing,3) the type of neural representation for expression. The dissertation has the below theoretical implications on the face studies.
Found the adaptation propagation between low-level system and face system.
Established the functional model for face aftereffect by means of simulation.
Confirmed the configuration based neural representation for the expression.
Clarified the functional relationship between facial identity processing and expression processing.
引文
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