The contribution of the wrist, elbow and shoulder joints to single-finger tapping

We aimed to determine the role of the wrist, elbow and shoulder joints to single-finger tapping. Six human subjects tapped with their index finger at a rate of 3 taps/s on a keyswitch across five conditions, one freestyle (FS) and four instructed tapping strategies. The four instructed conditions were to tap on a keyswitch using the finger joint only (FO), the wrist joint only (WO), the elbow joint only (EO), and the shoulder joint only (SO). A single-axis force plate measured the fingertip force. An infra-red active-marker three-dimensional motion analysis system measured the movement of the fingertip, hand, forearm, upper arm and trunk. Inverse dynamics estimated joint torques for the metacarpal-phalangeal (MCP), wrist, elbow, and shoulder joints. For FS tapping 27%, 56%, and 18% of the vertical fingertip movement were a result of flexion of the MCP joint and wrist joint and extension of the elbow joint, respectively. During the FS movements the net joint powers between the MCP, wrist and elbow were positively correlated (correlation coefficients between 0.46 and 0.76) suggesting synergistic efforts. For the instructed tapping strategies (FO, WO, EO, and SO), correlations decreased to values below 0.35 suggesting relatively independent control of the different joints. For FS tapping, the kinematic and kinetic data indicate that the wrist and elbow contribute significantly, working in synergy with the finger joints to create the fingertip tapping task.     

Quantum-like brain: "Interference of minds"

We present a contextualist statistical realistic model for quantum-like representations in physics, cognitive science, and psychology. We apply this model to describe cognitive experiments to check quantum-like structures of mental processes. The crucial role is played by interference of probabilities for mental observables. Recently one such experiment based on recognition of images was performed. This experiment confirmed our prediction on the quantum-like behavior of mind. In our approach "quantumness of mind" has no direct relation to the fact that the brain (as any physical body) is composed of quantum particles. We invented a new terminology "quantum-like (QL) mind." Cognitive QL-behavior is characterized by a nonzero coefficient of interference lambda. This coefficient can be found on the basis of statistical data. There are predicted not only cos theta-interference of probabilities, but also hyperbolic cosh theta-interference. This interference was never observed for physical systems, but we could not exclude this possibility for cognitive systems. We propose a model of brain functioning as a QL-computer (there is a discussion on the difference between quantum and QL computers).     

Numerical study to evaluate the effect of a surface-based sensor on arterial tonometry

Abstract

Arterial tonometry is a widely used non-invasive blood pressure measurement method. In contrast to the cuff-based method, it is possible to obtain a continuous pressure profile with respect to systolic and diastolic pressures using this method. However, due to a requirement of arterial tonometry—that a sensor needs to be placed directly above a blood vessel—placement error is inevitable if the measurement device is only capable of measuring local regions. This study assumed that the plate sensor is flexible, thus reducing the placement error. We investigated the pressure distribution along the wrist surface rather than the local region through the contact simulation between the flexible plate sensor and the wrist. As a result, we concluded that there is a unique pressure distribution for any specific wrist, regardless of the length and position of the plate, and that it is possible to measure the blood pressure using the response at the wrist surface to the pressure inside the radial artery.     

Nonparametric sparsification of complex multiscale networks

Many real-world networks tend to be very dense. Particular examples of interest arise in the construction of networks that represent pairwise similarities between objects. In these cases, the networks under consideration are weighted, generally with positive weights between any two nodes. Visualization and analysis of such networks, especially when the number of nodes is large, can pose significant challenges which are often met by reducing the edge set. Any effective "sparsification" must retain and reflect the important structure in the network. A common method is to simply apply a hard threshold, keeping only those edges whose weight exceeds some predetermined value. A more principled approach is to extract the multiscale "backbone" of a network by retaining statistically significant edges through hypothesis testing on a specific null model, or by appropriately transforming the original weight matrix before applying some sort of threshold. Unfortunately, approaches such as these can fail to capture multiscale structure in which there can be small but locally statistically significant similarity between nodes. In this paper, we introduce a new method for backbone extraction that does not rely on any particular null model, but instead uses the empirical distribution of similarity weight to determine and then retain statistically significant edges. We show that our method adapts to the heterogeneity of local edge weight distributions in several paradigmatic real world networks, and in doing so retains their multiscale structure with relatively insignificant additional computational costs. We anticipate that this simple approach will be of great use in the analysis of massive, highly connected weighted networks.     

