03432nas a2200361 4500008004100000022001400041245014400055210006900199260001300268300001100281490000800292520223300300653001002533653002002543653001502563653002602578653002702604653001102631653003102642100003102673700002702704700002002731700001702751700002102768700001902789700001902808700002302827700002602850700002702876700001802903700002602921856012302947 2024 eng d a1872-678X00aAnatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods.0 aAnatomical registration of intracranial electrodes Robust modelb c2024 Apr a1100560 v4043 a

BACKGROUND: Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration errors when fusing post-implantation CT and pre-implantation MR images. Brain-shift compensation methods project electrode coordinates to cortex, but either fail to produce smooth solutions or do not account for brain deformations.

NEW METHODS: We first introduce GridFit, a model-based fitting approach that simultaneously localizes all electrodes' CT artifacts in grids, strips, or depth arrays. Second, we present CEPA, a brain-shift compensation algorithm combining orthogonal-based projections, spring-mesh models, and spatial regularization constraints.

RESULTS: We tested GridFit on ∼6000 simulated scenarios. The localization of CT artifacts showed robust performance under difficult scenarios, such as noise, overlaps, and high-density implants (<1 mm errors). Validation with data from 20 challenging patients showed 99% accurate localization of the electrodes (3160/3192). We tested CEPA brain-shift compensation with data from 15 patients. Projections accounted for simple mechanical deformation principles with < 0.4 mm errors. The inter-electrode distances smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance.

COMPARISON WITH EXISTING METHODS: GridFit succeeded in difficult scenarios that challenged available methods and outperformed visual localization by preserving the inter-electrode distance. CEPA registration errors were smaller than those obtained for well-established alternatives. Additionally, modeling resting-state high-frequency activity in five patients further supported CEPA.

CONCLUSION: GridFit and CEPA are versatile tools for registering intracranial electrode coordinates, providing highly accurate results even in the most challenging implantation scenarios. The methods are implemented in the iElectrodes open-source toolbox.

10aBrain10aCerebral Cortex10aElectrodes10aElectrodes, Implanted10aElectroencephalography10aHumans10aMagnetic Resonance Imaging1 aBlenkmann, Alejandro, Omar1 aLeske, Sabine, Liliana1 aLlorens, Anaïs1 aLin, Jack, J1 aChang, Edward, F1 aBrunner, Peter1 aSchalk, Gerwin1 aIvanovic, Jugoslav1 aLarsson, Pål, Gunnar1 aKnight, Robert, Thomas1 aEndestad, Tor1 aSolbakk, Anne-Kristin uhttps://www.neurotechcenter.org/publications/2024/anatomical-registration-intracranial-electrodes-robust-model-based-002553nas a2200325 4500008004100000022001400041245011400055210006900169260001200238300001000250490000800260520151900268653002401787653001001811653001801821653002001839653002501859653001101884653001301895100002401908700002001932700002401952700002301976700002201999700002102021700002502042700001902067700001902086856012202105 2023 eng d a1872-895200aPassive functional mapping of receptive language cortex during general anesthesia using electrocorticography.0 aPassive functional mapping of receptive language cortex during g c03/2023 a31-440 v1473 a

OBJECTIVE: To investigate the feasibility of passive functional mapping in the receptive language cortex during general anesthesia using electrocorticographic (ECoG) signals.

METHODS: We used subdurally placed ECoG grids to record cortical responses to speech stimuli during awake and anesthesia conditions. We identified the cortical areas with significant responses to the stimuli using the spectro-temporal consistency of the brain signal in the broadband gamma (BBG) frequency band (70-170 Hz).

RESULTS: We found that ECoG BBG responses during general anesthesia effectively identify cortical regions associated with receptive language function. Our analyses demonstrated that the ability to identify receptive language cortex varies across different states and depths of anesthesia. We confirmed these results by comparing them to receptive language areas identified during the awake condition. Quantification of these results demonstrated an average sensitivity and specificity of passive language mapping during general anesthesia to be 49±7.7% and 100%, respectively.

CONCLUSION: Our results demonstrate that mapping receptive language cortex in patients during general anesthesia is feasible.

SIGNIFICANCE: Our proposed protocol could greatly expand the population of patients that can benefit from passive language mapping techniques, and could eliminate the risks associated with electrocortical stimulation during an awake craniotomy.

10aAnesthesia, General10aBrain10aBrain Mapping10aCerebral Cortex10aElectrocorticography10aHumans10aLanguage1 aNourmohammadi, Amin1 aSwift, James, R1 ade Pesters, Adriana1 aGuay, Christian, S1 aAdamo, Matthew, A1 aDalfino, John, C1 aRitaccio, Anthony, L1 aSchalk, Gerwin1 aBrunner, Peter uhttps://www.neurotechcenter.org/publications/2023/passive-functional-mapping-receptive-language-cortex-during-general02272nas a2200337 4500008004100000022001400041245011100055210006900166260001200235300001100247490000800258520124200266653002501508653001001533653000901543653001701552653002001569653001801589653002601607653002501633653001101658653001101669653000901680653001601689100002301705700003201728700001901760700001901779700001901798856011701817 2021 eng d a1095-957200aModulation in cortical excitability disrupts information transfer in perceptual-level stimulus processing.0 aModulation in cortical excitability disrupts information transfe c11/2021 a1184980 v2433 a

Despite significant interest in the neural underpinnings of behavioral variability, little light has been shed on the cortical mechanism underlying the failure to respond to perceptual-level stimuli. We hypothesized that cortical activity resulting from perceptual-level stimuli is sensitive to the moment-to-moment fluctuations in cortical excitability, and thus may not suffice to produce a behavioral response. We tested this hypothesis using electrocorticographic recordings to follow the propagation of cortical activity in six human subjects that responded to perceptual-level auditory stimuli. Here we show that for presentations that did not result in a behavioral response, the likelihood of cortical activity decreased from auditory cortex to motor cortex, and was related to reduced local cortical excitability. Cortical excitability was quantified using instantaneous voltage during a short window prior to cortical activity onset. Therefore, when humans are presented with an auditory stimulus close to perceptual-level threshold, moment-by-moment fluctuations in cortical excitability determine whether cortical responses to sensory stimulation successfully connect auditory input to a resultant behavioral response.

