Rephrasing voice : art, practice-led research and the limits and sites of articulacy

While my PhD is practice-led research, it is my contention that such an inquiry cannot develop as long as it tries to emulate other models of research. I assert that practice-led research needs to account for an epistemological unknown or uncertainty central to the practice of art. By focusing on what I call the artist's 'voice,' I will show how this 'voice' is comprised of a dual motivation—'articulate' representation and 'inarticulate' affect—which do not even necessarily derive from the artist. Through an analysis of art-historical precedents, critical literature (the work of Jean-François Lyotard and Andrew Benjamin, the critical methods of philosophy, phenomenology and psychoanalysis) as well as of my own painting and digital arts practice, I aim to demonstrate how this unknown or uncertain aspect of artistic inquiry can be mapped. It is my contention that practice-led research needs to address and account for this dualistic 'voice' in order to more comprehensively articulate its unique contribution to research culture.

A dominant-negative mutation in the TRESK potassium channel is linked to familial migraine with aura

Migraine with aura is a common, debilitating, recurrent headache disorder associated with transient and reversible focal neurological symptoms. A role has been suggested for the two-pore domain (K2P) potassium channel, TWIK-related spinal cord potassium channel (TRESK, encoded by KCNK18), in pain pathways and general anaesthesia. We therefore examined whether TRESK is involved in migraine by screening the KCNK18 gene in subjects diagnosed with migraine. Here we report a frameshift mutation, F139WfsX24, which segregates perfectly with typical migraine with aura in a large pedigree. We also identified prominent TRESK expression in migraine-salient areas such as the trigeminal ganglion. Functional characterization of this mutation demonstrates that it causes a complete loss of TRESK function and that the mutant subunit suppresses wild-type channel function through a dominant-negative effect, thus explaining the dominant penetrance of this allele. These results therefore support a role for TRESK in the pathogenesis of typical migraine with aura and further support the role of this channel as a potential therapeutic target.

Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.