The Bayesian Power Imaging (BPI) method for magnetic source imaging

In the biomagnetic inverse problem the main interest is the activation of a region of interest, i.e. the power dissipated in that region. The Bayesian power imaging method (BPI) provides a quantified probability that the activation of a region of interest is above a given threshold. This paper introduces the method and derives the equations used. The method is illustrated in this paper using both experimental and simulated data

The Bayesian Power Imaging (BPI) test for task/control experiments

The Bayesian power imaging (BPI) method is a new approach to the biomagnetic inverse problem that is introduced in [1]. In this paper the method is extended to analyze not one but two sets of experimental data in order to highlight the differences between them

A Bayesian test for the appropriateness of a model in the biomagnetic inverse problem

This paper extends the work of Clarke [1] on the Bayesian foundations of the biomagnetic inverse problem. It derives expressions for the expectation and variance of the a posteriori source current probability distribution given a prior source current probability distribution, a source space weight function and a data set. The calculation of the variance enables the construction of a Bayesian test for the appropriateness of any source model that is chosen as the a priori infomation. The test is illustrated using both simulated (multi-dipole) data and the results of a study of early latency processing of images of human faces. [1] C.J.S. Clarke. Error estimates in the biomagnetic inverse problem. Inverse Problems, 10:77--86, 1994.Comment: 13 pages, 16 figures. Submitted to Inverse Problem

The FuturICT education accelerator

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year ‘man-on-the-moon’ project is proposed in which FuturICT’s unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a ‘wind tunnel’ for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT

The FuturICT education accelerator

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year ‘man-on-the-moon’ project is proposed in which FuturICT’s unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a ‘wind tunnel’ for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT

Face processing in individuals with autism: a longitudinal magnetoencephalographic study

Behavioural data suggest that individuals with autism use anomalous cognitive strategies when processing faces. Recent neurophysiological and neuroimaging data points to different-from-normal neural activity in able adults with autism when viewing faces. The development of face processing skills, however, is still rather poorly understood both under typical and atypical conditions

Locating brand equity: neural correlates of virtual shopping choices

Marketers are fundamentally interested in how consumers make buying decisions. A recent method of noninvasive brain imaging, magneto encephalography (MEG), was used to observe subjects making decisions on a virtual (video) supermarket visit. At each of 90 stops, the subject was invited to choose one of three brands. Package height discrimination between a subset of the same stimuli provided a control experiment. Subjects also completed a questionnaire to indicate their familiarity with each of the brands shown in the video. The objectives were to identify brain regions which become differentially engaged when choosing brands, as against discriminating packaging height, and the extent to which familiarity with the brand would affect both the choice and the associated brain processes. As expected, activations in brand choice differed from those for height discrimination and were faster when one brand was more familiar. Brand choice appeared to involve silent vocalization. The right parietal cortex was only activated where the subject indicated strong relative brand familiarity. This therefore appears to be a key location for brand equity both because it is only activated for the most salient brands and because it seems to be linked with intentionality. This is probably the first time brand equity has been located. The paper concludes with the benefits for marketers and marketing research