Amplitude Variance Research Articles

Focusing effects of L‐dopa in Parkinson's disease

Previous fMRI motor studies in Parkinson's disease (PD) have suggested that L-dopa may "normalize" areas of hypo- and hyperactivity. However, results from these studies, which were largely based on analyzing BOLD signal amplitude, have been conflicting. Examining only amplitude changes at distinct loci may thus be inadequate in fully capturing the activation changes induced by L-dopa. In this article, we extended prior analyses on the effects of L-dopa by investigating both amplitude and spatial changes of brain activation before and after L-dopa. Ten subjects with PD, both on and off medication, and ten healthy, age-matched controls performed a visuo-motor tracking task in which they sinusoidally squeezed a bulb at 0.25, 0.5, and 0.75 Hz. This task was contrasted with static squeezing to generate fMRI activation maps. To investigate the effects of L-dopa, we examined the amplitude and spatial variance of the BOLD response within anatomically-defined regions of interest (ROIs). L-dopa had significant main effects on the amplitude of BOLD signal in bilateral primary motor cortex and left SMA. In contrast, L-dopa-mediated spatial changes were apparent in bilateral cerebellar hemispheres, M1, SMA, and right prefrontal cortex. Moreover, L-dopa appeared to normalize the spatial distribution of ROI activation in PD to that of the controls. Specifically, L-dopa had a "focusing" effect on activity-an effect more pronounced than the typically-measured fMRI amplitude changes. This observation is consistent with modeling studies, which demonstrated that dopamine increases the signal-to-noise ratio at the neuronal level with a resultant focusing of representations at the macroscopic level.

The nature of individual differences in EEG parameters during homogeneous visual field in 5- and 6-year-old twins: A pilot study

To assess the genetic and environmental influences on the inter-individual variability of spectral EEG parameters under two conditions of reduced visual input in preschoolers. EEG was recorded in 21 monozygotic and 20 same-sex dizygotic twin pairs aged 5-6 years under the Closed eyes and Darkness conditions. The contributions of genetic and environmental influences to individual EEG parameters were estimated using structural equation modeling. The alpha rhythm parameters - both spectral amplitude and frequency - were influenced mainly by genetic factors. Theta spectral amplitude variance was presumably accounted for by both genetic and shared environmental factors. The difference in the nature of population variance between EEG alpha and theta band spectral amplitudes was reproduced for two identical functional loads: Closed eyes and Darkness. The majority of EEG spectral parameters in preschool children are determined by genetic factors. Tentative finding on systematic environmental influences on theta spectral amplitude under the condition of reduced visual input may point to the role of experience in the individual differences in the functioning of theta response system. The findings contribute to the scanty knowledge about the heritability of EEG rhythms in preschool children.

The Estimated Signal Parameter Detector: Incorporating Signal Parameter Statistics Into the Signal Processor

Acoustic propagation through a time-varying and spatially varying environment can produce variations in the received signal over multiple observations, possibly degrading receiver performance. This paper presents a signal processing structure that utilizes knowledge of received signal statistics to recoup lost performance. Recent research has shown that received signal parameter statistics can be calculated using Monte Carlo simulation and knowledge of ocean environment properties and processes. The processor possesses an estimator-correlator structure, and is referred to in this paper as the estimated signal parameter detector (ESPD). To demonstrate ESPD performance, the derivation is implemented to distinguish between monotone sinusoids with Gaussian-distributed amplitudes with identical means but different variances, embedded in zero-mean white Gaussian noise. In general, the amplitude distributions can possess any form and the noise distribution must belong to a general class of probability density functions (pdfs). The present assumptions allow for analytical results, and performance of the ESPD is seen to depend upon the signal-to-noise ratio (SNR) as well as the difference between the amplitude variances. Larger SNR and greater difference in amplitude variance result in better receiver performance, eventually leading to an asymptotic performance bound prediction.

The error‐related negativity is related to risk taking and empathy in young men

We related self-report measures of risk taking and empathy to the error-related negativity (ERN) elicited during a flanker task in boys in late adolescence. We found that risk propensity (risk taking, sensation seeking, and sensitivity to reward) and empathy related to ERN amplitude (negatively and positively, respectively) but not to each other or to behavioral measures of response time, accuracy, and post-error slowing. They accounted for separate sources of variance in the ERN amplitude, suggesting that there are multiple routes to activation of its generator in the anterior cingulate. Impulsivity and sensitivity to punishment were unrelated to the ERN. The present study provides support that risk-taking traits and empathy affect anterior cingulate responsiveness to errors, and the ERN reflects the influence of the extent of individuals' concern with the outcome of events.

