Methods and Approaches for Characterizing Learning Related Changes Observed in functional MRI Data — A Review

Brain imaging data have so far revealed a wealth of information about neuronal circuits involved in higher mental functions like memory, attention, emotion, language etc. Our efforts are toward understanding the learning related effects in brain activity during the acquisition of visuo-motor sequential skills. The aim of this paper is to survey various methods and approaches of analysis that allow the characterization of learning related changes in fMRI data. Traditional imaging analysis using the Statistical Parametric Map (SPM) approach averages out temporal changes and presents overall differences between different stages of learning. We outline other potential approaches for revealing learning effects such as statistical time series analysis, modelling of haemodynamic response function and independent component analysis. We present example case studies from our visuo-motor sequence learning experiments to describe application of SPM and statistical time series analyses. Our review highlights that the problem of characterizing learning induced changes in fMRI data remains an interesting and challenging open research problem

A Multi-disciplinary Approach to the Investigation of Aspects of Serial Order in Cognition

Serial order processing or Sequence processing underlies many human activities such as speech, language, skill learning, planning, problem solving, etc. Investigating the\ud neural bases of sequence processing enables us to understand serial order in cognition and helps us building intelligent devices. In the current paper, various\ud cognitive issues related to sequence processing will be discussed with examples. Some of the issues are: distributed versus local representation, pre-wired versus\ud adaptive origins of representation, implicit versus explicit learning, fixed/flat versus hierarchical organization, timing aspects, order information embedded in sequences, primacy versus recency in list learning and aspects of sequence perception such as recognition, recall and generation. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, theoretical frameworks based on Markov models and Reinforcement Learning paradigm will be presented. These theoretical ideas are useful for studying sequential phenomena in a principled way

Investigation of sequence processing: A cognitive and computational neuroscience perspective

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes

Supply chain challenges for sustainability: the case of waste textiles as raw materials

Purpose: This paper addresses the growing problem of textile waste in the rapidly developing cities of subSaharan Africa and examines, from a supply chain perspective, the potential for waste textile materials to be transformed into the raw materials for new consumer products. Research Approach: The paper reflects on the outcomes of a field trip to Dar es Salaam in which stakeholders in a hypothesised textile waste supply chain were interviewed and waste textile materials were analysed in order to determine their content and appropriateness for reuse. Findings from the field study have been compared with current literature on logistics and market creation, waste generation, management and recycling in sub-Saharan Africa. Findings and Originality: The findings show that a rudimentary system has been in place for many years to collect and recycle textiles in Dar es Salaam. However, at the same time as textile waste is projected to increase in the city, collection rates are falling. The chief reasons for the falling rates are failures in the ‘modernised mixture’ approach to waste collection employed by Dar es Salaam City Council and market failure for the collected materials. Alternative combinations of ‘modernised mixtures’, incorporating community-based organisations, are likely to increase textile yields from unplanned urban areas but previous high-profile failures in such systems within Dar es Salaam mean there is caution on both sides in entering into such a relationship. The more pressing problem is to identify appropriate end markets for the textile materials, since in a country where recycling is entirely market-driven, failure to do so will undermine any attempt to improve the collection system. Whilst many studies have considered general recycling practices in sub-Saharan Africa, there are few investigations into textile waste. Furthermore, those existing studies do not consider the importance of understanding fibre composition of the materials in order to determine the most appropriate end markets. Research Impact: The research contributes to the growing body of knowledge on ‘bottom of the pyramid’ approaches to sustainable futures. Practical Impact: The work presented considers supply chain problems and offers approaches to tackling the increasing waste management issues of Dar es Salaam and proposes a mechanism for doing so which has the potential to provide income for the poorest sectors of the urban society

Extreme events prediction from nonlocal partial information in a spatiotemporally chaotic microcavity laser

The forecasting of high-dimensional, spatiotemporal nonlinear systems has made tremendous progress with the advent of model-free machine learning techniques. However, in real systems it is not always possible to have all the information needed; only partial information is available for learning and forecasting. This can be due to insufficient temporal or spatial samplings, to inaccessible variables or to noisy training data. Here, we show that it is nevertheless possible to forecast extreme events occurrence in incomplete experimental recordings from a spatiotemporally chaotic microcavity laser using reservoir computing. Selecting regions of maximum transfer entropy, we show that it is possible to get higher forecasting accuracy using nonlocal data vs local data thus allowing greater warning times, at least twice the time horizon predicted from the nonlinear local Lyapunov exponent

