斑图识别

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In psychology and cognitive neuroscience, pattern recognition describes cognitive process that matches information from a stimulus with information retrieved from memory.[1]

In psychology and cognitive neuroscience, pattern recognition describes cognitive process that matches information from a stimulus with information retrieved from memory.

在心理学和认知神经科学心理学中,模式识别描述了将刺激信息与从记忆中提取的信息相匹配的认知过程。



Pattern recognition occurs when information from the environment is received and entered into short-term memory, causing automatic activation of a specific content of long-term memory. An early example of this is learning the alphabet in order. When a carer repeats ‘A, B, C’ multiple times to a child, utilizing the pattern recognition, the child says ‘C’ after he/she hears ‘A, B’ in order. Recognizing patterns allow us to predict and expect what is coming. The process of pattern recognition involves matching the information received with the information already stored in the brain. Making the connection between memories and information perceived is a step of pattern recognition called identification. Pattern recognition requires repetition of experience. Semantic memory, which is used implicitly and subconsciously is the main type of memory involved with recognition.[2]

Pattern recognition occurs when information from the environment is received and entered into short-term memory, causing automatic activation of a specific content of long-term memory. An early example of this is learning the alphabet in order. When a carer repeats ‘A, B, C’ multiple times to a child, utilizing the pattern recognition, the child says ‘C’ after he/she hears ‘A, B’ in order. Recognizing patterns allow us to predict and expect what is coming. The process of pattern recognition involves matching the information received with the information already stored in the brain. Making the connection between memories and information perceived is a step of pattern recognition called identification. Pattern recognition requires repetition of experience. Semantic memory, which is used implicitly and subconsciously is the main type of memory involved with recognition.

当来自环境的信息被接收并进入短时记忆时,模式识别就发生了,从而导致长时记忆中某一特定内容的自动激活。一个早期的例子就是按顺序学习字母表。当一个照顾者对一个孩子重复“ a,b,c”多次,利用模式识别,孩子在听到“ a,b”后说“ c”。识别模式使我们能够预测和期待即将发生的事情。模式识别的过程包括将接收到的信息与已经存储在大脑中的信息进行匹配。使记忆和信息之间的联系被感知是模式识别的一个步骤,称为识别。模式识别需要重复的经验。语义记忆是与再认相关的主要记忆类型,它是隐性和潜意识使用的记忆。



Pattern recognition is not only crucial to humans, but to other animals as well. Even koalas, who possess less-developed thinking abilities, use pattern recognition to find and consume eucalyptus leaves. The human brain has developed more, but holds similarities to the brains of birds and lower mammals. The development of neural networks in the outer layer of the brain in humans has allowed for better processing of visual and auditory patterns. Spatial positioning in the environment, remembering findings, and detecting hazards and resources to increase chances of survival are examples of the application of pattern recognition for humans and animals.[3]

Pattern recognition is not only crucial to humans, but to other animals as well. Even koalas, who possess less-developed thinking abilities, use pattern recognition to find and consume eucalyptus leaves. The human brain has developed more, but holds similarities to the brains of birds and lower mammals. The development of neural networks in the outer layer of the brain in humans has allowed for better processing of visual and auditory patterns. Spatial positioning in the environment, remembering findings, and detecting hazards and resources to increase chances of survival are examples of the application of pattern recognition for humans and animals.

模式识别不仅对人类至关重要,对其他动物也是如此。即使是思维能力较弱的考拉,也会使用模式识别技术来寻找和消耗桉树叶。人类的大脑进化得更多,但与鸟类和低等哺乳动物的大脑有相似之处。人类大脑外层的神经网络的发展使得视觉和听觉模式的处理能力得以提高。在环境中进行空间定位,记住发现,检测危险和资源以增加生存机会,这些都是模式识别在人类和动物中应用的例子。



There are six main theories of pattern recognition: template matching, prototype-matching, feature analysis, recognition-by-components theory, bottom-up and top-down processing, and Fourier analysis. The application of these theories in everyday life is not mutually exclusive. Pattern recognition allows us to read words, understand language, recognize friends, and even appreciate music. Each of the theories applies to various activities and domains where pattern recognition is observed. Facial, music and language recognition, and seriation are a few of such domains. Facial recognition and seriation occur through encoding visual patterns, while music and language recognition use the encoding of auditory patterns.

There are six main theories of pattern recognition: template matching, prototype-matching, feature analysis, recognition-by-components theory, bottom-up and top-down processing, and Fourier analysis. The application of these theories in everyday life is not mutually exclusive. Pattern recognition allows us to read words, understand language, recognize friends, and even appreciate music. Each of the theories applies to various activities and domains where pattern recognition is observed. Facial, music and language recognition, and seriation are a few of such domains. Facial recognition and seriation occur through encoding visual patterns, while music and language recognition use the encoding of auditory patterns.

模式识别主要有6种理论: 模板匹配、原型匹配、特征分析、按部件识别理论、自下而上和自上而下的处理以及傅立叶变换家族中的关系。这些理论在日常生活中的应用并不是相互排斥的。模式识别允许我们阅读文字,理解语言,认识朋友,甚至欣赏音乐。每一种理论都适用于观察模式识别的各种活动和领域。面部、音乐、语言识别和序列化是其中的几个领域。人脸识别和序列化是通过编码视觉模式实现的,而音乐和语言识别则是通过编码听觉模式实现的。



Theories

Theories

理论



Template matching

Template matching

模板匹配

Template matching theory describes the most basic approach to human pattern recognition. It is a theory that assumes every perceived object is stored as a "template" into long-term memory.[4] Incoming information is compared to these templates to find an exact match.[5] In other words, all sensory input is compared to multiple representations of an object to form one single conceptual understanding. The theory defines perception as a fundamentally recognition-based process. It assumes that everything we see, we understand only through past exposure, which then informs our future perception of the external world.[6] For example, A, A, and A are all recognized as the letter A, but not B. This viewpoint is limited, however, in explaining how new experiences can be understood without being compared to an internal memory template.[citation needed]

Template matching theory describes the most basic approach to human pattern recognition. It is a theory that assumes every perceived object is stored as a "template" into long-term memory. Incoming information is compared to these templates to find an exact match. In other words, all sensory input is compared to multiple representations of an object to form one single conceptual understanding. The theory defines perception as a fundamentally recognition-based process. It assumes that everything we see, we understand only through past exposure, which then informs our future perception of the external world. For example, A, A, and A are all recognized as the letter A, but not B. This viewpoint is limited, however, in explaining how new experiences can be understood without being compared to an internal memory template.

模板匹配理论描述了人类模式识别最基本的方法。这个理论假设每一个感知到的物体都作为一个“模板”储存到长期记忆中。输入的信息与这些模板进行比较,以找到精确的匹配。换句话说,所有的感官输入都与一个物体的多重表征相比较,从而形成一个单一的概念理解。该理论将感知定义为一个基本的基于认知的过程。它假设我们所看到的一切,我们只能通过过去的接触来理解,然后通过过去的接触来影响我们对外部世界的未来感知。例如,a、 a 和 a 都被认为是字母 a,而不是字母 b。然而,这种观点在解释如何理解新的经验而不用与内部记忆模板相比较方面是有限的。



Prototype matching

Prototype matching

原型匹配

Unlike the exact, one-to-one, template matching theory, prototype matching instead compares incoming sensory input to one average prototype.[citation needed] This theory proposes that exposure to a series of related stimuli leads to the creation of a "typical" prototype based on their shared features.[6] It reduces the number of stored templates by standardizing them into a single representation.[4] The prototype supports perceptual flexibility, because unlike in template matching, it allows for variability in the recognition of novel stimuli.[citation needed] For instance, if a child had never seen a lawn chair before, they would still be able to recognize it as a chair because of their understanding of its essential characteristics as having four legs and a seat. This idea, however, limits the conceptualization of objects that cannot necessarily be "averaged" into one, like types of canines, for instance. Even though dogs, wolves, and foxes are all typically furry, four-legged, moderately sized animals with ears and a tail, they are not all the same, and thus cannot be strictly perceived with respect to the prototype matching theory.