On the Rate of Quantum Ergodicity for Quantised Maps

We study the distribution of expectation values and transition amplitudes for quantised maps on the torus. If the classical map is ergodic then the variance of the distribution of expectation values will tend to zero in the semiclassical limit by the quantum ergodicity theorem. Similarly the variance of transition amplitude goes to zero if the map is weak mixing. In this paper we derive estimates on the rate by which these variances tend to zero. For a class of hyperbolic maps we derive a rate which is logarithmic in the semiclassical parameter, and then show that this bound is sharp for cat maps. For a parabolic map we get an algebraic rate which again is sharp.

Top-Down Regulation of Plasticity in the Birdsong System: “Premotor” Activity in the Nucleus HVC Predicts Song Variability Better Than It Predicts Song Features

We studied real-time changes in brain activity during active vocal learning in the zebra finch songbird. The song nucleus HVC is required for the production of learned song. To quantify the relationship of HVC activity and behavior, HVC population activity during repeated vocal sequences (motifs) was recorded and temporally aligned relative to the motif, millisecond by millisecond. Somewhat surprisingly, HVC activity did not reliably predict any vocal feature except amplitude and, to a lesser extent, entropy and pitch goodness (sound periodicity). Variance in "premotor" HVC activity did not reliably predict variance in behavior. In contrast, HVC activity inversely predicted the variance of amplitude, entropy, frequency, pitch, and FM. We reasoned that, if HVC was involved in song learning, the relationship of HVC activity to learned features would be developmentally regulated. To test this hypothesis, we compared the HVC song feature relationships in adults and juveniles in the sensorimotor "babbling" period. We found that the relationship of HVC activity to variance in FM was developmentally regulated, with the greatest difference at an HVC vocalization lag of 50 ms. Collectively, these data show that, millisecond by millisecond, bursts in HVC activity predict song stability on-line during singing, whereas decrements in HVC activity predict plasticity. These relationships between neural activity and plasticity may play a role in vocal learning in songbirds by enabling the selective stabilization of parts of the song that match a learned tutor model.

Squeezed single-atom laser in a photonic crystal

We study nonclassical and spectral properties of a strongly driven single-atom laser engineered within a photonic crystal that facilitates a frequency-dependent reservoir. In these studies, we apply a dressed atom model approach to derive the master equation of the system and study the properties of the dressed laser under the frequency-dependent transition rates. By going beyond the secular approximation in the dressed-atom cavity-field interaction, we find that if, in addition, the nonsecular terms are included into the dynamics of the system, then nonlinear processes can occur that lead to interesting aspects of cavity field behavior. We calculate variances of the quadrature phase amplitudes and the incoherent part of the spectrum of the cavity field and show that they differ qualitatively from those observed under the secular approximation. In particular, it is found that the nonlinear processes lead to squeezing of the fluctuations of the cavity field below the quantum shot noise limit. The squeezing depends on the relative population of the dressed states of the system and is found only if there is no population inversion between the dressed states. Furthermore, we find a linewidth narrowing below the quantum limit in the spectrum of the cavity field that is achieved only when the secular approximation is not made. An interpretation of the linewidth narrowing is provided in terms of two phase-dependent noise (squeezing) spectra that make up the incoherent spectrum. We establish that the linewidth narrowing is due to squeezing of the fluctuations in one quadrature phase components of the cavity field.

Experimental generation of genuine four-partite entangled states with total three-party correlation for continuous variables

We experimentally prepare a type of continuous variable genuine four-partite entangled states, the quantum correlation property of which is different from that of the four-mode Greenberger-Horne-Zeilinger and cluster states, and which has not any qubit counterpart to be proposed at present. In the criterion inequalities for the full inseparability of the genuine four-partite entangled states, the amplitude and phase quadrature correlation variances totally consisting of three-party combination from the four entangled modes are involved. The measured correlation variances among the quadratures of the prepared entangled states satisfy the sufficient requirements for the full inseparability.

