Cognitive motor processes: The role of motor imagery in the study of motor representations

Munzert, Jörn; Lorey, Britta; Zentgraf, Karen

doi:10.1016/j.brainresrev.2008.12.024

Cited by 635 publications

(504 citation statements)

References 253 publications

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“…These electrodes were selected on the basis of the hypothesized location of the overlap between brain activity associated with illusory hand ownership and hand motor imagery (e.g. Kanayama et al, 2009;Munzert et al, 2009) and because somatosensory evoked potentials at electrodes C3 and C4 have been shown to be modulated by illusory ownership (Peled et al, 2003;Press et al, 2008). We note, however, that EEG changes at scalp electrodes C3/C4 may result from neural generators at close and distant locations in the brain (Michel and Murray, 2012).…”

Section: Eeg: Preprocessingmentioning

confidence: 99%

“…The application of a linear, distributed inverse solution localized these changes to contralateral and ipsilateral fronto-parietal cortex including premotor and posterior parietal cortices as well as the postcentral gyrus. These regions have been involved in a number of studies in motor imagery (see reviews from Grèzes and Decety, 2001;Munzert et al, 2009). Several studies using neuroimaging (Kosslyn et al, 2001), transcranial magnetic stimulation (Ganis et al, 2000), or clinical investigations (Sirigu et al, 1996) showed that motor imagery shares neural mechanisms with movement planning (Decety et al, 1989) and movement execution (Gerardin et al, 2000;Parsons et al, 1995), in particular in premotor cortex (e.g.…”

Section: Shared Spectral and Anatomical Mechanisms Between Motor Imagmentioning

confidence: 99%

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Shared electrophysiology mechanisms of body ownership and motor imagery

Evans

Blanke

2013

NeuroImage

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Although we feel, see, and experience our hands as our own (body or hand ownership), recent research has shown that illusory hand ownership can be induced for fake or virtual hands and may be useful for neuroprosthetics and brain-computer interfaces. Despite the vast amount of behavioral data on illusory hand ownership, neuroimaging studies are rare, in particular electrophysiological studies. Thus, while the neural systems underlying hand ownership are relatively well described, the spectral signatures of body ownership as measured by electroencephalography (EEG) remain elusive. Here we induced illusory hand ownership in an automated, computer-controlled manner using virtual reality while recording 64-channel EEG and found that illusory hand ownership is reflected by a body-specific modulation in the mu-band over fronto-parietal cortex. In a second experiment in the same subjects, we then show that mu as well as beta-band activity in highly similar fronto-parietal regions was also modulated during a motor imagery task often used in paradigms employing non-invasive brain-computer interface technology. These data provide insights into the electrophysiological brain mechanisms of illusory hand ownership and their strongly overlapping mechanisms with motor imagery in fronto-parietal cortex. They also highlight the potential of combining high-resolution EEG with virtual reality setups and automatized stimulation protocols for systematic, reproducible stimulus presentation in cognitive neuroscience, and may inform the design of non-invasive brain-computer interfaces.

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Section: Eeg: Preprocessingmentioning

confidence: 99%

Section: Shared Spectral and Anatomical Mechanisms Between Motor Imagmentioning

confidence: 99%

Shared electrophysiology mechanisms of body ownership and motor imagery

Evans

Blanke

2013

NeuroImage

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“…the mental simulation of a motor act. It has been suggested that kinesthetic motor imagery involves the same neural network as motor planning (Jeannerod, 1994;Jeannerod and Frak, 1999), which in turn is thought to rely on the same motor structures as motor execution (Johnson-Frey, 2004;Munzert et al, 2009;Sharma et al, 2006). In support of this view, motor imagery shares a number of similarities with overt movement execution, such as behavioral (Decety and Jeannerod, 1995) and physiological parameters (Kranczioch et al, 2008(Kranczioch et al, , 2009, and, importantly, the functional neuroanatomical correlates (Decety, 1996;Lotze and Halsband, 2006;Porro et al, 1996;Szameitat et al, 2007aSzameitat et al, , 2007b.…”

Section: Introductionmentioning

confidence: 98%

Cortical activation during executed, imagined, observed, and passive wrist movements in healthy volunteers and stroke patients

et al. 2012

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“…MI is defined as an internal, conscious, and self‐intended rehearsal of movements from a first‐person perspective without any overt physical movement [Crammond, 1997; Decety and Jeannerod, 1996; Hanakawa et al, 2008; Jeannerod, 1994; see Munzert et al, 2009; Vogt et al, 2013, for reviews]. On a neural level, it has been proposed that MI is a simulation that uses the motor system as a substrate [Lange et al, 2006; Jeannerod 2001].…”

Section: Introductionmentioning

confidence: 99%

“…This has been supported by several neuroimaging studies showing that roughly the same brain areas are involved in both motor execution and MI [Decety et al, 1994; Deiber et al, 1996; Hanakawa et al, 2008; Lotze et al, 1999; Porro et al, 1996]. More precisely, this neural network is believed to be organized around the following motor and motor‐related regions: the supplementary motor area (SMA), the premotor cortex (PMC), the primary motor cortex (M1), posterior parietal regions such as the inferior (IPL) and the superior parietal lobe (SPL), the basal ganglia (BG), and the cerebellum [Guillot et al, 2008; Lotze et al, 1999; Munzert et al, 2009]. …”

Section: Introductionmentioning

confidence: 99%

Motor imagery of hand actions: Decoding the content of motor imagery from brain activity in frontal and parietal motor areas

et al. 2015

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How motor maps are organized while imagining actions is an intensely debated issue. It is particularly unclear whether motor imagery relies on action‐specific representations in premotor and posterior parietal cortices. This study tackled this issue by attempting to decode the content of motor imagery from spatial patterns of Blood Oxygen Level Dependent (BOLD) signals recorded in the frontoparietal motor imagery network. During fMRI‐scanning, 20 right‐handed volunteers worked on three experimental conditions and one baseline condition. In the experimental conditions, they had to imagine three different types of right‐hand actions: an aiming movement, an extension–flexion movement, and a squeezing movement. The identity of imagined actions was decoded from the spatial patterns of BOLD signals they evoked in premotor and posterior parietal cortices using multivoxel pattern analysis. Results showed that the content of motor imagery (i.e., the action type) could be decoded significantly above chance level from the spatial patterns of BOLD signals in both frontal (PMC, M1) and parietal areas (SPL, IPL, IPS). An exploratory searchlight analysis revealed significant clusters motor‐ and motor‐associated cortices, as well as in visual cortices. Hence, the data provide evidence that patterns of activity within premotor and posterior parietal cortex vary systematically with the specific type of hand action being imagined. Hum Brain Mapp 37:81–93, 2016. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

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Cognitive motor processes: The role of motor imagery in the study of motor representations

Cited by 635 publications

References 253 publications

Shared electrophysiology mechanisms of body ownership and motor imagery

Shared electrophysiology mechanisms of body ownership and motor imagery

Cortical activation during executed, imagined, observed, and passive wrist movements in healthy volunteers and stroke patients

Motor imagery of hand actions: Decoding the content of motor imagery from brain activity in frontal and parietal motor areas

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