The topographic distribution of the magnetic P100M to full- and half-field stimulation

Visual evoked magnetic responses were recorded to full-field and left and right half-field stimulation with three check sizes (70′, 34′ and 22′) in five normal subjects. Recordings were made sequentially on a 20-position grid (4 × 5) based on the inion, by means of a single-channel direct current-Superconducting Quantum Interference Device second-order gradiometer. The topographic maps were consistent on the same subjects recorded 2 months apart. The half-field responses produced the strongest signals in the contralateral hemisphere and were consistent with the cruciform model of the calcarine fissure. Right half fields produced upper-left-quadrant outgoing fields and lower-left-quadrant ingoing fields, while the left half field produced the opposite response. The topographic maps also varied with check size, with the larger checks producing positive or negative maximum position more anteriorly than small checks. In addition, with large checks the full-field responses could be explained as the summation of the two half fields, whereas full-field responses to smaller checks were more unpredictable and may be due to sources located at the occipital pole or lateral surface. In addition, dipole sources were located as appropriate with the use of inverse problem solutions. Topographic data will be vital to the clinical use of the visual evoked field but, in addition, provides complementary information to visual evoked potentials, allowing detailed studies of the visual cortex. © 1992 Kluwer Academic Publishers.

Negative data in DEA:a directional distance approach applied to bank branches

This paper is drawn from the use of data envelopment analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but apart from some exceptions, traditional DEA models have hitherto been restricted to non-negative data. We report on the development of a model to handle unrestricted data in a DEA framework and illustrate the use of this model on data from the bank concerned.

Ethnic diversity as a multilevel construct:the combined effects of dissimilarity, group diversity, and societal status on learning performance in work groups

The authors present a model of the multilevel effects of diversity on individual learning performance in work groups. For ethnically diverse work groups, the model predicts that group diversity elicits either positive or negative effects on individual learning performance, depending on whether a focal individual’s ethnic dissimilarity from other group members is high or low. By further considering the societal status of an individual’s ethnic origin within society (Anglo versus non-Anglo for our U.K. context), the authors hypothesize that the model’s predictions hold more strongly for non-Anglo group members than for Anglo group members. We test this model with data from 412 individuals working on a 24-week business simulation in 87 four- to seven-person groups with varying degrees of ethnic diversity. Two of the three hypotheses derived from the model received full support and one hypothesis received partial support. Implications for theory development, methods, and practice in applied group diversity research are discussed.

Intentional forgetting in depressed states

The aim of this thesis was to extend previous research on intentional forgetting in depressed states. The first experiment used the think/no-think paradigm, and found that although dysphoric individuals were significantly worse at suppressing emotional (positive and negative) words than non-dysphoric individuals, both groups were unsuccessful at direct thought suppression. However, there was no effect of rumination on dysphoric individuals' ability to intentionally forget material. Furthermore, there was also no group differences in attentional measures of Stroop and IDEO. The second experiment involved modifying the TNT task, by including the use of substitute words in the suppression phase, in order to determine whether recalling substitute words during suppression would increase the level of forgetting. The findings from the study revealed that both dysphoric and non-dysphoric individuals were successful at intentionally forgetting neutral words using a thought substitution strategy. However, both groups were impaired at suppressing words in the direct thought substitution condition. The third experiment investigated the influence of thought substitution on intentional forgetting of emotional words in dysphoria. The study replicated experiment two, but used emotional (i.e. positive and depression-relevant) words instead of neutral words. The study found that dysphoric individuals were still impaired in their ability to suppress emotional material. Furthermore, dysphoric individuals were recalling significantly more depression­ relevant respond and previously-suppressed words. The fourth experiment examined the role of executive control in intentional forgetting. In the study, dysphoric and non­ dysphoric participants were categorised as having good or poor executive control based on their scores on the operation span with words task (OSPAN). The study found that non-dysphoric individuals with good control demonstrated successful suppression. However, dysphoric individuals with good control were unsuccessful at suppression. The fifth experiment investigated whether experimentally induced changes in mood state would alter an individual's ability to intentionally forget emotional material. Non-dysphoric healthy participants were given a positive or negative autobiographical memory and music mood induction. They completed two modified think/no-think tasks, one prior to the mood induction and one after the mood induction. The study found that transient negative mood state impaired intentional forgetting of depression-relevant material. Summary: Taken together, the findings suggest that individuals in a depressed mood are impaired in their ability to intentionally forget emotional material, even with the use of a thought substitution strategy. Furthermore, the findings implicate poor executive control and negative mood state in impaired intentional forgetting. An important theme emerging from the findings was the role of an inhibitory mechanism in intentional forgetting. The findings reported in this thesis suggest that thought substitution involves engaging an inhibitory control mechanism that contributes to successful intentional forgetting. The findings have clear implications on depressed individuals everyday functioning, and suggest that even with the presence of effective distraction, dysphoric indivduals are imapired in their ability to suppress emotional material. Furthermore, it is suggested that impaired intentional forgetting of emotional material may contribute to the maintenance of depressed mood, and could potentially worsen ongoing depression.