TH‐C‐332‐04: Comparison of Residual Motion Artifacts in Phase‐ and Amplitude‐Binned Onboard 4D‐CBCT Imaging

Purpose: Linac‐mounted 4D‐Cone Beam CT (CBCT) imaging is an important tool for extending 3D IGRT techniques to respiration‐motion synchronized treatments. Our purpose is to evaluate the effects of two different projection binning strategies, phase and amplitude binning, on the image quality of our recently implemented 4D‐CBCT method using the Varian On Board Imager and RPM breathing motion surrogate. Method and Materials: We have implemented a 4D‐CBCT imaging procedure that adjusts the acquisition parameters to the breathing period. The Varian Real‐time Position Management system (RPM) was used to establish temporal coincidence between the respiratory motion and the CBCT projections. Projections were sorted into 10 bins. For the projections sorted into each bin, the variances about the RPM amplitude and phase means was calculated and compared to the image quality achieved in CBCT images. 4D‐CBCTs were studied with a phantom with irregular motion cycle. The phantom consists of two acrylic spheres and one cylinder on a motion platform to mimic the superior‐inferior tumor motion mostly seen in patients. Results: With breathing cycle period variation but not amplitude variation, we found that amplitude binning produced fewer blurring artifacts which was consistent with RPM analysis which showed significantly smaller amplitude variances for amplitude binning. For the patient subjects, the RPM amplitude but not phase variances were smaller for amplitude binning. However, image quality was significantly better when phase binning was used. We hypothesize that the under‐sampling artifacts play a major role over the motion artifacts which is the case for amplitude binning, while the phase binning has a good control of aliasing artifacts. Residual motion artifacts persist in both phase‐ and amplitude‐ binning 4D‐CBCT images. Conclusion: Optimizing the binning strategies requires understanding complex interplay between residual motion in each bin and other factors such as uniformity and adequacy of angular sampling.Supported by PPG‐NIH‐P01116602.

Calcium-dependent Inactivation Terminates Calcium Release in Skeletal Muscle of Amphibians

In skeletal muscle of amphibians, the cell-wide cytosolic release of calcium that enables contraction in response to an action potential appears to be built of Ca2+ sparks. The mechanism that rapidly terminates this release was investigated by studying the termination of Ca2+ release underlying sparks. In groups of thousands of sparks occurring spontaneously in membrane-permeabilized frog muscle cells a complex relationship was found between amplitude a and rise time T, which in sparks corresponds to the active time of the underlying Ca2+ release. This relationship included a range of T where a paradoxically decreased with increasing T. Three different methods were used to estimate Ca2+ release flux in groups of sparks of different T. Using every method, it was found that T and flux were inversely correlated, roughly inversely proportional. A simple model in which release sources were inactivated by cytosolic Ca2+ was able to explain the relationship. The predictive value of the model, evaluated by analyzing the variance of spark amplitude, was found to be high when allowance was made for the out-of-focus error contribution to the total variance. This contribution was estimated using a theory of confocal scanning (Ríos, E., N. Shirokova, W.G. Kirsch, G. Pizarro, M.D. Stern, H. Cheng, and A. González. Biophys. J. 2001. 80:169–183), which was confirmed in the present work by simulated line scanning of simulated sparks. Considering these results and other available evidence it is concluded that Ca2+-dependent inactivation, or CDI, provides the crucial mechanism for termination of sparks and cell-wide Ca2+ release in amphibians. Given the similarities in kinetics of release termination observed in cell-averaged records of amphibian and mammalian muscle, and in spite of differences in activation mechanisms, CDI is likely to play a central role in mammals as well. Trivially, an inverse proportionality between release flux and duration, in sparks or in global release of skeletal muscle, maintains constancy of the amount of released Ca2+.

