Investigating music tempo as a feedback mechanism for closed-loop BCI control

The feedback mechanism used in a brain-computer interface (BCI) forms an integral part of the closed-loop learning process required for successful operation of a BCI. However, ultimate success of the BCI may be dependent upon the modality of the feedback used. This study explores the use of music tempo as a feedback mechanism in BCI and compares it to the more commonly used visual feedback mechanism. Three different feedback modalities are compared for a kinaesthetic motor imagery BCI: visual, auditory via music tempo, and a combined visual and auditory feedback modality. Visual feedback is provided via the position, on the y-axis, of a moving ball. In the music feedback condition, the tempo of a piece of continuously generated music is dynamically adjusted via a novel music-generation method. All the feedback mechanisms allowed users to learn to control the BCI. However, users were not able to maintain as stable control with the music tempo feedback condition as they could in the visual feedback and combined conditions. Additionally, the combined condition exhibited significantly less inter-user variability, suggesting that multi-modal feedback may lead to more robust results. Finally, common spatial patterns are used to identify participant-specific spatial filters for each of the feedback modalities. The mean optimal spatial filter obtained for the music feedback condition is observed to be more diffuse and weaker than the mean spatial filters obtained for the visual and combined feedback conditions.

Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures

Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using noninvasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (N30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2- dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25–90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks

Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.

Advances in Discourse Studies

Methods of approaching the study of discourse have developed rapidly in the last ten years, influenced by a growing interdisciplinary spirit among linguistics and anthropology, sociology, cognitive and cultural psychology and cultural studies, as well as among established sub-fields within linguistics itself. Among the more recent developments are an increasing ‘critical’ turn in discourse analysis, a growing interest in historical, ethnographic and corpus-based approaches to discourse, more concern with the social contexts in which discourse occurs, the social actions that it is used to take and the identities that are constructed through it, as well as a revaluation of what counts as ‘discourse’ to include multi-modal texts and interaction. Advances in Discourse Studies brings together contributions from leading scholars in the field, investigating the historical and theoretical relationships between new advances in discourse studies and pointing towards new directions for the future of the discipline. Featuring discussion questions, classroom projects and recommended readings at the end of each section, as well as case studies illustrating each approach discussed, this is an invaluable resource for students of interdisciplinary discourse analysis.

Development and illustrative outputs of the Community Integrated Assessment System (CIAS), a multi-institutional modular integrated assessment approach for modelling climate change.

This paper describes the development and first results of the “Community Integrated Assessment System” (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the community of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers’ ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth’s climate system is provided.

A customizable multi-agent system for distributed data mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.

Requirements analysis for an e-government system to support multi-organisational collaborative groups

We present a conceptual architecture for a Group Support System (GSS) to facilitate Multi-Organisational Collaborative Groups (MOCGs) initiated by local government and including external organisations of various types. Multi-Organisational Collaborative Groups (MOCGs) consist of individuals from several organisations which have agreed to work together to solve a problem. The expectation is that more can be achieved working in harmony than separately. Work is done interdependently, rather than independently in diverse directions. Local government, faced with solving complex social problems, deploy MOCGs to enable solutions across organisational, functional, professional and juridical boundaries, by involving statutory, voluntary, community, not-for-profit and private organisations. This is not a silver bullet as it introduces new pressures. Each member organisation has its own goals, operating context and particular approaches, which can be expressed as their norms and business processes. Organisations working together must find ways of eliminating differences or mitigating their impact in order to reduce the risks of collaborative inertia and conflict. A GSS is an electronic collaboration system that facilitates group working and can offer assistance to MOCGs. Since many existing GSSs have been primarily developed for single organisation collaborative groups, even though there are some common issues, there are some difficulties peculiar to MOCGs, and others that they experience to a greater extent: a diversity of primary organisational goals among members; different funding models and other pressures; more significant differences in other information systems both technologically and in their use than single organisations; greater variation in acceptable approaches to solve problems. In this paper, we analyse the requirements of MOCGs led by local government agencies, leading to a conceptual architecture for an e-government GSS that captures the relationships between 'goal', 'context', 'norm', and 'business process'. Our models capture the dynamics of the circumstances surrounding each individual representing an organisation in a MOCG along with the dynamics of the MOCG itself as a separate community.

Suboptimal system recovery from communication loss in a multi-robot localization scenario using EKF algorithms

This paper describes a multi-robot localization scenario where, for a period of time, the robot team loses communication with one of the robots due to system error. In this novel approach, extended Kalman filter (EKF) algorithms utilize relative measurements to localize the robots in space. These measurements are used to reliably compensate "dead-com" periods were no information can be exchanged between the members of the robot group.

The mobility system of the multi-tasking rover (MTR)

Current and planned robotic rovers for space exploration are focused on science and correspondingly carry a science payload. Future missions will need robotic rovers that can demonstrate a wider range of functionality. This paper proposes an approach to offering this greater functionality by employing science and/or tool packs aboard a highly mobile robotic chassis. The packs are interchangeable and each contains different instruments or tools. The appropriate selection of science and/or tool packs enables the robot to perform a great variety of tasks either alone or in cooperation with other robots. The multi-tasking rover (MTR), thus conceived, provides a novel method for high return on investment. This paper describes the mobility system of the MTR and reports on initial experimental evaluation of the robotic chassis.

Minimising the latency induced by consistency control, within a large scale multi-user distributed virtual reality system

Where users are interacting in a distributed virtual environment, the actions of each user must be observed by peers with sufficient consistency and within a limited delay so as not to be detrimental to the interaction. The consistency control issue may be split into three parts: update control; consistent enactment and evolution of events; and causal consistency. The delay in the presentation of events, termed latency, is primarily dependent on the network propagation delay and the consistency control algorithms. The latency induced by the consistency control algorithm, in particular causal ordering, is proportional to the number of participants. This paper describes how the effect of network delays may be reduced and introduces a scalable solution that provides sufficient consistency control while minimising its effect on latency. The principles described have been developed at Reading over the past five years. Similar principles are now emerging in the simulation community through the HLA standard. This paper attempts to validate the suggested principles within the schema of distributed simulation and virtual environments and to compare and contrast with those described by the HLA definition documents.