The Dynamical Analysis of Inter-Trial Fluctuations Near Goal Equivalent Manifolds

Cusumano, Joseph P.; Mahoney, Joseph M.; Dingwell, Jonathan B.

doi:10.1007/978-1-4939-1338-1_9

Cited by 7 publications

(16 citation statements)

References 37 publications

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“…Recent efforts have seen the use of time series analyses to interpret model outputs and/or predictions [ 46 , 48 , 54 , 66 ]. These efforts have yielded findings qualitatively similar to ours, and consistent with our interpretations of inter-trial variabilty presented both here and elsewhere [ 25 , 26 , 28 , 29 ]. Even though these efforts have focused on motor learning, which we do not, conceptually there is a strong affinity between these papers and the work presented here.…”

Section: Discussionsupporting

confidence: 92%

“…The work in this paper expands on previous efforts [ 25 , 28 ] suggesting that such a unification can be achieved by considering the inter-trial dynamics of fluctuations near a task’s goal equivalent manifold (GEM). These studies have shown that a fundamental feature of such inter-trial fluctuations is that they are dynamically anisotropic in a manner that respects the local geometry of the GEM [ 25 – 29 ], an observation supported by work carried out from different task manifold perspectives [ 30 , 54 , 65 ].…”

Section: Discussionmentioning

confidence: 94%

“…This initial work has demonstrated the central importance of taking a dynamical approach when analyzing motor variability. A fundamental feature of variability highlighted by these studies is that inter-trial fluctuations are found to be dynamically anisotropic with respect to the GEM [ 25 – 29 ]: that is, it is found that the local stability and correlation properties are congruent with the local GEM geometry, with greater stability and lower temporal correlation being associated with the components of time series transverse to the GEM, and lower stability and greater correlation for times series components along the GEM. A similar directionality in correlation properties has been found in a study of skill acquisition [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

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Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task

2016

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We study inter-trial movement fluctuations exhibited by human participants during the repeated execution of a virtual shuffleboard task. Focusing on skilled performance, theoretical analysis of a previously-developed general model of inter-trial error correction is used to predict the temporal and geometric structure of variability near a goal equivalent manifold (GEM). The theory also predicts that the goal-level error scales linearly with intrinsic body-level noise via the total body-goal sensitivity, a new derived quantity that illustrates how task performance arises from the interaction of active error correction and passive sensitivity properties along the GEM. Linear models estimated from observed fluctuations, together with a novel application of bootstrapping to the estimation of dynamical and correlation properties of the inter-trial dynamics, are used to experimentally confirm all predictions, thus validating our model. In addition, we show that, unlike “static” variability analyses, our dynamical approach yields results that are independent of the coordinates used to measure task execution and, in so doing, provides a new set of task coordinates that are intrinsic to the error-regulation process itself.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

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Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task

2016

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“…Human movements are subject to both inherent physiological noise [1, 2] and multiple levels of redundancy [3–5]: i.e., the body has more mechanical degrees-of-freedom than needed to execute most movements, more muscles than needed to move a given joint, etc. Likewise, most tasks we perform exhibit equifinality [3, 6–8]: i.e., we can achieve them with equal success by an infinite number of movements [9–12]. It remains a fundamental question in human motor neuroscience to determine how the human nervous system generates accurate and repeatable goal-directed movements in the face of these challenges.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, it is possible purposeful (goal-directed) walking requires precise step-to-step control of position and/or heading to stay on one’s desired path (or trajectory) [52, 53]. Conversely, people may adopt less stringent control that corrects errors in position and/or heading only when they become “sufficiently large” as to need correcting [3, 8, 12]. To our knowledge, the question of how humans regulate their lateral stepping movements from each step to the next within their respective environment has not been addressed, either experimentally or computationally.…”

Section: Introductionmentioning

confidence: 99%

Humans use multi-objective control to regulate lateral foot placement when walking

2019

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A fundamental question in human motor neuroscience is to determine how the nervous system generates goal-directed movements despite inherent physiological noise and redundancy. Walking exhibits considerable variability and equifinality of task solutions. Existing models of bipedal walking do not yet achieve both continuous dynamic balance control and the equifinality of foot placement humans exhibit. Appropriate computational models are critical to disambiguate the numerous possibilities of how to regulate stepping movements to achieve different walking goals. Here, we extend a theoretical and computational Goal Equivalent Manifold (GEM) framework to generate predictive models, each posing a different experimentally testable hypothesis. These models regulate stepping movements to achieve any of three hypothesized goals, either alone or in combination: maintain lateral position, maintain lateral speed or “heading”, and/or maintain step width. We compared model predictions against human experimental data. Uni-objective control models demonstrated clear redundancy between stepping variables, but could not replicate human stepping dynamics. Most multi-objective control models that balanced maintaining two of the three hypothesized goals also failed to replicate human stepping dynamics. However, multi-objective models that strongly prioritized regulating step width over lateral position did successfully replicate all of the relevant step-to-step dynamics observed in humans. Independent analyses confirmed this control was consistent with linear error correction and replicated step-to-step dynamics of individual foot placements. Thus, the regulation of lateral stepping movements is inherently multi-objective and balances task-specific trade-offs between competing task goals. To determine how people walk in their environment requires understanding both walking biomechanics and how the nervous system regulates movements from step-to-step. Analogous to mechanical “templates” of locomotor biomechanics, our models serve as “control templates” for how humans regulate stepping movements from each step to the next. These control templates are symbiotic with well-established mechanical templates, providing complimentary insights into walking regulation.

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Searching Strategies in Practice: The Role of Stability in the Performer-Task Interaction

Pacheco

Santos

Tani

2021

Ecological Psychology

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Through the view of the search strategies approach to skill acquisition-and its dynamic systems theoretical background-non-local changes in behavior are expected to emerge through a process of decreased stability (increased variability) of the ongoing movement pattern as to allow exploration of new regions of the perceptual-motor workspace. However, previous studies have not found such relation; only in non-redundant tasks. We believe that such issue occurs because these previous studies have focused on the movement pattern variability while in redundant tasks the variability that matters is at the task space level. Therefore, we analyzed the data of 15 individuals that practiced a throwing task for five days in terms of their movement patterns and release parameters to test whether increased variability at the task level was predictive of non-local changes in practice. We found that, for non-local changes at both release parameters and movement pattern levels, performance and performance variability were significant predictors. We discuss these results highlighting that they support a strong assumption of the search strategies approach, corroborate to the dynamical systems view on motor learning, and pointing the lack of consideration of non-local changes in other theories of motor learning.

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The Dynamical Analysis of Inter-Trial Fluctuations Near Goal Equivalent Manifolds

Cited by 7 publications

References 37 publications

Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task

Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task

Humans use multi-objective control to regulate lateral foot placement when walking

Searching Strategies in Practice: The Role of Stability in the Performer-Task Interaction

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