The interactive effect of workplace stressors and mood on creativity and implementation activities: a dual level approach

This thesis analyses the impact of workplace stressors and mood on innovation activities. Based on three competitive frameworks offered by cognitive spreading activation theory, mood repair perspective, and mood-as-information theory, different sets of predictions are developed. These hypotheses are tested in a field study involving 41 R&D teams and 123 individual R&D workers, and in an experimental study involving 54 teams of students. Results of the field study suggest that stressors and mood interact to predict innovation activities in such a way that with increasing stressors a high positive ( or negative) mood is more detrimental to innovation activities than a low positive (or negative) mood, lending support to the mood repair perspective. These effects are found for both individuals and teams. In the experimental study this effect is replicated and potential boundary conditions and mediators are tested. In addition, this thesis includes the development of an instrument to assess creativity and implementation activities within the realm of task-related innovative performance.

Income and poverty in a developing economy

We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the income from trade, which may be positive or negative, is proportional to the trader's income. These assumptions lead to a Langevin model with multiplicative noise, from which we derive a Fokker-Planck (FP) equation for the income probability density function (IPDF) and its variation in time. We find that high earners have a power law income distribution while the low-income groups have a Levy IPDF. Comparing our analysis with the Indian survey data (obtained from the world bank website: http://go.worldbank.org/SWGZB45DN0) taken over many years we obtain a near-perfect data collapse onto our model's equilibrium IPDF. Using survey data to relate the IPDF to actual food consumption we define a poverty index (Sen A. K., Econometrica., 44 (1976) 219; Kakwani N. C., Econometrica, 48 (1980) 437), which is consistent with traditional indices, but independent of an arbitrarily chosen "poverty line" and therefore less susceptible to manipulation. Copyright © EPLA, 2010.

We want drama! The effect of online conflict on social capital in online communities of consumption

Online communities (OC) are an expanding social phenomenon gaining increasing interest from marketing practitioners. Community managers thus aim to increase OCs’ social capital. Diversity of individuals interacting in OCs provokes a lot of conflict. However, the influence of online conflict on OCs’ social capital is not clear as research indicates both positive and negative effects. The research aims to explain these contradictory effects by conceptualizing conflict as drama and developing a typology of online conflict. Based on netnographic investigations of a forum, four types of conflicts are thus distinguished depending on valence of emotions and the type of members involved. The research contributes to literature on OC dynamics and is of particular interest for community managers working in any company or organization.