Measurement of calcium channel inactivation is dependent upon the test pulse potential.

We have developed two methods to measure Ca2+ channel inactivation in Lymnaea neurons-one method, based upon the conventional double-pulse protocol, uses currents during a moderately large depolarizing pulse, and the other uses tail currents after a very strong activating pulse. Both methods avoid contamination by proton currents and are unaffected by rundown of Ca2+ current. The magnitude of inactivation measured differs for the two methods; this difference arises because the measurement of inactivation is inherently dependent upon the test pulse voltage used to monitor the Ca2+ channel conductance. We discuss two models that can generate such test pulse dependence of inactivation measurements-a two-channel model and a two-open-state model. The first model accounts for this by assuming the existence of two types of Ca2+ channels, different proportions of which are activated by the different test pulses. The second model assumes only one Ca2+ channel type, with two closed and open states; in this model, the test pulse dependence is due to the differential activation of channels in the two closed states by the test pulses. Test pulse dependence of inactivation measurements of Ca2+ channels may be a general phenomenon that has been overlooked in previous studies.     

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Most of this knowledge is derived from studies of subtype B genotypes, despite not being the most abundant subtype worldwide. Here, we present a methodology for the comparison of mutational networks in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational networks from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models for a larger number of resistance mutations and develop a statistical test to assess differences in the inferred mutational networks between two groups. We apply this method to infer the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional cohort of HIV-1 subtype C genotypes from South Africa, as well as to a data set of subtype B genotypes obtained from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. The inferred mutational networks for subtype B versus C are significantly different sharing only five constraints on the order of accumulating mutations with mutation at residue 54 as the parental event. The results also suggest that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational networks between any two groups.     

A novel method to replicate the kinematics of the carpus using a six degree-of-freedom robot

Understanding the kinematics of the carpus is essential to the understanding and treatment of wrist pathologies. However, many of the previous techniques presented are limited by non-functional motion or the interpolation of points from static images at different postures. We present a method that has the capability of replicating the kinematics of the wrist during activities of daily living using a unique mechanical testing system. To quantify the kinematics of the carpal bones, we used bone pin-mounted markers and optical motion capture methods. In this paper, we present a hammering motion as an example of an activity of daily living. However, the method can be applied to a wide variety of movements. Our method showed good accuracy (1.0–2.6°) of in vivo movement reproduction in our ex vivo model. Most carpal motion during wrist flexion–extension occurs at the radiocarpal level while in ulnar deviation the motion is more equally shared between radiocarpal and midcarpal joints, and in radial deviation the motion happens mainly at the midcarpal joint. For all rotations, there was more rotation of the midcarpal row relative to the lunate than relative to the scaphoid or triquetrum. For the functional motion studied (hammering), there was more midcarpal motion in wrist extension compared to pure wrist extension while radioulnar deviation patterns were similar to those observed in pure wrist radioulnar deviation. Finally, it was found that for the amplitudes studied the amount of carpal rotations was proportional to global wrist rotations.     

