M King1, H G Rauch2, D J Stein3, S J Brooks3. 1. Department of Human Biology, Faculty of Medicine, University of Cape Town, UCT/MRC Research Unit for Exercise Science and Sports Medicine, South Africa. Electronic address: michaeltcking@me.com. 2. Department of Human Biology, Faculty of Medicine, University of Cape Town, UCT/MRC Research Unit for Exercise Science and Sports Medicine, South Africa. 3. Department of Psychiatry and Mental Health, University of Cape Town, South Africa.
Abstract
BACKGROUND: Handgrip is a ubiquitous human movement that was critical in our evolution. However, the differences in brain activity between grip type (i.e. power or precision) and pattern (i.e. dynamic or static) are not fully understood. In order to address this, we performed Activation Likelihood Estimation (ALE) analysis between grip type and grip pattern using functional magnetic resonance imaging (fMRI) data. ALE provides a probabilistic summary of the BOLD response in hundreds of subjects, which is often beyond the scope of a single fMRI experiment. METHODS: We collected data from 28 functional magnetic resonance data sets, which included a total of 398 male and female subjects. Using ALE, we analyzed the BOLD response during power, precision, static and dynamic grip in a range of forces and age in right handed healthy individuals without physical impairment, cardiovascular or neurological dysfunction using a variety of grip tools, feedback and experimental training. RESULTS: Power grip generates unique activation in the postcentral gyrus (areas 1 and 3b) and precision grip generates unique activation in the supplementary motor area (SMA, area 6) and precentral gyrus (area 4a). Dynamic handgrip generates unique activation in the precentral gyrus (area 4p) and SMA (area 6) and of particular interest, both dynamic and static grip share activation in the area 2 of the postcentral gyrus, an area implicated in the evolution of handgrip. According to effect size analysis, precision and dynamic grip generates stronger activity than power and static, respectively. CONCLUSION: Our study demonstrates specific differences between grip type and pattern. However, there was a large degree of overlap in the pre and postcentral gyrus, SMA and areas of the frontal-parietal-cerebellar network, which indicates that other mechanisms are potentially involved in regulating handgrip. Further, our study provides empirically based regions of interest, which can be downloaded here within, that can be used to more effectively study power grip in a range of populations and conditions.
BACKGROUND: Handgrip is a ubiquitous human movement that was critical in our evolution. However, the differences in brain activity between grip type (i.e. power or precision) and pattern (i.e. dynamic or static) are not fully understood. In order to address this, we performed Activation Likelihood Estimation (ALE) analysis between grip type and grip pattern using functional magnetic resonance imaging (fMRI) data. ALE provides a probabilistic summary of the BOLD response in hundreds of subjects, which is often beyond the scope of a single fMRI experiment. METHODS: We collected data from 28 functional magnetic resonance data sets, which included a total of 398 male and female subjects. Using ALE, we analyzed the BOLD response during power, precision, static and dynamic grip in a range of forces and age in right handed healthy individuals without physical impairment, cardiovascular or neurological dysfunction using a variety of grip tools, feedback and experimental training. RESULTS: Power grip generates unique activation in the postcentral gyrus (areas 1 and 3b) and precision grip generates unique activation in the supplementary motor area (SMA, area 6) and precentral gyrus (area 4a). Dynamic handgrip generates unique activation in the precentral gyrus (area 4p) and SMA (area 6) and of particular interest, both dynamic and static grip share activation in the area 2 of the postcentral gyrus, an area implicated in the evolution of handgrip. According to effect size analysis, precision and dynamic grip generates stronger activity than power and static, respectively. CONCLUSION: Our study demonstrates specific differences between grip type and pattern. However, there was a large degree of overlap in the pre and postcentral gyrus, SMA and areas of the frontal-parietal-cerebellar network, which indicates that other mechanisms are potentially involved in regulating handgrip. Further, our study provides empirically based regions of interest, which can be downloaded here within, that can be used to more effectively study power grip in a range of populations and conditions.
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