Glycinergic Transmission Shaped by the Corelease of GABA in a Mammalian Auditory Synapse

The firing pattern of neurons is shaped by the convergence of excitation and inhibition, each with finely tuned magnitude and duration. In an auditory brainstem nucleus, glycinergic inhibition features fast decay kinetics, the mechanism of which is unknown. By applying glycine to native or recombinant glycine receptors, we show that response decay times are accelerated by addition of GABA, a weak partial agonist of glycine receptors. Systematic variation in agonist exposure time revealed that fast synaptic time course may be achieved with submillisecond exposures to mixtures of glycine and GABA at physiological concentrations. Accordingly, presynaptic terminals generally contained both transmitters, and depleting terminals of GABA slowed glycinergic synaptic currents. Thus, coreleased GABA accelerates glycinergic transmission by acting directly on glycine receptors, narrowing the time window for effective inhibition. Packaging both weak and strong agonists in vesicles may be a general means by which presynaptic neurons regulate the duration of postsynaptic responses.

Exploring event‐related brain dynamics with tests on complex valued time–frequency representations

A question subject to intense debate is whether scalp-recorded event-related brain potentials are due to phase resetting of the ongoing electroencephalogram (EEG) or rather to the superimposition of time-locked components on background activity. The two hypotheses are usually assessed by means of statistics in the time-frequency domain, for example, through wavelet transformation of multiple EEG trials that yield for each time and frequency a scatter plot of complex values coefficients. Currently, intertrial phase correlation (phase locking or phase coherence) is taken as evidence for phase resetting at a given frequency and latency. Here we present a formal analysis using a complex t-statistic to illustrate that such measures are, in effect, tests for the mean vector of the repeated trials, and as such on their own are inappropriate measures of phase resetting. We also propose simple t-like statistics for testing changes in (i) the mean (presence of an event-related potential), (ii) the amplitude variance (presence of (de)synchronization) and (iii) the concentration of phases (phase locking). The first two statistics are found to be proper measures of the presence of a non-zero mean activity and induced activity, respectively. In the third case, two different tests are introduced: one based on measuring the alignment of coefficients in the complex plane and another derived from the argument that phase locking persists when the mean of the coefficients is removed. Both statistics gave unambiguous evidence of the presence of phase locking suggesting that they constitute promising tools in the analysis of event-related brain dynamics.

A Method for Projecting Functional Data Onto a Low-Dimensional Space

Functional data are intrinsically infinite-dimensional, and so dimension reduction is an attractive precursor to functional data analysis. Methods based on principal components analysis are widely used, but their value is limited by the awkwardness of interpreting the components, which are defined in a relatively abstract way. Sometimes, quantities that are nonlinear functions of the data curves are easier to interpret, and convey more information for classification and discrimination, than relatively conventional principal components. Here we illustrate this property in a particular case, by introducing four easily understood variables associated with each member of a functional dataset. These quantities represent the mean and variance of the frequency of each curve, and the mean and variance of the curve's amplitude. In fact, just two of these variables, the means, convey much of the information. These quantities can be used very effectively for clustering and classification, often with greater success than the first two principal components. A simulation study, and an application to Ramsay's classic weather-station dataset, illustrate this point.

Recent developments in visual sign language recognition

Research in the field of sign language recognition has made significant advances in recent years. The present achievements provide the basis for future applications with the objective of supporting the integration of deaf people into the hearing society. Translation systems, for example, could facilitate communication between deaf and hearing people in public situations. Further applications, such as user interfaces and automatic indexing of signed videos, become feasible. The current state in sign language recognition is roughly 30 years behind speech recognition, which corresponds to the gradual transition from isolated to continuous recognition for small vocabulary tasks. Research efforts were mainly focused on robust feature extraction or statistical modeling of signs. However, current recognition systems are still designed for signer-dependent operation under laboratory conditions. This paper describes a comprehensive concept for robust visual sign language recognition, which represents the recent developments in this field. The proposed recognition system aims for signer-independent operation and utilizes a single video camera for data acquisition to ensure user-friendliness. Since sign languages make use of manual and facial means of expression, both channels are employed for recognition. For mobile operation in uncontrolled environments, sophisticated algorithms were developed that robustly extract manual and facial features. The extraction of manual features relies on a multiple hypotheses tracking approach to resolve ambiguities of hand positions. For facial feature extraction, an active appearance model is applied which allows identification of areas of interest such as the eyes and mouth region. In the next processing step, a numerical description of the facial expression, head pose, line of sight, and lip outline is computed. The system employs a resolution strategy for dealing with mutual overlapping of the signer’s hands and face. Classification is based on hidden Markov models which are able to compensate time and amplitude variances in the articulation of a sign. The classification stage is designed for recognition of isolated signs, as well as of continuous sign language. In the latter case, a stochastic language model can be utilized, which considers uni- and bigram probabilities of single and successive signs. For statistical modeling of reference models each sign is represented either as a whole or as a composition of smaller subunits—similar to phonemes in spoken languages. While recognition based on word models is limited to rather small vocabularies, subunit models open the door to large vocabularies. Achieving signer-independence constitutes a challenging problem, as the articulation of a sign is subject to high interpersonal variance. This problem cannot be solved by simple feature normalization and must be addressed at the classification level. Therefore, dedicated adaptation methods known from speech recognition were implemented and modified to consider the specifics of sign languages. For rapid adaptation to unknown signers the proposed recognition system employs a combined approach of maximum likelihood linear regression and maximum a posteriori estimation.

