Three-dimensional locations and boundaries of motor and premotor cortices as defined by functional brain imaging: A meta-analysis

Mayka, Mary A.; Corcos, Daniel M.; Leurgans, Sue E.; Vaillancourt, David E.

doi:10.1016/j.neuroimage.2006.02.004

Cited by 652 publications

(566 citation statements)

References 205 publications

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“…A smaller portion corresponded to significant increases of activation in areas surrounding the controlling electrode. To determine anatomically relevant patterns of activity dynamics, electrodes were assigned to cortical areas using the human motor area template (HMAT) atlas (29) and the Talairach Daemon (30,31). Significant lessening of activation was found in 31 electrodes corresponding to labels of PMd, PMv, PFC, and PPC, as shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Distributed cortical adaptation during learning of a brain–computer interface task

Wander¹,

Blakely²,

Miller

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

134

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The majority of subjects who attempt to learn control of a braincomputer interface (BCI) can do so with adequate training. Much like when one learns to type or ride a bicycle, BCI users report transitioning from a deliberate, cognitively focused mindset to near automatic control as training progresses. What are the neural correlates of this process of BCI skill acquisition? Seven subjects were implanted with electrocorticography (ECoG) electrodes and had multiple opportunities to practice a 1D BCI task. As subjects became proficient, strong initial task-related activation was followed by lessening of activation in prefrontal cortex, premotor cortex, and posterior parietal cortex, areas that have previously been implicated in the cognitive phase of motor sequence learning and abstract task learning. These results demonstrate that, although the use of a BCI only requires modulation of a local population of neurons, a distributed network of cortical areas is involved in the acquisition of BCI proficiency.brain-machine interface | motor learning | plasticity | electrophysiology | high gamma

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Section: Resultsmentioning

confidence: 99%

Distributed cortical adaptation during learning of a brain–computer interface task

Wander¹,

Blakely²,

Miller

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

134

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“…1A) (SI Materials and Methods). Stimulation intensity was set to 90% of individual RMT of the left motor hand area and was corrected for the difference in the scalp-cortex distance between the motor cortex (mean coordinates taken from Mayka et al [36]) and the SMG (37) (SI Materials and Methods). During each experimental trial, a four-pulse train of biphasic stimuli was applied at a rate of 10 Hz over left, right, or bilateral SMG 100 ms after word onset (Fig.…”

Section: Methodsmentioning

confidence: 99%

Phonological decisions require both the left and right supramarginal gyri

Hartwigsen

Baumgaertner

Price

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

307

221

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Recent functional imaging studies demonstrated that both the left and right supramarginal gyri (SMG) are activated when healthy right-handed subjects make phonological word decisions. However, lesion studies typically report difficulties with phonological processing after left rather than right hemisphere damage. Here, we used a unique dual-site transcranial magnetic stimulation (TMS) approach to test whether the SMG in the right hemisphere contributes to modality-independent (i.e., auditory and visual) phonological decisions. To test task-specificity, we compared the effect of real or sham TMS during phonological, semantic, and perceptual decisions. To test laterality and anatomical specificity, we compared the effect of TMS over the left, right, or bilateral SMG and angular gyri. The accuracy and reaction times of phonological decisions were selectively disrupted relative to semantic and perceptual decisions when real TMS was applied over the left, right, or bilateral SMG. These effects were not observed for TMS over the angular gyri. A follow-up experiment indicated that the threshold-intensity for inducing a disruptive effect on phonological decisions was identical for unilateral TMS over the right or left SMG. Taken together, these findings provide converging evidence that the right SMG contributes to accurate and efficient phonological decisions in the healthy brain, with no evidence that the left and right SMG can compensate for one another during TMS. Our findings motivate detailed studies of phonological processing in patients with acute or long-term damage of the right SMG.M any previous functional imaging studies have shown that the left and right supramarginal gyri (SMG) are activated when right-handed participants make decisions about the sounds of words (i.e., their phonology) compared with decisions about their meanings (i.e., their semantics) (1-4). However, the functional significance of right SMG activation is unclear because lesion studies have reported phonological difficulties following left rather than right temporo-parietal lesions (5-8). Consequently, anatomical models of phonological processing have included left but not right parietal cortex (9, 10). The present study was designed to address the discrepancy between functional imaging and lesion studies. More specifically, we examined how "online" transcranial magnetic stimulation (i.e., TMS during a task) over the left and right SMG influences phonological word processing in healthy subjects (Fig. 1). We used the neurodisruptive effect of TMS to distinguish between three alternative hypotheses to explain right SMG activation with phonological processing.Hypothesis 1 is that right SMG only contributes to the speed but not the accuracy of phonological decisions. Consequently, right SMG lesions have a subtle effect on phonological processing that might be missed unless reaction times were measured. In this case, we expect a selective effect of right SMG TMS on reaction times in the healthy brain without affecting error rates.Hypothesis 2 i...

