Finger Somatotopy in Human Motor Cortex

Beisteiner, Roland; Windischberger, Christian; Lanzenberger, Rupert; Edward, Vinod; Cunnington, Ross; Erdler, Marcus; Gartus, Andreas; Streibl, B.; Moser, Ewald; Deecke, L.

doi:10.1006/nimg.2000.0737

Cited by 124 publications

(104 citation statements)

References 35 publications

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“…Others have taken from McGonigle et al [2000] the simple broadbrush conclusion that there was a "large amount of session variability" [e.g., Beisteiner et al, 2001;Chee et al, 2003]. One of the purposes here is to address this misconception; for example, we show that for this dataset, intersession variability was of similar magnitude to within-session variability.…”

Section: Introductionmentioning

confidence: 66%

“…Nevertheless, unfortunately, many researchers [e.g., Beisteiner et al, 2001;Chee et al, 2003] seem to have taken these messages from the study. One of the causes of this is the apparent variability in Figures 2-4 in McGonigle et al [2000], which show for each paradigm each session's thresholded activation image (as a single sagittal slice maximum intensity projection).…”

Section: On (Not) Drawing Conclusion About Sessionmentioning

confidence: 99%

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Variability in fMRI: A re‐examination of inter‐session differences

Smith

Beckmann

Ramnani

et al. 2005

Human Brain Mapping

167

116

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Abstract:We revisit a previous study on inter-session variability (McGonigle et al. [2000]: Neuroimage 11:708 -734), showing that contrary to one popular interpretation of the original article, inter-session variability is not necessarily high. We also highlight how evaluating variability based on thresholded single-session images alone can be misleading. Finally, we show that the use of different first-level preprocessing, time-series statistics, and registration analysis methodologies can give significantly different inter-session analysis results. Hum Brain Mapp 24:248 -257, 2005.

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Section: Introductionmentioning

confidence: 66%

Section: On (Not) Drawing Conclusion About Sessionmentioning

confidence: 99%

Variability in fMRI: A re‐examination of inter‐session differences

Smith

Beckmann

Ramnani

et al. 2005

Human Brain Mapping

167

116

View full text Add to dashboard Cite

show abstract

“…In the primary motor cortex of monkeys, single neurons are active during multiple digit movements and such neurons are dispersed through the entire representation of the hand (Poliakov and Schieber 1999). In humans, fMRI studies suggest partial segregation of digit-specific regions in primary motor cortex (Kleinschmidt et al 1997;Beisteiner et al 2001) and this may contribute to the ability of humans to individuate digit movements. Moreover, clinical studies of the effects of small cortical lesions also suggest some degree of digit specialization in primary motor cortex (Schieber 1999;Kim 2001).…”

Section: Factors Contributing To the Pattern Of Digit Independencementioning

confidence: 99%

The statistics of natural hand movements

et al. 2008

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Humans constantly use their hands to interact with the environment and they engage spontaneously in a wide variety of manual activities during everyday life. In contrast, laboratorybased studies of hand function have used a limited range of predefined tasks. The natural movements made by the hand during everyday life have thus received little attention. Here, we developed a portable recording device that can be worn by subjects to track movements of their right hand as they go about their daily routine outside of a laboratory setting. We analyse the kinematic data using various statistical methods. Principal component analysis of the joint angular velocities showed that the first two components were highly conserved across subjects, explained 60% of the variance and were qualitatively similar to those reported in previous studies of reachto-grasp movements. To examine the independence of the digits, we developed a measure based on the degree to which the movements of each digit could be linearly predicted from the movements of the other four digits. Our independence measure was highly correlated with results from previous studies of the hand, including the estimated size of the digit representations in primary motor cortex and other laboratory measures of digit individuation. Specifically, the thumb was found to be the most independent of the digits and the index finger was the most independent of the fingers. These results support and extend laboratory-based studies of the human hand.

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“…Studies using fMRI have revealed somatotopic representations of the hand, fingers, wrist, elbow, shoulder, foot, toes, lips, and tongue in human brains (Alkadhi et al, 2002;Beisteiner et al, 2001;Blankenburg et al, 2003;Dechent and Frahm, 2003;Francis et al, 2000;Gelnar et al, 1998;Golaszewski et al, 2006;Hanakawa et al, 2005;Hlustik et al, 2001;Kurth et al, 2000;Lotze et al, 2000;McGlone et al, 2002;Miyamoto et al, 2006;Moore et al, 2000a;Overduin and Servos, 2004;Ruben et al, 2001;Servos et al, 1998;Stippich et al, 1999Stippich et al, , 2004van Westen et al, 2004; also see reviews in Burton, 2002). The human face contains important sensory organs and is essential for verbal and nonverbal communications in daily life.…”

Section: Introductionmentioning

confidence: 99%

Dodecapus: An MR-compatible system for somatosensory stimulation

Huang

Sereno

2007

NeuroImage

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Somatotopic mapping of human body surface using fMRI is challenging. First, it is difficult to deliver tactile stimuli in the scanner. Second, multiple stimulators are often required to cover enough area of the complex-shaped body surface, such as the face. In this study, a computer-controlled pneumatic system was constructed to automatically deliver air puffs to 12 locations on the body surface through an MR-compatible manifold (Dodecapus) mounted on a head coil inside the scanner bore. The timing of each air-puff channel is completely programmable and this allows systematic and precise stimulation on multiple locations on the body surface during functional scans. Three two-condition block-design "Localizer" paradigms were employed to localize the cortical representations of the face, lips, and fingers, respectively. Three "Phase-encoded" paradigms were employed to map the detailed somatotopic organizations of the face, lips, and fingers following each "Localizer" paradigm. Multiple somatotopic representations of the face, lips, and fingers were localized and mapped in primary motor cortex (MI), ventral premotor cortex (PMv), polysensory zone (PZ), primary (SI) and secondary (SII) somatosensory cortex, parietal ventral area (PV) and 7b, as well as anterior and ventral intraparietal areas (AIP and VIP). The Dodecapus system is portable, easy to setup, generates no radio frequency interference, and can also be used for EEG and MEG experiments. This system could be useful for non-invasive somatotopic mapping in both basic and clinical studies.

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Finger Somatotopy in Human Motor Cortex

Cited by 124 publications

References 35 publications

Variability in fMRI: A re‐examination of inter‐session differences

Variability in fMRI: A re‐examination of inter‐session differences

The statistics of natural hand movements

Dodecapus: An MR-compatible system for somatosensory stimulation

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