多巴胺系统基因对注意网络的调控作用

多巴胺是脑内重要的神经递质之一,与注意活动紧密相关。本文选取作用于突触前膜、间隙和后膜的多巴胺系统基因——多巴胺转运蛋白基因、儿茶酚氧化甲基转移酶基因和多巴胺受体基因,整合影像遗传学研究,探讨多巴胺基因对注意网络的调控。元分析发现背侧和腹侧注意网络的主要脑区均有较大的基因调控效应,且腹侧网络的效应值显著大于背侧网络,表明多巴胺系统基因在全脑范围内调控注意网络,且对腹侧网络的调控作用更强于背侧网络。     

Accuracy and performance of the state-based Φ and liveliness measures of information integration

A number of people have suggested that there is a link between information integration and consciousness, and a number of algorithms for calculating information integration have been put forward. The most recent of these is Balduzzi and Tononi’s state-based Φ algorithm, which has factorial dependencies that severely limit the number of neurons that can be analyzed. To address this issue an alternative state-based measure known as liveliness has been developed, which uses the causal relationships between neurons to identify the areas of maximum information integration. This paper outlines the state-based Φ and liveliness algorithms and sets out a number of test networks that were used to compare their accuracy and performance. The results show that liveliness is a reasonable approximation to state-based Φ for some network topologies, and it has a much more scalable performance than state-based Φ.     

Unmasking a shady mirror effect: Recognition of normal versus obscured faces

Hockley, Hemsworth, and Consoli (1999) Hockley, W. E., Hemsworth, D. E. and Consoli, A. 1999. Shades of the mirror effect: Recognition of faces with and without sunglasses. Memory & Cognition, 27: 128–138. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] found that following the study of normal faces, a recognition test of normal faces versus faces wearing sunglasses produced a mirror effect: The sunglasses manipulation decreased hit rates and increased false-alarm rates. The stimuli used by Hockley et al. (1999) Hockley, W. E., Hemsworth, D. E. and Consoli, A. 1999. Shades of the mirror effect: Recognition of faces with and without sunglasses. Memory & Cognition, 27: 128–138. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] consisted of separate poses of models wearing or not wearing sunglasses. In the current experiments, we separately manipulated same versus different depictions of individual faces and whether or not the faces were partially obscured. The results of a simulation and four experiments suggest that the test-based, mirror effect observed by Hockley et al. (1999) Hockley, W. E., Hemsworth, D. E. and Consoli, A. 1999. Shades of the mirror effect: Recognition of faces with and without sunglasses. Memory & Cognition, 27: 128–138. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] is actually two separable effects.     

Variation in individuals' semantic networks for common knowledge is associated with false memory

Three experiments assessed the relationships between false memories of words and their degree of connectedness within individual semantic networks. In the first two experiments, participants studied associated word lists (e.g., hot, winter, ice), completed a recognition test that included related nonstudied words (e.g., cold, snow), and then rated the semantic relatedness of all word pairs including studied and nonstudied words. In the third experiment, the task order was reversed; participants completed pairwise ratings and then, two weeks later, completed the false memory task. The relatedness ratings were analysed using the Pathfinder scaling algorithm. In all experiments, items that an individual falsely recognized had higher semantic Pathfinder node densities than those items correctly rejected.     

Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks

Convolutional neural networks (CNNs) are increasingly widely used in psychology and neuroscience to predict how human minds and brains respond to visual images. Typically, CNNs represent these images using thousands of features that are learned through extensive training on image datasets. This raises a question: How many of these features are really needed to model human behavior? Here, we attempt to estimate the number of dimensions in CNN representations that are required to capture human psychological representations in two ways: (1) directly, using human similarity judgments and (2) indirectly, in the context of categorization. In both cases, we find that low-dimensional projections of CNN representations are sufficient to predict human behavior. We show that these low-dimensional representations can be easily interpreted, providing further insight into how people represent visual information. A series of control studies indicate that these findings are not due to the size of the dataset we used and may be due to a high level of redundancy in the features appearing in CNN representations.     