Unlike the exact, one-to-one, template matching theory, prototype matching instead compares incoming sensory input to one average prototype. This theory proposes that exposure to a series of related stimuli leads to the creation of a "typical" prototype based on their shared features. It reduces the number of stored templates by standardizing them into a single representation. The prototype supports perceptual flexibility, because unlike in template matching, it allows for variability in the recognition of novel stimuli. For instance, if a child had never seen a lawn chair before, they would still be able to recognize it as a chair because of their understanding of its essential characteristics as having four legs and a seat. This idea, however, limits the conceptualization of objects that cannot necessarily be "averaged" into one, like types of canines, for instance. Even though dogs, wolves, and foxes are all typically furry, four-legged, moderately sized animals with ears and a tail, they are not all the same, and thus cannot be strictly perceived with respect to the prototype matching theory.

与精确的一对一的模板匹配理论不同,原型匹配是将输入的感官输入与一个平均的原型进行比较。这一理论认为,暴露于一系列相关的刺激,导致创建一个“典型的”原型的基础上,他们的共同特征。它通过将存储的模板标准化为单个表示形式来减少存储的模板数量。原型支持感知灵活性,因为不同于模板匹配,它允许在识别新的刺激变化。例如,如果一个孩子以前从未见过草坪椅,他们仍然能够认出它是一把椅子,因为他们理解它的基本特征是有四条腿和一个座位。然而,这种想法限制了对象的概念化,不一定能够“平均化”成一个对象,例如犬齿的类型。尽管狗、狼和狐狸都是典型的毛茸茸的、四条腿的、有耳朵和尾巴的中等大小的动物,但它们并不都是一样的,因此根据原型匹配理论,它们并不能被严格地理解。



Feature analysis

Feature analysis

特征分析

Multiple theories try to explain how humans are able to recognize patterns in their environment. Feature detection theory proposes that the nervous system sorts and filters incoming stimuli to allow the human (or animal) to make sense of the information. In the organism, this system is made up of feature detectors, which are individual neurons, or groups of neurons, that encode specific perceptual features. The theory proposes an increasing complexity in the relationship between detectors and the perceptual feature. The most basic feature detectors respond to simple properties of the stimuli. Further along the perceptual pathway, higher organized feature detectors are able to respond to more complex and specific stimuli properties. When features repeat or occur in a meaningful sequence, we are able to identify these patterns because of our feature detection system.

Multiple theories try to explain how humans are able to recognize patterns in their environment. Feature detection theory proposes that the nervous system sorts and filters incoming stimuli to allow the human (or animal) to make sense of the information. In the organism, this system is made up of feature detectors, which are individual neurons, or groups of neurons, that encode specific perceptual features. The theory proposes an increasing complexity in the relationship between detectors and the perceptual feature. The most basic feature detectors respond to simple properties of the stimuli. Further along the perceptual pathway, higher organized feature detectors are able to respond to more complex and specific stimuli properties. When features repeat or occur in a meaningful sequence, we are able to identify these patterns because of our feature detection system.

多种理论试图解释人类如何能够识别环境中的模式。特征提取理论认为,神经系统对接收到的刺激进行分类和过滤,使人类(或动物)能够理解这些信息。在有机体中,这个系统是由特征探测器组成的,这些特征探测器是编码特定感知特征的单个神经元或神经元组。该理论认为检测器和感知特征之间的关系越来越复杂。最基本的特征探测器响应简单的属性的刺激。进一步沿着感知路径,更高的组织特征探测器能够响应更复杂和特定的刺激特性。当特征以一个有意义的顺序重复或出现时,我们能够识别这些模式,因为我们的特征提取系统。



Multiple discrimination scaling

Multiple discrimination scaling

多重鉴别标度

模板:Unclear


Template and feature analysis approaches to recognition of objects (and situations) have been merged / reconciled / overtaken by multiple discrimination theory. This states that the amounts in a test stimulus of each salient feature of a template are recognized in any perceptual judgment as being at a distance in the universal unit of 50% discrimination (the objective performance 'JND'模板:Clarification needed[7]) from the amount of that feature in the template.[8]

Template and feature analysis approaches to recognition of objects (and situations) have been merged / reconciled / overtaken by multiple discrimination theory. This states that the amounts in a test stimulus of each salient feature of a template are recognized in any perceptual judgment as being at a distance in the universal unit of 50% discrimination (the objective performance 'JND') from the amount of that feature in the template.

基于模板和特征分析的目标(和情景)识别方法已被多重判别理论融合、调和、超越。这表明,在任何感知判断中,模板每个显著特征的测试刺激的数量与模板中该特征的数量相差50% 的通用识别单位(客观表现为“ JND”)。



Recognition by components theory

Recognition by components theory

用构件理论进行识别

文件:Breakdown of objects into Geons.png
Image showing the breakdown of common geometric shapes (geons)

Image showing the breakdown of common geometric shapes (geons)

图片显示了常见 Unicode几何图形列表的分类

Similar to feature detection theory, recognition by components (RBC) focuses on the bottom-up features of the stimuli being processed. First proposed by Irving Biederman (1987), this theory states that humans recognize objects by breaking them down into their basic 3D geometric shapes called geons (i.e. cylinders, cubes, cones, etc.). An example is how we break down a common item like a coffee cup: we recognize the hollow cylinder that holds the liquid and a curved handle off the side that allows us to hold it. Even though not every coffee cup is exactly the same, these basic components helps us to recognize the consistency across examples (or pattern). RBC suggests that there are fewer than 36 unique geons that when combined can form a virtually unlimited number of objects. To parse and dissect an object, RBC proposes we attend to two specific features: edges and concavities. Edges enable the observer to maintain a consistent representation of the object regardless of the viewing angle and lighting conditions. Concavities are where two edges meet and enable the observer to perceive where one geon ends and another begins.

Similar to feature detection theory, recognition by components (RBC) focuses on the bottom-up features of the stimuli being processed. First proposed by Irving Biederman (1987), this theory states that humans recognize objects by breaking them down into their basic 3D geometric shapes called geons (i.e. cylinders, cubes, cones, etc.). An example is how we break down a common item like a coffee cup: we recognize the hollow cylinder that holds the liquid and a curved handle off the side that allows us to hold it. Even though not every coffee cup is exactly the same, these basic components helps us to recognize the consistency across examples (or pattern). RBC suggests that there are fewer than 36 unique geons that when combined can form a virtually unlimited number of objects. To parse and dissect an object, RBC proposes we attend to two specific features: edges and concavities. Edges enable the observer to maintain a consistent representation of the object regardless of the viewing angle and lighting conditions. Concavities are where two edges meet and enable the observer to perceive where one geon ends and another begins.

