@article {4459, title = {A somato-cognitive action network alternates with effector regions in motor cortex.}, journal = {Nature}, volume = {617}, year = {2023}, month = {05/2023}, pages = {351-359}, abstract = {

Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down~the precentral gyrus from foot to face representations, despite evidence for concentric functional zones and maps of complex actions. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action and physiological control, arousal, errors and pain. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions and connectivity to internal organs such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.

}, keywords = {Animals, Brain Mapping, Child, Cognition, Datasets as Topic, Foot, Hand, Humans, Infant, Infant, Newborn, Macaca, Magnetic Resonance Imaging, Motor Cortex, Mouth}, issn = {1476-4687}, doi = {10.1038/s41586-023-05964-2}, author = {Gordon, Evan M and Chauvin, Roselyne J and Van, Andrew N and Rajesh, Aishwarya and Nielsen, Ashley and Newbold, Dillan J and Lynch, Charles J and Seider, Nicole A and Krimmel, Samuel R and Scheidter, Kristen M and Monk, Julia and Miller, Ryland L and Metoki, Athanasia and Montez, David F and Zheng, Annie and Elbau, Immanuel and Madison, Thomas and Nishino, Tomoyuki and Myers, Michael J and Kaplan, Sydney and Badke D{\textquoteright}Andrea, Carolina and Demeter, Damion V and Feigelis, Matthew and Ramirez, Julian S B and Xu, Ting and Barch, Deanna M and Smyser, Christopher D and Rogers, Cynthia E and Zimmermann, Jan and Botteron, Kelly N and Pruett, John R and Willie, Jon T and Brunner, Peter and Shimony, Joshua S and Kay, Benjamin P and Marek, Scott and Norris, Scott A and Gratton, Caterina and Sylvester, Chad M and Power, Jonathan D and Liston, Conor and Greene, Deanna J and Roland, Jarod L and Petersen, Steven E and Raichle, Marcus E and Laumann, Timothy O and Fair, Damien A and Dosenbach, Nico U F} } @article {2100, title = {Mapping broadband electrocorticographic recordings to two-dimensional hand trajectories in humans Motor control features.}, journal = {Neural Netw}, volume = {22}, year = {2009}, month = {11/2009}, pages = {1257-70}, abstract = {

Brain-machine interfaces (BMIs) aim to translate the motor intent of locked-in patients into neuroprosthetic control commands. Electrocorticographical (ECoG) signals provide promising neural inputs to BMIs as shown in recent studies. In this paper, we utilize a broadband spectrum above the fast gamma ranges and systematically study the role of spectral resolution, in which the broadband is partitioned, on the reconstruction of the patients{\textquoteright} hand trajectories. Traditionally, the power of ECoG rhythms (\<200-300 Hz) has been computed in short duration bins and instantaneously and linearly mapped to cursor trajectories. Neither time embedding, nor nonlinear mappings have been previously implemented in ECoG neuroprosthesis. Herein, mapping of neural modulations to goal-oriented motor behavior is achieved via linear adaptive filters with embedded memory depths and as a novelty through echo state networks (ESNs), which provide nonlinear mappings without compromising training complexity or increasing the number of model parameters, with up to 85\% correlation. Reconstructed hand trajectories are analyzed through spatial, spectral and temporal sensitivities. The superiority of nonlinear mappings in the cases of low spectral resolution and abundance of interictal activity is discussed.

}, keywords = {Algorithms, Brain, Brain Mapping, Electrodes, Implanted, Electrodiagnosis, Epilepsy, Feasibility Studies, Hand, Humans, Linear Models, Motor Activity, Neural Networks (Computer), Nonlinear Dynamics, Signal Processing, Computer-Assisted}, issn = {1879-2782}, doi = {10.1016/j.neunet.2009.06.036}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19647981}, author = {Gunduz, Aysegul and Sanchez, Justin C and Carney, Paul R and Principe, Jose} } @article {2098, title = {Extraction and localization of mesoscopic motor control signals for human ECoG neuroprosthetics.}, journal = {J Neurosci Methods}, volume = {167}, year = {2008}, month = {01/2008}, pages = {63-81}, abstract = {

Electrocorticogram (ECoG) recordings for\ neuroprosthetics\ provide a\ mesoscopic\ level of abstraction of brain function between microwire single neuron recordings and the electroencephalogram (EEG). Single-trial\ ECoG\ neural interfaces require appropriate feature\ extraction\ and signal processing methods to identify and model in real-time signatures of\ motor\ events in spontaneous brain activity. Here, we develop the clinical experimental paradigm and analysis tools to record broadband (1Hz to 6kHz)\ ECoG\ from patients participating in a reaching and pointing task. Motivated by the significant role of amplitude modulated rate coding in extracellular spike based brain-machine interfaces (BMIs), we develop methods to quantify spatio-temporal intermittent increased\ ECoG\ voltages to determine if they provide viable\ control\ inputs for\ ECoG\ neural interfaces. This study seeks to explore preprocessing modalities that emphasize amplitude modulation across frequencies and channels in the\ ECoG\ above the level of noisy background fluctuations in order to derive the commands for complex, continuous\ control\ tasks. Preliminary experiments show that it is possible to derive online predictive models and spatially localize the generation of commands in the cortex for\ motor\ tasks using amplitude modulated\ ECoG.

