Incremental planning in sequence production.

Palmer, Caroline; Pfordresher, Peter Q.

doi:10.1037/0033-295x.110.4.683

Cited by 127 publications

(203 citation statements)

References 128 publications

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“…Palmer & Baldwin, 2004). Other research has likewise suggested that strongly accented metrical positions attract attention (Large & Jones, 1999) and act as salient points in memory (Palmer & Krumhansl, 1990;Palmer & Pfordresher, 2003). If, as these results suggest, strong metrical accents function as stable points in music, performers may be less sensitive to the influence of auditory feedback when evaluating instruction cues that are positioned on strong beats.…”

Section: Resultsmentioning

confidence: 85%

Activation of learned action sequences by auditory feedback

et al. 2011

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The present research addressed whether auditory feedback associated with a learned action sequence can activate the action representation of that sequence. Nonpianist participants learned to perform two melodies at a piano keyboard repeatedly during a trial. The participants heard feedback either from the melody they were performing (normal feedback) or from the other learned melody (termed alternate feedback). An additional tone functioned as an instruction cue to either switch melodies or continue the current melody. Following the instruction cues, participants typically paused just before switching, and paused similarly during trials with a continue cue. Participants paused longer after a continue cue when they experienced alternate rather than normal feedback. This effect was specific to instruction cues positioned at weak metrical accents-positions at which participants were less likely to switch overall. Feedback did not influence timing on switch trials. These findings indicate that influences of auditory feedback can activate learned action sequences, leading to longer latencies associated with cue evaluation.

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Section: Resultsmentioning

confidence: 85%

Activation of learned action sequences by auditory feedback

et al. 2011

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“…Such demands are plausible; the memory of serial order is critical to the representation and production of musical sequences (e.g., Palmer & Pfordresher, 2003), and so musical processing might draw particularly heavily on the ability to maintain and update representations involving serial order. Note that music might be even more demanding on working memory updating than language, for example.…”

Section: Discussionmentioning

confidence: 99%

Tuning the mind: Exploring the connections between musical ability and executive functions

et al. 2016

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A growing body of research suggests that musical experience and ability are related to a variety of cognitive abilities, including executive functioning (EF). However, it is not yet clear if these relationships are limited to specific components of EF, limited to auditory tasks, or reflect very general cognitive advantages. This study investigated the existence and generality of the relationship between musical ability and EFs by evaluating the musical experience and ability of a large group of participants and investigating whether this predicts individual differences on three different components of EF – inhibition, updating, and switching – in both auditory and visual modalities. Musical ability predicted better performance on both auditory and visual updating tasks, even when controlling for a variety of potential confounds (age, handedness, bilingualism, and socio-economic status). However, musical ability was not clearly related to inhibitory control and was unrelated to switching performance. These data thus show that cognitive advantages associated with musical ability are not limited to auditory processes, but are limited to specific aspects of EF. This supports a process-specific (but modality-general) relationship between musical ability and non-musical aspects of cognition.GRAMMY Foundatio

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“…In favor of this idea, Reeves, Schmauder, and Morris (2000) showed that stress patterns in serial recall stimuli can induce specific grouping strategies (see also Frankish, 1995). Even more to the point, Palmer and Pfordresher (2003) showed that, in music performance, 17 In some cases, the present model could apparently be applied directly to further phenomena: for instance, item frequency or suffix effects. In others, a more elaborate implementation would clearly be needed.…”

Section: Groupingmentioning

confidence: 99%

Short-term memory for serial order: A recurrent neural network model.

Botvinick¹,

Plaut²

2006

Psychological Review

325

413

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Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according to which sequence information is encoded through sustained patterns of activation within a recurrent neural network architecture. As demonstrated through a series of computer simulations, the model provides a parsimonious account for numerous benchmark characteristics of immediate serial recall, including data that have been considered to preclude the application of recurrent neural networks in this domain. Unlike most competing accounts, the model deals naturally with findings concerning the role of background knowledge in serial recall and makes contact with relevant neuroscientific data. Furthermore, the model gives rise to numerous testable predictions that differentiate it from competing theories. Taken together, the results presented indicate that recurrent neural networks may offer a useful framework for understanding short-term memory for serial order.

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Incremental planning in sequence production.

Cited by 127 publications

References 128 publications

Activation of learned action sequences by auditory feedback

Activation of learned action sequences by auditory feedback

Tuning the mind: Exploring the connections between musical ability and executive functions

Short-term memory for serial order: A recurrent neural network model.

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