与特征提取理论相似,成分识别关注的是刺激被处理时的自下而上的特征。这个理论最早由 Irving Biederman (1987)提出,他认为人类识别物体的方法是把它们分解成基本的3 d Unicode几何图形列表,称为 geons。圆柱体、立方体、圆锥体等)。举个例子,我们如何分解一个普通的东西,比如咖啡杯: 我们认出了容纳液体的中空圆柱体和一个可以让我们容纳它的弯曲手柄。尽管不是每个咖啡杯都是完全相同的,但这些基本组件可以帮助我们识别不同例子(或模式)的一致性。Rbc 认为,只有不到36个唯一的吉恩,当它们组合在一起时,可以形成几乎无限数量的物体。为了解析和剖析一个对象,RBC 建议我们关注两个特定的特征: 边和凹陷。边使观察者能够保持一致的代表性的对象,不管视角和照明条件。凹陷是两条边相交的地方,使观察者能够感知一条外科手术的终点和另一条手术的起点。



The RBC principles of visual object recognition can be applied to auditory language recognition as well. In place of geons, language researchers propose that spoken language can be broken down into basic components called phonemes. For example, there are 44 phonemes in the English language.

The RBC principles of visual object recognition can be applied to auditory language recognition as well. In place of geons, language researchers propose that spoken language can be broken down into basic components called phonemes. For example, there are 44 phonemes in the English language.

视觉对象识别的 RBC 原理也可以应用于听觉语言识别。语言研究人员提出,口语可以分解成基本的组成部分,称为音素。例如,英语中有44个音素。



Top-down and bottom-up processing

Top-down and bottom-up processing

自上而下和自下而上的处理

Top-down processing

Top-down processing

自顶向下处理

Top-down processing refers to the use of background information in pattern recognition.[9] It always begins with a person’s previous knowledge, and makes predictions due to this already acquired knowledge.[10] Psychologist Richard Gregory estimated that about 90% of the information is lost between the time it takes to go from the eye to the brain, which is why the brain must guess what the person sees based on past experiences. In other words, we construct our perception of reality, and these perceptions are hypotheses or propositions based on past experiences and stored information. The formation of incorrect propositions will lead to errors of perception such as visual illusions.[9] Given a paragraph written with difficult handwriting, it is easier to understand what the writer wants to convey if one reads the whole paragraph rather than reading the words in separate terms. The brain may be able to perceive and understand the gist of the paragraph due to the context supplied by the surrounding words.[11]

Top-down processing refers to the use of background information in pattern recognition. It always begins with a person’s previous knowledge, and makes predictions due to this already acquired knowledge. Psychologist Richard Gregory estimated that about 90% of the information is lost between the time it takes to go from the eye to the brain, which is why the brain must guess what the person sees based on past experiences. In other words, we construct our perception of reality, and these perceptions are hypotheses or propositions based on past experiences and stored information. The formation of incorrect propositions will lead to errors of perception such as visual illusions.

自顶向下处理是指背景信息在模式识别中的应用。它总是从一个人之前的知识开始,然后根据这些已经获得的知识做出预测。心理学家理查德 · 格雷戈里估计,大约90% 的信息在从眼睛到大脑的这段时间里丢失了,这就是为什么大脑必须根据过去的经验来猜测人们看到了什么。换句话说,我们建构我们对现实的感知,这些感知是基于过去的经验和储存的信息的假设或命题。错误命题的形成会导致错误的知觉,如视错觉。



Bottom-up processing

Bottom-up processing

自下而上的处理

Bottom-up processing is also known as data-driven processing, because it originates with the stimulation of the sensory receptors.[10] Psychologist James Gibson opposed the top-down model and argued that perception is direct, and not subject to hypothesis testing as Gregory proposed. He stated that sensation is perception and there is no need for extra interpretation, as there is enough information in our environment to make sense of the world in a direct way. His theory is sometimes known as the "ecological theory" because of the claim that perception can be explained solely in terms of the environment. An example of bottom up-processing involves presenting a flower at the center of a person's field. The sight of the flower and all the information about the stimulus are carried from the retina to the visual cortex in the brain. The signal travels in one direction.[11]

Bottom-up processing is also known as data-driven processing, because it originates with the stimulation of the sensory receptors. Psychologist James Gibson opposed the top-down model and argued that perception is direct, and not subject to hypothesis testing as Gregory proposed. He stated that sensation is perception and there is no need for extra interpretation, as there is enough information in our environment to make sense of the world in a direct way. His theory is sometimes known as the "ecological theory" because of the claim that perception can be explained solely in terms of the environment. An example of bottom up-processing involves presenting a flower at the center of a person's field. The sight of the flower and all the information about the stimulus are carried from the retina to the visual cortex in the brain. The signal travels in one direction.

自下而上的处理也被称为数据驱动的处理,因为它起源于感官接收器的刺激。心理学家詹姆斯 · 吉布森反对自上而下的模型,他认为知觉是直接的,不像格雷戈里提出的那样受假设检验的影响。他说,感觉就是感觉,没有必要额外的解释,因为我们的环境中有足够的信息,可以直接感知这个世界。他的理论有时被称为“生态学理论” ,因为他声称感知可以只用环境来解释。自底向上处理的一个例子是在一个人的能量场的中心呈现一朵花。花的视觉和有关刺激的所有信息都从视网膜传送到大脑的视觉皮层。信号向一个方向传播。



Seriation

Seriation

系列化

文件:Seriation task w shapes.jpg
A simple seriation task involving arranging shapes by size

A simple seriation task involving arranging shapes by size

一个简单的序列化任务,包括按大小排列形状

In psychologist Jean Piaget's theory of cognitive development, the third stage is called the Concrete Operational State. It is during this stage that the abstract principle of thinking called "seriation" is naturally developed in a child.引用错误:没有找到与</ref>对应的<ref>标签 Seriation is the ability to arrange items in a logical order along a quantitative dimension such as length, weight, age, etc.[12] It is a general cognitive skill which is not fully mastered until after the nursery years .[13] To seriate means to understand that objects can be ordered along a dimension,[14] and to effectively do so, the child needs to be able to answer the question "What comes next?"[13] Seriation skills also help to develop problem-solving skills, which are useful in recognizing and completing patterning tasks.

</ref> Seriation is the ability to arrange items in a logical order along a quantitative dimension such as length, weight, age, etc. It is a general cognitive skill which is not fully mastered until after the nursery years . To seriate means to understand that objects can be ordered along a dimension, and to effectively do so, the child needs to be able to answer the question "What comes next?" Seriation skills also help to develop problem-solving skills, which are useful in recognizing and completing patterning tasks.

/ ref 序列化是按逻辑顺序排列项目的能力,这些项目沿着一个定量维度排列,例如长度、重量、年龄等。这是一种普遍的认知技能,直到幼儿园年龄之后才能完全掌握。序列化意味着理解对象可以沿着一个维排序,并且为了有效地这样做,子对象需要能够回答“接下来会发生什么? ”序列化技能还有助于提高解决问题的能力,这对于识别和完成模式化任务非常有用。



Piaget's work on seriation

Piaget's work on seriation

皮亚杰关于序列化的著作

Piaget studied the development of seriation along with Szeminska in an experiment where they used rods of varying lengths to test children's skills.[15] They found that there were three distinct stages of development of the skill. In the first stage, children around the age of 4 could not arrange the first ten rods in order. They could make smaller groups of 2-4, but could not put all the elements together. In

Piaget studied the development of seriation along with Szeminska in an experiment where they used rods of varying lengths to test children's skills. They found that there were three distinct stages of development of the skill. In the first stage, children around the age of 4 could not arrange the first ten rods in order. They could make smaller groups of 2-4, but could not put all the elements together. In

在一项实验中,皮亚杰和 Szeminska 一起研究了系列化的发展过程,他们用不同长度的棒子来测试孩子们的技能。他们发现这项技能的发展有三个不同的阶段。在第一阶段,4岁左右的儿童无法按顺序排列前十个杆子。他们可以分成2-4个小组,但不能把所有的元素放在一起。在

the second stage where the children were 5–6 years of age, they could succeed in the seriation task with the first ten rods through the process of trial and error. They could insert the other set of rods into order through trial and error. In the third stage, the 7-8-year-old children could arrange all the rods in order without much trial and error. The children used the systematic method of first looking for the smallest rod first and the smallest among the rest.[15]

the second stage where the children were 5–6 years of age, they could succeed in the seriation task with the first ten rods through the process of trial and error. They could insert the other set of rods into order through trial and error. In the third stage, the 7-8-year-old children could arrange all the rods in order without much trial and error. The children used the systematic method of first looking for the smallest rod first and the smallest among the rest.

