神经同步

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Neural synchrony is the correlation of brain activity across two or more people over time. In social and affective neuroscience, neural synchrony specifically refers to the degree of similarity between the spatio-temporal neural fluctuations of multiple people. This phenomenon represents the convergence and coupling of different people's neurocognitive systems, and it is thought to be the neural substrate for many forms of interpersonal dynamics and shared experiences. Some research also refers to neural synchrony as inter-brain synchrony, brain-to-brain coupling, inter-subject correlation, between-brain connectivity, or neural coupling. In the current literature, neural synchrony is notably distinct from intra-brain synchrony—sometimes also called neural synchrony—which denotes the coupling of activity across regions of a single individual's brain.

Neural synchrony is the correlation of brain activity across two or more people over time. In social and affective neuroscience, neural synchrony specifically refers to the degree of similarity between the spatio-temporal neural fluctuations of multiple people. This phenomenon represents the convergence and coupling of different people's neurocognitive systems, and it is thought to be the neural substrate for many forms of interpersonal dynamics and shared experiences. Some research also refers to neural synchrony as inter-brain synchrony, brain-to-brain coupling, inter-subject correlation, between-brain connectivity, or neural coupling. In the current literature, neural synchrony is notably distinct from intra-brain synchrony—sometimes also called neural synchrony—which denotes the coupling of activity across regions of a single individual's brain.

神经同步是两个或两个以上的人随着时间的推移大脑活动的相关性。在社会和情绪神经科学中，神经同步特指多个人的时空神经波动之间的相似程度。这种现象代表了不同人的神经认知系统的聚合和耦合，它被认为是许多形式的人际关系动力学和共享经验的神经基础。一些研究也提到神经的同步性，如大脑间的同步性、大脑与大脑的耦合性、主体间的相关性、大脑间的连接性或神经耦合性。在目前的文献中，神经同步性明显不同于脑内同步性(有时也称为神经同步性) ，后者表示单个个体大脑各区域活动的耦合。

Increasingly implemented by social and affective neuroscientists, neural synchrony approaches represent an important theoretical and methodological contribution to the field. Since its conception, studies of neural synchrony have helped elucidate the mechanisms underlying social phenomena, including communication, narrative processing, coordination, and cooperation. By emphasizing the social dynamics of the brain, this area of research has played a critical role in making neuroscience more attuned to people's social proclivities—a perspective that is often lost on individual-level approaches to understanding the brain.

Increasingly implemented by social and affective neuroscientists, neural synchrony approaches represent an important theoretical and methodological contribution to the field. Since its conception, studies of neural synchrony have helped elucidate the mechanisms underlying social phenomena, including communication, narrative processing, coordination, and cooperation. By emphasizing the social dynamics of the brain, this area of research has played a critical role in making neuroscience more attuned to people's social proclivities—a perspective that is often lost on individual-level approaches to understanding the brain.

越来越多的社会和情感神经科学家实施，神经同步方法代表了一个重要的理论和方法学贡献的领域。自从神经同步的概念提出以来，神经同步的研究就帮助阐明了社会现象背后的机制，包括交流、叙事加工、协调和合作。通过强调大脑的社会动力学，这一研究领域在使神经科学更适应人们的社会倾向方面发挥了关键作用——在理解大脑的个人层面方法上，这一观点往往被忽略。

History

History

= 历史 =

Motivation

Driven by the desire to understand the social nature of the human brain, the study of neural synchrony stems from social cognition, a subfield of psychology that explores how we understand and interact with other people through processes like mentalization or theory of mind.[1] Given that it relies on measuring brain activity, neural synchrony also has its roots in cognitive neuroscience.[2]

Driven by the desire to understand the social nature of the human brain, the study of neural synchrony stems from social cognition, a subfield of psychology that explores how we understand and interact with other people through processes like mentalization or theory of mind. Given that it relies on measuring brain activity, neural synchrony also has its roots in cognitive neuroscience.

由于渴望了解人类大脑的社会本质，神经同步性的研究源于心理学的一个分支---- 社会认知，探索我们如何通过心理化或心理理论来理解和与他人互动。由于它依赖于对大脑活动的测量，神经同步性也起源于21认知神经科学。

Despite the growth of social cognition and cognitive neuroscience prior to the early 2000s, research into the brain neglected interpersonal processes, focusing mostly on the neural mechanisms of individuals' behaviors.[2] Furthermore, neuroscience research that did probe social questions only investigated how social processes affect neural dynamics in a single brain.[3] Considering that researchers clearly recognized how interpersonal interaction was fundamental to human cognition, the paucity of social and multi-brain neuroscience research represented a tension in the field. In response to the discrepancy between the complexity of social interaction and the single-brain focus of cognitive neuroscience, researchers called for a multi-person, interaction-oriented approach to understanding the brain.[1][2][4][5][6]

Despite the growth of social cognition and cognitive neuroscience prior to the early 2000s, research into the brain neglected interpersonal processes, focusing mostly on the neural mechanisms of individuals' behaviors. Furthermore, neuroscience research that did probe social questions only investigated how social processes affect neural dynamics in a single brain. Considering that researchers clearly recognized how interpersonal interaction was fundamental to human cognition, the paucity of social and multi-brain neuroscience research represented a tension in the field. In response to the discrepancy between the complexity of social interaction and the single-brain focus of cognitive neuroscience, researchers called for a multi-person, interaction-oriented approach to understanding the brain.

尽管在2000年代早期之前社会认知和认知神经科学的发展，对大脑的研究忽视了人际交往过程，主要集中在个体行为的神经机制上。此外，神经科学研究只是调查了社会过程如何影响单个大脑的神经动力学。考虑到研究人员清楚地认识到人际交往是人类认知的基础，社会和多脑神经科学研究的缺乏代表了该领域的紧张局势。为了回应社会互动的复杂性和认知神经科学的单一大脑焦点之间的差异，研究人员呼吁采用多人、面向互动的方法来理解大脑。

Early history

In 2002, the American neuroscientist P. Read Montague[4] articulated the need to examine the neural activity of multiple individuals at one time. To this point, Montague and his colleagues wrote, "Studying social interactions by scanning the brain of just one person is analogous to studying synapses while observing either the presynaptic neuron or the postsynaptic neuron, but never both simultaneously."[7] They performed the first brain scan of more than one person by using functional magnetic resonance imaging (fMRI) to take simultaneous recordings of two people engaged in a simple deception game. While this study marked the first example of multi-brain neuroimaging, in 2005, King-Casas and others[8] combined neuroimaging with an economic exchange game to conduct the first study that directly compared neural activity between pairs of subjects.[3] Since then, multi-brain imaging studies have grown in popularity, leading to the formation of preliminary neural synchrony frameworks.[2]

In 2002, the American neuroscientist P. Read Montague articulated the need to examine the neural activity of multiple individuals at one time. To this point, Montague and his colleagues wrote, "Studying social interactions by scanning the brain of just one person is analogous to studying synapses while observing either the presynaptic neuron or the postsynaptic neuron, but never both simultaneously." They performed the first brain scan of more than one person by using functional magnetic resonance imaging (fMRI) to take simultaneous recordings of two people engaged in a simple deception game. While this study marked the first example of multi-brain neuroimaging, in 2005, King-Casas and others combined neuroimaging with an economic exchange game to conduct the first study that directly compared neural activity between pairs of subjects. Since then, multi-brain imaging studies have grown in popularity, leading to the formation of preliminary neural synchrony frameworks.

