Related Experiment Video
Updated: Dec 27, 2025
09:23
A Low Cost Setup for Behavioral Audiometry in Rodents
Published on: October 16, 2012
13.1K
Transition bandwidths for stimuli with sparse spectral densities (L)
Matthew D Turner1, Bruce G Berg1
1Department of Cognitive Sciences, University of California Irvine, Irvine, California 92697-5100, USA.
The Journal of the Acoustical Society of America
|March 2, 2020
Summary
Individual differences in transition bandwidths are substantial. This bandwidth shifts from temporal to spectral processing when stimuli allow across-channel comparisons, even with large frequency differences.
Area of Science:
- Auditory perception
- Psychoacoustics
- Signal processing
Background:
- Transition bandwidths are key metrics in psychoacoustic experiments, revealing how listeners discriminate auditory stimuli.
- These bandwidths show significant individual variability and are linked to changes in auditory processing strategies.
Purpose of the Study:
- To investigate the characteristics of transition bandwidths in auditory discrimination.
- To determine the relationship between transition bandwidths and spectral/temporal processing.
- To explore the influence of stimulus properties on the transition from temporal to spectral analysis.
Main Methods:
- Utilizing band-widening discrimination experiments to measure transition bandwidths.
- Analyzing threshold functions to identify peaks corresponding to transition bandwidths.
- Varying spectral density and frequency differences to assess their impact on transition bandwidths.
Main Results:
- Observed a tenfold range in individual differences for transition bandwidths.
- Found that transition bandwidths are unaffected by spectral density, tolerating frequency differences up to 400 Hz.
- Demonstrated an automatic shift from temporal to spectral processing (profile analysis) when stimuli enable across-channel comparisons.
Conclusions:
- Transition bandwidths are robust to spectral variations, suggesting early peripheral filtering distinguishes spectral and temporal cues.
- The findings support models where spectral and temporal auditory processing are separated early in the auditory system.
- Auditory processing strategies adapt based on stimulus complexity, transitioning to across-channel analysis for widerband signals.
Related Concept Videos
01:17Bandpass Sampling
433
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
433
01:15Sampling Theorem
1.2K
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
1.2K
01:08IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations
1.7K
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
1.7K
01:04¹³C NMR: ¹H–¹³C Decoupling
1.6K
The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
1.6K
01:19Expected Frequencies in Goodness-of-Fit Tests
6.7K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).
6.7K
01:24IR Frequency Region: X–H Stretching
1.3K
In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of 2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
1.3K