在第二阶段,孩子们5-6岁,他们可以通过试验和错误的过程,成功地完成前10棒的连续任务。他们可以通过反复试验,把另外一套棒子整理好。在第三个阶段,7-8岁的孩子可以不经过多少试验和错误就把所有的杆子按顺序排列好。孩子们采用系统的方法,首先寻找最小的棒子,然后在其余的棒子中寻找最小的棒子。





Development of problem-solving skills

Development of problem-solving skills

培养解决问题的能力

To develop the skill of seriation, which then helps advance problem-solving skills, children should be provided with opportunities to arrange things in order using the appropriate language, such as "big" and "bigger" when working with size relationships. They should also be given the chance to arrange objects in order based on the texture, sound, flavor and color.[13] Along with specific tasks of seriation, children should be given the chance to compare the different materials and toys they use during play. Through activities like these, the true understanding of characteristics of objects will develop. To aid them at a young age, the differences between the objects should be obvious.[13] Lastly, a more complicated task of arranging two different sets of objects and seeing the relationship between the two different sets should also be provided. A common example of this is having children attempt to fit saucepan lids to saucepans of different sizes, or fitting together different sizes of nuts and bolts.[13]

To develop the skill of seriation, which then helps advance problem-solving skills, children should be provided with opportunities to arrange things in order using the appropriate language, such as "big" and "bigger" when working with size relationships. They should also be given the chance to arrange objects in order based on the texture, sound, flavor and color. Along with specific tasks of seriation, children should be given the chance to compare the different materials and toys they use during play. Through activities like these, the true understanding of characteristics of objects will develop. To aid them at a young age, the differences between the objects should be obvious. Lastly, a more complicated task of arranging two different sets of objects and seeing the relationship between the two different sets should also be provided. A common example of this is having children attempt to fit saucepan lids to saucepans of different sizes, or fitting together different sizes of nuts and bolts.

为了发展系列化的技能,从而有助于提高解决问题的技能,应该为儿童提供机会,让他们在处理体型关系时使用适当的语言,例如”大”和”大”。他们还应该有机会根据质地、声音、味道和颜色来排列物体。除了具体的系列任务,孩子们应该有机会比较不同的材料和玩具,他们在玩耍中使用。通过这些活动,对物体特征的真正理解将得到发展。为了帮助他们在年轻的时候,物体之间的差异应该是明显的。最后,还应提供一项更复杂的任务,即安排两组不同的对象并查看两组不同对象之间的关系。一个常见的例子就是让孩子们尝试把炖锅的盖子安装到不同大小的炖锅上,或者把不同大小的螺母和螺栓安装在一起。



Application of seriation in schools

Application of seriation in schools

系列化在学校中的应用

To help build up math skills in children, teachers and parents can help them learn seriation and patterning. Young children who understand seriation can put numbers in order from lowest to highest. Eventually, they will come to understand that 6 is higher than 5, and 20 is higher than 10.[16] Similarly, having children copy patterns or create patterns of their own, like ABAB patterns, is a great way to help them recognize order and prepare for later math skills, such as multiplication. Child care providers can begin exposing children to patterns at a very young age by having them make groups and count the total number of objects.[16]

To help build up math skills in children, teachers and parents can help them learn seriation and patterning. Young children who understand seriation can put numbers in order from lowest to highest. Eventually, they will come to understand that 6 is higher than 5, and 20 is higher than 10. Similarly, having children copy patterns or create patterns of their own, like ABAB patterns, is a great way to help them recognize order and prepare for later math skills, such as multiplication. Child care providers can begin exposing children to patterns at a very young age by having them make groups and count the total number of objects.

为了帮助孩子建立数学技能,老师和家长可以帮助他们学习系列化和模式化。懂得序列化的幼儿可以将数字按从低到高的顺序排列。最终,他们会明白6比5高,20比10高。类似地,让孩子们模仿模式或者创建他们自己的模式,比如 ABAB 模式,是帮助他们识别顺序和为以后的数学技能做准备的好方法,比如乘法。儿童保育提供者可以让儿童在很小的时候就开始接触这些模式,让他们分组并计算物品的总数。



Facial pattern recognition

Facial pattern recognition

面部模式识别

Recognizing faces is one of the most common forms of pattern recognition. Humans are incredibly effective at remembering faces, but this ease and automaticity belies a very challenging problem.[17][18] All faces are physically similar. Faces have two eyes, one mouth, and one nose all in predictable locations, yet humans can recognize a face from several different angles and in various lighting conditions.[18]

Recognizing faces is one of the most common forms of pattern recognition. Humans are incredibly effective at remembering faces, but this ease and automaticity belies a very challenging problem. All faces are physically similar. Faces have two eyes, one mouth, and one nose all in predictable locations, yet humans can recognize a face from several different angles and in various lighting conditions.

人脸识别是最常见的模式识别形式之一。人类在记忆面孔方面的效率令人难以置信,但这种轻松和自动性掩盖了一个非常具有挑战性的问题。所有的面孔在外形上都是相似的。人脸有两只眼睛,一张嘴和一个鼻子,所有这些都在可预测的位置,但是人类可以从几个不同的角度和在不同的光线条件下认出一张脸。



Neuroscientists posit that recognizing faces takes place in three phases. The first phase starts with visually focusing on of the physical features. The facial recognition system then needs to reconstruct the identity of the person from previous experiences. This provides us with the signal that this might be a person we know. The final phase of recognition completes when the face elicits the name of the person.[19]

Neuroscientists posit that recognizing faces takes place in three phases. The first phase starts with visually focusing on of the physical features. The facial recognition system then needs to reconstruct the identity of the person from previous experiences. This provides us with the signal that this might be a person we know. The final phase of recognition completes when the face elicits the name of the person.

神经科学家认为人脸识别分为三个阶段。第一阶段从视觉上关注物理特征开始。然后,面部识别系统需要根据之前的经验重建人的身份。这给了我们一个信号,这可能是一个我们认识的人。识别的最后阶段是当面孔提取出人的名字时。



Although humans are great at recognizing faces under normal viewing angles, upside-down faces are tremendously difficult to recognize. This demonstrates not only the challenges of facial recognition but also how humans have specialized procedures and capacities for recognizing faces under normal upright viewing conditions.[18]

Although humans are great at recognizing faces under normal viewing angles, upside-down faces are tremendously difficult to recognize. This demonstrates not only the challenges of facial recognition but also how humans have specialized procedures and capacities for recognizing faces under normal upright viewing conditions.