早期历史早在2002年，美国神经科学家 p · 里德 · 蒙塔古明确表示需要同时检查多个个体的神经活动。关于这一点，蒙塔古和他的同事写道，“通过扫描一个人的大脑来研究社会互动，就像研究突触，同时观察突触前神经元或突触后神经元，但绝不能同时观察两者。”他们首次对一个以上的人进行了大脑扫描，使用功能性磁共振成像磁共振成像(fMRI)同时记录两个人在进行一个简单的欺骗游戏。虽然这项研究标志着第一个多脑神经成像的例子，但在2005年，King-Casas 和其他研究人员将神经成像与经济交换游戏结合起来，进行了第一项研究，直接比较了两对受试者之间的神经活动。从那时起，多脑成像研究越来越受欢迎，导致初步的神经同步框架的形成。

Early conceptualizations of neural synchrony, mostly from the Hasson Lab at Princeton University, were motivated by models of stimulus-to-brain coupling. In these models, aspects of the physical environment emit mechanical, chemical, and electromagnetic signals, which the brain receives and translates into electrical impulses that guide our actions and allow us to understand the world.[2] Researchers presumed that the synchronization of neural activity between two brains should leverage the same system that binds one's neural activity to environmental stimuli. If the stimulus is another person, then the perceptual system of one brain may couple with the behaviors or emotions of the other person, causing "vicarious activations"[9] that manifest as synchronized neural responses across perceiver and agent.[2] According to the theory, this process also occurs through more complex, synergistic interactions, especially when people communicate and convey meaning.[10]

Early conceptualizations of neural synchrony, mostly from the Hasson Lab at Princeton University, were motivated by models of stimulus-to-brain coupling. In these models, aspects of the physical environment emit mechanical, chemical, and electromagnetic signals, which the brain receives and translates into electrical impulses that guide our actions and allow us to understand the world. Researchers presumed that the synchronization of neural activity between two brains should leverage the same system that binds one's neural activity to environmental stimuli. If the stimulus is another person, then the perceptual system of one brain may couple with the behaviors or emotions of the other person, causing "vicarious activations" that manifest as synchronized neural responses across perceiver and agent. According to the theory, this process also occurs through more complex, synergistic interactions, especially when people communicate and convey meaning.

神经同步的早期概念化主要来自普林斯顿大学的哈森实验室，其动机是刺激到大脑的耦合模型。在这些模型中，物理环境的各个方面发射出机械信号、化学信号和电磁信号，大脑接收并转化为电脉冲，引导我们的行动，让我们理解这个世界。研究人员推测，两个大脑之间神经活动的同步应该利用同一个系统，将一个人的神经活动与环境刺激结合起来。如果刺激源是另一个人，那么一个大脑的感知系统可能与另一个人的行为或情绪结合在一起，导致“替代性激活”，表现为感知者和主体之间的同步神经反应。根据这个理论，这个过程也通过更复杂的协同作用发生，特别是当人们交流和传达意义的时候。

Further development

Over the last two decades, neural synchrony has become an increasingly common topic of study in social and affective neuroscience research, spurring conceptual and methodological development. Along with an emphasis on ecologically valid, naturalistic experimental designs, the focus on multi-brain neuroscience studies has increased researchers' ability to explore neural synchrony in social contexts. As a result, conceptualizations of neural synchrony have been expanded to incorporate a wider range of ideas, though it is often viewed as a neural correlate for two or more people's shared experiences. Studies now involve a variety of social processes, with applications spanning simple motor synchronization to classroom learning.[3]

Over the last two decades, neural synchrony has become an increasingly common topic of study in social and affective neuroscience research, spurring conceptual and methodological development. Along with an emphasis on ecologically valid, naturalistic experimental designs, the focus on multi-brain neuroscience studies has increased researchers' ability to explore neural synchrony in social contexts. As a result, conceptualizations of neural synchrony have been expanded to incorporate a wider range of ideas, though it is often viewed as a neural correlate for two or more people's shared experiences. Studies now involve a variety of social processes, with applications spanning simple motor synchronization to classroom learning.

在过去的二十年里，神经同步已经成为社会和情绪神经科学研究中越来越普遍的课题，促进了概念和方法论的发展。随着对生态有效性和自然主义实验设计的强调，对多脑神经科学研究的重视提高了研究人员在社会环境中探索神经同步性的能力。因此，神经同步的概念化已经扩展到包含更广泛的思想，尽管它通常被视为两个或两个以上的人的共同经历的神经关联。现在的研究涉及多种社会过程，应用范围从简单的运动同步到课堂学习。

Notable methodological advancements have come from the evolution of multi-brain imaging techniques beyond fMRI, especially magnetoencephalography/electroencephalography (MEG/EEG) and functional near-infrared spectroscopy (fNIRS)—methods which afford more socially interactive experimental designs.[3][11] These technologies are also complemented by comprehensive data processing techniques that are useful in multi-brain analyses,[12][13] such as Granger causality[14] or Phase Locking Value (PLV).[15]

Notable methodological advancements have come from the evolution of multi-brain imaging techniques beyond fMRI, especially magnetoencephalography/electroencephalography (MEG/EEG) and functional near-infrared spectroscopy (fNIRS)—methods which afford more socially interactive experimental designs. These technologies are also complemented by comprehensive data processing techniques that are useful in multi-brain analyses, such as Granger causality or Phase Locking Value (PLV).

在功能性磁共振成像技术之外的多脑成像技术，尤其是脑磁图/脑脑电图(MEG/EEG)和功能性近红外光谱技术(fNIRS)的发展，在方法学上取得了显著的进步，这些方法提供了更具社会交互性的实验设计。这些技术还辅之以全面的数据处理技术，这些技术在多脑分析中非常有用，例如格兰杰因果关系或相位锁定值(PLV)。

As a progressively paradigmatic approach in social and affective neuroscience, neural synchrony undergirds the field's search for the brain basis of social interaction.[3]

As a progressively paradigmatic approach in social and affective neuroscience, neural synchrony undergirds the field's search for the brain basis of social interaction.

