Incremental planning in sequence production.

2003 ◽  
Vol 110 (4) ◽  
pp. 683-712 ◽  
Author(s):  
Caroline Palmer ◽  
Peter Q. Pfordresher
Keyword(s):  
Sequence Production ◽  
Incremental Planning

Evidence for chunking vs. statistical learning in motor sequence production

2018 ◽  
Author(s):  
Nicola J. Popp ◽  
Neda Kordjaz ◽  
Paul Gribble ◽  
Jörn Diedrichsen
Keyword(s):  
Statistical Learning ◽  
Motor Sequence ◽  
Sequence Production

scholarly journals Motor Chunking in Internally Guided Sequencing

2021 ◽  
Vol 11 (3) ◽  
pp. 292 ◽  
Author(s):  
Krishn Bera ◽  
Anuj Shukla ◽  
Raju S. Bapi
Keyword(s):  
Response Times ◽  
Skill Learning ◽  
Motor Tasks ◽  
Performance Improvements ◽  
Sequence Production ◽  
Serial Reaction ◽  
Motor Movements ◽  
Motor Actions ◽  
Reaction Task ◽  
Or Task

Motor skill learning involves the acquisition of sequential motor movements with practice. Studies have shown that we learn to execute these sequences efficiently by chaining several elementary actions in sub-sequences called motor chunks. Several experimental paradigms, such as serial reaction task, discrete sequence production, and m × n task, have investigated motor chunking in externally specified sequencing where the environment or task paradigm provides the sequence of stimuli, i.e., the responses are stimulus driven. In this study, we examine motor chunking in a class of more realistic motor tasks that involve internally guided sequencing where the sequence of motor actions is self-generated or internally specified. We employ a grid-navigation task as an exemplar of internally guided sequencing to investigate practice-driven performance improvements due to motor chunking. The participants performed the grid-sailing task (GST) (Fermin et al., 2010), which required navigating (by executing sequential keypresses) a 10 × 10 grid from start to goal position while using a particular type of key mapping between the three cursor movement directions and the three keyboard buttons. We provide empirical evidence for motor chunking in grid-navigation tasks by showing the emergence of subject-specific, unique temporal patterns in response times. Our findings show spontaneous chunking without pre-specified or externally guided structures while replicating the earlier results with a less constrained, internally guided sequencing paradigm.

scholarly journals The effects of habits on motor skill learning

2018 ◽  
Author(s):  
Nicola J. Popp ◽  
Atsushi Yokoi ◽  
Paul L. Gribble ◽  
Jörn Diedrichsen
Keyword(s):  
Athletic Training ◽  
Motor Skill ◽  
Habit Formation ◽  
Motor Pattern ◽  
Performance Outcomes ◽  
Skill Learning ◽  
Training Period ◽  
Production Task ◽  
Motor Sequence ◽  
Sequence Production

AbstractSkill learning involves the formation of stable motor patterns. In musical and athletic training, however, these stable motor habits can also impede the attainment of higher levels of performance. We developed an experimental paradigm to induce a specific motor pattern in the context of a discrete sequence production task and to investigate how these habits affect performance over a 3-week training period. Participants initially practiced small segments of 2 to 3 finger movements (“chunks”) and then learned longer sequences composed of these chunks. This initial training induced a persistent temporal pattern during execution, with shorter inter-press-intervals within a chunk and longer ones at chunk boundaries. This pattern remained stable during the subsequent 10 days of training, in which participants were asked to produce the sequence as fast as possible from memory. The habit was also preserved when the sequences were directly displayed, removing the need for memory recall. We were able to induce chunking patterns that were either beneficial or detrimental to performance by taking into consideration the biomechanical constraints of the sequences. While we observed an overall reduction in the detrimental effect of the disadvantageous chunking instructions with training, our results show that the degree to which these detrimental chunk structures were maintained, was predictive of lower levels of final performance. In sum, we were able to induce beneficial and detrimental motor habits in a motor sequence production task and show that these initial instructions influenced performance outcomes over a prolonged period of time.Significance StatementA habit is defined as an automatized action that resists modification once sufficiently established. Preventing bad habits, while reinforcing good habits, is a key objective when teaching new motor skills. While habit formation is an integral part of motor skill acquisition, previous research has focused on habit formation in terms of action selection. In this paper, we examine habit formation in terms of motor skill execution, after the action has been selected. We were able to induce beneficial or detrimental motor habits in the production of motor sequences. Habits were stable over a prolonged training period. Our results demonstrate how cognitive instruction can lead to persistent motor habits and we explore how these habits are potentially modified with training.

