Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods

Abstract:

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.

Authors:

• Alejandro Omar Blenkmann

• Sabine Liliana Leske

• Anaïs Llorens

• Jack J. Lin

• Edward F. Chang

• Peter Brunner

• Gerwin Schalk

• Jugoslav Ivanovic

• Pål Gunnar Larsson

• Robert Thomas Knight

• Tor Endestad

• Anne-Kristin Solbakk

Date: 2024

DOI: https://doi.org/10.1016/j.jneumeth.2024.110056

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Grasp-specific high-frequency broadband mirror neuron activity during reach-and-grasp movements in humans

Abstract:

Broadly congruent mirror neurons, responding to any grasp movement, and strictly congruent mirror neurons, responding only to specific grasp movements, have been reported in single-cell studies with primates. Delineating grasp properties in humans is essential to understand the human mirror neuron system with implications for behavior and social cognition. We analyzed electrocorticography data from a natural reach-and-grasp movement observation and delayed imitation task with 3 different natural grasp types of everyday objects. We focused on the classification of grasp types from high-frequency broadband mirror activation patterns found in classic mirror system areas, including sensorimotor, supplementary motor, inferior frontal, and parietal cortices. Classification of grasp types was successful during movement observation and execution intervals but not during movement retention. Our grasp type classification from combined and single mirror electrodes provides evidence for grasp-congruent activity in the human mirror neuron system potentially arising from strictly congruent mirror neurons.

Authros:

• Alexander M. Dreyer

• Leo Michalke

• Anat Perry

• Edward F. Chang

• Jack J. Lin

• Robert T. Knight

• Jochem W. Rieger

Date: 2022

DOI: https://doi.org/10.1093/cercor/bhac504

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Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke

ABSTRACT

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation.

AUTHORS

• Dhakshin S. Ramanathan

• Ling Guo

• Tanuj Gulati

• April K. Hishinuma

• Seok-Joon Won

• Robert T. Knight

• Edward F. Chang

• Raymond A. Swanson

• Karunesh Ganguly

Date: 2018

DOI: 10.1038/s41591-018-0058-y

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Persistent neuronal activity in human prefrontal cortex links perception and action

ABSTRACT

How do humans flexibly respond to changing environmental demands on a subsecond temporal scale? Extensive research has highlighted the key role of the prefrontal cortex in flexible decision-making and adaptive behaviour, yet the core mechanisms that translate sensory information into behaviour remain undefined. Using direct human cortical recordings, we investigated the temporal and spatial evolution of neuronal activity (indexed by the broadband gamma signal) in 16 participants while they performed a broad range of self-paced cognitive tasks. Here we describe a robust domain- and modality-independent pattern of persistent stimulus-to-response neural activation that encodes stimulus features and predicts motor output on a trial-by-trial basis with near-perfect accuracy. Observed across a distributed network of brain areas, this persistent neural activation is centred in the prefrontal cortex and is required for successful response implementation, providing a functional substrate for domain-general transformation of perception into action, critical for flexible behaviour.

AUTHORS

• Matar Haller

• John Case

• Nathan E. Crone

• Edward F. Chang

• David King-Stephens

• Kenneth D. Laxer

• Peter B. Weber

• Josef Parvizi

• Robert T. Knight

• Avgusta Y. Shestyuk

Date: 2017

DOI: 10.1038/s41562-017-0267-2

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Frontal and motor cortex contributions to response inhibition: evidence from electrocorticography

ABSTRACT

Changes in the environment require rapid modification or inhibition of ongoing behavior. We used the stop-signal paradigm and intracranial recordings to investigate response preparation, inhibition, and monitoring of task-relevant information. Electrocorticographic data were recorded in eight patients with electrodes covering frontal, temporal, and parietal cortex, and time-frequency analysis was used to examine power differences in the beta (13–30 Hz) and high-gamma bands (60 –180 Hz). Over motor cortex, beta power decreased, and high-gamma power increased during motor preparation for both go trials (Go) and unsuccessful stops (US). For successful stops (SS), beta increased, and high-gamma was reduced, indexing the cancellation of the prepared response. In the middle frontal gyrus (MFG), stop signals elicited a transient high-gamma increase. The MFG response occurred before the estimated stop-signal reaction time but did not distinguish between SS and US trials, likely signaling attention to the salient stop stimulus. A postresponse high-gamma increase in MFG was stronger for US compared with SS and absent in Go, supporting a role in behavior monitoring. These results provide evidence for differential contributions of frontal subregions to response inhibition, including motor preparation and inhibitory control in motor cortex and cognitive control and action evaluation in lateral prefrontal cortex.