作为社会和情绪神经科学的一种渐进式的聚合方法，神经同步加强了该领域对社会互动的大脑基础的研究。

Methods

Methods

= = 方法 =

Hyperscanning

The study of neural synchrony is predicated on advanced neuroimaging methods, particularly hyperscanning. Coined in 2002 by Montague et al.,[4] hyperscanning refers to the method of simultaneously measuring the hemodynamic or neuroelectric responses of two or more brains as they engage with the same task or stimulus.[16][17][18] The ability to record time-locked activity from multiple brains makes hyperscanning conducive to exploring the variation in activity across brains. It also allows experimenters to examine various aspects of neural recordings in naturalistic scenarios, from low-level stimulus processing to high-level social cognition.[13] For these reasons, hyperscanning has helped foster a systematic investigation of interpersonal dynamics at the level of the brain.[18][19]

The study of neural synchrony is predicated on advanced neuroimaging methods, particularly hyperscanning. Coined in 2002 by Montague et al., hyperscanning refers to the method of simultaneously measuring the hemodynamic or neuroelectric responses of two or more brains as they engage with the same task or stimulus. The ability to record time-locked activity from multiple brains makes hyperscanning conducive to exploring the variation in activity across brains. It also allows experimenters to examine various aspects of neural recordings in naturalistic scenarios, from low-level stimulus processing to high-level social cognition. For these reasons, hyperscanning has helped foster a systematic investigation of interpersonal dynamics at the level of the brain.

超扫描研究神经同步性是以先进的神经影像学方法为基础的，特别是超扫描。2002年由 Montague et al. 提出，超扫描指的是同时测量两个或两个以上大脑在执行相同任务或刺激时的血流动力学或神经电反应的方法。记录多个大脑的时间锁定活动的能力使得超级扫描有助于探索大脑活动的变化。它还允许实验者在自然场景中检查神经记录的各个方面，从低级刺激处理到高级社会认知。由于这些原因，超级扫描帮助促进了在大脑水平上对人际动力学的系统性研究。

Though hyperscanning has become the most common imaging technique for studying neural synchrony, researchers do not necessarily need to scan brains simultaneously. Sometimes referred to as off-line measurement, or "pseudo-hyperscanning";[19] this alternative approach follows the same basic premise as hyperscanning, except that participants' brain activity is recorded one at a time. Data from different scans of isolated participants are then analyzed to compare functional similarities during identical tasks or stimuli.[17][18]

Though hyperscanning has become the most common imaging technique for studying neural synchrony, researchers do not necessarily need to scan brains simultaneously. Sometimes referred to as off-line measurement, or "pseudo-hyperscanning"; this alternative approach follows the same basic premise as hyperscanning, except that participants' brain activity is recorded one at a time. Data from different scans of isolated participants are then analyzed to compare functional similarities during identical tasks or stimuli.

虽然超扫描已经成为研究神经同步性最常用的成像技术，但研究人员并不一定需要同时扫描大脑。有时被称为离线测量，或“伪超扫描”; 这种替代方法遵循与超扫描相同的基本前提，除了参与者的大脑活动一次记录一个。然后分析来自孤立参与者的不同扫描数据，比较在完成相同任务或刺激时的功能相似性。

Imaging techniques

Hyperscanning and off-line scanning methods can be achieved through common noninvasive hemodynamic or neuroelectric brain imaging techniques. A review of neural synchrony hyperscanning studies showed that the most prevalent methods are EEG, fNIRS, and fMRI, which account for 47%, 35%, and 17% of studies, respectively.[3] Each technique offers unique contributions to the understanding of neural synchrony given their relative advantages and limitations.[17]

Hyperscanning and off-line scanning methods can be achieved through common noninvasive hemodynamic or neuroelectric brain imaging techniques. A review of neural synchrony hyperscanning studies showed that the most prevalent methods are EEG, fNIRS, and fMRI, which account for 47%, 35%, and 17% of studies, respectively. Each technique offers unique contributions to the understanding of neural synchrony given their relative advantages and limitations.

超扫描和离线扫描方法可以通过常见的无创血液动力学或神经电脑成像技术来实现。对神经同步超扫描研究的回顾表明，最常用的方法是脑电图、脑电图、功能磁共振成像，分别占研究的47% 、35% 和17% 。由于各自的优势和局限性，每种技术都为理解神经同步性提供了独特的贡献。

EEG measures the brain's electrical activity through the scalp. It is widely used to study neural synchrony because of its superior millisecond-range temporal resolution.[20] Though susceptible to head movements, EEG still allows for exploring neural synchrony through naturalistic designs where people can interact socially.[11] The downside to EEG is its relatively poor spatial resolution, which makes it difficult to elucidate spatial qualities of brain activation in social contexts.[17]  

EEG measures the brain's electrical activity through the scalp. It is widely used to study neural synchrony because of its superior millisecond-range temporal resolution. Though susceptible to head movements, EEG still allows for exploring neural synchrony through naturalistic designs where people can interact socially. The downside to EEG is its relatively poor spatial resolution, which makes it difficult to elucidate spatial qualities of brain activation in social contexts.  

脑电图通过头皮测量大脑的电活动。由于它具有良好的毫秒时间解析度，因此被广泛用于研究神经同步性。尽管易受头部运动的影响，脑电图仍然允许通过自然主义的设计探索神经的同步性，在那里人们可以进行社交互动。脑电图的缺点是其相对较差的空间分辨率，这使得在社会环境中阐明大脑活动的空间特性变得困难。

fNIRS uses near infrared waves to measure the blood-oxygen-level-dependent (BOLD) response in the brain. It is an increasingly popular imaging method for neural synchrony studies because of its portability and motion tolerance, which makes it ideal for testing real-world social stimuli.[21] fNIRS only measures the cortical regions of the brain, and its temporal resolution is not as fine as EEG. However, the balance between spatial and temporal properties, combined with subjects' ability to move around and interact with relative freedom during scanning, qualify fNIRS as a versatile option for exploring neural synchrony.[3]

fNIRS uses near infrared waves to measure the blood-oxygen-level-dependent (BOLD) response in the brain. It is an increasingly popular imaging method for neural synchrony studies because of its portability and motion tolerance, which makes it ideal for testing real-world social stimuli. fNIRS only measures the cortical regions of the brain, and its temporal resolution is not as fine as EEG. However, the balance between spatial and temporal properties, combined with subjects' ability to move around and interact with relative freedom during scanning, qualify fNIRS as a versatile option for exploring neural synchrony.

fNIRS 使用近红外波测量大脑中血氧水平依赖性(BOLD)反应。由于它的便携性和运动耐受性，使其成为神经同步性研究的一种日益流行的成像方法，是测试现实世界社会刺激的理想方法。fNIRS 只测量大脑皮层区域，而且它的时间解析度不如 EEG 精确。然而，空间和时间属性之间的平衡，加上受试者在扫描过程中四处移动和相对自由的交互能力，使 fNIRS 成为探索神经同步性的一个多功能选项。

fMRI uses magnetic resonance to measure the brain's BOLD response. The major advantage of fMRI is the precise spatial resolution. fMRI allows researchers to examine in-depth neurocognitive processes that occur across brains. However, fMRI has low temporal resolution, is highly sensitive to motion, and requires that subjects lie flat in a loud MRI machine while interacting with a screen. These factors pose limitations to the study of neural synchrony, which often calls for naturalistic environments and tasks that are representative of real-world social contexts.[3][6]

fMRI uses magnetic resonance to measure the brain's BOLD response. The major advantage of fMRI is the precise spatial resolution. fMRI allows researchers to examine in-depth neurocognitive processes that occur across brains. However, fMRI has low temporal resolution, is highly sensitive to motion, and requires that subjects lie flat in a loud MRI machine while interacting with a screen. These factors pose limitations to the study of neural synchrony, which often calls for naturalistic environments and tasks that are representative of real-world social contexts.