Gamma oscillations in gerbil auditory cortex during a target-discrimination task reflect matches with short-term memory

Tightly stimulus-locked “evoked” and not tightly stimulus-locked “induced” gamma-band oscillations have been implicated in a variety of cognitive functions as well as more basic stimulus-related aspects of neuronal activity. The present study aimed at dissociating both aspects using a preparation in rodents trained to perform in a target-discrimination task while recording the intracerebral electrocorticogram in parallel from left and right auditory cortex. While stimulus-related aspects of gamma-band activity were already evident in the naïve subjects, aspects related to successful target-discrimination only emerged with learning. Frequency-modulated tones were employed as stimuli and were varied with respect to two stimulus dimensions, viz. “spectral content” and “modulation direction”. A target stimulus had to be discriminated in a GO/(NO-GO) paradigm from three non-target stimuli matching the target in only one or none of these dimensions. Analysis of the event-related potentials indicated that the physical stimulus parameters explained most of the variance in amplitude of most event-related potential components. For the evoked gamma-band activity no learning related modulations were found. The induced gamma-band activity showed a relationship with the similarity of a stimulus with the target that was most prominent in the right hemisphere. The correspondence between task-specific behavior and the amplitude of induced gamma-band activity, both developing with learning, supports a functional relevance of this form of oscillation beyond merely processing physical stimulus attributes.

Calcium signaling in vasopressin-induced aquaporin-2 trafficking

It has been the general consensus that cAMP-mediated PKA-dependent phosphorylation of aquaporin-2 is the primary mechanism of vasopressin to regulate osmotic water permeability in kidney collecting duct. By using laser scanning confocal microscopy to monitor [Ca2+]i and apical exocytosis in individual cells of inner medullary collecting duct, we have demonstrated that vasopressin also triggers intracellular Ca2+ mobilization, which is coupled to apical exocytotic insertion of aquaporin-2. Vasopressin-induced Ca2+ mobilization is in the form of oscillations, which involves both intracellular Ca2+ release from ryanodine-gated Ca2+ stores and extracellular Ca2+ influx via capacitative calcium entry. Each individual cell operates as an independent calcium oscillator with time variance in frequency and amplitude. Vasopressin-induced Ca2+ mobilization is mediated by cAMP, but is independent of PKA. Exogenous cAMP analog (8-pCPT-2'-O-Me-cAMP), which activates Epac (exchange protein directly activated by cAMP), but not PKA, triggers Ca2+ mobilization and apical exocytosis. These observations suggest that activation of Epac by cAMP may also contribute to the action of vasopressin in regulating osmotic water permeability. There are multiple plausible candidates for downstream effectors of vasopressin-induced Ca2+ signal including calmodulin, myosin light chain kinase, calmodulin kinase II, and calcineurin. All of them have been implicated in the regulation of aquaporin-2 trafficking and/or water permeability.

Estimation techniques for GMSK using linear detectors in satellite communications

This paper describes data-aided signal level and noise variance estimators for Gaussian minimum shift keying (GMSK) when the observations are limited to the output of a filter matched to the first pulse-amplitude modulation (PAM) pulse in the equivalent PAM representation. The estimators are based on the maximum likelihood (ML) principle and assume burst-mode transmission with known timing and a block of L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> known bits. While it is well known that ML estimators are asymptotically unbiased and efficient, the analysis quantifies the rate at which the estimators approach these asymptotic properties. It is shown that the carrier phase, amplitude, and noise variance estimators are unbiased and can achieve their corresponding Cramer-Rao bounds with modest combinations of signal-to-noise ratio and observation length. The estimates are used to estimate the signal-to-noise ratio. It is shown that the mean squared error performance of the ratio increases with signal-to-noise ratio while the mean squared error performance of the ratio in decibels decreases with signal-to-noise ratio. Simulation results are provided to confirm the accuracy of the analytic results.