Modeling of Quantum Key Distribution System for Secure Information Transfer

2014 ◽  
pp. 811-840
Author(s):  
K. E. Rumyantsev ◽  
D. M. Golubchikov
Keyword(s):  
Distribution System ◽  
Quantum Key Distribution ◽  
Information Transfer ◽  
Distribution Systems ◽  
Key Distribution ◽  
Photon State ◽  
Secure Information ◽  
Sequence Production ◽  
Security Infrastructure ◽  
Processing Algorithms

This chapter is an analysis of commercial quantum key distribution systems. Upon analysis, the generalized structure of QKDS with phase coding of a photon state is presented. The structure includes modules that immediately participate in the task of distribution and processing of quantum states. Phases of key sequence productions are studied. Expressions that allow the estimation of physical characteristics of optoelectronic components, as well as information processing algorithms impact to rate of key sequence production, are formed. Information security infrastructure can be utilized, for instance, to formulate requirements to maximize tolerable error level in quantum channel with a given rate of key sequence production.

scholarly journals Sequence learning is driven by improvements in motor planning

2019 ◽  
Vol 121 (6) ◽  
pp. 2088-2100 ◽  
Author(s):  
Giacomo Ariani ◽  
Jörn Diedrichsen
Keyword(s):  
Sequence Learning ◽  
Forced Response ◽  
Learning Effects ◽  
Production Task ◽  
Motor Execution ◽  
Motor Sequence ◽  
Single Action ◽  
Online Planning ◽  
Sequence Production ◽  
Planning Processes

The ability to perform complex sequences of movements quickly and accurately is critical for many motor skills. Although training improves performance in a large variety of motor sequence tasks, the precise mechanisms behind such improvements are poorly understood. Here we investigated the contribution of single-action selection, sequence preplanning, online planning, and motor execution to performance in a discrete sequence production task. Five visually presented numbers cued a sequence of five finger presses, which had to be executed as quickly and accurately as possible. To study how sequence planning influenced sequence production, we manipulated the amount of time that participants were given to prepare each sequence by using a forced-response paradigm. Over 4 days, participants were trained on 10 sequences and tested on 80 novel sequences. Our results revealed that participants became faster in selecting individual finger presses. They also preplanned three or four sequence items into the future, and the speed of preplanning improved for trained, but not for untrained, sequences. Because preplanning capacity remained limited, the remaining sequence elements had to be planned online during sequence execution, a process that also improved with sequence-specific training. Overall, our results support the view that motor sequence learning effects are best characterized by improvements in planning processes that occur both before and concurrently with motor execution. NEW & NOTEWORTHY Complex skills often require the production of sequential movements. Although practice improves performance, it remains unclear how these improvements are achieved. Our findings show that learning effects in a sequence production task can be attributed to an enhanced ability to plan upcoming movements. These results shed new light on planning processes in the context of movement sequences and have important implications for our understanding of the neural mechanisms that underlie skill acquisition.

scholarly journals Multifaceted aspects of chunking enable robust algorithms

2014 ◽  
Vol 112 (8) ◽  
pp. 1849-1856 ◽  
Author(s):  
Daniel E. Acuna ◽  
Nicholas F. Wymbs ◽  
Chelsea A. Reynolds ◽  
Nathalie Picard ◽  
Robert S. Turner ◽  
...  
Keyword(s):  
Motor Behavior ◽  
Response Times ◽  
Reaction Times ◽  
Error Rates ◽  
Physiological Data ◽  
Bayesian Algorithm ◽  
Robust Algorithms ◽  
Sequence Production ◽  
Standard Tool

Sequence production tasks are a standard tool to analyze motor learning, consolidation, and habituation. As sequences are learned, movements are typically grouped into subsets or chunks. For example, most Americans memorize telephone numbers in two chunks of three digits, and one chunk of four. Studies generally use response times or error rates to estimate how subjects chunk, and these estimates are often related to physiological data. Here we show that chunking is simultaneously reflected in reaction times, errors, and their correlations. This multimodal structure enables us to propose a Bayesian algorithm that better estimates chunks while avoiding overfitting. Our algorithm reveals previously unknown behavioral structure, such as an increased error correlations with training, and promises a useful tool for the characterization of many forms of sequential motor behavior.

Processes for sequence production.

1974 ◽  
Vol 81 (3) ◽  
pp. 187-198 ◽  
Author(s):  
James G. Greeno ◽  
Herbert A. Simon
Keyword(s):  
Sequence Production

USING INCREMENTAL PLANNING TO FOSTER APPLICATION FRAMEWORK REUSE

2000 ◽  
Vol 10 (04) ◽  
pp. 433-448 ◽  
Author(s):  
ALVARO ORTIGOSA ◽  
MARCELO CAMPO
Keyword(s):  
Object Oriented ◽  
Application Framework ◽  
Fundamental Idea ◽  
Planning Methods ◽  
User Tasks ◽  
High Level ◽  
Incremental Planning

In this work, we present an approach for documenting object-oriented application frameworks and use the documentation to guide the framework instantiation process. Our approach is based on a shift from a framework-centered to a functionality-centered documentation, through which a tool can guide the instantiation process according to the functionality required for the new application. The fundamental idea of our work is the combination of the concept of user-tasks modeling and least commitment planning methods to guide the instantiation process. Based on these techniques, the tool is able to present the different high level activities that can be carried out when creating a new application from a framework to the developer, taking as a basis the documentation provided by the designer through instantiation rules.

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