功能磁共振成像使用磁共振来测量大脑的大胆反应。功能磁共振成像的主要优点是具有精确的空间分辨率。功能磁共振成像使研究人员能够深入研究发生在大脑中的神经认知过程。然而，功能磁共振成像时间解析度低，对运动高度敏感，要求受试者在与屏幕互动时，平躺在噪音很大的 MRI 机器中。这些因素限制了神经同步性的研究，而神经同步性往往需要自然的环境和任务来代表现实世界的社会背景。

Analysis

A standard approach to investigating neural synchrony, especially with data from naturalistic experimental designs, is inter-subject correlation (ISC).[22][23] Often, ISC is the Pearson correlation, or robust regression, of spatio-temporal patterns of neural activity in multiple subjects. In ISC, an individual's brain responses are either correlated across the average of the other subjects in a leave-one-out analysis, or all pairs of subjects are correlated in a pairwise analysis.[13] This method leverages time-locked stimuli in order to understand how brain activity across participants relates to different parts of the task. Rather than focusing on the strength of activation in brain areas, ISC explores the variability in neural activity across subjects,[24] allowing researchers to probe the level of similarity or idiosyncrasy in people's brain responses.[25] Shared variance in neural activity is assumed to be indicative of similar processing of identical stimuli or tasks. Similar to the general linear model, it is important to compare ISC values to a null, which can be derived from recordings of resting states or irrelevant stimuli. Because it depends on extended designs that allow for activity recording over time, ISC is especially conducive to social interaction studies, which makes it a powerful approach for exploring neural synchrony in social contexts. However, ISC depends on stimulus-driven responses, which poses difficulties for researchers interested in resting-state activity.[26]

A standard approach to investigating neural synchrony, especially with data from naturalistic experimental designs, is inter-subject correlation (ISC). Often, ISC is the Pearson correlation, or robust regression, of spatio-temporal patterns of neural activity in multiple subjects. In ISC, an individual's brain responses are either correlated across the average of the other subjects in a leave-one-out analysis, or all pairs of subjects are correlated in a pairwise analysis. This method leverages time-locked stimuli in order to understand how brain activity across participants relates to different parts of the task. Rather than focusing on the strength of activation in brain areas, ISC explores the variability in neural activity across subjects, allowing researchers to probe the level of similarity or idiosyncrasy in people's brain responses. Shared variance in neural activity is assumed to be indicative of similar processing of identical stimuli or tasks. Similar to the general linear model, it is important to compare ISC values to a null, which can be derived from recordings of resting states or irrelevant stimuli. Because it depends on extended designs that allow for activity recording over time, ISC is especially conducive to social interaction studies, which makes it a powerful approach for exploring neural synchrony in social contexts. However, ISC depends on stimulus-driven responses, which poses difficulties for researchers interested in resting-state activity.

= = = 分析 = = 研究神经同步性的标准方法，特别是自然实验设计的数据，是主题间相关(ISC)。通常，ISC 是多个受试者神经活动的时空模式的皮尔逊相关，或强有力的回归。在 ISC 中，一个人的大脑反应要么在一项省略分析中与其他受试者的平均值相关，要么在一项成对分析中所有受试者的大脑反应都相关。这种方法利用时间锁定的刺激，以了解参与者的大脑活动如何与任务的不同部分相关。不是关注大脑区域的激活强度，ISC 探索了不同受试者神经活动的差异性，允许研究人员探究人们大脑反应的相似程度或特质。神经活动的共享差异被认为是相似的刺激或任务加工的指示。类似于一般线性模型，重要的是将 ISC 值与零值进行比较，零值可以从静息状态或无关刺激的记录中获得。因为它依赖于扩展的设计，允许随着时间的推移记录活动，ISC 特别有利于社会互动研究，这使得它成为探索社会环境中神经同步性的一个强有力的方法。然而，ISC 依赖于刺激驱动的反应，这给研究静息状态活动带来了困难。

Recently, inter-subject representational similarity analysis (IS-RSA) has been put forward as a way to detect the individual differences, or “idiosynchrony,” across people experiencing naturalistic experimental stimuli. This analysis takes the neural synchrony of each subject to the other subjects and relates it to known individual behavioral measures, allowing researchers to compare multi-person-level brain data with individual-level traits and behaviors.[13][27]

Recently, inter-subject representational similarity analysis (IS-RSA) has been put forward as a way to detect the individual differences, or “idiosynchrony,” across people experiencing naturalistic experimental stimuli. This analysis takes the neural synchrony of each subject to the other subjects and relates it to known individual behavioral measures, allowing researchers to compare multi-person-level brain data with individual-level traits and behaviors.

近年来，人们提出了主体间表征相似性分析(intersubject representational similarity analysis，IS-RSA)来检测人们在经历自然实验刺激时的个体差异或“特质”。这种分析将每个受试者与其他受试者的神经同步性与已知的个体行为测量联系起来，使研究人员能够比较多人水平的大脑数据与个体水平的特征和行为。

Best practices

Neural synchrony is a relatively new area of study that affords a variety of approaches, and no prevailing paradigm exists to collect, analyze, and interpret the data. Many decisions, such as imaging techniques or analysis methods, depend on researchers’ goals. However, there are some generally agreed upon best practices when designing these experiments. For example, sample sizes of about 30 are necessary to acquire reliable and reproducible statistical ISC maps.[26] Furthermore, when studying shared responses, researchers typically prefer a strong stimulus that is able to generate significant brain responses, allowing researchers to detect greater levels of neural synchrony across participants. The exception to this preference is when researchers are more interested in the individual differences that drive synchrony. In these cases, researchers should employ stimuli that are strong enough to evoke neural synchrony, yet modest enough to maintain sufficient neural variability that researchers can later relate to the variability in behavioral measures.[28][13]

Neural synchrony is a relatively new area of study that affords a variety of approaches, and no prevailing paradigm exists to collect, analyze, and interpret the data. Many decisions, such as imaging techniques or analysis methods, depend on researchers’ goals. However, there are some generally agreed upon best practices when designing these experiments. For example, sample sizes of about 30 are necessary to acquire reliable and reproducible statistical ISC maps. Furthermore, when studying shared responses, researchers typically prefer a strong stimulus that is able to generate significant brain responses, allowing researchers to detect greater levels of neural synchrony across participants. The exception to this preference is when researchers are more interested in the individual differences that drive synchrony. In these cases, researchers should employ stimuli that are strong enough to evoke neural synchrony, yet modest enough to maintain sufficient neural variability that researchers can later relate to the variability in behavioral measures.

