试论康德心理学思想及其对当代的影响

康德著作中蕴含着丰富的心理学思想,其在继承沃尔夫理性心理学与经验心理学二分的基础上,通过批评理性心理学,消解了我思的主体地位,为解决二元论问题做出了重要努力;通过批评经验心理学,指明了心理学在成长为一门科学过程中必须面对的诸多问题。新康德主义在继承并改造康德思想的过程中,发展出一系列影响深远的心理学理论;认知心理学的重要代表人物皮亚杰基于对康德思想独具特色的把握,提出了发生认识论;而当代认知科学的图式理论,则完全是建基于对康德经验图式理论框架的全面继承上。     

On the empirical indistinguishability of knowledge structures

In recent years a number of articles have focused on the identifiability of the basic local independence model. The identifiability issue usually concerns two model parameter sets predicting an identical probability distribution on the response patterns. Both parameter sets are applied to the same knowledge structure. However, nothing is known about cases where different knowledge structures predict the same probability distribution. This situation is referred to as ʻempirical indistinguishabilityʼ between two structures and is the main subject of the present paper. Empirical indistinguishability is a stronger form of unidentifiability, which involves not only the parameters, but also the structural and combinatorial properties of the model. In particular, as far as knowledge structures are concerned, a consequence of empirical indistinguishability is that the existence of certain knowledge states cannot be empirically established. Most importantly, it is shown that model identifiability cannot guarantee that a certain knowledge structure is empirically distinguishable from others. The theoretical findings are exemplified in a number of different empirical scenarios.     

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.     

RELIGIOUS ETHICS AND EMPIRICAL ETHICS

In recent decades, cognitive and behavioral scientists have learned a great deal about how people think and behave. On the most general level, there is a basic consensus that many judgments, including ethical judgments, are made by intuitive, even unconscious, impulses. This basic insight has opened the door to a wide variety of more particular studies that investigate how judgments are influenced by group identity, self‐conception, emotions, perceptions of risk, and many other factors. When these forms of research engage ethical issues, they are sometimes called empirical ethics. This essay argues that the field of religious ethics would benefit from a more robust engagement with empirical ethics than it has thus far undertaken. In doing so, it offers a brief account of how issues of moral psychology and moral anthropology have been treated in religious ethics, and it highlights ways that the scientific findings challenge some prevailing norms in religious ethics. It ends by suggesting avenues by which religious ethics research could productively engage empirical ethics.     

Information matrix estimation procedures for cognitive diagnostic models

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance.     

Simple discrimination in stingless bees (Melipona quadrifasciata): Probing for select‐ and reject‐stimulus control

Simple and conditional discrimination training may produce various types of controlling relations. Responses may be controlled primarily by the positive stimulus (select–control relation) or by the negative stimulus (reject–control relation; the subject excludes the negative stimulus and chooses the positive). Bees learn to respond in simple and conditional discriminations. However, no study has searched for reject–control responding in Melipona bees. We trained Melipona quadrifasciata on a simple discrimination task (S+ vs. S‐; e.g., blue vs. yellow) and then probed for stimulus control with two types of probe trials, S+ versus a new stimulus (Select–control probes) and S‐ versus a new stimulus (Reject–control probes). For Group Different, a new‐stimulus color (e.g., white) was used in one type of probe and another color (e.g., black) was used in the other type. For Group Same, a single new‐stimulus color was used in both types of probes. On Select probes, the bees always preferred S+ to the new stimulus. On Reject probes, results were mixed. Depending on the colors used in training and probing, bees responded to both stimuli, and even preferred the S‐. The data suggest no control by the negative function of the S‐ and support the select‐stimulus control hypothesis of responding.     

Implications of an initial empirical victory for the truth of the theory and additional empirical victories

Psychologists take two propositions for granted. Specifically, empirical verification of predictions derived from a theory (a) support that the theory is more likely to be true and (b) support that additional predictions derived from the theory have an increased probability of being sustained if subjected to empirical testing. In contrast, I argue that both propositions depend strongly on whether auxiliary assumptions are taken into account. When auxiliary assumptions are not taken into account, the first proposition is valid but the second is not. When auxiliary assumptions are taken into account, the first proposition is not valid, and the second proposition encounters additional problems. I use Venn diagrams and Bayesian principles to demonstrate these conclusions.     

Empirical Propositions and the Change of Language-Games

People unavoidably provide reasons for their words and deeds when reasoning in a language-game.Wittgenstein thinks that when people in different language-games argue with one other,they insist on adopting a doubtful attitude toward the reasons provided by the other side.His use of the term "language-game" here is a metaphor,and implies that people in different cultures can scarcely reason with one another.Indeed,according to Wittgenstein's consideration of concepts of logic in On Certainty,language-games are incompatible with one another because their internal logic and reasons are different from each other.However,in his discussion of empirical propositions Wittgenstein has also shown us the possibility that the intemal reasons of one language-game can transmit beyond its own borders and be valid in another language-game.     

Inferring hidden causal structure

We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a pattern of associations and interventions on a novel causal system. Given minimal training and no feedback, participants in Experiment 1 used causal graph notation to spontaneously draw structures containing one observed cause, one unobserved common cause, and two unobserved independent causes, depending on the pattern of associations and interventions they saw. We replicated these findings with less-informative training (Experiments 2 and 3) and a new apparatus (Experiment 3) to show that the pattern of data leads to hidden causal inferences across a range of prior constraints on causal knowledge.     

计算机化自适应测验中原始题项目参数的估计

计算机化自适应测验(Computerized Adaptive Testing, 简称CAT)其安全性面临着新的挑战, 小题库的安全更受威胁。如何建设一个大型、优质的题库成为CAT研究中一个非常重要的课题。目前CAT题库的建设存在一些问题, 如成本高且保密性较差。尤其是等值技术较复杂且锚题重复使用容易造成泄露。如能在实施CAT过程中插入未经过参数估计的项目(原始题), 同时对原始题项目参数进行估计, 这对建设大型、优质的CAT题库来说其意义是不言而喻的。本文基于1PLM和2PLM对此进行研究, 提出了原始题在线估计的新方法以及推导出了求区分度参数a迭代初值的计算公式。研究结果表明：无论是模拟研究还是实证研究, 原始题被作答的次数对项目参数估计结果都会产生不同的影响, 并且原始题作答人数越多项目参数估计精度也越高。