AUTHORS

• Y.M. Fonken

• Jochem W. Rieger

• Elinor Tzvi

• Nathan E. Crone

• Edward F. Chang

• Josef Parvizi

• Robert T. Knight

• Ulrike M. Krämer

Date: 2016

DOI: 10.1038/srep25803

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Oscillatory dynamics coordinating human frontal networks in support of goal maintenance

Abstract:

Humans have a capacity for hierarchical cognitive control—the ability to simultaneously control immediate actions while holding more abstract goals in mind. Neuropsychological and neuroimaging evidence suggests that hierarchical cognitive control emerges from a frontal architecture whereby prefrontal cortex coordinates neural activity in the motor cortices when abstract rules are needed to govern motor outcomes. We utilized the improved temporal resolution of human intracranial electrocorticography to investigate the mechanisms by which frontal cortical oscillatory networks communicate in support of hierarchical cognitive control. Responding according to progressively more abstract rules resulted in greater frontal network theta phase encoding (4–8 Hz) and increased prefrontal local neuronal population activity (high gamma amplitude, 80–150 Hz), which predicts trial-by-trial response times. Theta phase encoding coupled with high gamma amplitude during inter-regional information encoding, suggesting that inter-regional phase encoding is a mechanism for the dynamic instantiation of complex cognitive functions by frontal cortical subnetworks.

Authors:

• Bradley Voytek

• Andrew S. Kayser

• David Badre

• David Fegen

• Edward F. Chang

• Nathan E. Crone

• Josef Parvizi

• Robert T. Knight

• Mark D'Esposito

Date: 2015

DOI: 10.1038/nn.4071

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Support vector machine and hidden Markov model based decoding of finger movements using electrocorticography

Authors:

• Tobias Wissel

• Tim Pfeiffer

• Robert Frysch

• Robert T. Knight

• Edward F. Chang

• Hermann Hinrichs

• Jochem W. Rieger

• Georg Rose

Date: 2013

DOI: 10.1088/1741-2560/10/5/056020

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Abstract:

Objective. Support vector machines (SVM) have developed into a gold standard for accurate classification in brain–computer interfaces (BCI). The choice of the most appropriate classifier for a particular application depends on several characteristics in addition to decoding accuracy. Here we investigate the implementation of hidden Markov models (HMM) for online BCIs and discuss strategies to improve their performance. Approach. We compare the SVM, serving as a reference, and HMMs for classifying discrete finger movements obtained from electrocorticograms of four subjects performing a finger tapping experiment. The classifier decisions are based on a subset of low-frequency time domain and high gamma oscillation features. Main results. We show that decoding optimization between the two approaches is due to the way features are extracted and selected and less dependent on the classifier. An additional gain in HMM performance of up to 6% was obtained by introducing model constraints. Comparable accuracies of up to 90% were achieved with both SVM and HMM with the high gamma cortical response providing the most important decoding information for both techniques. Significance. We discuss technical HMM characteristics and adaptations in the context of the presented data as well as for general BCI applications. Our findings suggest that HMMs and their characteristics are promising for efficient online BCIs.

Oscillatory dynamics track motor learning in human cortex

Authors:

• S. Durschmid

• Fanny Quandt

• Ulrike M. Krämer

• Hermann Hinrichs

• R. T. Schultz

• H. Pannek

• Edward F. Chang

• Robert T. Knight

Date: 2014

DOI: 10.1371/journal.pone.0089576

PubMed: 24586885

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Abstract:

Improving performance in motor skill acquisition is proposed to be supported by tuning of neural networks. To address this issue we investigated changes of phase-amplitude cross-frequency coupling (paCFC) in neuronal networks during motor performance improvement. We recorded intracranially from subdural electrodes (electrocorticogram; ECoG) from 6 patients who learned 3 distinct motor tasks requiring coordination of finger movements with an external cue (serial response task, auditory motor coordination task, go/no-go). Performance improved in all subjects and all tasks during the first block and plateaued in subsequent blocks. Performance improvement was paralleled by increasing neural changes in the trial-to-trial paCFC between theta ([Formula: see text]; 4-8 Hz) phase and high gamma (HG; 80-180 Hz) amplitude. Electrodes showing this covariation pattern (Pearson's r ranging up to .45) were located contralateral to the limb performing the task and were observed predominantly in motor brain regions. We observed stable paCFC when task performance asymptoted. Our results indicate that motor performance improvement is accompanied by adjustments in the dynamics and topology of neuronal network interactions in the [Formula: see text] and HG range. The location of the involved electrodes suggests that oscillatory dynamics in motor cortices support performance improvement with practice.