In vivo repeatability of the pulse wave inverse problem in human carotid arteries

Accurate arterial stiffness measurement would improve diagnosis and monitoring for many diseases. Atherosclerotic plaques and aneurysms are expected to involve focal changes in vessel wall properties; therefore, a method to image the stiffness variation would be a valuable clinical tool. The pulse wave inverse problem (PWIP) fits unknown parameters from a computational model of arterial pulse wave propagation to ultrasound-based measurements of vessel wall displacements by minimizing the difference between the model and measured displacements. The PWIP has been validated in phantoms, and this study presents the first in vivo demonstration. The common carotid arteries of five healthy volunteers were imaged five times in a single session with repositioning of the probe and subject between each scan. The 1D finite difference computational model used in the PWIP spanned from the start of the transducer to the carotid bifurcation, where a resistance outlet boundary condition was applied to approximately model the downstream reflection of the pulse wave. Unknown parameters that were estimated by the PWIP included a 10-segment linear piecewise compliance distribution and 16 discrete cosine transformation coefficients for each of the inlet boundary conditions. Input data was selected to include pulse waves resulting from the primary pulse and dicrotic notch. The recovered compliance maps indicate that the compliance increases close to the bifurcation, and the variability of the average pulse wave velocity estimated through the PWIP is on the order of 11%, which is similar to that of the conventional processing technique which tracks the wavefront arrival time (13%).     

Recurrent neural networks of integrate-and-fire cells simulating short-term memory and wrist movement tasks derived from continuous dynamic networks

Dynamic recurrent neural networks composed of units with continuous activation functions provide a powerful tool for simulating a wide range of behaviors, since the requisite interconnections can be readily derived by gradient descent methods. However, it is not clear whether more realistic integrate-and-fire cells with comparable connection weights would perform the same functions. We therefore investigated methods to convert dynamic recurrent neural networks of continuous units into networks with integrate-and-fire cells. The transforms were tested on two recurrent networks derived by backpropagation. The first simulates a short-term memory task with units that mimic neural activity observed in cortex of monkeys performing instructed delay tasks. The network utilizes recurrent connections to generate sustained activity that codes the remembered value of a transient cue. The second network simulates patterns of neural activity observed in monkeys performing a step-tracking task with flexion/extension wrist movements. This more complicated network provides a working model of the interactions between multiple spinal and supraspinal centers controlling motoneurons. Our conversion algorithm replaced each continuous unit with multiple integrate-and-fire cells that interact through delayed "synaptic potentials". Successful transformation depends on obtaining an appropriate fit between the activation function of the continuous units and the input-output relation of the spiking cells. This fit can be achieved by adapting the parameters of the synaptic potentials to replicate the input-output behavior of a standard sigmoidal activation function (shown for the short-term memory network). Alternatively, a customized activation function can be derived from the input-output relation of the spiking cells for a chosen set of parameters (demonstrated for the wrist flexion/extension network). In both cases the resulting networks of spiking cells exhibited activity that replicated the activity of corresponding continuous units. This confirms that the network solutions obtained through backpropagation apply to spiking networks and provides a useful method for deriving recurrent spiking networks performing a wide range of functions.     

Investigating protein unfolding kinetics by pulse proteolysis

Investigation of protein unfolding kinetics of proteins in crude samples may provide many exciting opportunities to study protein energetics under unconventional conditions. As an effort to develop a method with this capability, we employed “pulse proteolysis” to investigate protein unfolding kinetics. Pulse proteolysis has been shown to be an effective and facile method to determine global stability of proteins by exploiting the difference in proteolytic susceptibilities between folded and unfolded proteins. Electrophoretic separation after proteolysis allows monitoring protein unfolding without protein purification. We employed pulse proteolysis to determine unfolding kinetics of E. coli maltose binding protein (MBP) and E. coli ribonuclease H (RNase H). The unfolding kinetic constants determined by pulse proteolysis are in good agreement with those determined by circular dichroism. We then determined an unfolding kinetic constant of overexpressed MBP in a cell lysate. An accurate unfolding kinetic constant was successfully determined with the unpurified MBP. Also, we investigated the effect of ligand binding on unfolding kinetics of MBP using pulse proteolysis. On the basis of a kinetic model for unfolding of MBP•maltose complex, we have determined the dissociation equilibrium constant (K_d) of the complex from unfolding kinetic constants, which is also in good agreement with known K_d values of the complex. These results clearly demonstrate the feasibility and the accuracy of pulse proteolysis as a quantitative probe to investigate protein unfolding kinetics.     

