An investigation of psychological and physiological changes apparently elicited by musical stimuli

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Fibre-grating sensors for the measurement of physiological pulsations

Mechanical physiological pulsations are movements of a body surface incited by the movements of muscles in organs inside the body. Here we demonstrate the use of long-period grating sensors in the detection of cardio-vascular pulsations (CVP), in particular apex and carotid pulsations. To calibrate the sensors, we use a mechanical tool designed specifically to measure the sensor response to a localized perturbation at different grating curvatures as working points. From the data we infer the amplitude of the CVP. Together with the electrophysiological signals, the CVP signals obtained from the sensors can provide significant information on heart function which is inaccessible to the electrocardiogram. The low cost and easy handling of the fibre sensors increase their prospects to become the sensors of choice for novel diagnostic devices. © 2013 The Royal Swedish Academy of Sciences.

The sciatic nerve of the toad Xenopus laevis as a physiological model of the human cochlear nerve

The response of single fibres of the human cochlear nerve to electrical stimulation by a cochlear implant has previously been inferred from the response of the cochlear nerve in other mammals. These experiments are hindered by stimulus artefact and the range of stimulus currents used is therefore much less than the perceptual dynamic range (from threshold to discomfort) of human subjects. We have investigated use of the sciatic nerve of the toad Xenopus laevis as a convenient physiological model of the human cochlear nerve. Use of this completely dissected nerve reduces the problems of stimulus artefact whilst maintaining the advantages of a physiological preparation. The validity of the model was assessed by measuring the refractory periods, excitation time-constant, and relative spread of single fibres using microelectrode recording. We have also investigated the response of nerve fibres to sinusoidal stimulation. Based on these measurements, we propose that the sciatic nerve may be a suitable model of the human cochlear nerve if the timescales of stimuli are decreased by a factor of about five to compensate for the slower dynamics of the sciatic nerve and if noise is added to the stimuli to compensate for the lower internal noise of sciatic nerve fibres.

Improving brain drug targeting through exploitation of the nose-to-brain route:a physiological and pharmacokinetic perspective

With an ageing population and increasing prevalence of central-nervous system (CNS) disorders new approaches are required to sustain the development and successful delivery of therapeutics into the brain and CNS. CNS drug delivery is challenging due to the impermeable nature of the brain microvascular endothelial cells that form the blood-brain barrier (BBB) and which prevent the entry of a wide range of therapeutics into the brain. This review examines the role intranasal delivery may play in achieving direct brain delivery, for small molecular weight drugs, macromolecular therapeutics and cell-based therapeutics, by exploitation of the olfactory and trigeminal nerve pathways. This approach is thought to deliver drugs into the brain and CNS through bypassing the BBB. Details of the mechanism of transfer of administrated therapeutics, the pathways that lead to brain deposition, with a specific focus on therapeutic pharmacokinetics, and examples of successful CNS delivery will be explored. © 2014 Bentham Science Publishers.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.