Eating themselves to death: have "personal rights" gone too far in treating people with Prader-Willi syndrome?
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Biomedical subjects
Publications and source records attributed to F Moss.
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Attempts to detect and characterize chaos in biological systems are of considerable interest, especially in medical science, where successful demonstrations may lead to new diagnostic tools and therapies. Unfortunately, conventional methods for identifying chaos often yield equivocal results when applied to biological data, which are usually heavily contaminated with noise. For such applications, a new technique based on the detection of unstable periodic orbits holds promise. Infinite sets of unstable periodic orbits underlie chaos in dissipative systems; accordingly, the new method searches a time series only for rare events characteristic of these unstable orbits, rather than analysing the structure of the series as a whole. Here we demonstrate the efficacy of the method when applied to the dynamics of the crayfish caudal photoreceptor (subject to stimuli representative of the animal's natural habitat). Our findings confirm the existence of low-dimensional dynamics in the system, and strongly suggest the existence of deterministic chaos. More importantly, these results demonstrate the power of methods based on the detection of unstable periodic orbits for identifying low-dimensional dynamics--and, in particular, chaos--in biological systems.
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We discuss the well-known problems associated with efforts to detect and characterize chaos and other low dimensional dynamics in biological settings. We propose a new method which shows promise for addressing these problems, and we demonstrate its effectiveness in an experiment with the crayfish sensory system. Recordings of action potentials in this system are the data. We begin with a pair of assumptions; that the times of firings of neural action potentials are largely determined by high dimensional random processes or "noise"; and that most biological files are non stationary, so that only relatively short files can be obtained under approximately constant conditions. The method is thus statistical in nature. It is designed to recognize individual "events" in the form of particular sequences of time intervals between action potentials which are the signatures of certain well defined dynamical behaviors. We show that chaos can be distinguished from limit cycles, even when the dynamics is heavily contaminated with noise. Extracellular recordings from the crayfish caudal photoreceptor, obtained while hydrodynamically stimulating the array of hair receptors on the tailfan, are used to illustrate the method.
1. The caudal photoreceptor (CPR) interneurons in the sixth abdominal ganglion of the crayfish are complex, multi-modal interneurons. These cells respond directly to light with tonic spike discharges, and they integrate synaptic input from an array of fili-form mechanoreceptors on the tailfan. They also provide input to rostral command centers, inducing backward walking at high firing frequencies, and thus directly influence behavior. 2. We recorded CPR activity in response to weak hydrodynamic stimulation of the tailfan mechanoreceptors while under varying intensities of light shined on the sixth ganglion. Spike trains were characterized according to the mean discharge rate (MDR) and the power spectrum from which the signal-to-noise ratio (SNR) was calculated. 3. Illumination of the CPR enhances the efficiency of transmitting mechanosensory signals. It does so by increasing the SNR of mechanosensory input received from tailfan receptors. A sevenfold, nonlinear increase in the SNRs was observed with increasing light intensity, an effect especially pronounced for weak hydrodynamic stimuli. In comparison with the dark, illumination of the ganglion lowered the hydrodynamic threshold and heightened the response to suprathreshold stimulation. Unlike the SNR, the MDR is little affected by mechanosensory input. 4. These results are compared with simulated electronic activity from an analogue threshold model and are discussed with respect to the mechanism of stochastic resonance.
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Anyone considering a fundamental rethink of the role of consultants risks exposing tensions in the medical profession that have characterised the development of medical practice since the 18th century. That tense story was one of beds and money, power and domination. Rethinking the role of consultants must now take into account the relationship between consultants and their specialist colleagues and general practitioners; examine the distribution of work between consultants and junior doctors; and relate the contribution of the consultant as specialist to that of other health professionals. After half a century of a national health service characterised by equity of access to care, we urgently need to debate the roles of those who work in it and in doing so to focus primarily on the needs of patients.
Noise in dynamical systems is usually considered a nuisance. But in certain nonlinear systems, including electronic circuits and biological sensory apparatus, the presence of noise can in fact enhance the detection of weak signals. This phenomenon, called stochastic resonance, may find useful application in physical, technological and biomedical contexts.
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Many neurons at the sensory periphery receive periodic input, and their activity exhibits entrainment to this input in the form of a preferred phase for firing. This article describes a modeling study of neurons which skip a random number of cycles of the stimulus between firings over a large range of input intensities. This behavior was investigated using analog and digital simulations of the motion of a particle in a double-well with noise and sinusoidal forcing. Well residence-time distributions were found to exhibit the main features of the interspike interval histograms (ISIH) measured on real sensory neurons. The conditions under which it is useful to view neurons as simple bistable systems subject to noise are examined by identifying the features of the data which are expected to arise for such systems. This approach is complementary to previous studies of such data based, e.g., on non-homogeneous point processes. Apart from looking at models which form the backbone of excitable models, our work allows us to speculate on the role that stochastic resonance, which can arise in this context, may play in the transmission of sensory information.
The random sequence of openings and closings of single ion channels and the channel conductances have been the object of intense study over the past two decades with a view toward illuminating the underlying kinetics of the channel protein molecules. Channels that are sensitive to voltage, such as many K(+)-selective channels, have been particularly useful, because the kinetic rates can be manipulated by changing the membrane voltage. Most such studies have been performed under stationary conditions and usually at a single temperature. Here we report the results of experiments with sinusoidal modulation of the membrane potential performed at several temperatures. Dwell time and cycle histograms, objects not normally associated with ion channel experiments, are herein reported. From the last, the transition probability densities for channel opening and closing events are obtained. A new and unusual phase anticipation is observed in the cycle histograms, and its temperature dependence is measured.