Two different areas within the primary motor cortex of man

Geyer, Stefan; Ledberg, Anders; Schleicher, Axel; Kinomura, Shigeo; Schormann, Thorsten; Bürgel, Uli; Klingberg, Torkel; Larsson, Jonas; Zilles, Karl; Roland, Per E.

doi:10.1038/382805a0

Cited by 586 publications

(496 citation statements)

References 19 publications

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“…5b). The cytoarchitectural subdivision of BA 4 into BA 4a and 4p has been linked to the fact that these subareas are also functionally distinguished [Geyer et al, 1996]. Recently, we also demonstrated that BA 4p but not 4a responds to increasing GF levels with a BOLD signal changing in a complex nonlinear fashion [Alahmadi et al, 2015].…”

Section: Discussionmentioning

confidence: 90%

“…The SPM anatomy toolbox included individual areas such as: primary motor cortex [Brodmann areas (BA) 4a and 4p] [Geyer et al, 1996], premotor cortex (BA 6) [Geyer, 2003], primary somatosensory cortex (BA 3a, 3b, 1) [Geyer et al, 1996], somatosensory cortex (BA 2) [Grefkes et al, 2001], parietal operculum or S2 (OP 1‐4) [Eickhoff et al, 2006a, 2006b,2007a], intraparietal sulcus [Choi et al, 2006; Scheperjans et al, 2008a, 2008b], superior parietal cortex [Scheperjans et al, 2008a,,b], inferior parietal cortex [Caspers et al, 2008], and visual areas (V4) [Rottschy et al, 2007] (V4) [Malikovic et al, 2007]. Some Figures were generated using FIVE (www.nmr.mgh.harvard.edu/harvardagingbrain/People/AaronSchultz/FIVE) and MRIcron (http://www.nitrc.org/projects/mricron).…”

Section: Methodsmentioning

confidence: 99%

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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: Discussionmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

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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“…ROI ‐5 (blue) includes the posterior part of the BA 4 (Geyer et al. 1996). ROI ‐6 (green) includes BA 6 (Geyer 2003).…”

Section: Resultsmentioning

confidence: 99%

“…(1996), but selecting only the posterior part of the primary motor cortex (bilateral BA 4p) to focus on the hand representation.…”

Section: Methodsmentioning

confidence: 99%

Probing the reaching–grasping network in humans through multivoxel pattern decoding

et al. 2015

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IntroductionThe quest for a putative human homolog of the reaching–grasping network identified in monkeys has been the focus of many neuropsychological and neuroimaging studies in recent years. These studies have shown that the network underlying reaching‐only and reach‐to‐grasp movements includes the superior parieto‐occipital cortex (SPOC), the anterior part of the human intraparietal sulcus (hAIP), the ventral and the dorsal portion of the premotor cortex, and the primary motor cortex (M1). Recent evidence for a wider frontoparietal network coding for different aspects of reaching‐only and reach‐to‐grasp actions calls for a more fine‐grained assessment of the reaching–grasping network in humans by exploiting pattern decoding methods (multivoxel pattern analysis—MVPA).MethodsHere, we used MPVA on functional magnetic resonance imaging (fMRI) data to assess whether regions of the frontoparietal network discriminate between reaching‐only and reach‐to‐grasp actions, natural and constrained grasping, different grasp types, and object sizes. Participants were required to perform either reaching‐only movements or two reach‐to‐grasp types (precision or whole hand grasp) upon spherical objects of different sizes.ResultsMultivoxel pattern analysis highlighted that, independently from the object size, all the selected regions of both hemispheres contribute in coding for grasp type, with the exception of SPOC and the right hAIP. Consistent with recent neurophysiological findings on monkeys, there was no evidence for a clear‐cut distinction between a dorsomedial and a dorsolateral pathway that would be specialized for reaching‐only and reach‐to‐grasp actions, respectively. Nevertheless, the comparison of decoding accuracy across brain areas highlighted their different contributions to reaching‐only and grasping actions.ConclusionsAltogether, our findings enrich the current knowledge regarding the functional role of key brain areas involved in the cortical control of reaching‐only and reach‐to‐grasp actions in humans, by revealing novel fine‐grained distinctions among action types within a wide frontoparietal network.

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“…These include the subdivision of the primary motor area 4 (REF. 40), as well as the TE1.0 and TE1.1 (temporal cortex82) subdivisions of the primary auditory cortex, which were revealed by the distribution pattern of receptors (FIG. 4c).…”

Section: Molecular Architectonicsmentioning

confidence: 99%

Towards multimodal atlases of the human brain

et al. 2006

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Atlases of the human brain have an important impact on neuroscience. The emergence of ever more sophisticated imaging techniques, brain mapping methods and analytical strategies has the potential to revolutionize the concept of the brain atlas. Atlases can now combine data describing multiple aspects of brain structure or function at different scales from different subjects, yielding a truly integrative and comprehensive description of this organ. These integrative approaches have provided significant impetus for the human brain mapping initiatives, and have important applications in health and disease.The concept of the brain atlas is not new1. Cartographic approaches have been used for centuries to identify and target specific regions in the brain and to establish spatial relationships between a coordinate and a structure. Comprehensive maps of brain structure have been created, at a variety of spatial scales, from anatomical specimens2 -5 and various histological preparations that reveal regional cytoarchitecture6 , 7, myelination patterns8 -10, and protein and mRNA distributions. Most early and some more recent atlases of the human brain were derived from one, or at best a few, individual post-mortem specimens3 -5 , 11 -14. Such atlases provide anatomical references or represent a particular feature of the brain15 , 16, such as a specific neurochemical distribution17 or the cellular architecture of the cerebral cortex6. For example, Brodmann's map (1909) exclusively describes the cytoarchitectonic segregation of the cortex6, Dejerine's map (1901) describes fibre tract anatomy18, and the map by Schaltenbrand and Wahren (1977) describes the thalamus14. NIH Public Access Author ManuscriptNat Rev Neurosci. Author manuscript; available in PMC 2011 June 13. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptBeyond these traditional, anatomical atlases based on post-mortem tissue, modern brain atlases are being developed that incorporate flexible, computable systems, which accommodate the sometimes considerable variation in a population. The application of magnetic resonance imaging (MRI) to acquire detailed descriptions of anatomy in vivo is a driving force in brain mapping research. Tomographic imaging has the advantage of largely retaining the spatial integrity of the data by maintaining the intrinsic three-axis registration and simple volumetric coordinates19 , 20. The atlases derived from these images are digital, allowing a wealth of computational algorithms to be applied to automatically align new twoand three-dimensional imaging data into the coordinate systems of these atlases21. Furthermore, there is an increasing ability to image various structural (as well as functional and chemical) features in the brain such as nuclei, cytoarchitectural details and white matter tracts. Technological advances continue to improve spatial and contrast resolution and have led to multispectral characterization (using MRI) of brain anatomy, reflecting features such as lipid content or water ...

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Two different areas within the primary motor cortex of man

Cited by 586 publications

References 19 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

Probing the reaching–grasping network in humans through multivoxel pattern decoding

Towards multimodal atlases of the human brain

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