The Embodied Penman: Effector‐Specific Motor–Language Integration During Handwriting

Several studies have illuminated how processing manual action verbs (MaVs) affects the programming or execution of concurrent hand movements. Here, to circumvent key confounds in extant designs, we conducted the first assessment of motor–language integration during handwriting—a task in which linguistic and motoric processes are co‐substantiated. Participants copied MaVs, non‐manual action verbs, and non‐action verbs as we collected measures of motor programming and motor execution. Programming latencies were similar across conditions, but execution was faster for MaVs than for the other categories, regardless of whether word meanings were accessed implicitly or explicitly. In line with the Hand‐Action‐Network Dynamic Language Embodiment (HANDLE) model, such findings suggest that effector‐congruent verbs can prime manual movements even during highly automatized tasks in which motoric and verbal processes are naturally intertwined. Our paradigm opens new avenues for fine‐grained explorations of embodied language processes.     

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.     

How infant-directed actions enhance infants’ attention,learning, and exploration: Evidence from EEG and computational modeling

When teaching infants new actions, parents tend to modify their movements. Infants prefer these infant-directed actions (IDAs) over adult-directed actions and learn well from them. Yet, it remains unclear how parents’ action modulations capture infants’ attention. Typically, making movements larger than usual is thought to draw attention. Recent findings, however, suggest that parents might exploit movement variability to highlight actions. We hypothesized that variability in movement amplitude rather than higher amplitude is capturing infants’ attention during IDAs. Using EEG, we measured 15-month-olds’ brain activity while they were observing action demonstrations with normal, high, or variable amplitude movements. Infants’ theta power (4–5 Hz) in fronto-central channels was compared between conditions. Frontal theta was significantly higher, indicating stronger attentional engagement, in the variable compared to the other conditions. Computational modelling showed that infants’ frontal theta power was predicted best by how surprising each movement was. Thus, surprise induced by variability in movements rather than large movements alone engages infants’ attention during IDAs. Infants with higher theta power for variable movements were more likely to perform actions successfully and to explore objects novel in the context of the given goal. This highlights the brain mechanisms by which IDAs enhance infants’ attention, learning, and exploration.     

与立体视觉相关的视诱发电位研究

在微机上编制能产生动态随机点立体图（ＤＲＤＳ）,亮暗类棋盘格和随机点背景三种图形刺激的软件．记录了３４例正常人在这三种刺激下的ＶＢＰ．其结果为：（１）ＤＲＤＳ刺激下的ＶＥＰＮ１波潜伏期为２６５±２５ｍｓ,基波能量占总交流能量的６３．２±１８．９％．（２）亮暗类棋盘格刺激下的ＶＥＰＮ１波的潜伏期为１９０±２２ｍｓ,基波能量占总交流能量的３９．２±１９．６％．（３）随机点背景刺激下的ＶＥＰ波则为一些杂乱的小波．结果提示：动态ＲＤＳ刺激下的ＶＥＰ除在潜伏期方面具有特异性外,并在谐波的能量分布上也具有特异性,且客观性更强．根据这些特征有助于对立体视觉功能进行客观性评价．     

Dynamics Versus Development in Numerosity Estimation: A Computational Model Accurately Predicts a Developmental Reversal

Perceptual judgments result from a dynamic process, but little is known about the dynamics of number-line estimation. A recent study proposed a computational model that combined a model of trial-to-trial changes with a model for the internal scaling of discrete numbers. Here, we tested a surprising prediction of the model—a situation in which children's estimates of numerosity would be better than those of adults. Consistent with the model simulations, task contexts led to a clear developmental reversal: children made more adult-like, linear estimates when to-be-estimated numbers were descending over trials (i.e., backward condition), whereas adults became more like children with logarithmic estimates when numbers were ascending (i.e., forward condition). In addition, adults’ estimates were subject to inter-trial differences regardless of stimulus order. In contrast, children were not able to use the trial-to-trial dynamics unless stimuli varied systematically, indicating the limited cognitive capacity for dynamic updates. Together, the model adequately predicts both developmental and trial-to-trial changes in number-line tasks.     

Dynamic multi-criteria decision making

Most medium-and long-term decision making in industry and government can be viewed as dynamic multi-criteria decision making (MCDM), in which the decision makers are free to alter the emphasis placed on each objective in the light of developing circumstances. In this paper the problem of time-dependent weights in MCDM is discussed and an analysis of empirical data associated with dynamic decision making is presented.     

Creating nonbelieved memories for bizarre actions using an imagination inflation procedure

The current experiments examined the creation of nonbelieved true and false memories after imagining bizarre and familiar actions using the imagination inflation procedure (Goff & Roediger, 1998). In both experiments, participants took part in three sessions. In Session 1, participants had to perform or imagine simple familiar actions (e.g., “stir the water with the spoon”) and bizarre actions (e.g., “balance the spoon on your nose”). A day later, participants needed to imagine simple actions of which some were new actions, and some were old actions that appeared in the first session. After a week, the participants completed a recognition task. For those actions that were correctly or incorrectly remembered as having been performed, the participant was challenged that the action was not performed in order to evoke nonbelieved true and false memories. In general, we found that the imagination inflation procedure can successfully induce participants to produce nonbelieved memories. In Study 1, we successfully induced nonbelieved memories for bizarre actions, although in general nonbelieved memory rates were low. In Study 2, more participants formed nonbelieved memories for bizarre actions than for familiar actions. Also, we found that especially belief was more susceptible to revision when memories were challenged than recollection. In two experiments, we showed that nonbelieved memories can successfully be induced for both familiar and bizarre actions.     

The TROCA Project: An autonomous transportation robot controlled by a cognitive architecture

Autonomous mobile robots emerged as an important kind of transportation system in warehouses and factories. In this work, we present the use of MECA cognitive architecture in the development of an artificial mind for an autonomous robot responsible for multiple tasks, including transportation of packages along a factory floor, environment exploration, warehouse inventory, its internal energy management, self-monitoring and dealing with human operators and other robots. The present text provides a detailed specification for the architecture and its software implementation. Future work will present the simulation results under different configurations, together with a detailed analysis of the architecture performance and its generalization for autonomous robot control.     

Network change point detection in resting-state functional connectivity dynamics of mild cognitive impairment patients

Background/Objective: This study aims to characterize the differences on the short-term temporal network dynamics of the undirected and weighted whole-brain functional connectivity between healthy aging individuals and people with mild cognitive impairment (MCI). The Network Change Point Detection algorithm was applied to identify the significant change points in the resting-state fMRI register, and we analyzed the fluctuations in the topological properties of the sub-networks between significant change points. Method: Ten MCI patients matched by gender and age in 1:1 ratio to healthy controls screened during patient recruitment. A neuropsychological evaluation was done to both groups as well as functional magnetic images were obtained with a Philips 3.0T. All the images were preprocessed and statistically analyzed through dynamic point estimation tools. Results: No statistically significant differences were found between groups in the number of significant change points in the functional connectivity networks. However, an interaction effect of age and state was detected on the intra-participant variability of the network strength. Conclusions: The progression of states was associated to higher variability in the patient's group. Additionally, higher performance in the prospective and retrospective memory scale was associated with higher median network strength.