Continuous Interaction with a Virtual Human

Attentive Speaking and Active Listening require that a Virtual Human be capable of simultaneous perception/interpretation and production of communicative behavior. A Virtual Human should be able to signal its attitude and attention while it is listening to its interaction partner, and be able to attend to its interaction partner while it is speaking – and modify its communicative behavior on-the-fly based on what it perceives from its partner. This report presents the results of a four week summer project that was part of eNTERFACE’10. The project resulted in progress on several aspects of continuous interaction such as scheduling and interrupting multimodal behavior, automatic classification of listener responses, generation of response eliciting behavior, and models for appropriate reactions to listener responses. A pilot user study was conducted with ten participants. In addition, the project yielded a number of deliverables that are released for public access

Social mindfulness and prosociality vary across the globe

Humans are social animals, but not everyone will be mindful of others to the same extent. Individual differences have been found, but would social mindfulness also be shaped by one’s location in the world? Expecting cross-national differences to exist, we examined if and how social mindfulness differs across countries. At little to no material cost, social mindfulness typically entails small acts of attention or kindness. Even though fairly common, such low-cost cooperation has received little empirical attention. Measuring social mindfulness across 31 samples from industrialized countries and regions (n = 8,354), we found considerable variation. Among selected country-level variables, greater social mindfulness was most strongly associated with countries’ better general performance on environmental protection. Together, our findings contribute to the literature on prosociality by targeting the kind of everyday cooperation that is more focused on communicating benevolence than on providing material benefits

Social mindfulness and prosociality vary across the globe

Humans are social animals, but not everyone will be mindful of others to the same extent. Individual differences have been found, but would social mindfulness also be shaped by one’s location in the world? Expecting cross-national differences to exist, we examined if and how social mindfulness differs across countries. At little to no material cost, social mindfulness typically entails small acts of attention or kindness. Even though fairly common, such low-cost cooperation has received little empirical attention. Measuring social mindfulness across 31 samples from industrialized countries and regions (n = 8,354), we found considerable variation. Among selected country-level variables, greater social mindfulness was most strongly associated with countries’ better general performance on environmental protection. Together, our findings contribute to the literature on prosociality by targeting the kind of everyday cooperation that is more focused on communicating benevolence than on providing material benefits

Closed loop supply chain for end of life textiles

Purpose: This paper aims to summarise current closed loop supply chain systems available in the literature and identify key characteristics for efficient closed loop supply chains with specific reference to the textile industry. With the aim to reduce the environmental impact of waste textile, this work is looking to identify if this can be achieved by incorporating closed loop elements within the design of a textile supply chain system. This paper also examines supply chain networks and designs required within the context of end of life (Eol) management of textiles. Research Approach: The initial approach considered here is based on a detailed investigation of current literature from logistics, textile and system engineering journals which tackle the issue of closed loop supply chain systems. Concepts such as Extended Producer Responsibility, Industrial Ecology and Zero Waste will be detailed within this evaluation. The objective here is to understand how issues identified in the literature relate to a specific automotive interiors textile company. Therefore the following step in our approach is to consider a specific case study using Sage Automotive Interiors. Findings and Originality: Closed loop supply chain analyses were carried out by many researchers to aid product development, logistics and supply chain management. Most studies have centred their attention on chemicals, pharmaceuticals or food industries where few have tackled the textiles industry specifically because of its complex supply chain design, logistics, raw materials definitions and fibre mix issues. This work will capture current and specific details from an end of life closed loop supply chain system. Research Impact: This evaluation is looking to highlight potential sustainability issues from product, process and supply chain design and provide a research agenda in relation to these issues. Practical Impact: Many companies see sustainability not only from the type of products they use within their process, but also from the operations, procedures, materials used and the recycle opportunities offered by their final product. All these can be captured within the analysis of a complex closed loop supply chain system. This investigation aims to highlight key problem areas in closed loop supply chain systems and provide an evaluation for the benefit of the textile industry