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Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns

View Article: PubMed Central - PubMed

ABSTRACT

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10− and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities.

Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.

Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.

Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.

Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

No MeSH data available.


Discrimination performance for intact learned target CNs vs. novel CNs in the testing session. (A) Relationship between discrimination rates of learned target and novel CNs in each participant. Participants above the diagonal show higher rates for learned vs. novel CNs, suggesting that memory facilitated the discrimination task. (B) Discrimination rates of learned target and novel CNs over time (10 blocks).
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Figure 4: Discrimination performance for intact learned target CNs vs. novel CNs in the testing session. (A) Relationship between discrimination rates of learned target and novel CNs in each participant. Participants above the diagonal show higher rates for learned vs. novel CNs, suggesting that memory facilitated the discrimination task. (B) Discrimination rates of learned target and novel CNs over time (10 blocks).

Mentions: Participants performed the testing session a month after the learning session (mean interval 30.96 ± 4.2 days, range 23–41 days). In the testing session, discrimination sensitivity (a' testing) again did not vary between versions 1 and 2 of the experiment [F(1, 25) = 0.0057, p = 0.94] and therefore these data were pooled (n = 25). Detection of cyclicity in novel CNs did not change across the two sessions [Mean difference = 0.58, SE = 3.8, t(25) = 0.15, p = 0.8803] indicating that participants' performance in the task was similar over the 4 weeks. Furthermore, the number of times a participant performed each training stage during the learning session had no effect on the discrimination performance during the testing session (a' testing): training stage 1 [F(1, 25) = 0.09, p = 0.75], training stage 2 [F(1, 25) = 1.98, p = 0.17] and training stage 3 [F(1, 25) = 0.03, p = 0.86]. Within the testing session, discrimination rates were significantly higher for learned target CNs compared to novel CNs [F(1, 25) = 7.03, p < 0.014] (Figure 4A). This suggests that participants had memory for the CNs previously learned in the first session. Furthermore, to ensure that this higher discrimination rate for learned target CNs did not result from learning of features throughout the testing session (as opposed to long-term memory for features from the first session), the evolution of discrimination rates for learned vs. new CNs was analyzed over time. A two-way repeated-measures ANOVA on discrimination rates was computed, testing main effects and interaction of within-subjects factors “trial type” (2 levels, “learned target CN” and “novel CN”) and “block” (10 levels). Trial type was the only significant predictor of performance [F(1, 200) = 313.696, p < 0.0001] irrespective of block [F(9, 200) = 1.57, p = 0.127]. The effect of trial type was equivalent across blocks [F(9, 200) = 1.06, p = 0.394]. These results were confirmed by the absence of correlation between hit rate for learned and novel CNs over the 10 blocks [F(1, 100) = 0.14, p = 0.71; R2 = 0.001, slope = −0.03, intercept = 0.7, p = 0.71]. These results are shown in Figure 4B. Progression of the other trial types, i.e. looped and scrambled learned CNs, are summarized in Supplementary Figure 2.


Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns
Discrimination performance for intact learned target CNs vs. novel CNs in the testing session. (A) Relationship between discrimination rates of learned target and novel CNs in each participant. Participants above the diagonal show higher rates for learned vs. novel CNs, suggesting that memory facilitated the discrimination task. (B) Discrimination rates of learned target and novel CNs over time (10 blocks).
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Figure 4: Discrimination performance for intact learned target CNs vs. novel CNs in the testing session. (A) Relationship between discrimination rates of learned target and novel CNs in each participant. Participants above the diagonal show higher rates for learned vs. novel CNs, suggesting that memory facilitated the discrimination task. (B) Discrimination rates of learned target and novel CNs over time (10 blocks).
Mentions: Participants performed the testing session a month after the learning session (mean interval 30.96 ± 4.2 days, range 23–41 days). In the testing session, discrimination sensitivity (a' testing) again did not vary between versions 1 and 2 of the experiment [F(1, 25) = 0.0057, p = 0.94] and therefore these data were pooled (n = 25). Detection of cyclicity in novel CNs did not change across the two sessions [Mean difference = 0.58, SE = 3.8, t(25) = 0.15, p = 0.8803] indicating that participants' performance in the task was similar over the 4 weeks. Furthermore, the number of times a participant performed each training stage during the learning session had no effect on the discrimination performance during the testing session (a' testing): training stage 1 [F(1, 25) = 0.09, p = 0.75], training stage 2 [F(1, 25) = 1.98, p = 0.17] and training stage 3 [F(1, 25) = 0.03, p = 0.86]. Within the testing session, discrimination rates were significantly higher for learned target CNs compared to novel CNs [F(1, 25) = 7.03, p < 0.014] (Figure 4A). This suggests that participants had memory for the CNs previously learned in the first session. Furthermore, to ensure that this higher discrimination rate for learned target CNs did not result from learning of features throughout the testing session (as opposed to long-term memory for features from the first session), the evolution of discrimination rates for learned vs. new CNs was analyzed over time. A two-way repeated-measures ANOVA on discrimination rates was computed, testing main effects and interaction of within-subjects factors “trial type” (2 levels, “learned target CN” and “novel CN”) and “block” (10 levels). Trial type was the only significant predictor of performance [F(1, 200) = 313.696, p < 0.0001] irrespective of block [F(9, 200) = 1.57, p = 0.127]. The effect of trial type was equivalent across blocks [F(9, 200) = 1.06, p = 0.394]. These results were confirmed by the absence of correlation between hit rate for learned and novel CNs over the 10 blocks [F(1, 100) = 0.14, p = 0.71; R2 = 0.001, slope = −0.03, intercept = 0.7, p = 0.71]. These results are shown in Figure 4B. Progression of the other trial types, i.e. looped and scrambled learned CNs, are summarized in Supplementary Figure 2.

View Article: PubMed Central - PubMed

ABSTRACT

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10&minus; and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities.

Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.

Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.

Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.

Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

No MeSH data available.