Learning and generalization on five basic auditory discrimination tasks as assessed by threshold changes

Wright, Beverly A.; Fitzgerald, Matthew B.

doi:10.1007/0-387-27045-0_62

Cited by 15 publications

(17 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As expected from previous results in the perceptual learning literature (Tremblay et al, 1997;Irvine et al, 2000;Delhommeau et al, 2002;Demany and Semal, 2002;Hawkey et al, 2004;Amitay et al, 2005;Wright and Fitzgerald, 2005;van Wassenhove and Nagarajan, 2007;Halliday et al, 2008), thresholds for these highly experienced individuals were substantially lower. However, they showed a similarly large impact of protocol as inexperienced participants (Fig.…”

Section: Behavioral Experimentssupporting

confidence: 87%

From Comparison to Classification: A Cortical Tool for Boosting Perception

Nahum¹,

Daikhin²,

Lubin³

et al. 2010

J. Neurosci.

View full text Add to dashboard Cite

Humans are much better in relative than in absolute judgments. This common assertion is based on findings that discrimination thresholds are much lower when measured with methods that allow interstimuli comparisons than when measured with methods that require classification of one stimulus at a time and are hence sensitive to memory load. We now challenged this notion by measuring discrimination thresholds and evoked potentials while listeners performed a two-tone frequency discrimination task. We tested various protocols that differed in the pattern of cross-trial tone repetition. We found that best performance was achieved only when listeners effectively used cross-trial repetition to avoid interstimulus comparisons with the repeated reference tone. Instead, they classified one tone, the nonreference tone, as either high or low by comparing it with a recently formed internal reference. Listeners were not aware of the switch from interstimulus comparison to classification. Its successful use was revealed by the conjunction of improved behavioral performance and an event-related potential component (P3), indicating an implicit perceptual decision, which followed the nonreference tone in each trial. Interestingly,tonerepetitionitselfdidnotsufficefortheswitch,implyingthatthebottlenecktodiscriminationdoesnotresideatthelower,sensorystage. Rather, the temporal consistency of repetition was important, suggesting the involvement of higher-level mechanisms with longer time constants. These findings suggest that classification is based on more automatic and accurate mechanisms than interstimulus comparisons and that the ability to effectively use them depends on a dynamic interplay between higher-and lower-level cortical mechanisms.

show abstract

Section: Behavioral Experimentssupporting

confidence: 87%

From Comparison to Classification: A Cortical Tool for Boosting Perception

Nahum¹,

Daikhin²,

Lubin³

et al. 2010

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Wright and colleagues (e.g., Wright et al, 1997;Wright, 2001;Fitzgerald and Wright, 2005;Wright and Fitzgerald, 2005;Wright and Sabin, 2007) have extensively explored fundamental aspects of learning using relatively simple stimuli and perceptual tasks, allowing for good experimental control. Of course, speech perception by the impaired auditory system involves greater complexity, both in terms of stimuli and perception.…”

Section: Remaining Challenges In Auditory Training For CI Usersmentioning

confidence: 99%

Maximizing cochlear implant patients’ performance with advanced speech training procedures

2008

View full text Add to dashboard Cite

Advances in implant technology and speech processing have provided great benefit to many cochlear implant patients. However, some patients receive little benefit from the latest technology, even after many years' experience with the device. Moreover, even the best cochlear implant performers have great difficulty understanding speech in background noise, and music perception and appreciation remain major challenges. Recent studies have shown that targeted auditory training can significantly improve cochlear implant patients' speech recognition performance. Such benefits are not only observed in poorly performing patients, but also in good performers under difficult listening conditions (e.g., speech noise, telephone speech, music, etc.). Targeted auditory training has also been shown to enhance performance gains provided by new implant devices and/or speech processing strategies. These studies suggest that cochlear implantation alone may not fully meet the needs of many patients, and that additional auditory rehabilitation may be needed to maximize the benefits of the implant device. Continuing research will aid in the development of efficient and effective training protocols and materials, thereby minimizing the costs (in terms of time, effort and resources) associated with auditory rehabilitation while maximizing the benefits of cochlear implantation for all recipients.

show abstract

“…However, because the number of trials in experiment 1 was not sufficient for the non-musicians to achieve an optimal level of performance, a second experiment was performed, which involved protracted training in eight additional nonmusician listeners, using one of the stimulus conditions from experiment 1. Although several earlier studies have documented long-term training effects in frequency discrimination in non-musicians (Amitay et al, 2005;AriEven Roth et al, 2003, 2004Campbell and Small, 1963;Delhommeau et al, 2002Delhommeau et al, , 2005Demany, 1985;Demany and Semal, 2002;Grimault et al, 2002Grimault et al, , 2003Irvine et al, 2000;Wright and Fitzgerald, 2005), we reasoned that documenting learning effects in non-musicians using the same stimuli and test procedure as in one of the conditions 1 The notion that the listeners' initial lack of familiarity with the procedure and/or stimuli could lead to an under-estimation of the actual difference in sensory discrimination abilities between musicians and nonmusicians can be understood in terms of a signal-detection-theoretic model (Green and Swets, 1966) wherein frequency discrimination performance is limited by two types of additive sources of internal noise: ''sensory'' noise, which imposes an absolute upper limit on frequency discrimination abilities and is smaller in musicians than in non-musicians, and ''cognitive'' noise, which reflects the listeners' lack of familiarity with the specifics of the procedure and stimuli, and is the same for musicians and non-musicians. Under this model, the mean frequency discrimination threshold of the musicians can be expressed as h m / ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi s 2 m þ c 2 p , and that of the non-musicians as h n / ffiffiffiffiffiffiffiffiffiffiffiffiffiffi s 2 n þ c 2 p , where s 2 and c 2 denote the variance of the sensory and cognitive noises, respectively, the subscripts m and n refer to musicians and non-musicians, respectively, and µ is used to indicate a proportionality relationship.…”

Section: Introductionmentioning

confidence: 97%