Ipsilateral Loudness Adaptation Over Multiple Intensity Levels

Three mirror tracing experiments were conducted to investigate the connection between perception and motor behavior. In the first experiment, some subjects traced a hex-maze, other subjects traced a hex-maze after observing a model trace, others traced a hex-maze after reading instructions on mirror images, and others traced a hex-maze after having observed a model and heard the instructions. There were no significant differences between the groups' error scores, but their time scores differed significantly, although not always in the predicted direction. In Experiment 2, the subjects were to trace selected letters of the alphabet. Error scores for the second experiment did not differ much from those for the first experiment. In Experiment 3, the experimenter gave each subject commands for the correct directions of movement, using the subject's body as a frame of reference. There was little improvement in motor performance. These results suggest that the visual information presented in the mirror captured the subjects' attention and blocked their motor tracing program.     

多感觉整合范式中潜在的跨通道转换效应

大脑可以对来自不同感觉通道的信息进行处理与整合。与单一感觉通道相比, 个体对同时呈现在不同感觉通道的目标信号的响应会更快。对于这种现象的一种主要理论解释是共同激活模型, 该模型认为来自不同通道的刺激在特定的脑区汇聚整合, 比如顶叶内沟、颞上沟和前额叶皮层区域。整合后的信号强度更大, 可以更快地触发反应, 但是信号的整合发生在认知加工的哪一阶段目前尚未有明确结论。当个体对出现在不同感觉通道之间的任务转换进行加工时, 产生与感觉通道相关的任务转换的损失小于跨感觉通道转换损失与任务转换损失的总和, 这为与感觉通道相关的转换代价来源于任务设置的惯性和干扰提供了证据。而在单通道和多通道之间发生转换时, 跨通道转换代价会减小甚至消失, 这是由于同时发生的多感觉整合抵消了一部分损失, 这种现象支持了共同激活模型理论。然而, 多感觉信号整合对任务转换的神经加工过程产生怎样的影响并不清楚, 在未来的研究中可以把多感觉整合范式同经典的任务转换范式结合改进, 进而确定跨通道转换的加工机制和多感觉信号整合的发生阶段。     

Call combinations in monkeys: compositional or idiomatic expressions?

Syntax is widely considered the feature that most decisively sets human language apart from other natural communication systems. Animal vocalisations are generally considered to be holistic with few examples of utterances meaning something other than the sum of their parts. Previously, we have shown that male putty-nosed monkeys produce call series consisting of two call types in response to different events. They can also be combined into short sequences that convey a different message from those conveyed by either call type alone. Here, we investigate whether ‘pyow-hack’ sequences are compositional in that the individual calls contribute to their overall meaning. However, the monkeys behaved as if they perceived the sequence as an idiomatic expression rather than decoding the sequence. Nonetheless, while this communication system lacks the generative power of syntax it enables callers to increase the number of messages that can be conveyed by a small and innate call repertoire.     

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.     

Characterizing perceptual learning with external noise

Performance in perceptual tasks often improves with practice. This effect is known as ‘perceptual learning,’ and it has been the source of a great deal of interest and debate over the course of the last century. Here, we consider the effects of perceptual learning within the context of signal detection theory. According to signal detection theory, the improvements that take place with perceptual learning can be due to increases in internal signal strength or decreases in internal noise. We used a combination of psychophysical techniques (external noise masking and double-pass response consistency) that involve corrupting stimuli with externally added noise to discriminate between the effects of changes in signal and noise as observers learned to identify sets of unfamiliar visual patterns. Although practice reduced thresholds by as much as a factor of 14, internal noise remained virtually fixed throughout training, indicating learning served to predominantly increase the strength of the internal signal. We further examined the specific nature of the changes that took place in signal strength by correlating the externally added noise with observer’s decisions across trials (response classification). This technique allowed us to visualize some of the changes that took place in the linear templates used by the observers as learning occurred, as well as test the predictions of a linear template-matching model. Taken together, the results of our experiments offer important new theoretical constraints on models of perceptual learning.     

情绪研究中的一种整体观——弗里达群集理论述评

情绪的激起是情绪心理学中一个基本的问题。对这一问题 ,前人有很多的争议。在对前人观点进行概述的基础上 ,重点介绍了美国情绪心理学家弗里达 (Frjida ,N .H)的“情绪是由群集引发的”这一观点 ,并认为他用一种整体的观点来看待情绪的激起 ,对以后的情绪研究有一定的启示意义。     

Selection history-driven signal suppression

ABSTRACT

The control of attention is influenced by current goals, physical salience, and selection history. Under certain conditions, physically salient stimuli can be strategically suppressed below baseline levels, facilitating visual search for a target. It is unclear whether such signal suppression is a broad mechanism of selective information processing that extends to other sources of attentional priority evoked by task-irrelevant stimuli, or whether it is particular to physically salient perceptual signals. Using eye movements, in the present study we highlight a case where a former-target-colour distractor facilitates search for a target on a large percentage of trials. Our findings provide evidence that the principle of signal suppression extends to other sources of attentional priority beyond physical salience, and that selection history can be leveraged to strategically guide attention away from a stimulus.