10aAcoustic Stimulation10aAdult10aAged10aAlpha Rhythm10aAuditory Cortex10aBrain Mapping10aCortical Excitability10aElectrocorticography10aFemale10aHumans10aMale10aMiddle Aged1 aMoheimanian, Ladan1 aParaskevopoulou, Sivylla, E1 aAdamek, Markus1 aSchalk, Gerwin1 aBrunner, Peter uhttps://www.neurotechcenter.org/publications/2021/modulation-cortical-excitability-disrupts-information-transfer02753nas a2200373 4500008004100000022001400041245011800055210006900173260001200242300001100254490000800265520163200273653001001905653001501915653001701930653002001947653001501967653002501982653001102007653001702018653001102035653000902046653001602055653001402071653002802085653001802113653001602131100003202147700002102179700001902200700001902219700001902238856012202257 2021 eng d a1095-957200aWithin-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms.0 aWithinsubject reaction time variability Role of cortical network c08/2021 a1181270 v2373 a

Variations in reaction time are a ubiquitous characteristic of human behavior. Extensively documented, they have been successfully modeled using parameters of the subject or the task, but the neural basis of behavioral reaction time that varies within the same subject and the same task has been minimally studied. In this paper, we investigate behavioral reaction time variance using 28 datasets of direct cortical recordings in humans who engaged in four different types of simple sensory-motor reaction time tasks. Using a previously described technique that can identify the onset of population-level cortical activity and a novel functional connectivity algorithm described herein, we show that the cumulative latency difference of population-level neural activity across the task-related cortical network can explain up to 41% of the trial-by-trial variance in reaction time. Furthermore, we show that reaction time variance may primarily be due to the latencies in specific brain regions and demonstrate that behavioral latency variance is accumulated across the whole task-related cortical network. Our results suggest that population-level neural activity monotonically increases prior to movement execution, and that trial-by-trial changes in that increase are, in part, accounted for by inhibitory activity indexed by low-frequency oscillations. This pre-movement neural activity explains 19% of the measured variance in neural latencies in our data. Thus, our study provides a mechanistic explanation for a sizable fraction of behavioral reaction time when the subject's task is the same from trial to trial.

10aAdult10aAlgorithms10aAlpha Rhythm10aCerebral Cortex10aConnectome10aElectrocorticography10aFemale10aGamma Rhythm10aHumans10aMale10aMiddle Aged10aNerve Net10aPsychomotor Performance10aReaction Time10aYoung Adult1 aParaskevopoulou, Sivylla, E1 aCoon, William, G1 aBrunner, Peter1 aMiller, Kai, J1 aSchalk, Gerwin uhttps://www.neurotechcenter.org/publications/2021/within-subject-reaction-time-variability-role-cortical-networks-and02982nas a2200313 4500008004100000022001400041245013700055210006900192260001200261300001100273490000700284520198000291653001002271653001802281653002502299653002602324653002702350653001102377653003102388100001602419700001702435700001502452700001902467700001402486700001902500700001602519700001902535856011402554 2019 eng d a1741-255200aiEEGview: an open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes.0 aiEEGview an opensource multifunction GUIbased Matlab toolbox for c12/2019 a0160160 v173 a

OBJECTIVE: The precise localization of intracranial electrodes is a fundamental step relevant to the analysis of intracranial electroencephalography (iEEG) recordings in various fields. With the increasing development of iEEG studies in human neuroscience, higher requirements have been posed on the localization process, resulting in urgent demand for more integrated, easy-operation and versatile tools for electrode localization and visualization. With the aim of addressing this need, we develop an easy-to-use and multifunction toolbox called iEEGview, which can be used for the localization and visualization of human intracranial electrodes.

APPROACH: iEEGview is written in Matlab scripts and implemented with a GUI. From the GUI, by taking only pre-implant MRI and post-implant CT images as input, users can directly run the full localization pipeline including brain segmentation, image co-registration, electrode reconstruction, anatomical information identification, activation map generation and electrode projection from native brain space into common brain space for group analysis. Additionally, iEEGview implements methods for brain shift correction, visual location inspection on MRI slices and computation of certainty index in anatomical label assignment.

MAIN RESULTS: All the introduced functions of iEEGview work reliably and successfully, and are tested by images from 28 human subjects implanted with depth and/or subdural electrodes.

SIGNIFICANCE: iEEGview is the first public Matlab GUI-based software for intracranial electrode localization and visualization that holds integrated capabilities together within one pipeline. iEEGview promotes convenience and efficiency for the localization process, provides rich localization information for further analysis and offers solutions for addressing raised technical challenges. Therefore, it can serve as a useful tool in facilitating iEEG studies.

10aBrain10aBrain Mapping10aElectrocorticography10aElectrodes, Implanted10aElectroencephalography10aHumans10aMagnetic Resonance Imaging1 aLi, Guangye1 aJiang, Shize1 aChen, Chen1 aBrunner, Peter1 aWu, Zehan1 aSchalk, Gerwin1 aChen, Liang1 aZhang, Dingguo uhttps://www.neurotechcenter.org/publications/2019/ieegview-open-source-multifunction-gui-based-matlab-toolbox