@article {4462, title = {A motor association area in the depths of the central sulcus.}, journal = {Nat Neurosci}, volume = {26}, year = {2023}, month = {07/2023}, pages = {1165-1169}, abstract = {

Cells in the precentral gyrus directly send signals to the periphery to generate movement and are principally organized as a topological map of the body. We find that movement-induced electrophysiological responses from depth electrodes extend this map three-dimensionally throughout the gyrus. Unexpectedly, this organization is interrupted by a previously undescribed motor association area in the depths of the midlateral aspect of the central sulcus. This {\textquoteright}Rolandic motor association{\textquoteright} (RMA) area is active during movements of different body parts from both sides of the body and may be important for coordinating complex behaviors.

}, keywords = {Brain Mapping, Motor Cortex, Movement}, issn = {1546-1726}, doi = {10.1038/s41593-023-01346-z}, author = {Jensen, Michael A and Huang, Harvey and Valencia, Gabriela Ojeda and Klassen, Bryan T and van den Boom, Max A and Kaufmann, Timothy J and Schalk, Gerwin and Brunner, Peter and Worrell, Gregory A and Hermes, Dora and Miller, Kai J} } @article {4447, title = {Toward a fully implantable ecosystem for adaptive neuromodulation in humans: Preliminary experience with the CorTec BrainInterchange device in a canine model.}, journal = {Front Neurosci}, volume = {16}, year = {2022}, month = {12/2022}, pages = {932782}, abstract = {

This article describes initial work toward an ecosystem for adaptive neuromodulation in humans by documenting the experience of implanting CorTec{\textquoteright}s BrainInterchange (BIC) device in a beagle canine and using the BCI2000 environment to interact with the BIC device. It begins with laying out the substantial opportunity presented by a useful, easy-to-use, and widely available hardware/software ecosystem in the current landscape of the field of adaptive neuromodulation, and then describes experience with implantation, software integration, and post-surgical validation of recording of brain signals and implant parameters. Initial experience suggests that the hardware capabilities of the BIC device are fully supported by BCI2000, and that the BIC/BCI2000 device can record and process brain signals during free behavior. With further development and validation, the BIC/BCI2000 ecosystem could become an important tool for research into new adaptive neuromodulation protocols in humans.