虽然人类很擅长在正常视角下识别面孔,但是颠倒的面孔是非常难以识别的。这不仅表明了面部识别的挑战,而且也表明了人类在正常直立观看条件下识别面部的特殊程序和能力。



Neural mechanisms

Neural mechanisms

神经机制

文件:Fusiform Face Area - animation1.gif
Brain animation highlighting the fusiform face area, thought to be where facial processing and recognition takes place

Brain animation highlighting the fusiform face area, thought to be where facial processing and recognition takes place

大脑动画突出了梭状回面孔区,这被认为是面部处理和识别发生的地方

Scientists agree that there is a certain area in the brain specifically devoted to processing faces. This structure is called the fusiform gyrus, and brain imaging studies have shown that it becomes highly active when a subject is viewing a face.[20]

Scientists agree that there is a certain area in the brain specifically devoted to processing faces. This structure is called the fusiform gyrus, and brain imaging studies have shown that it becomes highly active when a subject is viewing a face.

科学家们一致认为,大脑中有一个特定的区域专门负责处理面孔信息。这种结构被称为梭状回,脑成像研究表明,当受试者观看一张脸时,梭状回变得高度活跃。



Several case studies have reported that patients with lesions or tissue damage localized to this area have tremendous difficulty recognizing faces, even their own. Although most of this research is circumstantial, a study at Stanford University provided conclusive evidence for the fusiform gyrus' role in facial recognition. In a unique case study, researchers were able to send direct signals to a patient's fusiform gyrus. The patient reported that the faces of the doctors and nurses changed and morphed in front of him during this electrical stimulation. Researchers agree this demonstrates a convincing causal link between this neural structure and the human ability to recognize faces.[20]

Several case studies have reported that patients with lesions or tissue damage localized to this area have tremendous difficulty recognizing faces, even their own. Although most of this research is circumstantial, a study at Stanford University provided conclusive evidence for the fusiform gyrus' role in facial recognition. In a unique case study, researchers were able to send direct signals to a patient's fusiform gyrus. The patient reported that the faces of the doctors and nurses changed and morphed in front of him during this electrical stimulation. Researchers agree this demonstrates a convincing causal link between this neural structure and the human ability to recognize faces.

一些案例研究报告说,病变或组织损伤局限于这一区域的患者极难识别面孔,甚至他们自己的面孔。虽然这项研究大部分是间接的,但斯坦福大学的一项研究为梭状回在面部识别中的作用提供了确凿的证据。在一个独特的案例研究中,研究人员能够向病人的梭状回直接发送信号。病人报告说,在电刺激过程中,医生和护士的面孔在他面前改变和变形。研究人员同意,这证明了这种神经结构与人类识别面孔的能力之间存在令人信服的因果关系。



Facial recognition development

Facial recognition development

面部识别的发展

Although in adults, facial recognition is fast and automatic, children do not reach adult levels of performance (in laboratory tasks) until adolescence.[21] Two general theories have been put forth to explain how facial recognition normally develops. The first, general cognitive development theory, proposes that the perceptual ability to encode faces is fully developed early in childhood, and that the continued improvement of facial recognition into adulthood is attributed to other general factors. These general factors include improved attentional focus, deliberate task strategies, and metacognition. Research supports the argument that these other general factors improve dramatically into adulthood.[21] Face-specific perceptual development theory argues that the improved facial recognition between children and adults is due to a precise development of facial perception. The cause for this continuing development is proposed to be an ongoing experience with faces.

Although in adults, facial recognition is fast and automatic, children do not reach adult levels of performance (in laboratory tasks) until adolescence. Two general theories have been put forth to explain how facial recognition normally develops. The first, general cognitive development theory, proposes that the perceptual ability to encode faces is fully developed early in childhood, and that the continued improvement of facial recognition into adulthood is attributed to other general factors. These general factors include improved attentional focus, deliberate task strategies, and metacognition. Research supports the argument that these other general factors improve dramatically into adulthood. Face-specific perceptual development theory argues that the improved facial recognition between children and adults is due to a precise development of facial perception. The cause for this continuing development is proposed to be an ongoing experience with faces.

虽然在成年人中,面部识别是快速和自动的,儿童直到青春期才达到成年人的表现水平(在实验室任务中)。人们提出了两种理论来解释面部识别是如何正常发展的。第一种是一般认知发展理论,认为对面孔进行编码的感知能力在童年早期就已经充分发展,而面孔识别能力在成年后的持续提高归因于其他一般因素。这些一般因素包括注意力集中程度的提高、刻意任务策略和元认知。研究支持这样的论点,即这些其他的一般因素在成年后会显著改善。面孔特异性知觉发展理论认为,儿童和成人之间面孔识别的提高是由于面孔知觉的精确发展。这种持续发展的原因被认为是一种持续的面孔经验。



Developmental issues

Developmental issues

发展问题

Several developmental issues manifest as a decreased capacity for facial recognition. Using what is known about the role of the fusiform gyrus, research has shown that impaired social development along the autism spectrum is accompanied by a behavioral marker where these individuals tend to look away from faces, and a neurological marker characterized by decreased neural activity in the fusiform gyrus. Similarly, those with developmental prosopagnosia (DP) struggle with facial recognition to the extent they are often unable to identify even their own faces. Many studies report that around 2% of the world’s population have developmental prosopagnosia, and that individuals with DP have a family history of the trait.引用错误:没有找到与</ref>对应的<ref>标签 Individuals with DP are behaviorally indistinguishable from those with physical damage or lesions on the fusiform gyrus, again implicating its importance to facial recognition. Despite those with DP or neurological damage, there remains a large variability in facial recognition ability in the total population.[18] It is unknown what accounts for the differences in facial recognition ability, whether it is a biological or environmental disposition. Recent research analyzing identical and fraternal twins showed that facial recognition was significantly higher correlated in identical twins, suggesting a strong genetic component to individual differences in facial recognition ability.[18]

http://www.apa.org/science/about/psa/2015/06/face-recognition.aspx</ref> Individuals with DP are behaviorally indistinguishable from those with physical damage or lesions on the fusiform gyrus, again implicating its importance to facial recognition. Despite those with DP or neurological damage, there remains a large variability in facial recognition ability in the total population. It is unknown what accounts for the differences in facial recognition ability, whether it is a biological or environmental disposition. Recent research analyzing identical and fraternal twins showed that facial recognition was significantly higher correlated in identical twins, suggesting a strong genetic component to individual differences in facial recognition ability.

患有 DP 的个体在行为上与那些梭状回有物理损伤或损伤的个体没有区别,再次暗示了其对面部识别的重要性。尽管有 DP 或神经损伤,在总人群中面部识别能力仍然存在很大的变异性。不知道是什么原因导致了面部识别能力的差异,无论是生物还是环境因素。最近分析同卵和异卵双胞胎的研究表明,同卵双胞胎的面部识别率明显高于同卵双胞胎,这表明面部识别能力的个体差异有很强的遗传因素。



Language development

Language development

语言发展



Pattern recognition in language acquisition

Pattern recognition in language acquisition

语言习得中的模式识别

Recent模板:When research reveals that infant language acquisition is linked to cognitive pattern recognition.[22] Unlike classical nativist and behavioral theories of language development,[23] scientists now believe that language is a learned skill.[22] Studies at the Hebrew University and the University of Sydney both show a strong correlation between the ability to identify visual patterns and to learn a new language.[22][24] Children with high shape recognition showed better grammar knowledge, even when controlling for the effects of intelligence and memory capacity.[24] This is supported by the theory that language learning is based on statistical learning,[22] the process by which infants perceive common combinations of sounds and words in language and use them to inform future speech production.

Recent research reveals that infant language acquisition is linked to cognitive pattern recognition. Unlike classical nativist and behavioral theories of language development, scientists now believe that language is a learned skill. Children with high shape recognition showed better grammar knowledge, even when controlling for the effects of intelligence and memory capacity. This is supported by the theory that language learning is based on statistical learning, the process by which infants perceive common combinations of sounds and words in language and use them to inform future speech production.

