Resource allocation and prioritization in auditory working memory

Abstract

A prevalent view of working memory (WM) considers it to be capacity-limited, fixed to a set number of items. However, recent shared resource models of WM have challenged this “quantized” account using measures of recall precision. Although this conceptual framework can account for several features of visual WM, it remains to be established whether it also applies to auditory WM.We used a novel pitch-matching paradigm to probe participants’ memory of pure tones in sequences of varying length, and measured their precision of recall. Crucially, this provides an index of the variability of memory representation around its true value, rather than a binary “yes/no” recall measure typically used in change detection paradigms. We show that precision of auditory WM varies with both memory load and serial order. Moreover, auditory WM resources can be prioritized to cued items, improving precision of recall, but with a concomitant cost to other items, consistent with a resource model account.

Auditory working memory predicts individual differences in absolute pitch learning

“…While the INM task was clearly musical in nature, as the target notes and starting notes were taken from the Western musical scale, due to the particular nature of the task we interpreted performance in terms of auditory working memory precision, since participants needed to remember the perceptual details of the target tone in the face of white noise and several intermediary tones. In support of our interpretation, a very similar pitch-matching task was recently used by Kumar et al (2013) to measure the precision of pitch in auditory working memory.…”

“…Thus, even though the INM task was significantly correlated with musical experience (operationalized as age of music onset and overall musical instruction), we included it in our model because it was meant to assess implicit auditory working memory, which is related to -but dissociable from -musicianship. Indeed, previous research using similar tests for implicit note memory have clearly demonstrated that performance can be interpreted in terms of precision of auditory working memory (Kumar et al, 2013), and performance is not necessarily tied to specifically musical experiences (e.g., Ross et al, 2003).…”

Working Memory for Sequences of Temporal Durations Reveals a Volatile Single-Item Store

“…The reported feature can then be compared to the veridical feature, providing a trial-wise, quantitative precision measure. Recently, these precision paradigms have been extended to auditory and vibrotactile frequencies, and similar effects have been demonstrated, indicating that features in various modalities may all be encoded in a similar way (Kumar et al, 2013; Joseph et al, 2015). In neural models of working memory, the ability to hold several continuous features in memory has been taken to suggest that the feature dimensions are encoded in a set of independent feature-tuned channels, which are activated upon encoding each feature for each item in memory (Compte et al, 2000; Wimmer et al, 2014).…”

Changing concepts of working memory

“…Continuous-resource models might also be extendable beyond visual working memory, to visual long-term memory 94 , other sensory domains 95 or other multiple-object tasks. Multiple-object tracking, for example, is often considered to be limited by a four-item limit, but this conclusion is being challenged 60,96,97 .…”