Chunking in tonal contexts: Information compression during serial recall of visually presented musical notes

Chunking is defined as information compression by means of encoding meaningful units. To advance the understanding of chunking in musical memory, the present study tested characteristics of melodic sequences that might enable a parsimonious memory representation, namely, the presence of a clear tonal context and of melodic cells with clear labels. Musical note symbols, which formed either triads (Experiment 1) or cadences (Experiment 2), were presented visually and sequentially to musically experienced participants for immediate serial recall. The melodic sequences were varied on the within-participant factors list length (long vs. short list) and tonal structure (chunking-supportive vs. chunking-obstructive). Chunking-supportive sequences contained tones from a single diatonic key that formed melodic cells with a clear label, such as “C major triad”. Transitional errors showed that participants grouped notes into melodic cells. Mixed logistic regression modeling revealed that recall was more accurate in chunking-supportive sequences and that this advantage was more pronounced for more experienced participants in the long list length condition of Experiment 2. The findings suggest that a clear tonal context and melodic cells with clear labels benefit chunking in melodic processing, but that the subtleties of the process are additionally influenced by type, size, and number of melodic cells.

Sources of Interference in Memory across Development

Episodic memory involves remembering not only what happened but also where and when the event happened. This multi-component nature introduces different sources of interference which stem from previous experience. However, it is unclear how different interferences change across development and what may cause the changes. To address these questions, we tested 4-5-year-olds (N = 103), 7-8-year-olds (N = 82), and adults (N = 70) using item and source recognition memory tasks with various manipulations (i.e., list-length, list-strength, and word-frequency), and decomposed sources of interference using a computational model. We find that interference stemming from other items on the study-list rapidly decreases with development, whereas interference from pre-experimental contexts gradually decreases but remains the major source of interference. The model further quantifies these changes indicating that the ability to discriminate items undergoes relatively rapid development, whereas the ability to discriminate contexts undergo protracted development. These results elucidate fundamental aspects of memory development.

Accounting for the build-up of proactive interference across lists in a list length paradigm reveals a dominance of item-noise in recognition memory

There has been a longstanding debate concerning whether interference in recognition memory is attributable to other items on the study list (i.e., item-noise) or to prior memories (i.e., context-noise and background-noise). Recently, Osth and Dennis (2015) devised a global matching model that could estimate the magnitude of each interference contribution and they found that context-noise and background-noise were dominant in recognition. In the present investigation, data from a list length experiment were analysed using variants of the Osth, Jansson, Dennis and Heathcote (2018) model, that integrates the memory retrieval components of the Osth and Dennis (2015) model with the diffusion decision model (Ratcliff, 1978) to jointly account for choice probabilities and RT distributions. The standard version of the model, like existing recognition models, treated each condition as if no proactive interference had accumulated over the session. A more comprehensive version of the model allowed both study and test items from prior conditions to contribute proactive interference (PI) to future conditions. While the standard model estimated a dominance of background-noise, the PI model estimated a dominance of item-noise, reversing the conclusions made by Osth and Dennis (2015). Along with list length, the experimental design provided a measure of the test position effect (TPE). While the standard model attributed the TPE to context drift, the PI model attributed the TPE to both context drift and increases in item-noise.