%0 Journal Article %J Proc Natl Acad Sci U S A %D 2010 %T Cortical activity during motor execution, motor imagery, and imagery-based online feedback. %A Miller, K.J. %A Gerwin Schalk %A Fetz, Eberhard E %A den Nijs, Marcel %A Ojemann, J G %A Rao, Rajesh P N %K Adolescent %K Adult %K Biofeedback, Psychology %K Cerebral Cortex %K Child %K Electric Stimulation %K Electrocardiography %K Female %K Humans %K Male %K Middle Aged %K Motor Activity %K Young Adult %X

Imagery of motor movement plays an important role in learning of complex motor skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie motor imagery-based learning? We measured electrocorticographic cortical surface potentials in eight human subjects during overt action and kinesthetic imagery of the same movement, focusing on power in "high frequency" (76-100 Hz) and "low frequency" (8-32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population activity during motor imagery mimics the spatial distribution of activity during actual motor movement. By comparing responses to electrocortical stimulation with imagery-induced cortical surface activity, we demonstrate the role of primary motor areas in movement imagery. The magnitude of imagery-induced cortical activity change was approximately 25% of that associated with actual movement. However, when subjects learned to use this imagery to control a computer cursor in a simple feedback task, the imagery-induced activity change was significantly augmented, even exceeding that of overt movement.

%B Proc Natl Acad Sci U S A %V 107 %P 4430-5 %8 03/2010 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/20160084 %N 9 %R 10.1073/pnas.0913697107 %0 Journal Article %J J Neural Eng %D 2009 %T Decoding flexion of individual fingers using electrocorticographic signals in humans. %A Kubánek, J %A Miller, John W %A Ojemann, J G %A Jonathan Wolpaw %A Gerwin Schalk %K Adolescent %K Adult %K Biomechanics %K Brain %K Electrodiagnosis %K Epilepsy %K Female %K Fingers %K Humans %K Male %K Microelectrodes %K Middle Aged %K Motor Activity %K Rest %K Thumb %K Time Factors %K Young Adult %X

Brain signals can provide the basis for a non-muscular communication and control system, a brain-computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function.

%B J Neural Eng %V 6 %P 066001 %8 12/2009 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/19794237 %N 6 %R 10.1088/1741-2560/6/6/066001 %0 Conference Proceedings %B Conf Proc IEEE Eng Med Biol Soc %D 2008 %T Three cases of feature correlation in an electrocorticographic BCI. %A Miller, John W %A Blakely, Timothy %A Gerwin Schalk %A den Nijs, Marcel %A Rao, Rajesh P N %A Ojemann, J G %K Adolescent %K Adult %K Algorithms %K Electrocardiography %K Evoked Potentials, Motor %K Female %K Humans %K Male %K Middle Aged %K Motor Cortex %K Pattern Recognition, Automated %K Statistics as Topic %K Task Performance and Analysis %K User-Computer Interface %X Three human subjects participated in a closed-loop brain computer interface cursor control experiment mediated by implanted subdural electrocorticographic arrays. The paradigm consisted of several stages: baseline recording, hand and tongue motor tasks as the basis for feature selection, two closed-loop one-dimensional feedback experiments with each of these features, and a two-dimensional feedback experiment using both of the features simultaneously. The two selected features were simple channel and frequency band combinations associated with change during hand and tongue movement. Inter-feature correlation and cross-correlation between features during different epochs of each task were quantified for each stage of the experiment. Our anecdotal, three subject, result suggests that while high correlation between horizontal and vertical control signal can initially preclude successful two-dimensional cursor control, a feedback-based learning strategy can be successfully employed by the subject to overcome this limitation and progressively decorrelate these control signals. %B Conf Proc IEEE Eng Med Biol Soc %P 5318-21 %8 2008 %G eng %R 10.1109/IEMBS.2008.4650415 %0 Journal Article %J Neurosurgery %D 2007 %T Electrocorticographic Frequency Alteration Mapping: A Clinical Technique for Mapping the Motor Cortex. %A Leuthardt, E C %A Miller, John W %A Nicholas R Anderson %A Gerwin Schalk %A Dowling, Joshua %A Miller, John W %A Moran, D %A Ojemann, J G %K Adult %K Biological Clocks %K Brain Mapping %K Electric Stimulation %K Electrodes, Implanted %K Electroencephalography %K Female %K Hand %K Humans %K Male %K Middle Aged %K Motor Cortex %K Oscillometry %K Signal Processing, Computer-Assisted %K Tongue %X

