Individual differences in the exploration of a redundant space-time motor task

King, Adam C.; Ranganathan, Rajiv; Newell, Karl M.

doi:10.1016/j.neulet.2012.08.014

Cited by 40 publications

(23 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Individuals demonstrate significant variability in motor learning (Ackerman, 1987; King et al, 2012). The ability to predict an individual’s learning skill could have utility in a number of settings, including clinical (Stinear, 2010).…”

Section: Introductionmentioning

confidence: 99%

Resting-state cortical connectivity predicts motor skill acquisition

et al. 2014

View full text Add to dashboard Cite

Many studies have examined brain states in an effort to predict individual differences in capacity for learning, with overall moderate results. The present study investigated how measures of cortical network function acquired at rest using dense-array EEG (256 leads) predict subsequent acquisition of a new motor skill. Brain activity was recorded in 17 healthy young subjects during three minutes of wakeful rest prior to a single motor skill training session on a digital version of the pursuit rotor task. Practice was associated with significant gains in task performance (% time on target increased from 24% to 41%, p < 0.0001). Using a partial least squares regression (PLS) model, coherence with the region of the left primary motor area (M1) in resting EEG data was a strong predictor of motor skill acquisition (R2 = 0.81 in a leave-one-out cross-validation analysis), exceeding the information provided by baseline behavior and demographics. Within this PLS model, greater skill acquisition was predicted by higher connectivity between M1 and left parietal cortex, possibly reflecting greater capacity for visuomotor integration, and by lower connectivity between M1 and left frontal-premotor areas, possibly reflecting differences in motor planning strategies. EEG coherence, which reflects functional connectivity, predicts individual motor skill acquisition with a level of accuracy that is remarkably high compared to prior reports using EEG or fMRI measures.

show abstract

Section: Introductionmentioning

confidence: 99%

Resting-state cortical connectivity predicts motor skill acquisition

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Researchers have identified individual differences in a large number of motor variables, including for example reaction time, speed and preferred frequency of arm movement and multi-limb coordination [25]–[27]. People swinging pendulums together converge to a frequency which is intermediate between their individually preferred frequencies [28], [29].…”

Section: Introductionmentioning

confidence: 99%

Individuality and Togetherness in Joint Improvised Motion

et al. 2014

View full text Add to dashboard Cite

Actors, dancers and musicians that improvise together report special moments of togetherness: high performance and synchrony, seemingly without a leader and a follower. Togetherness seems to conflict with individuality- the idiosyncratic character of each person's performance. To understand the relation of individuality and togetherness, we employed the mirror game paradigm in which two players are asked to mirror each other and create interesting synchronized motion, with and without a designated leader. The mirror game enables quantitative characterization of moments of togetherness in which complex motion is generated with high synchrony. We find that each person as a leader does basic strokes of motion with a characteristic signature, in terms of the shape of their velocity profile between two stopping events. In moments of togetherness both players change their signature to a universal stroke shape. This universal velocity profile resembles a half-period of a sine wave, and is therefore symmetric and maximally smooth. Thus, instead of converging to an intermediate motion signature, or having one player dominate, players seem to shift their basic motion signatures to a shape that is altogether different from their individually preferred shapes; the resulting motion may be easier to predict and to agree on. The players then build complex motion by using such smooth elementary strokes.

show abstract

“…Some earlier studies [3]–[6], [8] although not from a dynamical systems approach, did emphasize individual differences in motor learning. However, these studies did not examine how individual performance evolves over practicing because performance was only analysed at discrete moments in time; either at the beginning [6], at the end [3], [5] or at the beginning and towards the end of learning [4], [8].…”

Section: Introductionmentioning

confidence: 99%

“…However, these studies did not examine how individual performance evolves over practicing because performance was only analysed at discrete moments in time; either at the beginning [6], at the end [3], [5] or at the beginning and towards the end of learning [4], [8]. For example, a study analysing the beginning stage of learning by King et al [6] examined how individuals minimize a performance score, composed of spatial error and movement time, in a star tracing task. Results showed that different groups could be distinguished, one reducing spatial error, one reducing movement time and another one reducing both variables [6].…”

Section: Introductionmentioning

confidence: 99%

“…For example, a study analysing the beginning stage of learning by King et al [6] examined how individuals minimize a performance score, composed of spatial error and movement time, in a star tracing task. Results showed that different groups could be distinguished, one reducing spatial error, one reducing movement time and another one reducing both variables [6]. Cesqui et al [5], using experts who were able to show consistent behaviour in an unconstrained one-handed ball catching task, showed that also at the end stage of learning different ways of catching a ball can be observed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Individual Differences in Learning a Novel Discrete Motor Task

et al. 2014

View full text Add to dashboard Cite

Many motor learning studies focus on average performance while it is known from everyday life experience that humans differ in their way of learning new motor tasks. This study emphasises the importance of recognizing individual differences in motor learning. We studied individual tool grasping profiles of individuals who learned to pick up objects with a novel tool, a pair of pliers. The pair of pliers was attached to the thumb and the index finger so that the tip of the thumb and the tip of the index finger were displaced to the beaks of the pair of pliers. The grasp component was manipulated by varying the location of the hinge of the pair of pliers, which resulted in different relations between beak opening and closing and finger opening and closing. The Wider Beak group had the hinge at 7 cm, the Same Beak group had the hinge at 10 cm (i.e., in the middle), and the Smaller Beak group had the hinge at 13 cm from the digits. Each group consisted of ten right-handed participants who picked up an object with one of the pairs of pliers 200 times on two subsequent days. Hand opening, plateau phase, hand closing, grasping time and maximum aperture were analyzed. To characterize individual changes over practice time, a log function was fitted on these dependent variables and the ratio of improvement was determined. Results showed that at the beginning stage of tool use learning the characteristic grasping profile consisted of three phases; hand opening, plateau phase and hand closing. Over practicing individual participants differed in the number of phases that changed, the amount of change in a phase and/or the direction of change. Moreover, with different pliers different learning paths were found. The importance of recognizing individual differences in motor learning is discussed.

show abstract

Individual differences in the exploration of a redundant space-time motor task

Cited by 40 publications

References 18 publications

Resting-state cortical connectivity predicts motor skill acquisition

Resting-state cortical connectivity predicts motor skill acquisition

Individuality and Togetherness in Joint Improvised Motion

Individual Differences in Learning a Novel Discrete Motor Task

Contact Info

Product

Resources

About