神经同步是一个相对较新的研究领域，它提供了各种各样的方法，并且没有流行的范式来收集、分析和解释数据。许多决定，如成像技术或分析方法，取决于研究人员的目标。然而，在设计这些实验时，有一些公认的最佳实践。例如，大约30个样本大小是获得可靠和可重复的统计 ISC 地图所必需的。此外，在研究共享反应时，研究人员通常更喜欢能够产生显著大脑反应的强烈刺激，这使得研究人员能够在参与者之间检测到更大程度的神经同步。这种偏好的例外是，研究人员对驱动同步的个体差异更感兴趣。在这些情况下，研究人员应该使用足够强烈的刺激来引起神经同步，同时适度的保持足够的神经变异性，这样研究人员以后就可以将行为测量的变异性联系起来。

One of the biggest considerations for conducting neural synchrony studies concerns the ecological validity of the design. As an inherently social phenomenon, neural synchrony calls for multidimensional stimuli that emulate the richness of the social world.[16][29] Furthermore, by nature of how it is measured—through computing the variance in multiple brains' responses to a task over time—neural synchrony is particularly amenable to extended social stimuli. Ecological designs are notably difficult in most neuroimaging studies, yet they are especially important for capturing social processes, and they also play to the strengths and affordances of neural synchrony approaches.[16]

One of the biggest considerations for conducting neural synchrony studies concerns the ecological validity of the design. As an inherently social phenomenon, neural synchrony calls for multidimensional stimuli that emulate the richness of the social world. Furthermore, by nature of how it is measured—through computing the variance in multiple brains' responses to a task over time—neural synchrony is particularly amenable to extended social stimuli. Ecological designs are notably difficult in most neuroimaging studies, yet they are especially important for capturing social processes, and they also play to the strengths and affordances of neural synchrony approaches.

进行神经同步性研究的最大考虑之一是设计的生态有效性。作为一种内在的社会现象，神经同步需要多维刺激模仿社会世界的丰富性。此外，从测量方式的性质来看ーー通过计算多个大脑对一项任务的反应随时间的变化ーー神经同步特别适合于扩展的社会刺激。在大多数神经影像学研究中，生态设计都是相当困难的，然而它们对于捕捉社会过程尤其重要，而且它们还能发挥神经同步方法的优势和可行性。

Experimental evidence and implications

Experimental evidence and implications

= = 实验证据和影响 =

Communication

Examining neural synchrony through multi-brain studies has offered insight into the shared and idiosyncratic aspects of human communication. As a potential neural mechanism for the effective transfer of information across brains, neural synchrony has shown how brain activity temporally and spatially couples when people communicate. Synchrony during communication occurs in a number of brain frequencies and regions, notably alpha and gamma bands, the temporal parietal junction, and inferior frontal areas.[17]

Examining neural synchrony through multi-brain studies has offered insight into the shared and idiosyncratic aspects of human communication. As a potential neural mechanism for the effective transfer of information across brains, neural synchrony has shown how brain activity temporally and spatially couples when people communicate. Synchrony during communication occurs in a number of brain frequencies and regions, notably alpha and gamma bands, the temporal parietal junction, and inferior frontal areas.

通过对神经同步性的多脑研究，使我们对人类交流的共同和特殊方面有了更深入的了解。神经同步性是一种潜在的跨大脑有效信息传递的神经机制，它揭示了人们在交流时大脑活动是如何以时间和空间的方式联系在一起的。交流过程中的同步发生在大脑的许多频率和区域，特别是阿尔法和伽马波段，颞顶交界区和额下下区。

In a seminal study, Stephens et al.[30] demonstrated this inter-brain link through an fMRI analysis of speakers and listeners. Using the speaker's spatial and temporal neural responses to model the listener's responses during natural verbal communication, they found that brain activity synchronized in dyads in both a delayed and anticipatory manner, but this synchrony failed to occur when subjects did not communicate (e.g., speaking in a language the listener does not understand). Greater synchrony across brains, especially in the predictive anticipatory responses, indicated better scores on comprehension measures. Building on this work, other research has sought to pinpoint communicative factors associated with neural synchrony. By manipulating conversation modality and instruction, research has found that neural synchrony is strongest during face-to-face conversations that incorporate turn-taking behavior and multi-sensory verbal and nonverbal interaction.[31][32] Network structure dynamics also play a role in neural synchrony, such that central figures, like conversation leaders, tend to show greater neural synchrony than non-leaders with other discussion partners.[33]

In a seminal study, Stephens et al. demonstrated this inter-brain link through an fMRI analysis of speakers and listeners. Using the speaker's spatial and temporal neural responses to model the listener's responses during natural verbal communication, they found that brain activity synchronized in dyads in both a delayed and anticipatory manner, but this synchrony failed to occur when subjects did not communicate (e.g., speaking in a language the listener does not understand). Greater synchrony across brains, especially in the predictive anticipatory responses, indicated better scores on comprehension measures. Building on this work, other research has sought to pinpoint communicative factors associated with neural synchrony. By manipulating conversation modality and instruction, research has found that neural synchrony is strongest during face-to-face conversations that incorporate turn-taking behavior and multi-sensory verbal and nonverbal interaction. Network structure dynamics also play a role in neural synchrony, such that central figures, like conversation leaders, tend to show greater neural synchrony than non-leaders with other discussion partners.

在一项开创性的研究中，斯蒂芬斯等人。通过对说话者和听话者的 fMRI 分析，证明了这种大脑间的联系。通过使用说话者的空间和时间神经反应来模拟在自然语言交流中听话者的反应，他们发现大脑活动在延迟和预期两种方式下都是同步的，但是当受试者不交流时(例如，用听话者不懂的语言说话) ，这种同步就不会发生。大脑的同步性更强，尤其是预测性预期反应，表明在理解测试中得分更高。在这项工作的基础上，其他的研究已经试图找出与神经同步相关的交流因素。通过操纵谈话的情态和指令，研究发现，在面对面的谈话中，神经的同步性最强，这种谈话包括话轮转换行为和多感官的语言和非语言交互。网络结构动力学在神经同步性中也扮演着重要的角色，例如，中心人物，比如谈话的领导者，往往比非领导者与其他讨论伙伴表现出更大的神经同步性。

Neural synchrony is also found in nonverbal communication, such as hand gestures and facial expressions. An early study found synchronization across participants playing a game of charades. Using fMRI to record brain activity as people gestured or watched the gestures, researchers found synchronized temporal variation in brain activity in mirror neuron and mentalizing systems.[14] Another study showed that communicative behaviors like shared gaze and positive affect expression generated neural synchrony in romantic partners, though not in strangers.[34] As a whole, neural synchrony studies surrounding verbal, multi-sensory, and nonverbal communication demonstrate its potential as a tool for exploring the underlying mechanisms of interpersonal communication.[2]

Neural synchrony is also found in nonverbal communication, such as hand gestures and facial expressions. An early study found synchronization across participants playing a game of charades. Using fMRI to record brain activity as people gestured or watched the gestures, researchers found synchronized temporal variation in brain activity in mirror neuron and mentalizing systems. Another study showed that communicative behaviors like shared gaze and positive affect expression generated neural synchrony in romantic partners, though not in strangers. As a whole, neural synchrony studies surrounding verbal, multi-sensory, and nonverbal communication demonstrate its potential as a tool for exploring the underlying mechanisms of interpersonal communication.