Negative brand personality:the construct, its antecedents and outcome variables

By evolving brands and building on the importance of self-expression, Aaker (1997) developed the brand personality framework as a means to understand brand-consumer relationships. The brand personality framework captures the core values and characteristics described in human personality research in an attempt to humanize brands. Although influential across many streams of brand personality research, the current conceptualization of brand personality only offers a positively-framed approach. To date, no research, both conceptually and empirically, has thoroughly incorporated factors reflective of Negative Brand Personality, despite the fact that almost all researchers in personality are in agreement that factors akin to Extraversion (positive) and Neuroticism (negative) should be in a comprehensive personality scale to accommodate consumers’ expressions. As a result, the study of brand personality is only half complete since the current research trend is to position brand personality under brand image. However, with the brand personality concept being confused with brand identity at the empirical stage, factors reflective of Negative Brand Personality have been neglected. Accordingly, this thesis extends the current conceptualization of brand personality by demarcating the existing typologies of desirable brand personality and incorporating the characteristics reflective of consumers’ discrepant self-meaning to provide a more complete understanding of brand personality. However, it is not enough to interpret negative factors as the absence of positive factors. Negative factors reflect consumers’ anxious and frustrated feelings. Therefore, this thesis contributes to the current conceptualization of brand personality by, firstly, presenting a conceptual definition of Negative Brand Personality in order to provide a theoretical basis for the development of a Negative Brand Personality scale, then, secondly, identifying what constitutes Negative Brand Personality and to what extent consumers’ cognitive dissonance explains the nature of Negative Brand Personality, and, thirdly, ascertaining the impact Negative Brand Personality has on attitudinal constructs, namely: Negative Attitude, Detachment, Brand Loyalty and Satisfaction, which have proven to predict behaviors such as choice and (re-)purchasing. In order to deliver on the three main contributions, two comprehensive studies were conducted to a) develop a valid, parsimonious, yet relatively short measure of Negative Brand Personality, and b) ascertain how the Negative Brand Personality measure behaves within a network of related constructs. The mixed methods approach, grounded in theoretical and empirical development, provides evidence to suggest that there are four factors to Negative Brand Personality and, tested through use of a structural equation modeling technique, that these are influenced by Brand Confusion, Price Unfairness, Self- Incongruence and Corporate Hypocrisy. Negative Brand Personality factors mainly determined Consumers Negative Attitudes and Brand Detachment. The research contributes to the literature on brand personality by improving the consumer-brand relationship by means of engaging in a brandconsumer conversation in order to reduce consumers’ cognitive strain. The study concludes with a discussion on the theoretical and practical implications of the findings, its limitations, and potential directions for future research.

Application of Naïve Bayesian sequential analysis to primary care optometry

The objective of this study was to investigate the effects of circularity, comorbidity, prevalence and presentation variation on the accuracy of differential diagnoses made in optometric primary care using a modified form of naïve Bayesian sequential analysis. No such investigation has ever been reported before. Data were collected for 1422 cases seen over one year. Positive test outcomes were recorded for case history (ethnicity, age, symptoms and ocular and medical history) and clinical signs in relation to each diagnosis. For this reason only positive likelihood ratios were used for this modified form of Bayesian analysis that was carried out with Laplacian correction and Chi-square filtration. Accuracy was expressed as the percentage of cases for which the diagnoses made by the clinician appeared at the top of a list generated by Bayesian analysis. Preliminary analyses were carried out on 10 diagnoses and 15 test outcomes. Accuracy of 100% was achieved in the absence of presentation variation but dropped by 6% when variation existed. Circularity artificially elevated accuracy by 0.5%. Surprisingly, removal of Chi-square filtering increased accuracy by 0.4%. Decision tree analysis showed that accuracy was influenced primarily by prevalence followed by presentation variation and comorbidity. Analysis of 35 diagnoses and 105 test outcomes followed. This explored the use of positive likelihood ratios, derived from the case history, to recommend signs to look for. Accuracy of 72% was achieved when all clinical signs were entered. The drop in accuracy, compared to the preliminary analysis, was attributed to the fact that some diagnoses lacked strong diagnostic signs; the accuracy increased by 1% when only recommended signs were entered. Chi-square filtering improved recommended test selection. Decision tree analysis showed that accuracy again influenced primarily by prevalence, followed by comorbidity and presentation variation. Future work will explore the use of likelihood ratios based on positive and negative test findings prior to considering naïve Bayesian analysis as a form of artificial intelligence in optometric practice.

