Adnan Shah

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Nonparametric hemodynamic response function (HRF) estimation in functional near-infrared spectroscopy (fNIRS) data plays an important role when investigating the temporal dynamics of a brain region response during activations. Assuming the drift arising from both physical and physiological effects in fNIRS data is Lipschitz continuous; a novel algorithm for(More)
Hemodynamic response function (HRF) estimation in noisy functional magnetic resonance imaging (fMRI) plays an important role when investigating the temporal dynamic of a brain region response during activations. Nonparametric methods which allow more flexibility in the estimation by inferring the HRF at each time sample have provided improved performance in(More)
Many studies, using a variety of imaging techniques, have shown that deafness induces functional plasticity in the brain of adults with late-onset deafness, and in children changes the way the auditory brain develops. Cross modal plasticity refers to evidence that stimuli of one modality (e.g. vision) activate neural regions devoted to a different modality(More)
Correlation based measures have widely been used to characterize brain connectivity. In this paper, a new approach based on singular spectrum analysis is proposed to characterize brain connectivity. It is obtained by deriving the common basis vector of two or more trajectory matrices associated with functional brain responses. This approach has the(More)
Diseases are manifestations of complex biological processes in living systems. Through the applications of molecular biology and genetics, many diseases are now understood at the molecular level. This has provided researchers opportunities to develop lead molecules with the capacity of blocking a particular disease mechanism. Diabetes is a complex metabolic(More)
The univariate approach without a smoothing filter for detecting activation patterns in functional magnetic resonance imaging (fMRI) data suffers from a low sensitivity due to presence of high noise. The poor performance of univariate methods such as ordinary correlation is due to lack of their ability to take advantage of spatial correlation that exists in(More)
Discriminating between active and non-active brain voxels in noisy functional magnetic resonance imaging (fMRI) data plays an important role when investigating task-related activations of the neuronal sites. A novel method for efficiently capturing drifts in the functional magnetic resonance imaging (fMRI) data is presented that leads to enhanced fMRI(More)
Non-parametric hemodynamic response function (HRF) estimation in noisy functional near-infrared spectroscopy (fNIRS) plays an important role when investigating the temporal dynamics of a brain region response during activations. Assuming the drift Lipschitz continuous; a new algorithm for non-parametric HRF estimation from the oxygenated (HbO) and(More)