最近的研究表明,婴儿语言习得与认知模式识别有关。不像经典的先天论和语言发展的行为理论,科学家们现在相信语言是一种可学习的技能。形状识别率高的儿童表现出更好的语法知识,即使控制了智力和记忆容量的影响。这一观点得到了语言学习基于统计学习理论的支持。统计学习是指婴儿感知语言中常见的声音和词汇组合,并利用这些声音和词汇来指导未来的语言产出的过程。



Phonological development

Phonological development

语音发展

The first step in infant language acquisition is to decipher between the most basic sound units of their native language. This includes every consonant, every short and long vowel sound, and any additional letter combinations like "th" and "ph" in English. These units, called phonemes, are detected through exposure and pattern recognition. Infants use their "innate feature detector" capabilities to distinguish between the sounds of words.[23] They split them into phonemes through a mechanism of categorical perception. Then they extract statistical information by recognizing which combinations of sounds are most likely to occur together,[23] like "qu" or "h" plus a vowel. In this way, their ability to learn words is based directly on the accuracy of their earlier phonetic patterning.

The first step in infant language acquisition is to decipher between the most basic sound units of their native language. This includes every consonant, every short and long vowel sound, and any additional letter combinations like "th" and "ph" in English. These units, called phonemes, are detected through exposure and pattern recognition. Infants use their "innate feature detector" capabilities to distinguish between the sounds of words. They split them into phonemes through a mechanism of categorical perception. Then they extract statistical information by recognizing which combinations of sounds are most likely to occur together, like "qu" or "h" plus a vowel. In this way, their ability to learn words is based directly on the accuracy of their earlier phonetic patterning.

婴儿语言习得的第一步是在母语中最基本的语音单位之间进行辨认。这包括每个辅音,每个短元音和长元音,以及英语中任何附加的字母组合,如“ th”和“ ph”。这些单位,称为音素,是通过曝光和模式识别检测。婴儿使用他们的“先天特征探测器”能力来区分词语的发音。他们通过一种明确的知觉机制把它们分成音素。然后,他们通过识别哪些声音组合最有可能出现在一起来提取统计信息,比如“ qu”或者“ h”加上一个元音。这样,他们学习单词的能力就直接取决于他们早期语音模式的准确性。



Grammar development

Grammar development

语法发展

The transition from phonemic differentiation into higher-order word production[23] is only the first step in the hierarchical acquisition of language. Pattern recognition is furthermore utilized in the detection of prosody cues, the stress and intonation patterns among words.[23] Then it is applied to sentence structure and the understanding of typical clause boundaries.[23] This entire process is reflected in reading as well. First, a child recognizes patterns of individual letters, then words, then groups of words together, then paragraphs, and finally entire chapters in books.[25] Learning to read and learning to speak a language are based on the "stepwise refinement of patterns"[25] in perceptual pattern recognition.

The transition from phonemic differentiation into higher-order word production Learning to read and learning to speak a language are based on the "stepwise refinement of patterns" in perceptual pattern recognition.

从音位分化到高阶词产生的转变学习阅读和学习说话是基于知觉模式识别中的“模式的逐步细化”。



Music pattern recognition

Music pattern recognition

音乐模式识别

Music provides deep and emotional experiences for the listener.[26] These experiences become contents in long-term memory, and every time we hear the same tunes, those contents are activated. Recognizing the content by the pattern of the music affects our emotion. The mechanism that forms the pattern recognition of music and the experience has been studied by multiple researchers. The sensation felt when listening to our favorite music is evident by the dilation of the pupils, the increase in pulse and blood pressure, the streaming of blood to the leg muscles, and the activation of the cerebellum, the brain region associated with physical movement.[26]

Music provides deep and emotional experiences for the listener. These experiences become contents in long-term memory, and every time we hear the same tunes, those contents are activated. Recognizing the content by the pattern of the music affects our emotion. The mechanism that forms the pattern recognition of music and the experience has been studied by multiple researchers. The sensation felt when listening to our favorite music is evident by the dilation of the pupils, the increase in pulse and blood pressure, the streaming of blood to the leg muscles, and the activation of the cerebellum, the brain region associated with physical movement.

音乐为听众提供了深刻的情感体验。这些经历成为长期记忆的内容,每次我们听到相同的曲调,这些内容就被激活。通过音乐的模式来识别内容会影响我们的情绪。音乐模式识别的形成机制和经验已经成为众多学者研究的课题。听我们最喜欢的音乐时的感觉是明显的: 瞳孔放大,脉搏和血压升高,血液流向腿部肌肉,小脑活动,大脑区域与身体运动有关。

While retrieving the memory of a tune demonstrates general recognition of musical pattern, pattern recognition also occurs while listening to a tune for the first time. The recurring nature of the metre allows the listener to follow a tune, recognize the metre, expect its upcoming occurrence, and figure the rhythm. The excitement of following a familiar music pattern happens when the pattern breaks and becomes unpredictable. This following and breaking of a pattern creates a problem-solving opportunity for the mind that form the experience.[26] Psychologist Daniel Levitin argues that the repetitions, melodic nature and organization of this music create meaning for the brain.[27] The brain stores information in an arrangement of neurons which retrieve the same information when activated by the environment. By constantly referencing information and additional stimulation from the environment, the brain constructs musical features into a perceptual whole.[27]

While retrieving the memory of a tune demonstrates general recognition of musical pattern, pattern recognition also occurs while listening to a tune for the first time. The recurring nature of the metre allows the listener to follow a tune, recognize the metre, expect its upcoming occurrence, and figure the rhythm. The excitement of following a familiar music pattern happens when the pattern breaks and becomes unpredictable. This following and breaking of a pattern creates a problem-solving opportunity for the mind that form the experience. The brain stores information in an arrangement of neurons which retrieve the same information when activated by the environment. By constantly referencing information and additional stimulation from the environment, the brain constructs musical features into a perceptual whole.

虽然检索一个曲调的记忆展示了对音乐模式的一般识别,模式识别也发生在第一次听一个曲调的时候。韵律的重复性使得听众能够跟随一个曲调,识别出韵律,期待它即将到来的发生,并找到节奏。当一个熟悉的音乐模式被打破并且变得不可预知的时候,这种跟随着熟悉的音乐模式的兴奋就会发生。这种模式的遵循和打破为形成体验的头脑创造了一个解决问题的机会。大脑以神经元的排列方式存储信息,当被环境激活时,神经元也会检索同样的信息。通过不断参考信息和来自环境的额外刺激,大脑将音乐特征构建成一个感知的整体。



The medial prefrontal cortex – one of the last areas affected by Alzheimer’s disease – is the region activated by music.

The medial prefrontal cortex – one of the last areas affected by Alzheimer’s disease – is the region activated by music.

内侧脑前额叶外皮是受阿尔茨海默氏症影响的最后区域之一,是被音乐激活的区域。



Cognitive mechanisms

Cognitive mechanisms

认知机制

To understand music pattern recognition, we need to understand the underlying cognitive systems that each handle a part of this process. Various activities are at work in this recognition of a piece of music and its patterns. Researchers have begun to unveil the reasons behind the stimulated reactions to music. Montreal-based researchers asked ten volunteers who got "chills" listening to music to listen to their favorite songs while their brain activity was being monitored.[26] The results show the significant role of the nucleus accumbens (NAcc) region – involved with cognitive processes such as motivation, reward, addiction, etc. – creating the neural arrangements that make up the experience.[26] A sense of reward prediction is created by anticipation before the climax of the tune, which comes to a sense of resolution when the climax is reached. The longer the listener is denied the expected pattern, the greater the emotional arousal when the pattern returns. Musicologist Leonard Meyer used fifty measures of Beethoven’s 5th movement of the String Quartet in C-sharp minor, Op. 131 to examine this notion.[26] The stronger this experience is, the more vivid memory it will create and store. This strength affects the speed and accuracy of retrieval and recognition of the musical pattern. The brain not only recognizes specific tunes, it distinguishes standard acoustic features, speech and music.