}, keywords = {Adolescent, Biofeedback, Psychology, Brain Mapping, Cerebral Cortex, Electroencephalography, Epilepsies, Partial, Female, Hand, Humans, Magnetic Resonance Imaging, Physical Therapy Modalities, Psychomotor Performance, Signal Processing, Computer-Assisted, Spectrum Analysis, User-Computer Interface}, issn = {0165-0270}, doi = {10.1016/j.jneumeth.2007.04.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17582507}, author = {Sanchez, Justin C and Gunduz, Aysegul and Carney, Paul R and Principe, Jose} } @article {2188, title = {Unique cortical physiology associated with ipsilateral hand movements and neuroprosthetic implications.}, journal = {Stroke}, volume = {39}, year = {2008}, month = {12/2008}, pages = {3351-9}, abstract = {

BACKGROUND AND PURPOSE:\ 

Brain computer interfaces\ (BCIs) offer little direct benefit to patients with hemispheric stroke because current platforms rely on signals derived from the contralateral motor cortex (the same region injured by the stroke). For BCIs to assist hemiparetic patients, the implant must use unaffected cortex ipsilateral to the affected limb. This requires the identification of distinct electrophysiological features from the motor cortex associated with ipsilateral hand movements.

METHODS:\ 

In this study we studied 6 patients undergoing temporary placement of intracranial electrode arrays. Electrocorticographic (ECoG) signals were recorded while the subjects engaged in specific ipsilateral or contralateral hand motor tasks. Spectral changes were identified with regards to frequency, location, and timing.

RESULTS:\ 

Ipsilateral hand movements were associated with electrophysiological changes that occur in lower frequency spectra, at distinct anatomic locations, and earlier than changes associated with contralateral hand movements. In a subset of 3 patients, features specific to ipsilateral and contralateral hand movements were used to control a cursor on a screen in real time. In ipsilateral derived control this was optimal with lower frequency spectra.

CONCLUSIONS:\ 

There are distinctive cortical electrophysiological features associated with ipsilateral movements which can be used for device control. These findings have implications for patients with hemispheric stroke because they offer a potential methodology for which a single hemisphere can be used to enhance the function of a stroke induced hemiparesis.

}, keywords = {Adolescent, Adult, Artificial Limbs, Bionics, Brain Mapping, Child, Dominance, Cerebral, Electroencephalography, Female, Hand, Humans, Male, Middle Aged, Motor Cortex, Movement, Paresis, Prosthesis Design, Psychomotor Performance, Stroke, User-Computer Interface, Volition}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.108.518175}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18927456}, author = {Wisneski, Kimberly and Nicholas R Anderson and Gerwin Schalk and Smyth, Matt and Moran, D and Leuthardt, E C} } @article {2179, title = {Electrocorticographic Frequency Alteration Mapping: A Clinical Technique for Mapping the Motor Cortex.}, journal = {Neurosurgery}, volume = {60}, year = {2007}, month = {04/2007}, pages = {260-70; discussion 270-1}, abstract = {

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.

}, keywords = {Adult, Biological Clocks, Brain Mapping, Electric Stimulation, Electrodes, Implanted, Electroencephalography, Female, Hand, Humans, Male, Middle Aged, Motor Cortex, Oscillometry, Signal Processing, Computer-Assisted, Tongue}, issn = {1524-4040}, doi = {10.1227/01.NEU.0000255413.70807.6E}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17415162}, author = {Leuthardt, E C and Miller, John W and Nicholas R Anderson and Gerwin Schalk and Dowling, Joshua and Miller, John W and Moran, D and Ojemann, J G} } @article {2181, title = {An MEG-based brain-computer interface (BCI).}, journal = {Neuroimage}, volume = {36}, year = {2007}, month = {07/2007}, pages = {581-93}, abstract = {

Brain-computer interfaces (BCIs) allow for communicating intentions by mere brain activity, not involving muscles. Thus, BCIs may offer patients who have lost all voluntary muscle control the only possible way to communicate. Many recent studies have demonstrated that BCIs based on\ electroencephalography(EEG) can allow healthy and severely paralyzed individuals to communicate. While this approach is safe and inexpensive, communication is slow. Magnetoencephalography (MEG) provides signals with higher spatiotemporal resolution than\ EEG\ and could thus be used to explore whether these improved signal properties translate into increased BCI communication speed. In this study, we investigated the utility of an MEG-based BCI that uses voluntary amplitude modulation of sensorimotor mu and beta rhythms. To increase the signal-to-noise ratio, we present a simple spatial filtering method that takes the geometric properties of signal propagation in MEG into account, and we present methods that can process artifacts specifically encountered in an MEG-based BCI. Exemplarily, six participants were successfully trained to communicate binary decisions by imagery of limb movements using a feedback paradigm. Participants achieved significant mu rhythm self control within 32 min of feedback training. For a subgroup of three participants, we localized the origin of the amplitude modulated signal to the motor cortex. Our results suggest that an MEG-based BCI is feasible and efficient in terms of user training.

}, keywords = {Adult, Algorithms, Artifacts, Brain, Electroencephalography, Electromagnetic Fields, Electromyography, Feedback, Female, Foot, Hand, Head Movements, Humans, Magnetic Resonance Imaging, Magnetoencephalography, Male, Movement, Principal Component Analysis, Signal Processing, Computer-Assisted, User-Computer Interface}, issn = {1053-8119}, doi = {10.1016/j.neuroimage.2007.03.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17475511}, author = {Mellinger, J{\"u}rgen and Gerwin Schalk and Christoph Braun and Preissl, Hubert and Rosenstiel, W. and Niels Birbaumer and K{\"u}bler, A.} }