The Cambridge Handbook of Intelligence and Cognitive Neuroscience最新文献

An Integrated, Dynamic Functional Connectome Underlies Intelligence 一个集成的、动态的功能连接体是智力的基础

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 2021-07-01 DOI: 10.1017/9781108635462.017

J. Cohen, M. D’Esposito

引用次数: 2

The Neural Representation of Concrete and Abstract Concepts 具体和抽象概念的神经表征

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 2021-05-31 DOI: 10.1017/9781108635462.029

Robert Vargas, M. Just

{"title":"The Neural Representation of Concrete and Abstract Concepts","authors":"Robert Vargas, M. Just","doi":"10.1017/9781108635462.029","DOIUrl":"https://doi.org/10.1017/9781108635462.029","url":null,"abstract":"concepts elicited greater activation than concrete concepts in such verbal processing areas. By contrast, concrete concepts elicited greater activation than abstract concepts in visuospatial processing (precuneus, posterior cingulate, and fusiform gyrus). This meta-analysis was limited to univariate comparisons of categories of concepts and did not have access to the activation patterns evoked by individual concepts. This limitation potentially overlooks nuanced distinctions in the representational structure. Univariate contrasts potentially overlook critical relationships across neural states and neural regions (Mur et al., 2009). Through the use of MVPA techniques, more recent studies have begun to examine the underlying semantic structure of sets of abstract concepts. The next section focuses on various imaging studies examining the neural activation patterns associated with abstract concepts and explores the possible semantic structures that are specific to abstract concepts. Neurosemantic Dimensions of Abstract Meaning As in the case of concrete concepts, the semantic dimensions underlying abstract concept categories can be identified from their activation patterns. One of the first attempts to decode the semantic content of abstract semantic information was conducted by Anderson, Kiela, Clark, and Poesio (2017). A set of individual concepts that belonged to various taxonomic categories (tools, locations, social roles, events, communications, and attributes) were decoded from their activation patterns. Whether a concept belonged to one of two abstract semantic categories (i.e., Law orMusic) was also decoded from the activation patterns of individual concepts. Although these abstract semantic categories could be decoded based on their activation patterns, the localization of this dissociation is unclear. Neurally-based semantic dimensions underlying abstract concepts differ from the dimensions underlying concrete concepts. Vargas and Just (2019) investigated the fMRI activation patterns of 28 abstract concepts (e.g., ethics, truth, spirituality) focusing on individual concept representation and the relationship between the activation profiles of these concept representations. Factor analyses of the activation patterns evoked by the stimulus set revealed three underlying semantic dimensions. These dimensions corresponded to 1) the degree to which a concept was Verbally Represented, 2) whether a concept was External (or Internal) to the individual, and 3) whether the concept contained Social Content. The Verbal Representation dimension was present across all participants and was the most salient of the semantic dimensions. Concepts with large positive factor scores for this factor included compliment, faith, and ethics, while concepts with large negative scores for this factor included gravity, force, and acceleration. The former three concepts seem far less perceptual than the latter three. For the Externality factor, a concept that is externa","PeriodicalId":206489,"journal":{"name":"The Cambridge Handbook of Intelligence and Cognitive Neuroscience","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115306078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human Intelligence and Network Neuroscience 人类智能和网络神经科学

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 2021-05-31 DOI: 10.1017/9781108635462.009

A. Barbey

{"title":"Human Intelligence and Network Neuroscience","authors":"A. Barbey","doi":"10.1017/9781108635462.009","DOIUrl":"https://doi.org/10.1017/9781108635462.009","url":null,"abstract":"Flexibility is central to human intelligence and is made possible by the brain’s remarkable capacity to reconfigure itself – to continually update prior knowledge on the basis of new information and to actively generate internal predictions that guide adaptive behavior and decision making. Rather than lying dormant until stimulated, contemporary research conceives of the brain as a dynamic and active inference generator that anticipates incoming sensory inputs, forming hypotheses about that world that can be tested against sensory signals that arrive in the brain (Clark, 2013; Friston, 2010). Plasticity is therefore critical for the emergence of human intelligence, providing a powerful mechanism for updating prior beliefs, generating dynamic predictions about the world, and adapting in response to ongoing changes in the environment (Barbey, 2018). This perspective provides a catalyst for contemporary research on human intelligence, breaking away from the classic view that general intelligence (g) originates from individual differences in a fixed set of cortical regions or a singular brain network (for reviews, see Haier, 2017; Posner & Barbey, 2020). Early studies investigating the neurobiology of g focused on the lateral prefrontal cortex (Barbey, Colom, & Grafman, 2013b; Duncan et al., 2000), motivating an influential theory based on the role of this region in cognitive control functions for intelligent behavior (Duncan & Owen, 2000). The later emergence of network-based theories reflected an effort to examine the neurobiology of intelligence through a wider lens, accounting for individual differences in g on the basis of broadly distributed networks. For example, the Parietal-Frontal Integration Theory (P-FIT) was the first to propose that “a discrete parieto-frontal network underlies intelligence” (Jung & Haier, 2007) and that g reflects the capacity of this network to evaluate and test hypotheses for problem-solving (see also Barbey et al., 2012). A central feature","PeriodicalId":206489,"journal":{"name":"The Cambridge Handbook of Intelligence and Cognitive Neuroscience","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130486229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predictive Modeling Approaches 预测建模方法

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.020

引用次数: 0

Index 指数

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.030

引用次数: 0

Neuroimaging Methods and Findings 神经影像学方法和结果

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.013

引用次数: 0

Translating Research on the Neuroscience of Intelligence into Action 将智力神经科学研究转化为行动

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.023

引用次数: 0

Enhancing Cognition 提高认知能力

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.024

M. Posner, M. Rothbart

引用次数: 4

It’s about Time 这是关于时间的

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.010

R. Kievit, I. Simpson-Kent

引用次数: 0

Theories, Models, and Hypotheses 理论、模型和假设

The Cambridge Handbook of Intelligence and Cognitive Neuroscience Pub Date : 1900-01-01 DOI: 10.1017/9781108635462.007

引用次数: 0