Effects of Fourier-plane amplitude and phase errors on image reconstruction I Small amplitude errors

The effects of Fourier-plane, or spectral, amplitude and phase errors on reconstructed images are studied in terms of the expected mean square error in the image. The relationship between the variance of amplitude and phase errors and the expected mean square error is derived for small amplitude errors and arbitrarily large phase errors. This allows "equivalent" amplitude and phase errors to be defined. The effects of large amplitude errors are discussed in general terms. Simulations are used to verify these relationships, and the effects of spectral amplitude and phase errors on reconstructed images are compared.

Repolarization variability in the risk stratification of MADIT II patients

QT variability has been reported to be associated with ventricular arrhythmias and sudden cardiac death. There is limited data regarding variability in T-wave morphology and its prognostic value. In this study, we present a novel approach for the measurement of T-wave variability (TWV) reflecting changes in T-wave morphology, and we investigate the prognostic significance of Holter-derived TWV in patients with and without ventricular arrhythmias requiring appropriate implantable cardioverter defibrillator (ICD) therapy from the Multicenter Automatic Defibrillator Implantation Trial II (MADIT II). Methods Study population consisted of 275 ICD patients from MADIT II after excluding patients with intraventricular conduction abnormalities or atrial fibrillation. TWV was measured based on amplitude variance of T-wave amplitude. Results During 2-year follow-up, 58 (21%) patients had appropriate ICD therapy for ventricular tachycardia or fibrillation. Patients with appropriate ICD therapy had higher levels of TWV measures than those without arrhythmic events. After adjustment for heart rate, ejection fraction, and significant clinical predictors of arrhythmic events, a Cox proportional-hazards regression model revealed that dichotomized TWV values were predictive for ventricular tachyarrhythmias requiring appropriate ICD therapy (hazard ratio, 2.0; 95% CI; 1.2-3.5; P=0.01). On the basis of the comprehensive testing, TWV value >59 microV was found predictive for arrhythmic events in MADIT II population. Our newly designed method for the assessment of repolarization variability in ambulatory Holter recordings detected transient variability of T-wave morphology, which was predictive for ventricular tachyarrhythmias in the MADIT II population.

Saccades to the seeing visual hemifield in hemidecorticate patients exhibit task-dependent reaction times and hypometria

In three patients who had one cortical hemisphere removed surgically (hemidecortication), we studied visually-triggered saccades directed contralateral to the intact cortical hemisphere (i.e., ipsilesional saccades). Both saccade reaction times (SRTs) and accuracy of these saccades have been reported as abnormal in hemidecorticate patients, but not monkeys. One explanation for this difference is that deficits in hemidecorticate patients may not have been directly caused by removal of cortical oculomotor structures themselves, but may have been a manifestation of compensatory strategies used to cope with contralesional hemianopia. We hypothesized that deficits in saccade performance to the ipsilesional (seeing) visual hemifield would be directly linked to how easily patients could localize targets in their blind hemifield with searching saccades. To test this hypothesis, we examined how deficits in our patients varied when targets were: (1) randomly presented to either the seeing or blind hemifield for long durations thereby permitting searching saccades in the blind hemifield; (2) presented as in Experiment 1, but briefly flashed thereby removing visual feedback prior to saccade onset thereby rendering searching saccades useless; (3) briefly flashed as in Experiment 2, but at random locations in only the seeing hemifield (blind hemifield irrelevant). Mean SRTs to the seeing hemifield were 165 ms longer than normal in Experiment 2, but only about 40 ms longer in Experiments 1 and 3. Saccade accuracy was characterized by task-dependent hypometria in all three experiments with a mean undershoot of about twice the amplitude variance. The largest undershoots were in Experiments 2 and 3. Our data suggest that deficits resulted from the direct effects of the lesions themselves coupled with context-dependent strategies used to cope with contralesional hemianopia.