神经同步性也存在于非言语交际中，比如手势和面部表情。一项早期的研究发现，玩猜字谜游戏的参与者之间存在同步现象。研究人员利用功能磁共振成像技术记录人们打手势或观看手势时的大脑活动，发现镜像神经元和心理系统的大脑活动出现了同步的时间变化。另一项研究表明，交流行为，如共同注视和积极的情感表达，在浪漫的伴侣中产生了神经同步性，但在陌生人中并非如此。作为一个整体，围绕着语言、多感官和非言语交际的神经同步性研究证明了它作为探索人际沟通潜在机制的工具的潜力。

Narrative processing

Another focus of neural synchrony studies involves narrative processing. This direction of research has some crossover with neural synchrony studies of communication, but there remains sufficient interest in the similarities and differences in how people specifically process multimodal narrative information, such as watching movies, hearing stories, or reading passages. Importantly, narrative processing studies of neural synchrony observe hierarchical levels of processing that unfold over time,[35][36] starting in areas responsible for low-level processing of auditory or visual stimuli. As semantic information becomes more salient in the narrative, synchronized processing moves to more integrative networks, such as the inferior parietal lobe or temporal parietal junction.[35]

Another focus of neural synchrony studies involves narrative processing. This direction of research has some crossover with neural synchrony studies of communication, but there remains sufficient interest in the similarities and differences in how people specifically process multimodal narrative information, such as watching movies, hearing stories, or reading passages. Importantly, narrative processing studies of neural synchrony observe hierarchical levels of processing that unfold over time, starting in areas responsible for low-level processing of auditory or visual stimuli. As semantic information becomes more salient in the narrative, synchronized processing moves to more integrative networks, such as the inferior parietal lobe or temporal parietal junction.

= = 叙事加工 = = 神经同步研究的另一个焦点涉及叙事加工。这一研究方向与交流的神经同步性研究有一定的交叉，但是人们对于如何具体处理多模态叙事信息，如观看电影、听故事或阅读段落的异同仍然有足够的兴趣。重要的是，神经同步性的叙事加工研究观察随着时间的推移展开的加工层次，从负责听觉或视觉刺激的低级加工区开始。随着语义信息在叙述中变得越来越突出，同步加工转移到更加一体化的网络，如下顶叶或颞顶叶交界处。

Research shows that neural synchrony is indicative of the similarity in people's narrative recall and understanding, even for ambiguous narratives. One study demonstrated this phenomenon using Heider and Simmel's[37] classic paradigm, where simple shapes move around the screen in a way that causes people to imbue the shapes with stories and social meaning.[38] Participants who interpreted the movement of shapes in similar ways showed greater neural synchrony in cortical brain regions. This connection between neural synchrony and similarity in comprehension reliably occurs across other types of narratives, including listening to stories and free viewing of visual content,[39][40][22] and it persists throughout different stages of the narrative, such as consuming the story, recalling the story, and listening to another person recall the story. Together, these findings highlight neural synchrony as a reliable neural mechanism for the convergence of people's hierarchical narrative processing, suggesting that synchrony plays a critical role in how, if, and why we see meaning in the world similarly.[41][42]

Research shows that neural synchrony is indicative of the similarity in people's narrative recall and understanding, even for ambiguous narratives. One study demonstrated this phenomenon using Heider and Simmel's classic paradigm, where simple shapes move around the screen in a way that causes people to imbue the shapes with stories and social meaning. Participants who interpreted the movement of shapes in similar ways showed greater neural synchrony in cortical brain regions. This connection between neural synchrony and similarity in comprehension reliably occurs across other types of narratives, including listening to stories and free viewing of visual content, and it persists throughout different stages of the narrative, such as consuming the story, recalling the story, and listening to another person recall the story. Together, these findings highlight neural synchrony as a reliable neural mechanism for the convergence of people's hierarchical narrative processing, suggesting that synchrony plays a critical role in how, if, and why we see meaning in the world similarly.

研究表明，神经同步性表明人们在叙事记忆和理解方面具有相似性，即使对于模糊叙事也是如此。一项研究使用海德和西梅尔的经典范式证明了这一现象: 简单的形状在屏幕上移动，使人们赋予形状以故事和社会意义。以类似方式解释形状运动的参与者在大脑皮层区域表现出更大的神经同步性。这种神经同步性和理解上的相似性之间的联系可靠地发生在其他类型的叙事中，包括听故事和自由观看视觉内容，并且这种联系在整个叙事的不同阶段都持续存在，例如阅读故事，回忆故事，听另一个人回忆故事。总之，这些发现突出了神经同步作为一个可靠的神经机制，人们的叙事层次的汇聚，表明同步起着关键作用，如何，如果，为什么我们看到的意义在世界上类似。

Coordination

The pursuit of complex goals for individuals or groups depends on successful coordination, and neural synchrony provides a window into the underlying mechanisms of these processes as well. A review of hyperscanning research shows that neural synchrony approaches have explored coordination through a range of paradigms, including joint attention, movements, ideas, and tasks.[17] These findings also demonstrate synchronization across a variety of brain areas associated with sharing actions and mentalizing, namely the inferior and temporal parietal areas, as well as alpha band and other frequencies. Furthermore, converging evidence suggests that inter-brain models (i.e., neural synchrony) are more effective than intra-brain models at predicting performance for tasks requiring social coordination.[17]

The pursuit of complex goals for individuals or groups depends on successful coordination, and neural synchrony provides a window into the underlying mechanisms of these processes as well. A review of hyperscanning research shows that neural synchrony approaches have explored coordination through a range of paradigms, including joint attention, movements, ideas, and tasks. These findings also demonstrate synchronization across a variety of brain areas associated with sharing actions and mentalizing, namely the inferior and temporal parietal areas, as well as alpha band and other frequencies. Furthermore, converging evidence suggests that inter-brain models (i.e., neural synchrony) are more effective than intra-brain models at predicting performance for tasks requiring social coordination.

个体或群体对复杂目标的追求取决于成功的协调，而神经同步性也提供了了解这些过程的潜在机制的窗口。对超扫描研究的回顾表明，神经同步方法已经通过一系列范式来探索协调，包括联合注意、动作、想法和任务。这些发现也证明了与分享行为和心理化相关的大脑区域的同步性，即下顶叶和颞顶叶区域，以及阿尔法波段和其他频率。此外，汇聚的证据表明，在预测需要社会协调的任务的表现时，脑内模型(即神经同步)比脑内模型更有效。

Understanding how coordination via joint attention relates to neural synchrony, and how this relationship drives performance, is of particular interest to researchers. Research shows that even simple social interactions, like attention convergence, can induce synchrony. For example, in a task where one participant must direct another participant to a target location through eye gazing only, which requires that both participants eventually coordinate eye movements, researchers found significant neural synchrony in mentalizing regions of interacting pairs.[43] Other studies show strong neural synchrony during simple coordinated events like hand and finger movement imitation,[44][45] humming,[46] and even eye-blinking.[47]

Understanding how coordination via joint attention relates to neural synchrony, and how this relationship drives performance, is of particular interest to researchers. Research shows that even simple social interactions, like attention convergence, can induce synchrony. For example, in a task where one participant must direct another participant to a target location through eye gazing only, which requires that both participants eventually coordinate eye movements, researchers found significant neural synchrony in mentalizing regions of interacting pairs. Other studies show strong neural synchrony during simple coordinated events like hand and finger movement imitation, humming, and even eye-blinking.

