Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

Proportionally balanced designs: Some further results and general constructions

Proportionally balanced designs were introduced by Gray and Matters in response to a need for the allocation of markers of the Queensland Core Skills Test to have a certain property. Put simply, markers were allocated to pairs of units in proportions that reflected the relative numbers of markers allocated in total to each unit. In this paper, the first author extends the theoretical results relating to such designs and provides further instances, and two general constructions, in the case that the design comprises blocks of precisely two sizes.

Research output of Australian general practice: A comparison with medicine, surgery and public health

Objectives: To compare the productivity of Australian general practice in terms of research publications with the productivity of other medical disciplines. Design: A survey of Australian general practice, medicine, surgery and public health publications carried out by manual searching of specific journals and an electronic search of the US National Library of Medicine's PubMed database. Main outcome measures: The number of original research publications by Australian general practitioners, physicians, surgeons and public health physicians during 1999; the relative publication rate of Australian general practice, medicine, surgery and public health over the period 1990-1999. Results: Of original research articles published in 1999, GPs authored 65% (17/26) in Australian Family Physician and 3% (3/90) in the Medical Journal of Australia; physicians published 4% and 37%, respectively. The electronic search identified 54 research articles relating to Australian general practice published in 1999 in 21 different journals, only two of which were primary care journals. Over the period 1990-1999, there was a publication rate of one general practice [discipline] article per 1000 GPs in practice per year. Corresponding rates for medicine, surgery and public health were 105/1000, 61/1000 and 148/1000, respectively. Conclusions: There is considerable disparity between the level of research output of general practice and that of the disciplines of medicine, surgery and public health. If we are to have effective general practice research, we urgently need to develop research skills, a supportive infrastructure and a culture that nurtures research.