Gender differences in the sensitivity to negative stimuli:cross-modal affective priming study

Background: There is evidence showing that men and women differ with regard to the processing of emotional information. However, the mechanisms behind these differences are not fully understood. Method: The sample comprised of 275 (167 female) right-handed, healthy participants, recruited from the community. We employed a customized affective priming task, which consisted of three subtests, differing in the modality of the prime (face, written word, and sound). The targets were always written words of either positive or negative valence. The priming effect was measured as reaction time facilitation in conditions where both prime and target were emotional (of the same positive or negative valence) compared with conditions where the emotional targets were preceded by neutral primes. Results: The priming effect was observed across all three modalities, with an interaction of gender by valence: the priming effect in the emotionally negative condition in male participants was stronger compared with females. This was accounted for by the differential priming effect within the female group where priming was significantly smaller in the emotionally negative conditions compared with the positive conditions. The male participants revealed a comparable priming effect across both the emotionally negative and positive conditions. Conclusion: Reduced priming in negative conditions in women may reflect interference processes due to greater sensitivity to negative valence of stimuli. This in turn could underlie the gender-related differences in susceptibility to emotional disorders.

Cross-national differences in e-WOM influence

Purpose: This paper aims to present a cross-national study that investigates changes in purchase intentions of UK versus Chinese consumers following exposure to successive e-WOM comments in the form of positive and negative user reviews for experience versus search products. Design/methodology/approach: A 2(e-WOM valence and order: negative versus positive most recent)×2(product type: experience versus search)×3(purchase intentions at t 1, t 2, t 3) repeated-measures factorial design is used to test a set of hypotheses developed from the literature. Findings: Chinese consumers are susceptible to recent e-WOM comments regardless of their valence, while UK consumers anchor on negative information regardless of the order in which it is acquired. This holds particularly for experience products. Originality/value: This cross-national study contributes to the scarce literature on the impact of e-WOM on consumer purchase decisions by comparing UK and Chinese consumers. The authors suggest that culture moderates the development of product evaluations following exposure to e-WOM. © Emerald Group Publishing Limited.

Contextual semantics for sentiment analysis of Twitter

Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.

Emotions and a Prior Knowledge Representation in Artificial General Intelligence

In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.

Age-related striatal BOLD changes without changes in behavioral loss aversion

Loss aversion (LA), the idea that negative valuations have a higher psychological impact than positive ones, is considered an important variable in consumer research. The literature on aging and behavior suggests older individuals may show more LA, although it is not clear if this is an effect of aging in general (as in the continuum from age 20 and 50 years), or of the state of older age (e.g., past age 65 years). We also have not yet identified the potential biological effects of aging on the neural processing of LA. In the current study we used a cohort of subjects with a 30 year range of ages, and performed whole brain functional MRI (fMRI) to examine the ventral striatum/nucleus accumbens (VS/NAc) response during a passive viewing of affective faces with model-based fMRI analysis incorporating behavioral data from a validated approach/avoidance task with the same stimuli. Our a priori focus on the VS/NAc was based on (1) the VS/NAc being a central region for reward/aversion processing; (2) its activation to both positive and negative stimuli; (3) its reported involvement with tracking LA. LA from approach/avoidance to affective faces showed excellent fidelity to published measures of LA. Imaging results were then compared to the behavioral measure of LA using the same affective faces. Although there was no relationship between age and LA, we observed increasing neural differential sensitivity (NDS) of the VS/NAc to avoidance responses (negative valuations) relative to approach responses (positive valuations) with increasing age. These findings suggest that a central region for reward/aversion processing changes with age, and may require more activation to produce the same LA behavior as in younger individuals, consistent with the idea of neural efficiency observed with high IQ individuals showing less brain activation to complete the same task.

SentiCircles for contextual and conceptual semantic sentiment analysis of Twitter

Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words' sentiment orientation (positive, neural, negative) and/or sentiment strengths could change depending on context and targeted entities. In this paper we present SentiCircle; a novel lexicon-based approach that takes into account the contextual and conceptual semantics of words when calculating their sentiment orientation and strength in Twitter. We evaluate our approach on three Twitter datasets using three different sentiment lexicons. Results show that our approach significantly outperforms two lexicon baselines. Results are competitive but inconclusive when comparing to state-of-art SentiStrength, and vary from one dataset to another. SentiCircle outperforms SentiStrength in accuracy on average, but falls marginally behind in F-measure. © 2014 Springer International Publishing.