fMRI delineation of working memory for emotional prosody in the brain: commonalities with the lexico-semantic emotion network

Decoding emotional prosody is crucial for successful social interactions, and continuous monitoring of emotional intent via prosody requires working memory. It has been proposed by Ross and others that emotional prosody cognitions in the right hemisphere are organized in an analogous fashion to propositional language functions in the left hemisphere. This study aimed to test the applicability of this model in the context of prefrontal cortex working memory functions. BOLD response data were therefore collected during performance of two emotional working memory tasks by participants undergoing fMRI. In the prosody task, participants identified the emotion conveyed in pre-recorded sentences, and working memory load was manipulated in the style of an N-back task. In the matched lexico-semantic task, participants identified the emotion conveyed by sentence content. Block-design neuroimaging data were analyzed parametrically with SPM5. At first, working memory for emotional prosody appeared to be right-lateralized in the PFC, however, further analyses revealed that it shared much bilateral prefrontal functional neuroanatomy with working memory for lexico-semantic emotion. Supplementary separate analyses of males and females suggested that these language functions were less bilateral in females, but their inclusion did not alter the direction of laterality. It is concluded that Ross et al.'s model is not applicable to prefrontal cortex working memory functions, that evidence that working memory cannot be subdivided in prefrontal cortex according to material type is increased, and that incidental working memory demands may explain the frontal lobe involvement in emotional prosody comprehension as revealed by neuroimaging studies. (c) 2007 Elsevier Inc. All rights reserved.

Age-related decline in the ability to decode emotional prosody: primary or secondary phenomenon?

Emotion processing deficits can cause catastrophic damage to a person's ability to interact socially. While it is known that older adults have difficulty identifying facial emotions, it is still not clear whether this difficulty extends to identification of the emotion conveyed by prosody. This study investigated whether the ability of older adults to decode emotional prosody falls below that of young adults after controlling for loss of hearing sensitivity and key features of cognitive ageing. Apart from frontal lobe load, only verbal IQ was associated with the age-related reduction in performance displayed by older participants, but a notable deficit existed after controlling for its effects. It is concluded that older adults may indeed have difficulty deducing the emotion conveyed by prosody, and that while this difficulty can be exaggerated by some aspects of cognitive ageing, it is primary in origin.

Reversing the emotional Stroop effect reveals that it is not what it seems: the role of fast and slow components

The relative contributions of slow and fast (online) components in a modified emotional Stroop task were evaluated. The slow component, neglected in previous research, was shown to lead to the prediction of a reversed emotional intrusion effect using pseudorandomly mixed negative and neutral stimuli. This prediction was supported in Experiments 1 and 2. In Experiments 3 and 4, a new paradigm was developed that allowed a more direct observation of the nature of disruptive effects from negative stimuli. The results provided a clear demonstration of the presence of the slow component. The fast component, which has generally been assumed to be the source of the interference, was shown, in fact, to have little or no role in the disruption.

Processing of faces and emotional expressions in infants at risk of social phobia

Individuals with social phobia display social information processing biases yet their aetiological significance is unclear. Infants of mothers with social phobia and control infants' responses were assessed at 10 days, 10 and 16 weeks, and 10 months to faces versus non-faces, variations in intensity of emotional expressions, and gaze direction. Infant temperament and maternal behaviours were also assessed. Both groups showed a preference for faces over non-faces at 10 days and 10 weeks, and full faces over profiles at 16 weeks; they also looked more to high vs. low intensity angry faces at 10 weeks, and fearful faces at 10 months; however, index infants' initial orientation and overall looking to high-intensity fear faces was relatively less than controls at 10 weeks. This was not explained by infant temperament or maternal behaviours. The findings suggest that offspring of mothers with social phobia show processing biases to emotional expressions in infancy.

Stabilizing swarm intelligence search via positive feedback resource allocation

A novel Swarm Intelligence method for best-fit search, Stochastic Diffusion Search, is presented capable of rapid location of the optimal solution in the search space. Population based search mechanisms employed by Swarm Intelligence methods can suffer lack of convergence resulting in ill defined stopping criteria and loss of the best solution. Conversely, as a result of its resource allocation mechanism, the solutions SDS discovers enjoy excellent stability.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.

A design for business intelligence service in demand driven supply chain management

This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

A swarm intelligence method for feature tracking in AMV derivation

Feature tracking is a key step in the derivation of Atmospheric Motion Vectors (AMV). Most operational derivation processes use some template matching technique, such as Euclidean distance or cross-correlation, for the tracking step. As this step is very expensive computationally, often shortrange forecasts generated by Numerical Weather Prediction (NWP) systems are used to reduce the search area. Alternatives, such as optical flow methods, have been explored, with the aim of improving the number and quality of the vectors generated and the computational efficiency of the process. This paper will present the research carried out to apply Stochastic Diffusion Search, a generic search technique in the Swarm Intelligence family, to feature tracking in the context of AMV derivation. The method will be described, and we will present initial results, with Euclidean distance as reference.