经验、材料性质及加工水平对虚假记忆的影响

本实验采用DRM研究范式,考察经验、材料性质和加工水平三个方面对虚假记忆的影响。实验首次采用句子的方式呈现,给被试提供符合经验和不符合经验的句子进行学习和再认。实验结果显示,三个因素对虚假记忆的影响都是显著的,其中,经验是导致虚假记忆产生的主导因素,加工深度同经验之间以及材料性质同经验之间的交互作用均存在显著的交互作用。     

Quantifying the psychopathic stare: Automated assessment of head motion is related to antisocial traits in forensic interviews

Clinicians have long noted that individuals with high psychopathic traits exhibit unique interpersonal style often observable during forensic interviews. Here we develop an automated approach for quantifying head dynamics during video-recorded naturalistic clinical interviews. We expected head dynamics would be related to psychopathic traits. As predicted, dwell times indicate that those with higher levels of psychopathic traits are characterized by more stationary head positions, focused directly towards the camera/interviewer, than were individuals low in psychopathic traits. These associations were primarily driven by developmental/antisocial features of psychopathy, indicating that those with severe and life-course persistent antisocial behavior exhibit more rigid and focused orienting of their head during interpersonal communication. These results encourage more research into the automated quantification of behavioral manifestations of personality to support clinical observations that psychopaths exhibit unique qualities in non-verbal interpersonal communication.     

Prior sleep timing and visual recognition of emotional faces in 6-month-old infants

Face recognition is an important mnemonic ability for infants when navigating the social world. While age-related changes in face processing abilities are relatively well documented, less is known about short-term intra-individual fluctuations in this ability. Given that sleep deprivation in adults leads to impairments in information processing, we assessed the role of prior sleep on 6-month-old infants’ (N = 17) visual recognition of faces showing three emotional expressions (neutral, sad, angry). Visual recognition was inferred by assessing novelty preferences for unfamiliar relative to familiarized faces in a visual recognition memory paradigm. In a within-subject design, infants participated once after they had recently woken up from a nap (nap condition) and once after they had been awake for an extended period of time (awake condition). Infants failed to show visual recognition for the neutral faces in either condition. Infants showed recognition for the sad and angry faces when tested in the awake condition, but not in the nap condition. This suggests that timing of prior sleep shapes how effectively infants process emotionally relevant information in their environment.     

A Computational Evaluation of Two Models of Retrieval Processes in Sentence Processing in Aphasia

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation-based model and the direct-access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self-paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k-fold cross-validation. For both IWAs and controls, the activation-based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation-based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing.     

Characterization of visual scanning while driving for the identification of drivers’ profiles

Assessing the driving skills of people with cognitive or visual impairments is often complex. The analysis of visual exploration strategies can be a good solution to identify the implementation or not of good strategies of information search in the visual scene (adaptation and compensation). In this study, we compared the visual exploration behaviours of 26 healthy, 19 glaucoma and 21 elderly participants. For this purpose, we used a driving simulator for which a visual field measurement test had been adapted to obtain measurements in static and dynamic conditions. The dynamics of the gaze was also measured. Our results showed that each of the three groups of participants had specific characteristics of visual exploration. Using a classification algorithm, we were able to show that it was possible to identify the group which a participant belonged to on the basis of the visual exploration’s characteristics. This finding opens the door to many applications in the context of driving assistance and training.     

The first prior: From co-embodiment to co-homeostasis in early life

The idea that our perceptions in the here and now are influenced by prior events and experiences has recently received substantial support and attention from the proponents of the Predictive Processing (PP) and Active Inference framework in philosophy and computational neuroscience. In this paper we look at how perceptual experiences get off the ground from the outset, in utero. One basic yet overlooked aspect of current PP approaches is that human organisms first develop within another human body. Crucially, while not all humans will have the experience of being pregnant or carrying a baby, the experience of being carried and growing within another person’s body is universal. Specifically, we focus on the development of minimal selfhood in utero as a process co-embodiment and co-homeostasis, and highlight their close relationship. We conclude with some implications on several critical questions fuelling current debates on the nature of conscious experiences, minimal self and social cognition.     

An extended application ‘Brain Q’ processing EEG and MEG data of finger stimulation extended from ‘Zeffiro’ based on machine learning and signal processing

GoalTo apply signal processing and machine learning skills and knowledge in processing the EEG and MEG signal and further localize and evaluate the source of the finger stimulation.MethodsCognitive control is usually applied in information processing and behavioral response. In the preprocessing, baseline correction is implemented to analyze the pre-stimuli, combining ERP to mark the event related potential, studying the time-locked only behavior. Z-score transform, coherence and spec trum are calculated and analyzed in the functional connectivity analysis.In addition to the functional analysis, Bayes Optimizer evaluates the neuro imaging according to the hierarchical Bayes. The introduction of the application is described from both user and developer’s prospects. Results: Introduction of both user and developers aspects, on its modules from pre-processing, functional analysis and results visualization and evaluation is conducted with one specific clinical data case, including the correlation is higher especially on gamma band and the MVAR coherence on the whole source space depicting the relation between different regions, especially on somatosensory (compared by thalamus) when stimulated by finger activity, phase-lock property of the E/MEG signal and etc. Compared to a manual selection, the scaling parameter prediction can be improved with support vector machine (SVM). The evaluation results with Bayes Optimization, location prediction is superior in the somatosensory area and in the thalamus, the total reconstructed source space is larger, one of the realization of cognitive system comparing different kernels and classifiers. The SVM and discriminant classifier gives similar results evaluating the dipole localization and the parameter choice related as well to the shape parameter, noise level, hyperprior and etc.ConclusionApproaches of Brain Q are found to be suitable for pre-processing for the EEG and MEG data. The system is capable of functional analysis including coherence and spectral related computation. Machine learning techniques are conducted as well to analyze and evaluate the result of the dipole reconstruction and help to predict the better model parameters and the localization of the origin dipoles. A case on finger stimulation clinical data is conducted and the results of the analysis temporarily and spatially manifests its functionality for users and potential extensions for developers.     

发展性阅读障碍者的快速命名缺陷

快速命名任务是一种需要命名多个高熟悉项目的认知任务,尤其适合用来对成因复杂的发展性阅读障碍进行研究。许多研究者使用不同类型的快速命名任务发现,发展性阅读障碍者的快速命名缺陷在眼动过程表现为中央凹和副中央凹的加工困难,在认知过程中表现为抑制能力较差等。未来的研究中应该注意到快速命名缺陷的复杂性,采用多种方法相结合的方式来探究快速命名缺陷的本质,从而建立系统性的假说。     

情绪加工中杏仁核的效价特异性

杏仁核是情绪信息加工的关键脑区。近年来心理学和神经科学领域发现了杏仁核情绪加工的效价特异性现象,并且整体存在左侧杏仁核对正性情绪、右侧杏仁核对负性情绪以及双侧杏仁核负性偏好的特异性趋势,且受到材料突出特征、个体差异、任务条件的调节。未来可进一步探索注意对杏仁核情绪效价特异性的调节作用,探究动态情绪刺激加工时杏仁核的活动特点,考察心理障碍患者加工负性情绪时的杏仁核激活模式,并确定杏仁核的效价特异性在思维、计划、决策等高级认知过程中的表现。