Asymmetric comparison and querying of biological networks

Comparing and querying the protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform these tasks operate symmetrically, i.e., they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how the corresponding organism is biologically well characterized. In this paper a new idea is developed, that is, to exploit differences in the characterization of organisms at hand in order to devise methods for comparing their PPI networks. We use the PPI network (called Master) of the best characterized organism as a fingerprint to guide the alignment process to the second input network (called Slave), so that generated results preferably retain the structural characteristics of the Master network. Technically, this is obtained by generating from the Master a finite automaton, called alignment model, which is then fed with (a linearization of) the Slave for the purpose of extracting, via the Viterbi algorithm, matching subgraphs. We propose an approach able to perform global alignment and network querying, and we apply it on PPI networks. We tested our method showing that the results it returns are biologically relevant.     

In vitro investigation of the factors affecting pulse oximetry

The effect of a number of physiological parameters on pulse oximetry accuracy has been investigated in an in vitro model. We have found that above 50% saturation, pulse oximeters will not be affected by variations in haematocrit, blood flow rate, tissue blood content and pulse amplitude. At low saturations, however, it is known that the accuracy of pulse oximeters decreases and our in vitro results suggest how this may be corrected.     

Prediction of fingers posture using artificial neural networks

Predicting the hand and fingers posture during grasping tasks is an important issue in the frame of biomechanics. In this paper, a technique based on neural networks is proposed to learn the inverse kinematics mapping between the fingertip 3D position and the corresponding joint angles. Finger movements are obtained by an instrumented glove and are mapped to a multichain model of the hand. From the fingertip desired position, the neural networks allow predicting the corresponding finger joint angles keeping the specific subject coordination patterns. Two sets of movements are considered in this study. The first one, the training set, consisting of free fingers movements is used to construct the mapping between fingertip position and joint angles. The second one, constructed for testing purposes, is composed of a sequence of grasping tasks of everyday-life objects. The maximal mean error between fingertip measured position and fingertip position obtained from simulated joint angles and forward kinematics is 0.99+/-0.76mm for the training set and 1.49+/-1.62mm for the test set. Also, the maximal RMS error of joint angles prediction is 2.85 degrees and 5.10 degrees for the training and test sets respectively, while the maximal mean joint angles prediction error is -0.11+/-4.34 degrees and -2.52+/-6.71 degrees for the training and test sets, respectively. Results relative to the learning and generalization capabilities of this architecture are also presented and discussed.     

Circadian response reduction in light and response restoration in darkness: a "skeleton" light pulse PRC study in mice (Mus musculus)

Entrainment may involve responses to dawn, to dusk, and to the light in between these transitions. Previous studies showed that the circadian system responds to only 2 light pulses, one at the beginning and one at the end of the day, in a similar way as to a full photoperiod, as long as the photoperiod is less than approximately 1/2 tau. The authors used a double 1-h light pulse protocol with different intervals of darkness in between (1, 2, 4, 7, 10, and 16 h) to study the phase responses of mice. The phase response curves obtained were compared to full light pulse PRCs of corresponding durations. Up to 6 hours, phase responses induced by double light pulses are virtually the same as by a corresponding full light pulse. The authors made a simple phase-only model to estimate the response reduction due to light exposure and response restoration due to dark exposure of the system. In this model, they assumed a 100% contribution of the first 1-h light pulse and fitted the reduction factor for the second light pulse to yield the best fit to the observations. The results suggest that after 1 h of light followed by less than 4 h of darkness, there is a considerable reduction in response to the second light pulse. Full response restoration requires more than 10 h of darkness. To investigate the influence of the duration of light on the response saturation, the authors performed a second series of experiments where the duration of the 2 light pulses was varied from 4 to 60 min each with a fixed duration of the stimulus (4 h). The response to 2 light pulses saturates when they are between 30 and 60 min long. In conclusion, double pulses replace single full light pulses of a corresponding duration of up to 6 h due to a response reduction during light, combined with response restoration during darkness. By the combined response reduction and response restoration, mice can maintain stable entrainment to the external LD cycle without being continuously exposed to it.     

