Mathew J Anderson

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Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent(More)
When two novel conditioned stimuli precede an unconditioned stimulus (US), the interval between the two conditioned stimuli (CS1 and CS2) influences the magnitude of the CS-US associability of each CS. As the interval between CS1 and CS2 increases, the associability of CS1 with the US decreases due to interference by CS2 and the associability of CS2(More)
Drosophila larvae reared inside a micro-metal box with an internal field strength 0.004 microT, were treated with a magnetic field of 50 Hz, 8 microT. for 20 min. Control experienced 0.004 microT. Cellular transcript levels were assessed using slot blots and quantified using a Phosphorimager. Blots were hybridised using probes against HSP 70a, Histone 1.9,(More)
Young adults (n = 54 for Exp. 1, n = 50 for Exp. 2) and elderly adults (the same n = 40 in each experiment) participated in studies that required nonspeeded magnitude estimation scaling in response to words that varied in frequency and number of meanings. Across both experiments and across both groups, subject and item analyses indicated significant word(More)
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