Effects of timbre and tempo change on memory for music

We investigated the effects of different encoding tasks and of manipulations of two supposedly surface parameters of music on implicit and explicit memory for tunes. In two experiments, participants were first asked to either categorize instrument or judge familiarity of 40 unfamiliar short tunes. Subsequently, participants were asked to give explicit and implicit memory ratings for a list of 80 tunes, which included 40 previously heard. Half of the 40 previously heard tunes differed in timbre (Experiment 1) or tempo (Experiment 2) in comparison with the first exposure. A third experiment compared similarity ratings of the tunes that varied in timbre or tempo. Analysis of variance (ANOVA) results suggest first that the encoding task made no difference for either memory mode. Secondly, timbre and tempo change both impaired explicit memory, whereas tempo change additionally made implicit tune recognition worse. Results are discussed in the context of implicit memory for nonsemantic materials and the possible differences in timbre and tempo in musical representations.

Perception of emotion in sounded and imagined music

WE STUDIED THE EMOTIONAL RESPONSES BY MUSICIANS to familiar classical music excerpts both when the music was sounded, and when it was imagined.We used continuous response methodology to record response profiles for the dimensions of valence and arousal simultaneously and then on the single dimension of emotionality. The response profiles were compared using cross-correlation analysis, and an analysis of responses to musical feature turning points, which isolate instances of change in musical features thought to influence valence and arousal responses. We found strong similarity between the use of an emotionality arousal scale across the stimuli, regardless of condition (imagined or sounded). A majority of participants were able to create emotional response profiles while imagining the music, which were similar in timing to the response profiles created while listening to the sounded music.We conclude that similar mechanisms may be involved in the processing of emotion in music when the music is sounded and when imagined.

Aging and memory for music: A review

People of all ages enjoy listening to music, yet most research in musical development has concentrated on infancy through childhood. Our recent research program examined various aspects of music cognition in younger (ages 18 through 30) and older adults (ages 60 through 80) with varying amounts of musical experience. The studies investigated the independent and combined influences of age and experience on a wide assortment of long and short-term memory tasks. Results showed that some musical tasks reflect the same age-related declines as seen in nonmusical tasks, and musical training does not reduce these age-related declines. In other tasks, experience differences were larger than age differences; in some cases, age differences were nonexistent. The analysis considers how aging and experience may affect different aspects of cognition, and the paper concludes by pointing out the many musical activities that even nonmusical seniors are well equipped to succeed at and enjoy.

Pedagogical techniques and student outcomes in applied instrumental lessons taught by experienced and pre-service American music teachers.

The purpose of the study was to examine the effect of teacher experience on student progress and performance quality in an introductory applied lesson. Nine experienced teachers and 15 pre-service teachers taught an adult beginner to play ‘Mary Had a Little Lamb’ on a wind instrument. The lessons were videotaped for subsequent analysis of teaching behaviors and performance achievement. Following instruction, a random sample of teachers was interviewed about their perceptions of the lesson. A panel of adjudicators rated final pupil performances. No significant difference was found between pupils taught by experienced and pre-service teachers in the quality of their final performance. Systematic observation of the videotaped lessons showed that participant teachers provided relatively frequent and highly positive reinforcement during the lessons. Pupils of experienced teachers talked significantly more during the lessons than did pupils of pre-service teachers. Pre-service teachers modeled significantly more on their instruments than did experienced teachers.

Music, perceived arousal, and intensity: psychophysiological reactions to Chopin's "Tristesse"

The present study investigates the relation of perceived arousal (continuous self-rating), autonomic nervous system activity (heart rate, heart rate variability) and musical characteristics (sound intensity, musical rhythm) upon listening to a complex musical piece. Twenty amateur musicians listened to two performances of Chopin's "Tristesse" with different rhythmic shapes. Besides conventional statistical methods for analyzing psychophysiological reactions (heart rate, respiration rate) and musical variables, semblance analysis was used. Perceived arousal correlated strongly with sound intensity; heart rate showed only a partial response to changes in sound intensity. Larger changes in heart rate were caused by the version with more rhythmic tension. The low-/high-frequency ratio of heart rate variability increased-whereas the high frequency component decreased-during music listening. We conclude that autonomic nervous system activity can be modulated not only by sound intensity but also by the interpreter's use of rhythmic tension. Semblance analysis enables us to track the subtle correlations between musical and physiological variables.