Priming effects of arithmetic signs in 10- to 15-year-old children

In this research, 10- to 12- and 13- to 15-year-old children were presented with very simple addition and multiplication problems involving operands from 1 to 4. Critically, the arithmetic sign was presented before the operands in half of the trials, whereas it was presented at the same time as the operands in the other half. Our results indicate that presenting the ‘x’ sign before the operands of a multiplication problem does not speed up the solving process, irrespective of the age of children. In contrast, presenting the ‘+’ sign before the operands of an addition problem facilitates the solving process, but only in 13 to 15-year-old children. Such priming effects of the arithmetic sign have been previously interpreted as the result of a pre-activation of an automated counting procedure, which can be applied as soon as the operands are presented. Therefore, our results echo previous conclusions of the literature that simple additions but not multiplications can be solved by fast counting procedures. More importantly, we show here that these procedures are possibly convoked automatically by children after the age of 13 years. At a more theoretical level, our results do not support the theory that simple additions are solved through retrieval of the answers from long-term memory by experts. Rather, the development of expertise for mental addition would consist in an acceleration of procedures until automatization.     

A Social Interpolation Model of Group Problem-Solving

How do people use information from others to solve complex problems? Prior work has addressed this question by placing people in social learning situations where the problems they were asked to solve required varying degrees of exploration. This past work uncovered important interactions between groups' connectivity and the problem's complexity: the advantage of less connected networks over more connected networks increased as exploration was increasingly required for optimally solving the problem at hand. We propose the Social Interpolation Model (SIM), an agent-based model to explore the cognitive mechanisms that can underlie exploratory behavior in groups. Through results from simulation experiments, we conclude that “exploration” may not be a single cognitive property, but rather the emergent result of three distinct behavioral and cognitive mechanisms, namely, (a) breadth of generalization, (b) quality of prior expectation, and (c) relative valuation of self-obtained information. We formalize these mechanisms in the SIM, and explore their effects on group dynamics and success at solving different kinds of problems. Our main finding is that broad generalization and high quality of prior expectation facilitate successful search in environments where exploration is important, and hinder successful search in environments where exploitation alone is sufficient.     

On the Generalization of Simple Alternating Category Structures

A fundamental question in the study of human cognition is how people learn to predict the category membership of an example from its properties. Leading approaches account for a wide range of data in terms of comparison to stored examples, abstractions capturing statistical regularities, or logical rules. Across three experiments, participants learned a category structure in a low-dimension, continuous-valued space consisting of regularly alternating regions of class membership (A B A B). The dependent measure was generalization performance for novel items outside the range of the training space. Human learners often extended the alternation pattern––a finding of critical interest given that leading theories of categorization based on similarity or dimensional rules fail to predict this behavior. In addition, we provide novel theoretical interpretations of the observed phenomenon.     

An exploratory analysis of the latent structure of process data via action sequence autoencoders

Computer simulations have become a popular tool for assessing complex skills such as problem-solving. Log files of computer-based items record the human–computer interactive processes for each respondent in full. The response processes are very diverse, noisy, and of non-standard formats. Few generic methods have been developed to exploit the information contained in process data. In this paper we propose a method to extract latent variables from process data. The method utilizes a sequence-to-sequence autoencoder to compress response processes into standard numerical vectors. It does not require prior knowledge of the specific items and human–computer interaction patterns. The proposed method is applied to both simulated and real process data to demonstrate that the resulting latent variables extract useful information from the response processes.     

不公平感及相关决策的认知神经机制

公平是人类社会生活的基本规范之一,不公平感及其相关决策则是研究者们关注的重要课题。长期以来,该领域的研究一般采用最后通牒博弈或其变式展开。大量脑成像研究探查了关于不公平感及相关决策的认知神经机制,尤其集中探讨了最后通牒博弈的回应者对不公平提议进行反应的脑区及其对应功能。经常得到关注的脑区包括了前脑岛、前扣带皮层、背外侧前额叶、内侧前额叶、杏仁核和颞顶交界等。对特殊人群的不公平感及相关决策进行研究可以帮助检验或澄清上述重要脑区及脑网络在不公平感及相关决策中扮演的角色,同时也阐释特殊人群的社会认知功能的特点。近年来,相当数量的研究关注了不同情境因素(包括分配方案相关因素和社会情境相关因素)调制不公平感及相关决策的过程,并讨论其背后的认知神经机制。未来的研究更应利用多模态数据分析方法,同时结合基因和激素层面的研究,以期深入对不公平感及相关决策的心理和生理机制的理解。