研究人员特别感兴趣的是，通过联合注意力来理解协调如何与神经同步相关，以及这种关系如何促进表现。研究表明，即使是简单的社会互动，比如注意力的集中，也会导致同步。例如，在一项任务中，一个参与者必须通过眼睛注视引导另一个参与者到达目标位置，这需要两个参与者最终协调眼睛运动，研究人员发现，在心理化相互作用对的区域时，显著的神经同步性。其他研究表明，在简单的协调活动中，比如模仿手和手指的动作，哼唱，甚至眨眼时，神经有很强的同步性。

Coordination studies also find neural synchrony in more complex social coordinations. A set of studies has demonstrated the prevalence of neural synchrony in music production while people coordinate rhythms and movements. Early studies showed that dyads of guitarists generate greater low frequency band neural synchrony when playing together than when playing solo.[48] Also, people who performed distinct roles in an intricate musical piece showed synchrony between brains during periods of coordination.[49] Another series of studies examined pilots and copilots in a flight simulator, finding that synchrony was strongest when the situation demanded more social coordination, such as during stressful scenarios or takeoff and landing.[50][51] These findings implicate neural synchrony as a reliable correlate of social coordination, even when interactions call for coordination of various forms and complexities.[52]

Coordination studies also find neural synchrony in more complex social coordinations. A set of studies has demonstrated the prevalence of neural synchrony in music production while people coordinate rhythms and movements. Early studies showed that dyads of guitarists generate greater low frequency band neural synchrony when playing together than when playing solo. Also, people who performed distinct roles in an intricate musical piece showed synchrony between brains during periods of coordination. Another series of studies examined pilots and copilots in a flight simulator, finding that synchrony was strongest when the situation demanded more social coordination, such as during stressful scenarios or takeoff and landing. These findings implicate neural synchrony as a reliable correlate of social coordination, even when interactions call for coordination of various forms and complexities.

协调研究还发现在更复杂的社会协调中存在神经同步性。一系列研究已经证明，当人们协调节奏和动作时，音乐制作中的神经同步现象十分普遍。早期的研究表明，吉他手的二重奏在一起演奏时比独奏时产生更大的低频带神经同步性。此外，在一个复杂的音乐片段中扮演不同角色的人在协调期间大脑之间表现出同步性。另一系列的研究调查了飞行员和副驾驶员在飞行模拟器中的情况，发现当情况需要更多的社会协调时，同步性最强，例如在紧张的场景或起飞和降落时。这些发现暗示了神经同步是社会协调的一个可靠的相关因素，即使交互需要各种形式和复杂性的协调。

Cooperation

As measured through tasks that involve interactive decision-making and games, results from the field suggest a close association between neural synchrony and cooperation. Decision-making contexts and games that demand greater levels of social, high-level, and goal-directed engagement with other people are typically more conducive to neural synchrony.[53] In this domain, researchers are particularly interested in how neural synchrony levels vary depending on whether people collaborate, compete, or play alone.[3][11]

As measured through tasks that involve interactive decision-making and games, results from the field suggest a close association between neural synchrony and cooperation. Decision-making contexts and games that demand greater levels of social, high-level, and goal-directed engagement with other people are typically more conducive to neural synchrony. In this domain, researchers are particularly interested in how neural synchrony levels vary depending on whether people collaborate, compete, or play alone.

= = 合作 = = 通过涉及互动决策和游戏的任务来衡量，该领域的研究结果表明，神经同步和合作之间有着密切的联系。决策环境和游戏需要更高层次的社交、高层次和目标导向的与他人的接触，这通常更有利于神经同步。在这个领域，研究人员特别感兴趣的是，神经同步程度如何随着人们是否合作、竞争或单独玩耍而变化。

For example, one study that employed a computer video game found high levels of neural synchrony - and better performance - across subjects when they played on the same team, but this effect disappeared when people played against each other or by themselves.[54] Similarly, researchers that administered a puzzle solving task found neural synchrony for people when they are working as a team, yet synchrony decreased for the same people when they worked separately or watched others solve the puzzle.[55] Another study using a classic prisoner's dilemma game showed that participants experienced higher neural synchrony with each other in the high-cooperation-context conditions than they did in the low-cooperation-context conditions or when they interacted with the computer.[56] Subjective measures of perceived cooperativeness mediated this effect. Critically, the idea that neural synchrony is robust during cooperation, that more interactive and demanding cooperative tasks recruit greater neural synchrony, and that better cooperation often links to better performance is corroborated throughout the neural synchrony literature.[11][16]

For example, one study that employed a computer video game found high levels of neural synchrony - and better performance - across subjects when they played on the same team, but this effect disappeared when people played against each other or by themselves. Similarly, researchers that administered a puzzle solving task found neural synchrony for people when they are working as a team, yet synchrony decreased for the same people when they worked separately or watched others solve the puzzle. Another study using a classic prisoner's dilemma game showed that participants experienced higher neural synchrony with each other in the high-cooperation-context conditions than they did in the low-cooperation-context conditions or when they interacted with the computer. Subjective measures of perceived cooperativeness mediated this effect. Critically, the idea that neural synchrony is robust during cooperation, that more interactive and demanding cooperative tasks recruit greater neural synchrony, and that better cooperation often links to better performance is corroborated throughout the neural synchrony literature.

例如，一项使用电脑视频游戏的研究发现，在同一个团队中，受试者的神经同步程度很高，表现也更好，但当人们互相对抗或自己玩时，这种效应就消失了。同样的，研究人员在进行解谜任务时发现，当人们作为一个团队工作时，他们的神经同步性会降低，而当他们分开工作或者看着其他人解谜时，同步性会降低。另一项使用经典囚徒困境游戏的研究显示，在高度合作情境中，参与者与其他人之间的神经同步程度高于在低度合作情境中或与电脑互动时。主观的合作性评价中介了这种效应。关键的是，神经同步性在合作过程中是强有力的，更多的交互和更高要求的合作任务需要更强的神经同步性，更好的合作通常与更好的表现联系在一起，这些观点在神经同步性的文献中得到了证实。

Individual-level differences

Much of the neural synchrony literature examines how stimuli drive responses across multiple brains. Because these responses are often task-dependent, it becomes hard to disentangle state-level factors from individual-level factors (e.g., traits). However, creative experimental designs, access to certain populations, and advances in analysis methods, like IS-RSA, have offered some recent insight into how individual-level differences affect neural synchrony.[13]

Much of the neural synchrony literature examines how stimuli drive responses across multiple brains. Because these responses are often task-dependent, it becomes hard to disentangle state-level factors from individual-level factors (e.g., traits). However, creative experimental designs, access to certain populations, and advances in analysis methods, like IS-RSA, have offered some recent insight into how individual-level differences affect neural synchrony.