High-resolution esophageal long-term ECG allows detailed atrial wave morphology analysis in case of atrial ectopic beats

Detection of arrhythmic atrial beats in surface ECGs can be challenging when they are masked by the R or T wave, or do not affect the RR-interval. Here, we present a solution using a high-resolution esophageal long-term ECG that offers a detailed view on the atrial electrical activity. The recorded ECG shows atrial ectopic beats with long coupling intervals, which can only be successfully classified using additional morphology criteria. Esophageal high-resolution ECGs provide this information, whereas surface long-term ECGs show poor atrial signal quality. This new method is a promising tool for the long-term rhythm monitoring with software-based automatic classification of atrial beats.

Comparative Analysis of Russian and French Prosodies: Theoretical, Experimental and Applied Aspects"

Experience shows that in teaching the pronunciation of a foreign language, it is the native syllable stereotype that resists correction most strongly. This is because the syllable is the basic unit of the perception and production of speech, and syllabic production is highly automatic and to some degree determines the prosody of speech at all levels: accent, rhythm, phrase, etc. The results of psycho-physiological studies show that the human acoustic analyser is a typical contemplator organ and new acoustic qualities are perceived through their inclusion into the already existing system of values characteristic to the mother tongue. This results in the adaptation of the perception and so production of foreign speech to native patterns. The less conscious the perception of the unit and the more 'primitive' its status, the greater the degree of its auditory assimilation, and the syllable is certainly among the less controllable linguistic units. The group carried out a complex investigation of the French and Russian languages at the level of syllable realisation, focusing on the stressed syllable of both open and closed types. The useful acoustic characteristics of the French/Russian syllable pattern were determined through identifying a typical syllable pattern within the system of each of the two languages, comparing these patterns to establish their contrasting features, and observing and systematising deviations from the pattern typical of the French/Russian language teaching situation. The components of the syllable pattern shown to need particular attention in teaching French pronunciation to Russian native speakers were intensity, fundamental frequency, and duration. The group then developed a method of correction which combines the auditory and visual canals of sound signal perception and tested this method with groups of Russian students of different levels.

Application of headspace solid phase microextraction to qualitative and quantitative analysis of tobacco additives in cigarettes

Cigarettes may contain up to 10% by weight additives which are intended to make them more attractive. A fast and rugged method for a cigarette-screening for additives with medium volatility was developed using automatic headspace solid phase microextraction (HS-SPME) with a 65 microm carbowax-divinylbenzene fiber and gas chromatography-mass spectrometry (GC-MS) with standard electron impact ionisation. In three runs, each cigarette sample was extracted in closed headspace vials using basic, acidic and neutral medium containing 0.5 g NaCl or Na2SO4. Furthermore, the method was optimized for quantitative determination of 17 frequently occurring additives. The practical applicability of the method was demonstrated for cigarettes from 32 brands.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Semi-automatic segmentation of fetal cardiac cavities: progress towards an automated fetal echocardiogram

OBJECTIVE: To develop a novel application of a tool for semi-automatic volume segmentation and adapt it for analysis of fetal cardiac cavities and vessels from heart volume datasets. METHODS: We studied retrospectively virtual cardiac volume cycles obtained with spatiotemporal image correlation (STIC) from six fetuses with postnatally confirmed diagnoses: four with normal hearts between 19 and 29 completed gestational weeks, one with d-transposition of the great arteries and one with hypoplastic left heart syndrome. The volumes were analyzed offline using a commercially available segmentation algorithm designed for ovarian folliculometry. Using this software, individual 'cavities' in a static volume are selected and assigned individual colors in cross-sections and in 3D-rendered views, and their dimensions (diameters and volumes) can be calculated. RESULTS: Individual segments of fetal cardiac cavities could be separated, adjacent segments merged and the resulting electronic casts studied in their spatial context. Volume measurements could also be performed. Exemplary images and interactive videoclips showing the segmented digital casts were generated. CONCLUSION: The approach presented here is an important step towards an automated fetal volume echocardiogram. It has the potential both to help in obtaining a correct structural diagnosis, and to generate exemplary visual displays of cardiac anatomy in normal and structurally abnormal cases for consultation and teaching.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