}, issn = {1662-4548}, doi = {10.3389/fnins.2022.932782}, author = {Schalk, Gerwin and Worrell, Samuel and Mivalt, Filip and Belsten, Alexander and Kim, Inyong and Morris, Jonathan M and Hermes, Dora and Klassen, Bryan T and Staff, Nathan P and Messina, Steven and Kaufmann, Timothy and Rickert, J{\"o}rn and Brunner, Peter and Worrell, Gregory A and Miller, Kai J} } @article {3556, title = {Intraoperative mapping of expressive language cortex using passive real-time electrocorticography.}, journal = {Epilepsy \& behavior case reports}, volume = {5}, year = {2016}, month = {Mar}, pages = {46{\textendash}51}, abstract = {In this case report, we investigated the utility and practicality of passive intraoperative functional mapping of expressive language cortex using high-resolution electrocorticography (ECoG). The patient presented here experienced new-onset seizures caused by a medium-grade tumor in very close proximity to expressive language regions. In preparation of tumor resection, the patient underwent multiple functional language mapping procedures. We examined the relationship of results obtained with intraoperative high-resolution ECoG, extraoperative ECoG utilizing a conventional subdural grid, extraoperative electrical cortical stimulation (ECS) mapping, and functional magnetic resonance imaging (fMRI). Our results demonstrate that intraoperative mapping using high-resolution ECoG is feasible and, within minutes, produces results that are qualitatively concordant to those achieved by extraoperative mapping modalities. They also suggest that functional language mapping of expressive language areas with ECoG may prove useful in many intraoperative conditions given its time efficiency and safety. Finally, they demonstrate that integration of results from multiple functional mapping techniques, both intraoperative and extraoperative, may serve to improve the confidence in or precision of functional localization when pathology encroaches upon eloquent language cortex.}, doi = {10.1016/j.ebcr.2016.03.003}, url = {http://www.ncbi.nlm.nih.gov/pubmed/27408802}, author = {Taplin, AmiLyn M. and de Pesters, Adriana and Peter Brunner and Hermes, Dora and Dalfino, John C. and Adamo, Matthew A. and A L Ritaccio and Gerwin Schalk} } @article {3552, title = {Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change.}, journal = {PLoS computational biology}, volume = {12}, year = {2016}, month = {Jan}, pages = {e1004660}, abstract = {The link between object perception and neural activity in visual cortical areas is a problem of fundamental importance in neuroscience. Here we show that electrical potentials from the ventral temporal cortical surface in humans contain sufficient information for spontaneous and near-instantaneous identification of a subject{\textquoteright}s perceptual state. Electrocorticographic (ECoG) arrays were placed on the subtemporal cortical surface of seven epilepsy patients. Grayscale images of faces and houses were displayed rapidly in random sequence. We developed a template projection approach to decode the continuous ECoG data stream spontaneously, predicting the occurrence, timing and type of visual stimulus. In this setting, we evaluated the independent and joint use of two well-studied features of brain signals, broadband changes in the frequency power spectrum of the potential and deflections in the raw potential trace (event-related potential; ERP). Our ability to predict both the timing of stimulus onset and the type of image was best when we used a combination of both the broadband response and ERP, suggesting that they capture different and complementary aspects of the subject{\textquoteright}s perceptual state. Specifically, we were able to predict the timing and type of 96\% of all stimuli, with less than 5\% false positive rate and a {\textasciitilde}20ms error in timing.}, keywords = {Visual Perception}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1004660}, url = {http://www.ncbi.nlm.nih.gov/pubmed/26820899}, author = {Miller, Kai J. and Gerwin Schalk and Hermes, Dora and Ojemann, Jeffrey G. and Rao, Rajesh P. N.} } @inbook {3548, title = {Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings}, booktitle = {Brain-Computer Interface Research: A State-of-the-Art Summary}, year = {2015}, pages = {105-114}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {New York City, NY}, abstract = {Human visual processing is of such complexity that, despite decades of focused research, many basic questions remain unanswered. Although we know that the inferotemporal cortex is a key region in object recognition, we don{\textquoteright}t fully understand its physiologic role in brain function, nor do we have the full set of tools to explore this question. Here we show that electrical potentials from the surface of the human brain contain enough information to decode a subject{\textquoteright}s perceptual state accurately, and with fine temporal precision. Electrocorticographic (ECoG) arrays were placed over the inferotemporal cortical areas of seven subjects. Pictures of faces and houses were quickly presented while each subject performed a simple visual task. Results showed that two well-known types of brain signals{\textemdash}event-averaged broadband power and event-averaged raw potential{\textemdash}can independently or together be used to classify the presented image. When applied to continuously recorded brain activity, our decoding technique could accurately predict whether each stimulus was a face, house, or neither, with ~20 ms timing error. These results provide a roadmap for improved brain-computer interfacing tools to help neurosurgeons, research scientists, engineers, and, ultimately, patients.}, keywords = {broadband power, Electrocorticography, event-related potential, fusiform cortex, human vision}, isbn = {978-3-319-25188-2}, issn = {978-3-319-25190-5}, doi = {10.1007/978-3-319-25190-5_10}, url = {http://link.springer.com/chapter/10.1007/978-3-319-25190-5_10}, author = {Miller, Kai J and Gerwin Schalk and Hermes, Dora and Ojemann, Jeffrey G and Rao, Rajesh P N} } @article {3416, title = {Proceedings of the Fifth International Workshop on Advances in Electrocorticography.}, journal = {Epilepsy Behav}, volume = {41}, year = {2014}, month = {12/2014}, pages = {183-92}, abstract = {

The Fifth International Workshop on Advances in Electrocorticography convened in San Diego, CA, on November 7-8, 2013. Advancements in methodology, implementation, and commercialization across both research and in the interval year since the last workshop were the focus of the gathering. Electrocorticography (ECoG) is now firmly established as a preferred signal source for advanced research in functional, cognitive, and neuroprosthetic domains. Published output in ECoG fields has increased tenfold in the past decade. These proceedings attempt to summarize the state of the art.