OBJECTIVE: 

Electrocortical stimulation (ECS) has been well established for delineating the eloquent cortex. However, ECS is still coarse and inefficient in delineating regions of the functional cortex and can be hampered by after-discharges. Given these constraints, an adjunct approach to defining the motor cortex is the use of electrocorticographic signal changes associated with active regions of the cortex. The broad range of frequency oscillations are categorized into two main groups with respect to the sensorimotor cortex: low and high frequency bands. The low frequency bands tend to show a power reduction with cortical activation, whereas the high frequency bands show power increases. These power changes associated with the activated cortex could potentially provide a powerful tool in delineating areas of the motor cortex. We explore electrocorticographic signal alterations as they occur with activated regions of the motor cortex, as well as its potential in clinical brain mapping applications.

METHODS: 

We evaluated seven patients who underwent invasive monitoring for seizure localization. Each patient had extraoperative ECS mapping to identify the motor cortex. All patients also performed overt hand and tongue motor tasks to identify associated frequency power changes in regard to location and degree of concordance with ECS results that localized either hand or tongue motor function.

RESULTS: 

The low frequency bands had a high sensitivity (88.9-100%) and a lower specificity (79.0-82.6%) for identifying electrodes with either hand or tongue ECS motor responses. The high frequency bands had a lower sensitivity (72.7-88.9%) and a higher specificity (92.4-94.9%) in correlation with the same respective ECS positive electrodes.

CONCLUSION: 

The concordance between stimulation and spectral power changes demonstrate the possible utility of electrocorticographic frequency alteration mapping as an adjunct method to improve the efficiency and resolution of identifying the motor cortex.

%B Neurosurgery %V 60 %P 260-70; discussion 270-1 %8 04/2007 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17415162 %N 4 Suppl 2 %R 10.1227/01.NEU.0000255413.70807.6E %0 Journal Article %J J Neurosci %D 2007 %T Spectral Changes in Cortical Surface Potentials During Motor Movement. %A Miller, John W %A Leuthardt, E C %A Gerwin Schalk %A Rao, Rajesh P N %A Nicholas R Anderson %A Moran, D %A Miller, John W %A Ojemann, J G %K Adult %K Brain Mapping %K Female %K Humans %K Male %K Middle Aged %K Motor Cortex %K Movement %X

In the first large study of its kind, we quantified changes in electrocorticographic signals associated with motor movement across 22 subjects with subdural electrode arrays placed for identification of seizure foci. Patients underwent a 5-7 d monitoring period with array placement, before seizure focus resection, and during this time they participated in the study. An interval-based motor-repetition task produced consistent and quantifiable spectral shifts that were mapped on a Talairach-standardized template cortex. Maps were created independently for a high-frequency band (HFB) (76-100 Hz) and a low-frequency band (LFB) (8-32 Hz) for several different movement modalities in each subject. The power in relevant electrodes consistently decreased in the LFB with movement, whereas the power in the HFB consistently increased. In addition, the HFB changes were more focal than the LFB changes. Sites of power changes corresponded to stereotactic locations in sensorimotor cortex and to the results of individual clinical electrical cortical mapping. Sensorimotor representation was found to be somatotopic, localized in stereotactic space to rolandic cortex, and typically followed the classic homunculus with limited extrarolandic representation.

%B J Neurosci %V 27 %P 2424-32 %8 02/2007 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17329441 %N 9 %R 10.1523/JNEUROSCI.3886-06.2007