The handyman's brain: A neuroimaging meta-analysis describing the similarities and differences between grip type and pattern in humans

King, Michael; Rauch, H. G. Laurie; Stein, Dan J.; Brooks, Samantha J.

doi:10.1016/j.neuroimage.2014.05.064

Cited by 36 publications

(29 citation statements)

References 105 publications

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“…The activation in this somatosensory region is in line with previous fMRI visuomotor grip studies [e.g., Alahmadi et al, 2015; King et al, 2014; Kuhtz‐Buschbeck et al, 2008]. What is more interesting is that, compared to the other grip types, the dynamic power grip generates activations that are uniquely localized in BA 3b, as shown by using an activation likelihood estimation analyses [King et al, 2014]. In our study, and regardless of the hand used, area BA 3b responded in a uniquely linear fashion, suggesting that this area may play a key role in mediating GF level‐dependent processing.…”

Section: Discussionsupporting

confidence: 90%

“…The primary somatosensory cortex not only showed a main effect of movement but it also showed an extended linear response, especially in BA 3b, between GF and BOLD signal. The activation in this somatosensory region is in line with previous fMRI visuomotor grip studies [e.g., Alahmadi et al, 2015; King et al, 2014; Kuhtz‐Buschbeck et al, 2008]. What is more interesting is that, compared to the other grip types, the dynamic power grip generates activations that are uniquely localized in BA 3b, as shown by using an activation likelihood estimation analyses [King et al, 2014].…”

Section: Discussionsupporting

confidence: 86%

“…Also, it is important to stress that this study investigated the visuomotor network in the context of a power grip dynamic task, where all fingers participated in performing the task (as opposed to a precision task where two fingers perform the task or to a finger tapping task). This is important as it has been shown that there are differences and specific activations between the two tasks [e.g., Khorrami et al, 2011; King et al, 2014]. …”

Section: Discussionmentioning

confidence: 99%

“…For example, some studies have focused on performing a motor task using finger tapping [Jäncke et al, 1998; Verstynen et al, 2005], repetitive [Kuhtz‐Buschbeck et al, 2008] or static [Keisker et al, 2010] power grip tasks. However, there are differences in the networks involved in controlling these movements [Keisker et al, 2010; Khorrami et al, 2011; King et al, 2014]. Additionally, task context has been variably defined by different authors, usually by appealing to the notion of “task complexity.” Several groups, for example, consider that more complex (difficult) tasks are implicitly performed with the NDH compared to the DH [Ng et al, 2008; Verstynen et al, 2005].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Differential involvement of cortical and cerebellar areas using dominant and nondominant hands: An FMRI study

Alahmadi

Pardini

Samson

et al. 2015

Human Brain Mapping

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Motor fMRI studies, comparing dominant (DH) and nondominant (NDH) hand activations have reported mixed findings, especially for the extent of ipsilateral (IL) activations and their relationship with task complexity. To date, no study has directly compared DH and NDH activations using an event‐related visually guided dynamic power‐grip paradigm with parametric (three) forces (GF) in healthy right‐handed subjects. We implemented a hierarchical statistical approach aimed to: (i) identify the main effect networks engaged when using either hand; (ii) characterise DH/NDH responses at different GFs; (iii) assess contralateral (CL)/IL‐specific and hemisphere‐specific activations. Beyond confirming previously reported results, this study demonstrated that increasing GF has an effect on motor response that is contextualised also by the use of DH or NDH. Linear analysis revealed increased activations in sensorimotor areas, with additional increased recruitments of subcortical and cerebellar areas when using the NDH. When looking at CL/IL‐specific activations, CL sensorimotor areas and IL cerebellum were activated with both hands. When performing the task with the NDH, several areas were also recruited including the CL cerebellum. Finally, there were hand‐side‐independent activations of nonmotor‐specific areas in the right and left hemispheres, with the right hemisphere being involved more extensively in sensori‐motor integration through associative areas while the left hemisphere showing greater activation at higher GF. This study shows that the functional networks subtending DH/NDH power‐grip visuomotor functions are qualitatively and quantitatively distinct and this should be taken into consideration when performing fMRI studies, particularly when planning interventions in patients with specific impairments. Hum Brain Mapp 36:5079–5100, 2015. © 2015 Wiley Periodicals, Inc.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Differential involvement of cortical and cerebellar areas using dominant and nondominant hands: An FMRI study

Alahmadi

Pardini

Samson

et al. 2015

Human Brain Mapping

View full text Add to dashboard Cite

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“…Particularly ALE has been applied to a wide range of different topics from cognitive (Chase et al, 2015; Molenberghs et al, 2012), affective (Kohn et al, 2014; Lamm et al, 2011) and motor (King et al, 2014; Yuan and Brown, 2015) neuroscience to the neurobiology of neurological (Herz et al, 2014; Rehme et al, 2012) and psychiatric (Bludau et al, 2015; Chan et al, 2011; Goodkind et al, 2015) disorders. Given the ever-growing expansion of ALE meta-analyses into smaller research areas in which the eligible literature is not as abundant as for, e.g., working memory or social cognitive tasks, the question regarding the number of experiments that is necessary to perform a valid ALE analyses has become increasingly important over the last years.…”

Section: Discussionmentioning

confidence: 99%

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

et al. 2016

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Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis.

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Cerebellar lobules and dentate nuclei mirror cortical force‐related‐BOLD responses: Beyond all (linear) expectations

Alahmadi

Pardini

Samson

et al. 2017

Human Brain Mapping

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The relationship between the BOLD response and an applied force was quantified in the cerebellum using a power grip task. To investigate whether the cerebellum responds in an on/off way to motor demands or contributes to motor responses in a parametric fashion, similarly to the cortex, five grip force levels were investigated under visual feedback. Functional MRI data were acquired in 13 healthy volunteers and their responses were analyzed using a cerebellum‐optimized pipeline. This allowed us to evaluate, within the cerebellum, voxelwise linear and non‐linear associations between cerebellar activations and forces. We showed extensive non‐linear activations (with a parametric design), covering the anterior and posterior lobes of the cerebellum with a BOLD‐force relationship that is region‐dependent. Linear responses were mainly located in the anterior lobe, similarly to the cortex, where linear responses are localized in M1. Complex responses were localized in the posterior lobe, reflecting its key role in attention and executive processing, required during visually guided movement. Given the highly organized responses in the cerebellar cortex, a key question is whether deep cerebellar nuclei show similar parametric effects. We found positive correlations with force in the ipsilateral dentate nucleus and negative correlations on the contralateral side, suggesting a somatotopic organization of the dentate nucleus in line with cerebellar and cortical areas. Our results confirm that there is cerebellar organization involving all grey matter structures that reflect functional segregation in the cortex, where cerebellar lobules and dentate nuclei contribute to complex motor tasks with different BOLD response profiles in relation to the forces. Hum Brain Mapp 38:2566–2579, 2017. © 2017 Wiley Periodicals, Inc.

show abstract

The handyman's brain: A neuroimaging meta-analysis describing the similarities and differences between grip type and pattern in humans

Cited by 36 publications

References 105 publications

Differential involvement of cortical and cerebellar areas using dominant and nondominant hands: An FMRI study

Differential involvement of cortical and cerebellar areas using dominant and nondominant hands: An FMRI study

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

Cerebellar lobules and dentate nuclei mirror cortical force‐related‐BOLD responses: Beyond all (linear) expectations

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