Both primary motor cortex and supplementary motor area play an important role in complex finger movement

Shibasaki, Hiroshi; Sadato, Norihiro; Lyshkow, Hugh; Yonekura, Yoshiharu; Honda, Manabu; Nakagawa, Takashi; Suwazono, Shugo; Magata, Yasuhiro; Ikeda, Akio; Miyazaki, Masahito; Fukuyama, Hidenao; Asato, R; Konishi, Junji

doi:10.1093/brain/116.6.1387

Cited by 478 publications

(217 citation statements)

References 15 publications

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“…PET studies have shown that MI is activated as much by whole hand movements as by the independent movement of the fingers [5]. Simultaneous movements of two fingers causes even less activation of MI than sequential movements of these fingers with the frequency of movements being kept constant [29]. Thus, to move or not to move individual digits of the hand may be mediated by excitatory MI-activity.…”

Section: Discussionmentioning

confidence: 99%

Electric and magnetic fields of the brain accompanying internal simulation of movement

Lang¹,

Cheyne

Höllinger³

et al. 1996

Cognitive Brain Research

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Methods of functional brain imaging have been used to identify brain structures which are active during internal simulation of movements (ISM). Between 1977 and 1993 it was consistently reported that the primary motor cortex (MI) is not active during ISM whereas other cortical areas, in particular the supplementary motor area (SMA) are active. ISM was assumed to be a situation of 'internal programming'. Brain systems involved in ISM or 'programming' were hypothesized to be superior to and separable from 'executive system' including MI. We have studied electric and magnetic fields of the brain when subjects internally simulated either a single movement or a sequence of movements. Results of the studies are consistent with the assumption that MI is active with ISM. Internally subjects experienced effort which was required to inhibit overt movements during ISM. A recent EEG study showed different patterns of cortical activity with ISM and with movement inhibition suggesting that different brain structures may be active during ISM and movement inhibition [23].

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Section: Discussionmentioning

confidence: 99%

Electric and magnetic fields of the brain accompanying internal simulation of movement

Lang¹,

Cheyne

Höllinger³

et al. 1996

Cognitive Brain Research

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“…For the purpose of BCI, we are interested in the brain signal associated with movement intention preceding movement. The intention to move is associated with at least two cortical activities over sensorimotor and supplementary motor cortices: the movement-related cortical potential, which occurs about −1.5 s before the movement (Shibasaki et al 1993); and event-related desynchronization (ERD) or power decrease in alpha and beta bands, which occurs as early as 2s before the movement (Toro et al 1994a). Furthermore, these activities are available even though no movement occurs (Castro et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG

Bai

Lin

Vorbach

et al. 2007

Clinical Neurophysiology

119

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Objectives-To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).Methods-Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD); temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT); pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. NIH Public AccessResults-The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention.Conclusions-Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could be the basis for a potential brain-computer interface based on human natural movement, which might reduce the requirement of long-term training.Significance-Effective combinations of computational methods can classify human movement intention from single trial EEG with reasonable accuracy.

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“…There has been a great deal of interest in factors thought to affect the functional activation associated with movements of the hand and arm, such as the spatial and temporal complexity (Roland et al, 1980b;Colebatch et al, 1991;Grafton et al, 1992;Matelli et al, 1993;Kawashima et al, 1994a,b;Shibasaki et al, 1993;Sadato et al, 1996), whether movements were stimulus triggered or internally generated (Roland et al, 1980a;Fox et al, 1985;Deiber et al, 1991Deiber et al, , 1996Rao et al, 1993Rao et al, , 1997Boecker et al, 1994;Larsson et al, 1996), and the learning and acquisition of motor skills (Seitz et al, 1990Seitz and Roland, 1992;Jenkins et al, 1994;Schlaug et al, 1994;Grafton et al, 1995;Deiber et al, 1997;Hazeltine et al, 1997;Jueptner et al, 1997a,b;Shadmehr and Holcomb, 1997). However, to our knowledge there have not been any functional imaging studies which have specifically addressed the issue of the predictability of a motor response.…”

Section: Introductionmentioning

confidence: 99%

Effects of movement predictability on cortical motor activation

Dassonville

Lewis

Zhu

et al. 1998

Neuroscience Research

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Humans have the ability to make motor responses to unpredictable visual stimuli, and do so as a matter of course on a daily basis. We used functional magnetic resonance imaging (fMRI) to examine the neural substrate of this behavior in six cortical motor areas. We found that five of these areas (premotor, cingulate, supplementary motor area, pre-supplementary motor area, and superior parietal lobule) showed increased activation in association with an unpredictable behavior compared to a predictable one; only the motor cortex remained unchanged. There was also a quantitative relation between the response time and functional activation in the premotor and cingulate cortex. There was less activation across all the motor areas with repetition of the motor tasks. With the exception of the pre-supplementary motor area, all areas were significantly lateralized, with a greater volume of activation in the hemisphere contralateral to the performing hand. In addition, a left hemisphere dominance was found in the activation of motor cortex and supplementary motor areas. Our results suggest that activation in motor areas is differentially and quantitatively related to higher order aspects of motor behavior such as movement predictability.

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Both primary motor cortex and supplementary motor area play an important role in complex finger movement

Cited by 478 publications

References 15 publications

Electric and magnetic fields of the brain accompanying internal simulation of movement

Electric and magnetic fields of the brain accompanying internal simulation of movement

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG

Effects of movement predictability on cortical motor activation

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