To understand music pattern recognition, we need to understand the underlying cognitive systems that each handle a part of this process. Various activities are at work in this recognition of a piece of music and its patterns. Researchers have begun to unveil the reasons behind the stimulated reactions to music. Montreal-based researchers asked ten volunteers who got "chills" listening to music to listen to their favorite songs while their brain activity was being monitored. The results show the significant role of the nucleus accumbens (NAcc) region – involved with cognitive processes such as motivation, reward, addiction, etc. – creating the neural arrangements that make up the experience. A sense of reward prediction is created by anticipation before the climax of the tune, which comes to a sense of resolution when the climax is reached. The longer the listener is denied the expected pattern, the greater the emotional arousal when the pattern returns. Musicologist Leonard Meyer used fifty measures of Beethoven’s 5th movement of the String Quartet in C-sharp minor, Op. 131 to examine this notion. The stronger this experience is, the more vivid memory it will create and store. This strength affects the speed and accuracy of retrieval and recognition of the musical pattern. The brain not only recognizes specific tunes, it distinguishes standard acoustic features, speech and music.

为了理解音乐模式识别,我们需要理解每个处理这个过程的一部分的潜在认知系统。各种各样的活动在这种对一段音乐及其模式的认识中起作用。研究人员已经开始揭示音乐刺激反应背后的原因。蒙特利尔的研究人员要求10名志愿者在听音乐时感到“发冷” ,同时监测他们的大脑活动。结果表明,伏隔核区域在动机、奖赏、成瘾等认知过程中起着重要作用。- 创造出组成体验的神经系统。预测奖励的感觉是在曲子高潮之前的期待中产生的,当达到高潮时,这种感觉就会消失。听者被拒绝预期模式的时间越长,当模式回归时,情绪唤起就越大。音乐学家 Leonard Meyer 使用了贝多芬的升 c 小调弦乐四重奏第五乐章 Op 中的五十个小节。131来检验这个概念。这种体验越强烈,它就会创造和储存越多生动的记忆。这种强度影响了音乐模式的检索和识别的速度和准确性。大脑不仅能识别特定的音调,还能区分标准的声学特征、语音和音乐。



MIT researchers conducted a study to examine this notion.[28] The results showed six neural clusters in the auditory cortex responding to the sounds. Four were triggered when hearing standard acoustic features, one specifically responded to speech, and the last exclusively responded to music. Researchers who studied the correlation between temporal evolution of timbral, tonal and rhythmic features of music, came to the conclusion that music engages the brain regions connected to motor actions, emotions and creativity. The research indicates that the whole brain "lights up" when listening to music.[29] This amount of activity boosts memory preservation, hence pattern recognition.

MIT researchers conducted a study to examine this notion. The results showed six neural clusters in the auditory cortex responding to the sounds. Four were triggered when hearing standard acoustic features, one specifically responded to speech, and the last exclusively responded to music. Researchers who studied the correlation between temporal evolution of timbral, tonal and rhythmic features of music, came to the conclusion that music engages the brain regions connected to motor actions, emotions and creativity. The research indicates that the whole brain "lights up" when listening to music. This amount of activity boosts memory preservation, hence pattern recognition.

麻省理工学院的研究人员进行了一项研究来检验这种观念。结果显示,听觉皮层中有六个神经簇对声音作出反应。其中四个是在听到标准的声学特征时触发的,一个是特别对语言作出反应,而最后一个是完全对音乐作出反应。研究音色、音调和节奏特征在时间上的进化关系的研究人员得出结论,音乐使大脑中与运动行为、情绪和创造力相关的区域参与进来。研究表明,当听音乐时,整个大脑都会“亮起来”。这种数量的活动促进记忆保存,因此模式识别。



Recognizing patterns of music is different for a musician and a listener. Although a musician may play the same notes every time, the details of the frequency will always be different. The listener will recognize the musical pattern and their types despite the variations. These musical types are conceptual and learned, meaning they might vary culturally.[30] While listeners are involved with recognizing (implicit) musical material, musicians are involved with recalling them (explicit).[2]

Recognizing patterns of music is different for a musician and a listener. Although a musician may play the same notes every time, the details of the frequency will always be different. The listener will recognize the musical pattern and their types despite the variations. These musical types are conceptual and learned, meaning they might vary culturally. While listeners are involved with recognizing (implicit) musical material, musicians are involved with recalling them (explicit).

对于音乐家和听众来说,识别音乐的模式是不同的。虽然一个音乐家可能每次演奏相同的音符,但是频率的细节总是不同的。尽管音乐有变化,听者还是能够辨认出它们的音乐模式和类型。这些类型的音乐是概念性的和后天习得的,这意味着他们可能在文化上有所不同。当听者参与识别(内隐的)音乐素材时,音乐家参与回忆(外显的)。



A UCLA study found that when watching or hearing music being played, neurons associated with the muscles needed for playing the instrument fire. Mirror neurons light up when musicians and non-musicians listen to a piece.[31]

A UCLA study found that when watching or hearing music being played, neurons associated with the muscles needed for playing the instrument fire. Mirror neurons light up when musicians and non-musicians listen to a piece.

加州大学洛杉矶分校的一项研究发现,当观看或听到音乐演奏时,神经元与演奏乐器所需的肌肉相关。当音乐家和非音乐家听一首曲子时,镜像神经元会发光。



Developmental issues

Developmental issues

发展问题

Pattern recognition of music can build and strengthen other skills, such as musical synchrony and attentional performance and musical notation and brain engagement. Even a few years of musical training enhances memory and attention levels. Scientists at University of Newcastle conducted a study on patients with severe acquired brain injuries (ABIs) and healthy participants, using popular music to examine music-evoked autobiographical memories (MEAMs).[29] The participants were asked to record their familiarity with the songs, whether they liked them and what memories they evoked. The results showed that the ABI patients had the highest MEAMs, and all the participants had MEAMs of a person, people or life period that were generally positive.[29] The participants completed the task by utilizing pattern recognition skills. Memory evocation caused the songs to sound more familiar and well-liked. This research can be beneficial to rehabilitating patients of autobiographical amnesia who do not have fundamental deficiency in autobiographical recall memory and intact pitch perception.[29]

Pattern recognition of music can build and strengthen other skills, such as musical synchrony and attentional performance and musical notation and brain engagement. Even a few years of musical training enhances memory and attention levels. Scientists at University of Newcastle conducted a study on patients with severe acquired brain injuries (ABIs) and healthy participants, using popular music to examine music-evoked autobiographical memories (MEAMs). The participants were asked to record their familiarity with the songs, whether they liked them and what memories they evoked. The results showed that the ABI patients had the highest MEAMs, and all the participants had MEAMs of a person, people or life period that were generally positive. The participants completed the task by utilizing pattern recognition skills. Memory evocation caused the songs to sound more familiar and well-liked. This research can be beneficial to rehabilitating patients of autobiographical amnesia who do not have fundamental deficiency in autobiographical recall memory and intact pitch perception.