Velocity pulse advances pressure pulse by close to 45 degrees in the rat pial arterioles

In order to clarify the phase relationship between velocity pulse and pressure pulse propagating along microvessels, the red cell velocity and intravascular pressure were simultaneously measured in the rat pial arterioles of 41-53 microm in diameter with a high temporal resolution by a laser-Doppler anemometer and a servo-null micropressure system. It was found that the velocity pulse preceded the pressure pulse in all the measured arterioles by 18.7-35.6 ms. The corresponding phase difference was 43.6+/-6.9 degrees (mean +/- SD), which is not statistically different from 45 degrees. The value is consistent with the phase difference predicted for the blood flow in microvessels with a small reflection coefficient at frequencies as low as the heart rate of the rats. The present results suggest that the upstream changes in blood flow are transmitted by the velocity pulse faster than by the pressure pulse in the microvasculature.     

Model for post-occlusive reactive hyperemia as measured noninvasively with pressure pulse waveform

Post-occlusive reactive hyperemia is a noninvasive maneuver to assess microvascular reactivity related to the bioavailability and/or bioactivity of endothelial-derived factors. The inability to respond to endogenous vasodilator substances is mostly described by a low peak flow after an event associated with a peak flow. The aim of this study is to propose a model to describe post-occlusive responses observed in the pressure waveforms after occlusion release. Model variables were investigated in search of those representatives of the endothelial response to the ischemic process. Radial pressure pulse waveforms were acquired in the anterior region of the wrist, superficial to the radial artery, using a piezoelectric transducer acquired by a 12 bits acquisition board model at a sampling rate of 1.0 kHz to increase the temporal resolution. The occlusion maneuver was performed using an arm-cuff placed over the brachial artery. A time series of pulse pressure (PP) values, calculated from successive values of beat-to-beat systolic and diastolic pressures, was found to be a useful variable representing blood pressure signal in the model. This data time series of the pulse pressure presents reduced initial values compared with the baseline measurement, and an increasing value until a steady state behavior was sustained after approximately 60 s. This behavior for the pulse pressure series was described by a hyperbolic tangent model with parameters K (rate of change of PP), PP₀ (first value of PP after cuff release), and ΔPP (change in PP). The model was applied to pulse pressure signals from normotensive and hypertensive subjects. The observed responses between groups suggest that PP₀ and ΔPP are related to an endothelial response to the ischemic process and could be used as a clinical tool to assess endothelial function in hypertension.     

Taking the pulse of nations: A biometric measure of well-being

A growing literature identifies associations between subjective and biometric indicators of wellbeing. These associations, together with the ability of subjective wellbeing metrics to predict health and behavioral outcomes, have spawned increasing interest in wellbeing as an important concept in its own right. However, some social scientists continue to question the usefulness of wellbeing metrics. We contribute to this literature in three ways. First, we introduce a biometric measure of wellbeing – pulse – that hs been little used. Using nationally representative data on 165,000 individuals from the Health Survey for England and Scottish Health Surveys we show that its correlates are similar in a number of ways to those for happiness, and that it is highly correlated with wellbeing metrics, as well as self-assessed health. Second, we examine the determinants of pulse rates in mid-life (age 42) among the 9000 members of the National Child Development Study, a birth cohort born in a single week in 1958 in Britain. Third, we track the impact of pulse measured in mid-life (age 42) on health and labor market outcomes at age 50 in 2008 and age 55 in 2013. The probability of working at age 55 is negatively impacted by pulse rate a decade earlier. The pulse rate has an impact over and above chronic pain measured at age 42. General health at 55 is lower the higher the pulse rate at age 42, while those with higher pulse rates at 42 also express lower life satisfaction and more pessimism about the future at age 50. Taken together, these results suggest social scientists can learn a great deal by adding pulse rates to the metrics they use when evaluating people’s wellbeing.