A Surface Displacement Analysis for Volcan Pacaya from October 2001 through March 2013 by Means of 3-D Modeling of Precise Position GPS Data

Volcán Pacaya is one of three currently active volcanoes in Guatemala. Volcanic activity originates from the local tectonic subduction of the Cocos plate beneath the Caribbean plate along the Pacific Guatemalan coast. Pacaya is characterized by generally strombolian type activity with occasional larger vulcanian type eruptions approximately every ten years. One particularly large eruption occurred on May 27, 2010. Using GPS data collected for approximately 8 years before this eruption and data from an additional three years of collection afterwards, surface movement covering the period of the eruption can be measured and used as a tool to help understand activity at the volcano. Initial positions were obtained from raw data using the Automatic Precise Positioning Service provided by the NASA Jet Propulsion Laboratory. Forward modeling of observed 3-D displacements for three time periods (before, covering and after the May 2010 eruption) revealed that a plausible source for deformation is related to a vertical dike or planar surface trending NNW-SSE through the cone. For three distinct time periods the best fitting models describe deformation of the volcano: 0.45 right lateral movement and 0.55 m tensile opening along the dike mentioned above from October 2001 through January 2009 (pre-eruption); 0.55 m left lateral slip along the dike mentioned above for the period from January 2009 and January 2011 (covering the eruption); -0.025 m dip slip along the dike for the period from January 2011 through March 2013 (post-eruption). In all bestfit models the dike is oriented with a 75° westward dip. These data have respective RMS misfit values of 5.49 cm, 12.38 cm and 6.90 cm for each modeled period. During the time period that includes the eruption the volcano most likely experienced a combination of slip and inflation below the edifice which created a large scar at the surface down the northern flank of the volcano. All models that a dipping dike may be experiencing a combination of inflation and oblique slip below the edifice which augments the possibility of a westward collapse in the future.

Automatic algorithm for monitoring systolic pressure variation and difference in pulse pressure

BACKGROUND: Difference in pulse pressure (dPP) reliably predicts fluid responsiveness in patients. We have developed a respiratory variation (RV) monitoring device (RV monitor), which continuously records both airway pressure and arterial blood pressure (ABP). We compared the RV monitor measurements with manual dPP measurements. METHODS: ABP and airway pressure (PAW) from 24 patients were recorded. Data were fed to the RV monitor to calculate dPP and systolic pressure variation in two different ways: (a) considering both ABP and PAW (RV algorithm) and (b) ABP only (RV(slim) algorithm). Additionally, ABP and PAW were recorded intraoperatively in 10-min intervals for later calculation of dPP by manual assessment. Interobserver variability was determined. Manual dPP assessments were used for comparison with automated measurements. To estimate the importance of the PAW signal, RV(slim) measurements were compared with RV measurements. RESULTS: For the 24 patients, 174 measurements (6-10 per patient) were recorded. Six observers assessed dPP manually in the first 8 patients (10-min interval, 53 measurements); no interobserver variability occurred using a computer-assisted method. Bland-Altman analysis showed acceptable bias and limits of agreement of the 2 automated methods compared with the manual method (RV: -0.33% +/- 8.72% and RV(slim): -1.74% +/- 7.97%). The difference between RV measurements and RV(slim) measurements is small (bias -1.05%, limits of agreement 5.67%). CONCLUSIONS: Measurements of the automated device are comparable with measurements obtained by human observers, who use a computer-assisted method. The importance of the PAW signal is questionable.