Evaluation of Auditory Stream Segregation in Musicians and Nonmusicians

Abstract Introduction One of the major cues that help in auditory stream segregation is spectral profiling. Musicians are trained to perceive a fine structural variation in the acoustic stimuli and have enhanced temporal perception and speech perception in noise. Objective To analyze the differences in spectral profile thresholds in musicians and nonmusicians. Methods The spectral profile analysis threshold was compared between 2 groups (musicians and nonmusicians) in the age range between 15 and 30 years old. The stimuli had 5 harmonics, all at the same amplitude (f0 = 330 Hz, mi4). The third (variable tone) has a similar harmonic structure; however, the amplitude of the third harmonic component was higher, producing a different timbre in comparison with the standards. The subject had to identify the odd timbre tone. The testing was performed at 60 dB HL in a sound-treated room. Results The results of the study showed that the profile analysis thresholds were significantly better in musicians compared with nonmusicians. The result of the study also showed that the profile analysis thresholds were better with an increase in the duration of music training. Thus, improved auditory processing in musicians could have resulted in a better profile analysis threshold. Conclusions Auditory stream segregation was found to be better in musicians compared with nonmusicians, and the performance improved with an increase in several years of training. However, further studies are essential on a larger group with more variables for validation of the results.

Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images.

Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2>0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique’s general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6−11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies’ spectral profiles. Future aspects of this technique are discussed herein.

Usefulness of Occipital EEG Spectral Profile in the Differential Diagnosis of Alzheimer Type and Vascular Dementia

BACKGROUND: Alzhiemeranjx disease (AD) and vascular dementia (VD) are common types of dementia. As a result of the development of new specific agents for AD, and because vascular dementia is a potentially preventable dementia, differentiating these diseases is of great importance. The role of EEG spectral analysis in the differential diagnosis between Alzheimer type and vascular dementia is still controversial. Since there have been few studies concerning the differential diagnosis of dementia by EEG, the present study has focused on this aspect. Usefulness of EEG in differen-tial diagnosis of dementia will be elucidated by clarifying relationship between type of dementia and spectral profile of EEG. METHODS: We analyzed the power spectra taken from 16 derivations and spectral profile was constructed by averaging twenty 2 sec epochs in three study groups (normal controls, AD and VD). Spectral profile was divided into three groups; (I) type A, showing a dominant 6.5-12 Hz peak (ii) type B, lacking a dominant peak in the 6.5-12 Hz (iii) type C, corresponding to a flat, low voltage, spectrum. To elucidate the relationship between spectral profile and other factors including diagnosis, statistical test was done. RESULTS: (1) In AD, type C profile was statistically more prevalent than in VD and type A profile was reversed. (2) In AD, Mini-Mental State Examination (MMSE) score was statistically lower in type C profile. (3) Spectral profile was not associated with age, age of symptom onset, and symptom duration. CONCLUSIONS: This study suggested that spectral profile is a useful tool for the differential diagnosis of dementia (AD and VD) and correlated with the severity of disease in AD.