Estimating Gap Detection Threshold and Comodulation Masking Release (Uncomodulated Noise Bands) on Android

2018 ◽  
Author(s):  
Gaurang Prasad ◽  
Sampath Kumar ◽  
M. M Kishan ◽  
K.S Hareesha ◽  
Poornima Kundapur
Keyword(s):  
Detection Threshold ◽  
Gap Detection ◽  
Masking Release ◽  
Comodulation Masking Release

Masking release for gap detection

1992 ◽  
Vol 336 (1278) ◽  
pp. 331-337 ◽  
Keyword(s):  
Random Noise ◽  
Detection Threshold ◽  
Signal Frequency ◽  
Frequency Noise ◽  
Gap Detection ◽  
Noise Masking ◽  
Level Difference ◽  
Masking Release ◽  
Masking Level Difference ◽  
Release From Masking

In random noise, masking is influenced almost entirely by noise components in a narrow band around the signal frequency. However, when the noise is not random, but has a modulation pattern which is coherent across frequency, noise components relatively remote from the signal frequency can actually produce a release from masking. This masking release has been called comodulation masking release (CMR). The present research investigated whether a similar release from masking occurs in the analysis of a suprathreshold signal. Specifically, the ability to detect the presence of a temporal gap was investigated in conditions which do and do not result in CMR for detection threshold. Similar conditions were investigated for the masking level difference (a binaural masking release phenomenon). The results indicated that suprathreshold masking release for gap detection occurred for both the masking-level difference (MLD) and for CMR. However, masking release for gap detection was generally smaller than that obtained for detection threshold. The largest gap detection masking release effects obtained corresponded to relatively low levels of stimulation, where gap detection was relatively poor.

Comodulation masking release in an off-frequency masking paradigm

2015 ◽  
Vol 138 (2) ◽  
pp. 1194-1205
Author(s):  
Ramona Grzeschik ◽  
Björn Lübken ◽  
Jesko L. Verhey
Keyword(s):  
Masking Release ◽  
Comodulation Masking Release

Disrupting within-channel cues to comodulation masking release

2011 ◽  
Vol 129 (5) ◽  
pp. 3181-3193 ◽  
Author(s):  
Simon A. Goldman ◽  
Thomas Baer ◽  
Brian C. J. Moore
Keyword(s):  
Masking Release ◽  
Comodulation Masking Release

Comodulation masking release for three types of modulator as a function of modulation rate

1989 ◽  
Vol 42 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Robert P. Carlyon ◽  
Søren Buus ◽  
Mary Florentine
Keyword(s):  
Masking Release ◽  
Comodulation Masking Release ◽  
Modulation Rate

Comodulation masking release in a songbird

1995 ◽  
Vol 87 (1-2) ◽  
pp. 157-164 ◽  
Author(s):  
G.M. Klump ◽  
U. Langemann
Keyword(s):  
Masking Release ◽  
Comodulation Masking Release

N1-P2 Recordings to Gaps in Broadband Noise

2013 ◽  
Vol 24 (01) ◽  
pp. 037-045 ◽  
Author(s):  
Shannon B. Palmer ◽  
Frank E. Musiek
Keyword(s):  
Temporal Resolution ◽  
Repeated Measures ◽  
Evoked Potential ◽  
Detection Threshold ◽  
Normal Hearing ◽  
Broadband Noise ◽  
Gap Detection ◽  
Electrophysiological Response ◽  
Repeated Measures Design ◽  
Waveform Amplitude

Background: Normal temporal processing is important for the perception of speech in quiet and in difficult listening situations. Temporal resolution is commonly measured using a behavioral gap detection task, where the patient or subject must participate in the evaluation process. This is difficult to achieve with subjects who cannot reliably complete a behavioral test. However, recent research has investigated the use of evoked potential measures to evaluate gap detection. Purpose: The purpose of the current study was to record N1-P2 responses to gaps in broadband noise in normal hearing young adults. Comparisons were made of the N1 and P2 latencies, amplitudes, and morphology to different length gaps in noise in an effort to quantify the changing responses of the brain to these stimuli. It was the goal of this study to show that electrophysiological recordings can be used to evaluate temporal resolution and measure the influence of short and long gaps on the N1-P2 waveform. Research Design: This study used a repeated-measures design. All subjects completed a behavioral gap detection procedure to establish their behavioral gap detection threshold (BGDT). N1-P2 waveforms were recorded to the gap in a broadband noise. Gap durations were 20 msec, 2 msec above their BGDT, and 2 msec. These durations were chosen to represent a suprathreshold gap, a near-threshold gap, and a subthreshold gap. Study Sample: Fifteen normal-hearing young adult females were evaluated. Subjects were recruited from the local university community. Data Collection and Analysis: Latencies and amplitudes for N1 and P2 were compared across gap durations for all subjects using a repeated-measures analysis of variance. A qualitative description of responses was also included. Results: Most subjects did not display an N1-P2 response to a 2 msec gap, but all subjects had present clear evoked potential responses to 20 msec and 2+ msec gaps. Decreasing gap duration toward threshold resulted in decreasing waveform amplitude. However, N1 and P2 latencies remained stable as gap duration changed. Conclusions: N1-P2 waveforms can be elicited by gaps in noise in young normal-hearing adults. The responses are present as low as 2 msec above behavioral gap detection thresholds (BGDT). Gaps that are below BGDT do not generally evoke an electrophysiological response. These findings indicate that when a waveform is present, the gap duration is likely above their BGDT. Waveform amplitude is also a good index of gap detection, since amplitude decreases with decreasing gap duration. Future studies in this area will focus on various age groups and individuals with auditory disorders.

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