= = = 个体水平的差异 = = = = 大部分神经同步文献研究了刺激如何驱动多个大脑的反应。因为这些反应往往是任务相关的，所以很难将状态层面的因素与个体层面的因素(例如，特质)区分开来。然而，创造性的实验设计、对特定人群的访问以及分析方法的进步，如 IS-RSA，已经提供了一些最新的洞察，个体水平的差异是如何影响神经同步的。

Using an ambiguous social narrative, Finn et al.[57] report that individuals with high-trait paranoia showed stronger neural synchrony with each other in socially-motivated cortical regions than they did with low-trait paranoia subjects - a finding that also scales when examining the semantic and syntactic similarities of their narrative recall. Similarly, research shows that people's cognitive styles affect their level of synchrony with each other. In response to viewing a film, Bacha-Trams et al. demonstrated that holistic thinkers showed greater neural synchrony with each other, and presumably understood the film more similarly, than analytic thinkers did with each other. The two groups also exhibited within-group synchrony in different brain regions.[58]

Using an ambiguous social narrative, Finn et al. report that individuals with high-trait paranoia showed stronger neural synchrony with each other in socially-motivated cortical regions than they did with low-trait paranoia subjects - a finding that also scales when examining the semantic and syntactic similarities of their narrative recall. Similarly, research shows that people's cognitive styles affect their level of synchrony with each other. In response to viewing a film, Bacha-Trams et al. demonstrated that holistic thinkers showed greater neural synchrony with each other, and presumably understood the film more similarly, than analytic thinkers did with each other. The two groups also exhibited within-group synchrony in different brain regions.

使用一个模棱两可的社会叙事，芬恩等人。研究报告显示，在社会动机皮层区域，高特质偏执狂个体与低特质偏执狂个体相比，表现出更强的神经同步性——这一发现在检查他们叙事记忆的语义和句法相似性时也具有尺度效应。同样，研究表明，人们的认知风格影响他们与其他人的同步程度。在回应观看电影，Bacha-Trams 等人。证明了整体思考者之间的神经同步性更强，而且大概比分析思考者之间对电影的理解更相似。两组大脑不同区域也表现出组内同步性。

The idea that individual-level differences affect neural synchrony extends to clinical areas as well. Some research indicates that people who manage autism spectrum disorder exhibit distinct and diminished patterns of neural synchrony compared to people without autism spectrum disorder.[59][60] Clinically driven discrepancies in neural synchrony have also been shown to increase along with symptom severity.[61]

The idea that individual-level differences affect neural synchrony extends to clinical areas as well. Some research indicates that people who manage autism spectrum disorder exhibit distinct and diminished patterns of neural synchrony compared to people without autism spectrum disorder. Clinically driven discrepancies in neural synchrony have also been shown to increase along with symptom severity.

个体水平差异影响神经同步性的观点也延伸到临床领域。一些研究表明，管理自闭症光谱的人与没有自闭症光谱的人相比，神经同步的模式明显减弱。临床驱动的差异神经同步性也表明随着症状的严重性增加。

The brain-as-predictor approach

Neural synchrony has major implications for the brain-as-predictor approach, which encourages the use of neuroimaging data to predict robust, ecologically valid behavioral outcomes. The brain-as-predictor approach has been effective in predicting outcomes across a variety of domains, including health and consumer choices. Given its social nature, neural synchrony has the potential to build on brain-as-predictor models by allowing for predictions about real-world social processes. Some researchers have started to employ this approach.[62]

Neural synchrony has major implications for the brain-as-predictor approach, which encourages the use of neuroimaging data to predict robust, ecologically valid behavioral outcomes. The brain-as-predictor approach has been effective in predicting outcomes across a variety of domains, including health and consumer choices. Given its social nature, neural synchrony has the potential to build on brain-as-predictor models by allowing for predictions about real-world social processes. Some researchers have started to employ this approach.

= = = 大脑作为预测器的方法 = = = = 神经同步对于大脑作为预测器的方法有着重要的意义，这种方法鼓励使用神经成像数据来预测可靠的、生态学上有效的行为结果。大脑作为预测器的方法已经在预测结果的各种领域，包括健康和消费者的选择有效。鉴于其社会性质，神经同步有可能建立在大脑作为预测模型的基础上，允许对现实世界的社会过程进行预测。一些研究人员已经开始采用这种方法。

In one study, members of a bounded social network watched a battery of short audiovisual movies in an MRI scanner. Hypothesizing that similarity in neural responses tracks with social closeness, the researchers used the strength of neural synchrony measures across participants to reliably predict real-world social network proximity and friendship. Another example of how neural synchrony can be leveraged to predict outcomes involves the use of neural reference groups, which can predict behaviors like partisan stance on controversial topics at above-chance levels. This approach requires identifying groups of people that perceive and respond to the world in similar ways, measuring their brain activity and dispositional attitudes related to any stimuli of interest, and then using a synchrony-based classification method to predict whether new individuals see the world similarly or differently depending on their synchrony with the reference group. Together, these findings illustrate the power and potential for neural synchrony to contribute to brain-as-predictor models, ultimately framing neural synchrony as a tool for understanding real-world outcomes above and beyond behavioral measures alone.[63]

In one study, members of a bounded social network watched a battery of short audiovisual movies in an MRI scanner. Hypothesizing that similarity in neural responses tracks with social closeness, the researchers used the strength of neural synchrony measures across participants to reliably predict real-world social network proximity and friendship. Another example of how neural synchrony can be leveraged to predict outcomes involves the use of neural reference groups, which can predict behaviors like partisan stance on controversial topics at above-chance levels. This approach requires identifying groups of people that perceive and respond to the world in similar ways, measuring their brain activity and dispositional attitudes related to any stimuli of interest, and then using a synchrony-based classification method to predict whether new individuals see the world similarly or differently depending on their synchrony with the reference group. Together, these findings illustrate the power and potential for neural synchrony to contribute to brain-as-predictor models, ultimately framing neural synchrony as a tool for understanding real-world outcomes above and beyond behavioral measures alone.

在一项研究中，一个有限的社交网络的成员在核磁共振扫描仪中观看一组短的视听电影。研究人员假设神经反应的相似性与社交亲密度有关，他们利用参与者的神经同步测量的强度来可靠地预测现实世界的社交网络亲密度和友谊。另一个利用神经同步来预测结果的例子涉及到神经参考组的使用，这些参考组可以预测行为，比如在高于概率水平的有争议话题上的党派立场。这种方法需要识别以相似方式感知和回应世界的人群，测量他们的大脑活动和与任何兴趣刺激相关的性格态度，然后使用基于同步的分类方法来预测新个体看待世界的方式是相似还是不同取决于他们与参照群体的同步性。总之，这些发现说明了神经同步性对大脑作为预测器模型的影响力和潜力，最终将神经同步性定义为一种工具，用于理解超越单纯行为测量的现实世界结果。

See also

See also

= 参见 =

  • Social cognition
  • Social neuroscience
  • Cognitive neuroscience
  • Behavioral synchrony
  • Group cohesiveness
  • Electroencephalography
  • Functional near-infrared spectroscopy
  • Functional magnetic resonance imaging


  • 社会认知社会神经科学
  • 认知神经科学
  • 行为同步性
  • 团队凝聚力
  • 脑电图
  • 功能近红外光谱技术
  • 功能性磁共振成像

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