@article {4142, title = {Encoding of Multiple Reward-Related Computations in Transient and Sustained High-Frequency Activity in Human OFC}, journal = {Current Biology}, volume = {28}, year = {2018}, pages = {2889 - 2899.e3}, abstract = {Summary Human orbitofrontal cortex (OFC) has long been implicated in value-based decision making. In recent years, convergent evidence from human and model organisms has further elucidated its role in representing reward-related computations underlying decision making. However, a detailed description of these processes remains elusive due in part to (1) limitations in our ability to observe human OFC neural dynamics at the timescale of decision processes and (2) methodological and interspecies differences that make it challenging to connect human and animal findings or to~resolve discrepancies when they arise. Here, we sought to address these challenges by conducting multi-electrode electrocorticography (ECoG) recordings in neurosurgical patients during economic decision making to elucidate the electrophysiological signature, sub-second temporal profile, and anatomical distribution of reward-related computations within human OFC. We found that high-frequency activity (HFA) (70{\textendash}200~Hz) reflected multiple valuation components grouped in two classes of valuation signals that were dissociable in temporal profile and information content: (1) fast, transient responses reflecting signals associated with choice and outcome processing, including anticipated risk and outcome regret, and (2) sustained responses explicitly encoding what happened in the immediately preceding trial. Anatomically, these responses were widely distributed in partially overlapping networks, including regions in the central OFC (Brodmann areas 11 and 13), which have been consistently implicated in reward processing in animal single-unit studies. Together, these results integrate insights drawn from human and animal studies and provide evidence for a role of human OFC in representing multiple reward computations.}, keywords = {ECoC, Electrocorticography, ERP, event-related potential, field potential, FP, HFA, high-frequency activity, OFC, orbitofrontal cortex, reward-prediction error, RPE}, issn = {0960-9822}, doi = {https://doi.org/10.1016/j.cub.2018.07.045}, url = {http://www.sciencedirect.com/science/article/pii/S0960982218309758}, author = {Ignacio Saez and Jack Lin and Arjen Stolk and Edward Chang and Josef Parvizi and Gerwin Schalk and Robert T. Knight and Ming Hsu} } @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 {2202, title = {Rapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG).}, journal = {Front Neurosci}, volume = {5}, year = {2011}, month = {02/2011}, pages = {5}, abstract = {

A\ brain-computer interface\ (BCI) can provide a non-muscular communication channel to severely disabled people. One particular realization of a\ BCI\ is the P300 matrix speller that was originally described by Farwell and Donchin (1988). This speller uses event-related potentials (ERPs) that include the P300 ERP. All previous online studies of the P300 matrix speller used scalp-recorded electroencephalography (EEG) and were limited in their communication performance to only a few characters per minute. In our study, we investigated the feasibility of using electrocorticographic (ECoG) signals for online operation of the matrix speller, and determined associated spelling rates. We used the matrix speller that is implemented in the BCI2000 system. This speller used ECoG signals that were recorded from frontal, parietal, and occipital areas in one subject. This subject spelled a total of 444 characters in online experiments. The results showed that the subject sustained a rate of 17\ characters/min (i.e., 69\ bits/min), and achieved a peak rate of 22\ characters/min (i.e., 113\ bits/min). Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller\ BCI\ system. Our results also point to potential reasons for the apparent advantages in spelling performance of ECoG compared to EEG. Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.

}, keywords = {brain-computer interface, Electrocorticography, event-related potential, P300, speller}, issn = {1662-453X}, doi = {10.3389/fnins.2011.00005}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21369351}, author = {Peter Brunner and A L Ritaccio and Emrich, Joseph F and H Bischof and Gerwin Schalk} } @article {3104, title = {A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns.}, journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology}, volume = {121}, year = {2010}, month = {07/2010}, pages = {1109{\textendash}1120}, abstract = {OBJECTIVE: An electroencephalographic brain-computer interface (BCI) can provide a non-muscular means of communication for people with amyotrophic lateral sclerosis (ALS) or other neuromuscular disorders. We present a novel P300-based BCI stimulus presentation - the checkerboard paradigm (CBP). CBP performance is compared to that of the standard row/column paradigm (RCP) introduced by Farwell and Donchin (1988). METHODS: Using an 8x9 matrix of alphanumeric characters and keyboard commands, 18 participants used the CBP and RCP in counter-balanced fashion. With approximately 9-12 min of calibration data, we used a stepwise linear discriminant analysis for online classification of subsequent data. RESULTS: Mean online accuracy was significantly higher for the CBP, 92\%, than for the RCP, 77\%. Correcting for extra selections due to errors, mean bit rate was also significantly higher for the CBP, 23 bits/min, than for the RCP, 17 bits/min. Moreover, the two paradigms produced significantly different waveforms. Initial tests with three advanced ALS participants produced similar results. Furthermore, these individuals preferred the CBP to the RCP. CONCLUSIONS: These results suggest that the CBP is markedly superior to the RCP in performance and user acceptability. SIGNIFICANCE: The CBP has the potential to provide a substantially more effective BCI than the RCP. This is especially important for people with severe neuromuscular disabilities.}, keywords = {brain-computer interface, brain-machine interface, EEG, event-related potential, P300, Rehabilitation}, issn = {1872-8952}, doi = {10.1016/j.clinph.2010.01.030}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20347387}, author = {Townsend, G. and LaPallo, B. K. and Chadwick B. Boulay and Krusienski, D. J. and Frye, G. E. and Hauser, C. K. and Schwartz, N. E. and Theresa M Vaughan and Jonathan Wolpaw and Sellers, E. W.} } @article {3108, title = {Toward a high-throughput auditory P300-based brain-computer interface.}, journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology}, volume = {120}, year = {2009}, month = {07/2009}, pages = {1252{\textendash}1261}, abstract = {OBJECTIVE: Brain-computer interface (BCI) technology can provide severely disabled people with non-muscular communication. For those most severely disabled, limitations in eye mobility or visual acuity may necessitate auditory BCI systems. The present study investigates the efficacy of the use of six environmental sounds to operate a 6x6 P300 Speller. METHODS: A two-group design was used to ascertain whether participants benefited from visual cues early in training. Group A (N=5) received only auditory stimuli during all 11 sessions, whereas Group AV (N=5) received simultaneous auditory and visual stimuli in initial sessions after which the visual stimuli were systematically removed. Stepwise linear discriminant analysis determined the matrix item that elicited the largest P300 response and thereby identified the desired choice. RESULTS: Online results and offline analyses showed that the two groups achieved equivalent accuracy. In the last session, eight of 10 participants achieved 50\% or more, and four of these achieved 75\% or more, online accuracy (2.8\% accuracy expected by chance). Mean bit rates averaged about 2 bits/min, and maximum bit rates reached 5.6 bits/min. CONCLUSIONS: This study indicates that an auditory P300 BCI is feasible, that reasonable classification accuracy and rate of communication are achievable, and that the paradigm should be further evaluated with a group of severely disabled participants who have limited visual mobility. SIGNIFICANCE: With further development, this auditory P300 BCI could be of substantial value to severely disabled people who cannot use a visual BCI.}, keywords = {brain-computer interface, brain-machine interface, EEG, event-related potential, P300, Rehabilitation}, issn = {1872-8952}, doi = {10.1016/j.clinph.2009.04.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19574091}, author = {Klobassa, D. S. and Theresa M Vaughan and Peter Brunner and Schwartz, N. E. and Jonathan Wolpaw and Neuper, C. and Sellers, E. W.} }