}, keywords = {Brain Mapping, brain-computer interface, electrical stimulation mapping, Electrocorticography, functional mapping, Gamma-frequency electroencephalography, High-frequency oscillations, Neuroprosthetics, Seizure detection, Subdural grid}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2014.09.015}, url = {http://www.ncbi.nlm.nih.gov/pubmed/25461213}, author = {A L Ritaccio and Peter Brunner and Gunduz, Aysegul and Hermes, Dora and Hirsch, Lawrence J and Jacobs, Joshua and Kamada, Kyousuke and Kastner, Sabine and Robert T. Knight and Lesser, Ronald P and Miller, Kai and Sejnowski, Terrence and Worrell, Gregory and Gerwin Schalk} } @article {2194, title = {Brain-computer interfacing based on cognitive control.}, journal = {Ann Neurol}, volume = {67}, year = {2010}, month = {06/2010}, pages = {809-16}, abstract = {

OBJECTIVE:\ 

Brain-computer interfaces (BCIs) translate deliberate intentions and associated changes in brain activity into action, thereby offering patients with severe paralysis an alternative means of communication with and control over their environment. Such systems are not available yet, partly due to the high performance standard that is required. A major challenge in the development of implantable BCIs is to identify cortical regions and related functions that an individual can reliably and consciously manipulate. Research predominantly focuses on the sensorimotor cortex, which can be activated by imagining motor actions. However, because this region may not provide an optimal solution to all patients, other neuronal networks need to be examined. Therefore, we investigated whether the cognitive control network can be used for BCI purposes. We also determined the feasibility of using functional magnetic resonance imaging (fMRI) for noninvasive localization of the cognitive control network.

METHODS:\ 

Three patients with intractable epilepsy, who were temporarily implanted with subdural grid electrodes for diagnostic purposes, attempted to gain BCI control using the electrocorticographic (ECoG) signal of the left dorsolateral prefrontal cortex (DLPFC).

RESULTS:\ 

All subjects quickly gained accurate BCI control by modulation of gamma-power of the left DLPFC. Prelocalization of the relevant region was performed with fMRI and was confirmed using the ECoG signals obtained during mental calculation localizer tasks.

INTERPRETATION:\ 

The results indicate that the cognitive control network is a suitable source of signals for BCI applications. They also demonstrate the feasibility of translating understanding about cognitive networks derived from functional neuroimaging into clinical applications.

}, keywords = {Cognition, Computers, Electrodes, Electroencephalography, Epilepsy, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neuropsychological Tests, Oxygen, Prefrontal Cortex, Psychomotor Performance, Spectrum Analysis, Time Factors, User-Computer Interface}, issn = {1531-8249}, doi = {10.1002/ana.21985}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20517943}, author = {Vansteensel, Mariska J and Hermes, Dora and Aarnoutse, Erik J and Bleichner, Martin G and Gerwin Schalk and van Rijen, Peter C and Leijten, Frans S S and Ramsey, Nick F} } @proceedings {2241, title = {Detection of spontaneous class-specific visual stimuli with high temporal accuracy in human electrocorticography.}, volume = {2009}, year = {2009}, month = {2009}, pages = {6465-8}, abstract = {Most brain-computer interface classification experiments from electrical potential recordings have been focused on the identification of classes of stimuli or behavior where the timing of experimental parameters is known or pre-designated. Real world experience, however, is spontaneous, and to this end we describe an experiment predicting the occurrence, timing, and types of visual stimuli perceived by a human subject from electrocorticographic recordings. All 300 of 300 presented stimuli were correctly detected, with a temporal precision of order 20 ms. The type of stimulus (face/house) was correctly identified in 95\% of these cases. There were approximately 20 false alarm events, corresponding to a late 2nd neuronal response to a previously identified event.}, keywords = {Algorithms, Electrocardiography, Evoked Potentials, Visual, Humans, Male, Pattern Recognition, Automated, Pattern Recognition, Visual, Photic Stimulation, Reproducibility of Results, Sensitivity and Specificity, User-Computer Interface, Visual Cortex}, issn = {1557-170X}, doi = {10.1109/IEMBS.2009.5333546}, author = {Miller, John W and Hermes, Dora and Gerwin Schalk and Ramsey, Nick F and Jagadeesh, Bharathi and den Nijs, Marcel and Ojemann, J G and Rao, Rajesh P N} }