对音乐的模式识别可以建立和加强其他技能,比如音乐的同步性和注意力表现,音乐记谱法和大脑的参与。即使是几年的音乐训练也能提高记忆力和注意力水平。纽卡斯尔大学的科学家们对严重后天性脑损伤患者和健康参与者进行了一项研究,使用流行音乐来检测音乐诱发的自传体记忆。参与者被要求记录他们对这些歌曲的熟悉程度,他们是否喜欢这些歌曲,以及这些歌曲唤起了他们什么样的回忆。结果显示,ABI 患者的 MEAMs 最高,所有参与者的 MEAMs 总体呈阳性,包括人、人或生命周期。参与者利用模式识别技能完成了任务。记忆的唤起使得歌曲听起来更加熟悉和喜欢。本研究对自传体遗忘症患者的自传体回忆记忆和音高知觉无基本缺陷的康复具有重要意义。



In a study at University of California, Davis mapped the brain of participants while they listened to music.[32] The results showed links between brain regions to autobiographical memories and emotions activated by familiar music. This study can explain the strong response of patients with Alzheimer’s disease to music. This research can help such patients with pattern recognition-enhancing tasks.

In a study at University of California, Davis mapped the brain of participants while they listened to music. The results showed links between brain regions to autobiographical memories and emotions activated by familiar music. This study can explain the strong response of patients with Alzheimer’s disease to music. This research can help such patients with pattern recognition-enhancing tasks.

在加利福尼亚大学的一项研究中,戴维斯绘制了参与者听音乐时的大脑图。结果显示,大脑区域与自传体记忆和熟悉的音乐所激活的情绪之间存在联系。这项研究可以解释阿尔茨海默病患者对音乐的强烈反应。这项研究可以帮助这些患者完成模式识别增强任务。



False pattern recognition

False pattern recognition

错误的模式识别


Whale, submarine or sheep?

[鲸鱼,潜水艇还是绵羊? ]

The human tendency to see patterns that do not actually exist is called apophenia. Examples include the Man in the Moon, faces or figures in shadows, in clouds, and in patterns with no deliberate design, such as the swirls on a baked confection, and the perception of causal relationships between events which are, in fact, unrelated. Apophenia figures prominently in conspiracy theories, gambling, misinterpretation of statistics and scientific data, and some kinds of religious and paranormal experiences. Misperception of patterns in random data is called pareidolia.

The human tendency to see patterns that do not actually exist is called apophenia. Examples include the Man in the Moon, faces or figures in shadows, in clouds, and in patterns with no deliberate design, such as the swirls on a baked confection, and the perception of causal relationships between events which are, in fact, unrelated. Apophenia figures prominently in conspiracy theories, gambling, misinterpretation of statistics and scientific data, and some kinds of religious and paranormal experiences. Misperception of patterns in random data is called pareidolia.

人们倾向于看到并不存在的图案,这种倾向被称为幻觉。例如,月球上的人,阴影中的人脸或人物,云彩中的人物,以及没有经过深思熟虑设计的图案,比如烘焙甜点上的漩涡,以及对事件之间因果关系的感知,事实上,这些事件是不相关的。阿皮尼亚在阴谋论、赌博、对统计数据和科学数据的误解以及某些宗教和超自然经历中占有突出地位。对随机数据中的模式的错误理解被称为幻想性视错觉。



See also

See also

参见











Notes

Notes

注释

模板:Notelist




References

References

参考资料

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  3. Mattson, M. P. (2014). Superior pattern processing is the essence of the evolved human brain. Frontiers in neuroscience, 8.
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  7. Torgerson, 1958
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  11. 11.0 11.1 Sincero, S. M. (2013) Top-Down VS Bottom-Up Processing. Retrieved Oct 20, 2017 from Explorable.com: https://explorable.com/top-down-vs-bottom-up-processing
  12. Berk, L. E. (2013). Development through the lifespan (6th ed.). Pearson.
  13. 13.0 13.1 13.2 13.3 13.4 Curtis, A. (2002). Curriculum for the pre-school child. Routledge.
  14. 引用错误:无效<ref>标签;未给name属性为Kidd的引用提供文字
  15. 15.0 15.1 Inhelder, B., & Piaget, J. (1964). Early growth of logic in the child; classification and seriation, aby Bärbel Inhelder and Jean Piaget. New York: Routledge and Paul.
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  18. 18.0 18.1 18.2 18.3 18.4 引用错误:无效<ref>标签;未给name属性为APA的引用提供文字
  19. Wlassoff, V. (2015). How the Brain Recognizes Faces. Brain Blogger. Retrieved from: http://brainblogger.com/2015/10/17/how-the-brain-recognizes-faces/
  20. 20.0 20.1 Norton, E. (2012). Identifying the Brain's own Facial Recognition System. Science Magazine. Retrieved from: http://www.sciencemag.org/news/2012/10/identifying-brains-own-facial-recognition-system
  21. 21.0 21.1 McKone, E., et al. (2012). A critical review of the development of face recognition: Experience is less important than previously believed. Cognitive Neuropsychology. doi 10.1080/02643294.2012.660138
  22. 22.0 22.1 22.2 22.3 Language ability linked to pattern recognition. (2013, May 29). VOA. Retrieved October 25, 2017 from https://www.voanews.com/a/language-ability-linked-to-pattern-recognition/1670776.html
  23. 23.0 23.1 23.2 23.3 23.4 23.5 Kuhl, P. K. (2000). A new view of language acquisition. Proceedings of the National Academy of Sciences, 97(22), 11850–11857. https://doi.org/10.1073/pnas.97.22.11850
  24. 24.0 24.1 University of Sydney. (2016, May 5). Pattern learning key to children's language development. ScienceDaily. Retrieved October 25, 2017 from http://www.sciencedaily.com/releases/2016/05/160505222938.htm
  25. 25.0 25.1 Basulto, D. (2013, July 24). Humans are the world’s best pattern-recognition machines, but for how long? Retrieved October 25, 2017 from http://bigthink.com/endless-innovation/humans-are-the-worlds-best-pattern-recognition-machines-but-for-how-long
  26. 26.0 26.1 26.2 26.3 26.4 26.5 Lehrer, Jonah. “The Neuroscience Of Music.” Wired, Conde Nast, 3 June 2017, www.wired.com/2011/01/the-neuroscience-of-music/.
  27. 27.0 27.1 Levitin, D. J. (2006). This is your brain on music: The science of a human obsession. Penguin.
  28. Bushak, L. (2017). This Is Your Brain On Music: How Our Brains Process Melodies That Pull On Our Heartstrings. [online] Medical Daily. Available at: http://www.medicaldaily.com/your-brain-music-how-our-brains-process-melodies-pull-our-heartstrings-271007 [Accessed 26 Oct. 2017]
  29. 29.0 29.1 29.2 29.3 Bergland, C. (2013, December 11). Why Do the Songs from Your Past Evoke Such Vivid Memories? Retrieved from https://www.psychologytoday.com/blog/the-athletes-way/201312/why-do-the-songs-your-past-evoke-such-vivid-memories
  30. Agus, T. R., Thorpe, S. J., & Pressnitzer, D. (2010). Rapid formation of robust auditory memories: insights from noise. Neuron, 66(4), 610-618.
  31. Byrne, D. (2012, October). How Do Our Brains Process Music? Retrieved from https://www.smithsonianmag.com/arts-culture/how-do-our-brains-process-music-32150302/?no-ist=&page=1
  32. Greensfelder, L. (2009, February). Study Finds Brain Hub that Links Music, Memory and Emotion. Retrieved from https://www.ucdavis.edu/news/study-finds-brain-hub-links-music-memory-and-emotion




External links

External links

外部链接

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类别: 包含视频剪辑的文章

Category:Pattern recognition

类别: 模式识别


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