Proprioceptive target matching asymmetries in left-handed individuals

Goble, Daniel J.; Noble, Brittany C.; Brown, Susan H.

doi:10.1007/s00221-009-1922-2

Cited by 83 publications

(68 citation statements)

References 42 publications

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“…This trend is well in line with some literature, suggesting proprioceptive processing advantages of the nondominant limb in some conditions,12,16,51–55 while others suggest gain differences of sensory-motor loops as an explanation 56. In contrast to those studies, other groups did not identify any difference between dominant and nondominant limb 18,22.…”

Section: Discussionsupporting

confidence: 91%

Age-based model for metacarpophalangeal joint proprioception in elderly

Rinderknecht¹,

Lambercy²,

Raible³

et al. 2017

CIA

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Neurological injuries such as stroke can lead to proprioceptive impairment. For an informed diagnosis, prognosis, and treatment planning, it is essential to be able to distinguish between healthy performance and deficits following the neurological injury. Since there is some evidence that proprioception declines with age and stroke occurs predominantly in the elderly population, it is important to create a healthy reference model in this specific age group. However, most studies investigate age effects by comparing young and elderly subjects and do not provide a model within a target age range. Moreover, despite the functional relevance of the hand in activities of daily living, age-based models of distal proprioception are scarce. Here, we present a proprioception model based on the assessment of the metacarpophalangeal joint angle difference threshold in 30 healthy elderly subjects, aged 55–80 years (median: 63, interquartile range: 58–66), using a robotic tool to apply passive flexion–extension movements to the index finger. A two-alternative forced-choice paradigm combined with an adaptive algorithm to define stimulus magnitude was used. The mixed-effects model analysis revealed that aging has a significant, increasing effect on the difference threshold at the metacarpophalangeal joint, whereas other predictors (eg, tested hand or sex) did not show a significant effect. The adaptive algorithm allowed reaching an average assessment duration <15 minutes, making its clinical applicability realistic. This study provides further evidence for an age-related decline in proprioception at the level of the hand. The established age-based model of proprioception in elderly may serve as a reference model for the proprioceptive performance of stroke patients, or of any other patient group with central or peripheral proprioceptive impairments. Furthermore, it demonstrates the potential of such automated robotic tools as a rapid and quantitative assessment to be used in research and clinical settings.

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Section: Discussionsupporting

confidence: 91%

Age-based model for metacarpophalangeal joint proprioception in elderly

Rinderknecht¹,

Lambercy²,

Raible³

et al. 2017

CIA

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“…The dynamic dominance hypothesis (Sainburg 2005) argues that the dominant limb is important for the control of movement trajectory, while the nondominant limb is important for the control of limb position. This pattern has been shown to be the opposite in left-handed individuals in studies looking at both visuomotor adaptation (Wang and Sainburg 2006) and proprioceptive matching (Goble et al 2009). Additionally, investigations with stroke patients have also supported this theory (Schaefer et al 2007(Schaefer et al , 2009).…”

