Staying Together: A Bidirectional Delay–Coupled Approach to Joint Action

To understand how individuals adapt to and anticipate each other in joint tasks, we employ a bidirectional delay–coupled dynamical system that allows for mutual adaptation and anticipation. In delay–coupled systems, anticipation is achieved when one system compares its own time‐delayed behavior, which implicitly includes past information about the other system’s behavior, with the other system’s instantaneous behavior. Applied to joint music performance, the model allows each system to adapt its behavior to the dynamics of the other. Model predictions of asynchrony between two simultaneously produced musical voices were compared with duet pianists’ behavior; each partner performed one voice while auditory feedback perturbations occurred at unpredictable times during live performance. As the model predicted, when auditory feedback from one musical voice was removed, the asynchrony changed: The pianist’s voice that was removed anticipated (preceded) the actions of their partner. When the auditory feedback returned and both musicians could hear each other, they rapidly returned to baseline levels of asynchrony. To understand how the pianists anticipated each other, their performances were fitted by the model to examine change in model parameters (coupling strength, time‐delay). When auditory feedback for one or both voices was removed, the fits showed the expected decrease in coupling strength and time‐delay between the systems. When feedback about the voice(s) returned, the coupling strength and time‐delay returned to baseline. These findings support the idea that when people perform actions together, they do so as a coupled bidirectional anticipatory system.     

Complex Communication Dynamics: Exploring the Structure of an Academic Talk

Communication is a multimodal phenomenon. The cognitive mechanisms supporting it are still understudied. We explored a natural dataset of academic lectures to determine how communication modalities are used and coordinated during the presentation of complex information. Using automated and semi‐automated techniques, we extracted and analyzed, from the videos of 30 speakers, measures capturing the dynamics of their body movement, their slide change rate, and various aspects of their speech (speech rate, articulation rate, fundamental frequency, and intensity). There were consistent but statistically subtle patterns in the use of speech rate, articulation rate, intensity, and body motion across the presentation. Principal component analysis also revealed patterns of system‐like covariation among modalities. These findings, although tentative, do suggest that the cognitive system is integrating body, slides, and speech in a coordinated manner during natural language use. Further research is needed to clarify the specific coordination patterns that occur between the different modalities.     

Evaluating young children''s cognitive capacities through computer versus hand drawings

Young normal and handicapped children, aged 3 to 6 years, were taught to draw a scene of a house, garden and a sky with a computer drawing program that uses icons and is operated by a mouse. The drawings were rated by a team of experts on a 7-category scale. The children's computer- and hand-produced drawings were compared with one another and with results on cognitive, visual and fine motor tests. The computer drawing program made it possible for the children to accurately draw closed shapes, to get instant feedback on the adequacy of the drawing, and to make corrections with ease. It was hypothesized that these features would compensate for the young children's limitations in such cognitive skills, as memory, concentration, planning and accomplishment, as well as their weak motor skills. In addition, it was hypothesized that traditional cognitive ratings of hand drawings may underestimate young children's intellectual ability, because drawing by hand demands motor skills and memory, concentration and planning skills that are more developed than that actually shown by young children. To test the latter hypothesis, the children completed a training program in using a computer to make drawings. The results show that cognitive processes such as planning, analysis and synthesis can be investigated by means of a computer drawing program in a way not possible using traditional pencil and paper drawings. It can be said that the method used here made it possible to measure cognitive abilities "under the floor" of what is ordinarily possible by means of traditionally hand drawings.     

Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.     

Connectionist models of conditioning: A tutorial

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations.     

The choice of constraints in correspondence analysis

A discussion of alternative constraint systems has been lacking in the literature on correspondence analysis and related techniques. This paper reiterates earlier results that an explicit choice of constraints has to be made which can have important effects on the resulting scores. The paper also presents new results on dealing with missing data and probabilistic category assignment.I am most grateful to the following for their helpful comments. Arto Demirjian, Michael Greenacre, Michael Healy, Shizuhiko Nishisato, Roderick Mcdonald, and several anonymous referees.     

内侧前额皮层-伏隔核环路在决策冲动中的作用：基于动物模型的研究

注意缺陷多动障碍(attentiondeficit/hyperactivitydisorder,ADHD)行为控制不足与决策冲动密切相关,后者受内侧前额皮层(medial prefrontal cortex, mPFC)与伏隔核(nucleus accumbens, NAc)调节。为调查ADHD决策冲动与m PFC-NAc间功能耦合的关系,研究采用ADHD模型SHR (spontaneously hypertensive rat, SHR)大鼠,结合延迟折扣任务和在体电生理,研究发现,与对照Wistar (WIS)大鼠相比, SHR大鼠对延迟大奖赏的选择百分比降低; WIS大鼠m PFC-NAc的Theta频段相干值表现为延迟选择时显著大于立即选择时、首次选择时大于连续选择时、转换试次时大于连续试次时,而SHR大鼠在上述条件均低于WIS大鼠。回归分析发现m PFC-NAc的相干差值与延迟大奖赏选择率显著正相关。结果表明m PFC-NAc间功能联系减弱是ADHD决策冲动缺陷的重要环路基础,该缺陷与其深度信息加工以及策略转换能力受损有关,扩展了ADHD决策冲动的认知和神经机制的认识。     

人类颜色视觉的计算理论

该文有机地结合了计算视觉理论和生态学视觉理论,指出颜色信息处理的根本任务是检测环境中的光不变量。在此基础上,作者提出了颜色视觉的计算理论以及计算理论本身的生物学标准。初级视觉计算是典型的不适定问题,动物的视觉系统则利用视环境中存在的条件将该不适定问题转化为定解问题。本文引入颜色视觉计算的免要条件,客观性约束,以及颜色认知的神经表象,证明了上述约束下颜色算法的存在性。本文给出了构造颜色知觉的基本假设。同时,该文还讨论了与上述问题密切相关的几个基本问题:神经表象的完备性,主观色觉的客观性,明度知觉和颜色知觉的统一,人类主观色觉的实现方式。