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“…The first 12 ROIs were specified using the Human Motor Areas Template (HMAT), which specifies cortical areas that are involved in human motor control based on a meta-analysis of 126 studies (Mayka et al, 2006). The areas included in the HMAT are the primary motor cortex (M1), the primary somatosensory cortex (S1), supplementary motor area (SMA), presupplementary motor area (pSMA), dorsal premotor cortex (PMd) and ventral premotor cortex (PMv).…”

Section: Roi Analysismentioning

confidence: 99%

Aging effects on the control of grip force magnitude: An fMRI study

Noble

Eng

Kokotilo

et al. 2011

Experimental Gerontology

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Functional neuroimaging techniques have allowed for investigations into the mechanisms of agerelated deterioration in motor control. This study used functional Magnetic Resonance Imaging (fMRI) to investigate age related differences in the control of grip force magnitude. Using an event-related design, fMRI scans were completed on 13 older adults, and 13 gender matched younger adults, while using their dominant hand to squeeze a rubber bulb for 4s at 10%, 40% or 70% of their maximum voluntary contraction. Both groups were able to match the relative force targets, however the older adults produced significantly lower levels of absolute force. fMRI analysis consisted of a 1) region of interest (ROI) approach to detect differences in selected motor areas within brain and 2) a voxel-wise whole brain comparison to find areas of differential activation that were not defined a priori between the older and younger group. The ROI analysis revealed that despite producing lower levels of absolute force, the older adults showed higher levels of activity predominantly in subcortical structures (putamen, thalamus and cerebellum) when compared to the younger group. The older adults also showed higher levels of activity in the ipsilateral ventral premotor cortex. A total of 19 of the 22 ROIs analyzed showed a significant main effect of the required force-level. In the majority of the ROIs that showed a significant force effect there were no significant differences in the magnitude of the blood-oxygen-level-dependent (BOLD) signal between the 10% and 40% conditions but a significantly higher BOLD signal in the 70% condition, suggesting that the modulation of brain activation with grip force may not be controlled in a linear fashion. It was also found that the older adult group demonstrate higher levels of activation in 7 areas during a force production task at higher force levels using a voxelwise analysis. The 7 clusters that showed significant differences tended to be areas that are involved in visual-spatial and executive processing. The results of this study revealed that older adults require significantly higher activation of several areas to perform the same motor task as younger adults. Higher magnitudes of the BOLD signal in older adults may represent a compensatory pattern to counter age related deterioration in motor control systems.Corresponding Author: Janice J. Eng, PT, OT, Ph.D., Professor, Department of Physical Therapy, University of British Columbia, 212-2177 Wesbrook Mall, Vancouver, BC, Canada V6T 1Z3, Janice.Eng@ubc.ca, Phone: IntroductionThe normal aging process leads to several declines of the motor system that are related to changes within the central nervous system, peripheral nervous system and the musculoskeletal system (Seidler et al., 2010). These changes have the potential to lead to decreased motor performance with aging, which has been observed in the forms of decreased coordination, increased movement variability, slower movements and difficulties with balance and gait (Seidler et al., 2...

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Three-dimensional locations and boundaries of motor and premotor cortices as defined by functional brain imaging: A meta-analysis

Cited by 652 publications

References 205 publications

Distributed cortical adaptation during learning of a brain–computer interface task

Distributed cortical adaptation during learning of a brain–computer interface task

Phonological decisions require both the left and right supramarginal gyri

Aging effects on the control of grip force magnitude: An fMRI study

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