Assessment Centre Observation Procedures: An Experimental Comparison of Traditional,Checklist and Coding Methods

Concern about the construct validity of assessment centre judgements has led to calls for research into observers’ cognitive processes. In an experiment comparing the Traditional observation procedure against use of a Behavioural Checklist and of Behavioural Coding, six outcome variables were examined. The methods were found to yield similar outcomes in terms of accuracy of judgement, accuracy of written evidence, correlation between dimension ratings, and attitude toward the method employed. However, significant between-method differences were observed in variability between observers and in their willingness to recommend a procedure. It is argued that Behavioural Coding has special merit in assessment centres; the method reduces the cognitive demands placed on assessors, and valuably structures their information-processing. Traditional objections to simultaneous observation and classification are shown to be inappropriate.     

Complex learning and information processing by pigeons: a critical analysis

Three models of conditional discrimination learning by pigeons are described: stimulus configuration learning, the multiple-rule model, and concept learning. A review of the literature reveals that true concept learning is not characteristic of the behavior of pigeons in matching-to-sample, oddity-from-sample, or symbolic matching studies. Instead, pigeons learn a set of sample-specific S^D rules. Transfer of the discrimination to novel stimuli, at least along the hue dimension, is predicted by a “coding hypothesis”, which holds that pigeons make a unique, but usually unobserved response, R₁, to each sample, and that the comparison stimulus chosen depends on which R₁ was emitted in the presence of the sample. Convincing evidence is found that pigeons do code sample hues, but there is little evidence that allows one to infer that the “coding event” must have behavioral properties. Parameters of the conditional discrimination paradigm are identified, and it is shown that by appropriate parametric manipulation, a variety of analogous tasks may be generated for both human and animal subjects. The tasks make possible the comparative study of complex learning, attention, memory, and information processing, with the added advantage that behavior processes may be compared systematically across tasks.     

Statistical inference based on ranks

This paper develops a unified approach, based on ranks, to the statistical analysis of data arising from complex experimental designs. In this way we answer a major objection to the use of rank procedures as a major methodology in data analysis. We show that the rank procedures, including testing, estimation and multiple comparisons, are generated in a natural way from a robust measure of scale. The rank methods closely parallel the familiar methods of least squares, so that estimates and tests have natural interpretations.This research was supported in part by grant MCS76-07292 from the National Science Foundation.     

群体面孔情绪的整体编码及其影响因素

当面孔以群体形式出现,认知神经系统会自动整合情绪信息提取平均情绪,此过程被称为群体面孔情绪的整体编码。探讨其与低水平整体表征的分离,与个体表征的关系及神经活动特点是揭示其加工机制的关键,但目前尚未形成系统性模型。未来应综合利用眼动、神经电生理和脑成像技术,结合注意、记忆及社会线索进一步拓展对其认知神经机制和影响因素的研究,同时关注具有认知情感障碍的特殊人群,并从毕生发展的角度探索其发展轨迹。     

A parametric characterization of mean–variance efficient solutions for general feasible action sets

In this paper we show how the mean–variance efficient solution problem may be converted to a parametric efficient solution problem with objective functions affine in the mean and second moment of the random variable of concern. Some potential uses are considered, the relationship with some other work is examined and two potential applications are given. © 1998 John Wiley & Sons, Ltd.     

情绪对联合行动中共同表征能力的影响机制

采用联合Simon任务通过3个实验探究不同情绪维度对联合任务中共同表征能力的影响机制。实验1a、1b分别考察在高、低唤醒度条件下不同效价对个体共同表征能力的影响; 实验2在此基础上进一步探索动机维度在其中的作用。结果发现：无论效价高低, 高唤醒度都是提高个体共同表征能力的关键因素, 且动机强度在其中起一定调节作用; 而在低唤醒度条件下, 高效价会起一定补偿作用。上述结果很好地支持了参照编码假说, 也澄清了情绪不同维度对联合动作表征的影响机制。     

Generative models, brain function and neuroimaging

The representational capacity and inherent function of any neuron, neuronal population or cortical area in the brain is dynamic and context-sensitive. Functional integration, or interactions among brain systems, that employ driving (bottom up) and backward (top-down) connections, mediate this adaptive and contextual specialisation. A critical consequence is that neuronal responses, in any given cortical area, can represent different things at different times. This can have fundamental implications for the design of brain imaging experiments and the interpretation of their results. Our arguments are developed under generative models of brain function, where higher-level systems provide a prediction of the inputs to lower-level regions. Conflict between the two is resolved by changes in the higher-level representations, which are driven by the ensuing error in lower regions, until the mismatch is "cancelled". From this perspective the specialisation of any region is determined both by bottom-up driving inputs and by top-down predictions. Specialisation is therefore not an intrinsic property of any region but depends on both forward and backward connections with other areas. Because the latter have access to the context in which the inputs are generated they are in a position to modulate the selectivity or specialisation of lower areas. The implications for classical models (e.g., classical receptive fields in electrophysiology, classical specialisation in neuroimaging and connectionism in cognitive models) are severe and suggest these models may provide incomplete accounts of real brain architectures. Here we focus on the implications for cognitive neuroscience in the context of neuroimaging.     

A global optimization approach for generating efficient points for multiobjective concave fractional programs

In this article, we present a global optimization approach for generating efficient points for multiobjective concave fractional programming problems. The main work of the approach involves solving an instance of a concave multiplicative fractional program (W̄). Problem (W̄) is a global optimization problem for which no known algorithms are available. Therefore, to render the approach practical, we develop and validate a branch and bound algorithm for globally solving problem (W̄). To illustrate the performance of the global optimization approach, we use it to generate efficient points for a sample multiobjective concave fractional program. Copyright © 2006 John Wiley & Sons, Ltd.     

Functional integration and the mind

Different cognitive functions recruit a number of different, often overlapping, areas of the brain. Theories in cognitive and computational neuroscience are beginning to take this kind of functional integration into account. The contributions to this special issue consider what functional integration tells us about various aspects of the mind such as perception, language, volition, agency, and reward. Here, I consider how and why functional integration may matter for the mind; I discuss a general theoretical framework, based on generative models, that may unify many of the debates surrounding functional integration and the mind; and I briefly introduce each of the contributions.     

Contextual learning induces an increase in the number of hippocampal CA1 neurons expressing high levels of BDNF

We examined behaviorally induced expression of brain-derived neurotrophic factor (BDNF) in area CA1 of the hippocampus. Sprague-Dawley rats were trained in a contextual fear conditioning (CFC) task, sacrificed 4h later, and their brains were processed for immunohistochemistry. We found distinctively high levels of BDNF immunoreactivity in a small number ( approximately 1%) of CA1 neurons in untrained animals. The number of these exceptional neurons, which are identified as BDNF(++) in this study, was increased by up to approximately 3% after CFC. This increase was blocked in the presence of a memory-impairing dose of a NMDA receptor antagonist (MK801 0.3 mg/kg, i.p.) given 30 min prior to training. The BDNF signal intensity in BDNF(++) neurons correlated with that of surrounding glutamic acid decarboxylase (GAD) 65. This correlation between GAD65 and BDNF signal intensities suggests that BDNF upregulation was associated with increased signaling via inhibitory GABAergic synapses that would lessen further intervening neuronal activity. Our observation that neurons which upregulate BDNF expression following a learning experience are rich in GAD65-enriched afferent synapses suggests that these neurons may have distinct roles in memory consolidation.