Section: Discussionmentioning

confidence: 98%

Handedness, Dexterity, and Motor Cortical Representations

Taylor²,

Seidler

2011

Journal of Neurophysiology

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. Motor system organization varies with handedness. However, previous work has focused almost exclusively on direction of handedness (right or left) as opposed to degree of handedness (strength). In the present study, we determined whether measures of interhemispheric interactions and degree of handedness are related to contra-and ipsilateral motor cortical representations. Participants completed a battery of handedness assessments including both handedness preference measures and behavioral measures of intermanual differences in dexterity, a computerized version of the Poffenberger paradigm (PP) to estimate interhemispheric transfer time (IHTT), and they underwent transcranial magnetic stimulation (TMS) mapping of both motor cortices while we recorded muscle activity from the first dorsal interosseous muscle bilaterally. A greater number of ipsilateral motor evoked potentials (iMEPs) were elicited in less lateralized individuals with the number of iMEPs correlated with IHTT. There were no relationships between handedness or lateralization of dexterity and symmetry of contralateral motor representations, although this symmetry was related to IHTT. Finally, IHTT was positively correlated with multiple measures of laterality and handedness. These findings demonstrate that degree of laterality of dexterity is related to the propensity for exhibiting iMEPs and the speed of interhemispheric interactions. However, it is not clear whether iMEPs are directly mediated via ipsilateral corticospinal projections or are transcallosally transmitted. I N T R O D U C T I O NIt is known that handedness is related to the organization of the sensorimotor system. For example, there is some evidence to indicate that left-and right-handers may differ in corpus callosum morphology (Habib et al. 1991;Westerhausen et al. 2004;Witelson 1985) and organization of motor cortical representations (Amunts et al. 1996;Dassonville et al. 1997;Kim et al. 1993;Volkmann et al. 1998). These neuroanatomical differences have been linked to behavior as well with lefthanders typically having faster and more accurate interhemispheric transmission than right-handers (Cherbuin and Brinkman 2006a,b;Marzi et al. 1991). However, the majority of work investigating relationships between handedness, neuroanatomy, and behavior has evaluated direction of handedness (left vs. right) as opposed to degree of handedness (how strongly handed one is), although there is evidence to support the importance of the latter (Dassonville et al. 1997;Luders et al. 2010;Siebner et al. 2002;Solodkin et al. 2001). Organization of motor cortex and handednessMotor cortex physiology is related to handedness. For example, left-and right-handers show different functional activation patterns in the primary motor cortex (M1) when performing motor tasks. Right-handers show more asymmetrical activation in M1, predominantly in the dominant (left) hemisphere, whereas left-handers show more bilateral activity (Kim et al. 1993;Siebner et al. 2002). Those that are more mixedhanded show the most ...

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“…These differences in reach accuracy and precision across starting and final targethand locations may reflect the kind of signals the brain uses to derive the position of the proprioceptive target. Behavioral and neurophysiological research has revealed the existence of both static (i.e., position) and dynamic (i.e., movement) proprioceptive information, and that both types of information can be used separately to determine final limb position (Burke, Hagbarth, Lofstedt, & Wallin, 1976;Edin & Vallbo, 1990;Goble, Noble, & Brown, 2009;Imanaka, 1989;Imanaka & Abernethy, 1992a, 1992bLonn, Crenshaw, Djupsjobacka, Pedersen, & Johansson, 2000;Sittig, Denier van der Gon, & Gielen, 1985;Smeets & Brenner, 1995). However, previous research compared localization errors across starting positions of the hand and have not examined if the effect of starting position of the hand on localization errors varies across final target-hand locations.…”

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confidence: 98%

“…Redundant sensory information about an aspect of a stimulus (e.g., the location of a reaching hand) from two or more sensory sources can be integrated in such a way that a more accurate or precise estimate of that aspect is derived than would be possible with either source in isolation (e.g., Ernst & Banks, 2002;Kording & Wolpert, 2004;Snijders, Holmes, & Spence, 2007;Sober & Sabes, 2005;van Beers, Sittig, & Denier van der Gon, 1996, 1999. If the proprioceptive target moves immediately before a reach, the central nervous system (CNS) could integrate static and dynamic proprioceptive information about the target, forming a reliable estimate of target location based on proprioceptive information (e.g., Goble, Noble, & Brown, 2009). This information might then be used, weighted based on its reliability, along with visual information to determine final target location.…”

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confidence: 99%

Reach endpoint errors do not vary with movement path of the proprioceptive target

Jones

Byrne

Fiehler

et al. 2012

Journal of Neurophysiology

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Previous research has shown that reach endpoints vary with the starting position of the reaching hand and the location of the reach target in space. We examined the effect of movement direction of a proprioceptive target-hand, immediately preceding a reach, on reach endpoints to that target. Participants reached to visual, proprioceptive (left target-hand), or visual-proprioceptive targets (left target-hand illuminated for 1 s prior to reach onset) with their right hand. Six sites served as starting and final target locations (35 target movement directions in total). Reach endpoints do not vary with the movement direction of the proprioceptive target, but instead appear to be anchored to some other reference (e.g., body). We also compared reach endpoints across the single and dual modality conditions. Overall, the pattern of reaches for visual-proprioceptive targets resembled those for proprioceptive targets, while reach precision resembled those for the visual targets. We did not, however, find evidence for integration of vision and proprioception based on a maximum-likelihood estimator in these tasks.

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Proprioceptive target matching asymmetries in left-handed individuals

Cited by 83 publications

References 42 publications

Age-based model for metacarpophalangeal joint proprioception in elderly

Age-based model for metacarpophalangeal joint proprioception in elderly

Handedness, Dexterity, and Motor Cortical Representations

Reach endpoint errors do not vary with movement path of the proprioceptive target

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