Have We Forgotten Auditory Sensory Memory? Retention Intervals in Studies of Nonverbal Auditory Working Memory

Nees, Michael A.

doi:10.3389/fpsyg.2016.01892

Cited by 59 publications

(42 citation statements)

References 48 publications

(67 reference statements)

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“…We suppose that the influence, or weight, of a given These hypotheses must be considered tentative, given the scarcity of empirical evidence directly relating memory constraints to auditory prediction. However, the notion of a short-lived memory buffer is consistent with pre-existing concepts of auditory sensory memory (Atkinson & Shiffrin, 1968;Nees, 2016;Neisser, 1967), and the continuous-decay phenomenon is consistent with well-established recency effects in statistical learning (Bröker et al, 2018;Harrison, 2011;Mattar et al, 2016;Meyniel et al, 2016;O'Reilly, 2013;Squires et al, 1976;Yu & Cohen, 2008).…”

Section: Modelsupporting

confidence: 75%

“…Auditory working memory has a more limited informational capacity, and a temporal capacity that can be extended for long periods through active rehearsal. Auditory long-term memory seems to be effectively unlimited in both temporal and informational capacity (Atkinson & Shiffrin, 1968;Kumar et al, 2016;Nees, 2016;Neisser, 1967).…”

Section: Experiments 3: Memory Decay Helps To Explain the Dynamics Of mentioning

confidence: 99%

“…Various such decay kernels are possible. Here we decided to base our decay kernel on the following psychological ideas, inspired by previous research into echoic memory (Atkinson & Shiffrin, 1968;Nees, 2016;Watson, 2016):…”

Section: Experiments 3: Memory Decay Helps To Explain the Dynamics Of mentioning

confidence: 99%

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PPM-Decay: A Computational Model of Auditory Prediction with Memory Decay

Harrison

Bianco

Chait

et al. 2020

Preprint

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Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies -one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pattern detection experiment -we show how this decay kernel improves the model's predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection.The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm).

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Section: Modelsupporting

confidence: 75%

Section: Experiments 3: Memory Decay Helps To Explain the Dynamics Of mentioning

confidence: 99%

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PPM-Decay: A Computational Model of Auditory Prediction with Memory Decay

Harrison

Bianco

Chait

et al. 2020

Preprint

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“…Finally, in the context of dynamic systems, it is also worth remembering that the role of auditory sensory memory may be uncertain; it could still contribute something despite the use of a mask, as was suggested by Nees (). Cowan, Nugent, Elliott, and Saults () found age differences in the temporal decay of auditory sensory memory derived from lists unattended at the time of their presentation and then post‐cued for recall, but with no indication of whether these age difference can survive a mask.…”

Section: Discussionmentioning

confidence: 99%

Development of the ability to combine visual and acoustic information in working memory

Cowan

Glass

et al. 2017

Developmental Science

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Presentation of two kinds of materials in working memory (visual and acoustic), with the requirement to attend to one or both modalities, poses an interesting case for working memory development because competing predictions can be formulated. In two experiments, we assessed such predictions with children 7–13 years old and adults. With development, the ability to hold more information in the focus of attention could lead to an increase in the size of the tradeoff between modalities; if attention can hold A items during unimodal-attention trials, then on average attention should hold A/2 of those same items during bimodal-attention trials. If A increases with age, so would the dual-task cost, A/2. The results clearly ruled out that possibility. It was the modality- or code-specific components of working memory that improved with age and not the central component. We discuss various mechanisms that could have produced these results, including alternative attention-based mechanisms. The findings point to a rich field for continued research.

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“…Here we report the results of two experiments investigating the time course of decay of sensory 112 memory (Cowan, 1984;Cowan et al, 1997;Nees, 2016). Auditory sensory memory enables integration 113 of auditory information and preservation of information over brief periods of time (Schröger, 2007).…”

mentioning

confidence: 99%

Temporal expectation modulates cortical dynamics of sensory memory

Wilsch

Obleser

2017

Preprint

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Increased memory load is often signified by enhanced neural oscillatory power in the alpha range (8–13 Hz), taken to reflect inhibition of task-irrelevant brain regions. The corresponding neural correlates of memory decay, however, are not yet well-understood. Here, we investigated auditory sensory memory decay using a delayed matching-to-sample task with pure-tone sequences. First, in a behavioral experiment we modeled memory behavior over six different delay-phase durations. Second, in a magnetoencephalography (MEG) experiment, we assessed alpha-power modulations over three different delay-phase durations. In both experiments, the temporal expectation for the to-be-remembered sound was manipulated, so that it was either temporally expected or not. In both studies, memory performance declined over time but this decline was less strong under a more precise temporal expectation. Similarly, patterns of alpha power in and alpha-tuned connectivity between sensory cortices changed parametrically with delay duration (i.e., decrease in occipito-parietal regions, increase in temporal regions). Notably, temporal expectation counteracted alpha-power decline in heteromodal brain areas (i.e., supramarginal gyrus), in line with its memory-decay counteracting effect on performance. Correspondingly, temporal expectation also boosted alpha connectivity within attention networks known to play an active role during memory maintenance. The present data outline how patterns of alpha power orchestrate sensory memory decay, and encourage a refined perspective on alpha power and its inhibitory role across brain space and time.Significance StatementOur sensory memories of the physical world fade quickly. We show here that this decay of sensory memory can be counteracted by so-called temporal expectation, that is, knowledge of when to expect the to-be-remembered sensory event (here, brief sound patterns). We also show that distinct patterns and modulations of neural oscillations in the “alpha” (8–13 Hz) range index both, the degree of memory decay, and any benefit from temporal expectation, both of which affect memory performance. Critically, spatially distributed cortical patterns of alpha power, with opposing effects in auditory vs. visual sensory cortices and alpha-tuned connectivity changes within supramodal attention networks, reflect the allocation of neural resources as sensory memory representations fade.

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Have We Forgotten Auditory Sensory Memory? Retention Intervals in Studies of Nonverbal Auditory Working Memory

Cited by 59 publications

References 48 publications

PPM-Decay: A Computational Model of Auditory Prediction with Memory Decay

PPM-Decay: A Computational Model of Auditory Prediction with Memory Decay

Development of the ability to combine visual and acoustic information in working memory

Temporal expectation modulates cortical dynamics of sensory memory

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