Proceedings of the Third International Workshop on Advances in Electrocorticography

Authors:

• Anthony Ritaccio

• Michael Beauchamp

• Conrado Bosman

• Peter Brunner

• Edward F. Chang

• Nathan E. Crone

• Ayesegul Gunduz

• Disha Gupta

• Robert T. Knight

• Eric Leuthardt

• Brian Litt

• Daniel Moran

• Jeffrey G. Ojemann

• Josef Parvizi

• Nick F. Ramsey

• Jochem W. Rieger

• Jonathan Viventi

• Bradley Voytek

• Justin Williams

• Gerwin Schalk

Date: 2012

DOI: 10.1016/j.yebeh.2012.09.016

PubMed: 23160096

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Abstract:

The Third International Workshop on Advances in Electrocorticography (ECoG) was convened in Washington, DC, on November 10–11, 2011. As in prior meetings, a true multidisciplinary fusion of clinicians, scientists, and engineers from many disciplines gathered to summarize contemporary experiences in brain surface recordings. The proceedings of this meeting serve as evidence of a very robust and transformative field but will yet again require revision to incorporate the advances that the following year will surely bring.

Human cortical sensorimotor network underlying feedback control of vocal pitch

Authors:

• Edward F. Chang

• Caroline A. Niziolek

• Robert T. Knight

• Srikantan S. Nagarajan

• John F. Houde

Date: 2013

DOI: 10.1073/pnas.1216827110

PubMed: 23345447

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Abstract:

The control of vocalization is critically dependent on auditory feedback. Here, we determined the human peri-Sylvian speech network that mediates feedback control of pitch using direct cortical recordings. Subjects phonated while a real-time signal processor briefly perturbed their output pitch (speak condition). Subjects later heard the same recordings of their auditory feedback (listen condition). In posterior superior temporal gyrus, a proportion of sites had suppressed responses to normal feedback, whereas other spatially independent sites had enhanced responses to altered feedback. Behaviorally, speakers compensated for perturbations by changing their pitch. Single-trial analyses revealed that compensatory vocal changes were predicted by the magnitude of both auditory and subsequent ventral premotor responses to perturbations. Furthermore, sites whose responses to perturbation were enhanced in the speaking condition exhibited stronger correlations with behavior. This sensorimotor cortical network appears to underlie auditory feedback-based control of vocal pitch in humans.

Reconstructing Speech from Human Auditory Cortex

Authors:

• Brian Pasley

• Stephen V. David

• Nima Mesgarani

• Adeen Flinker

• Shihab A. Shamma

• Nathan E. Crone

• Robert T. Knight

• Edward F. Chang

Date: 2012

DOI: 10.1371/journal.pbio.1001251

PubMed: 22303281

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Abstract:

How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acoustic information in speech sounds can be reconstructed from population neural activity. We found that slow and intermediate temporal fluctuations, such as those corresponding to syllable rate, were accurately reconstructed using a linear model based on the auditory spectrogram. However, reconstruction of fast temporal fluctuations, such as syllable onsets and offsets, required a nonlinear sound representation based on temporal modulation energy. Reconstruction accuracy was highest within the range of spectro-temporal fluctuations that have been found to be critical for speech intelligibility. The decoded speech representations allowed readout and identification of individual words directly from brain activity during single trial sound presentations. These findings reveal neural encoding mechanisms of speech acoustic parameters in higher order human auditory cortex.

Cortical Spatio-temporal Dynamics Underlying Phonological Target Detection in Humans

Authors:

• Edward F. Chang

• Erik Edwards

• Srikantan S. Nagarajan

• Noa Fogelson

• Sarang S. Dalal

• Ryan T. Canolty

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2011

DOI: 10.1162/jocn.2010.21466

PubMed: 20465359

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Abstract:

Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential recordings during this task revealed a highly ordered temporal progression of high gamma (HG, 70-200 Hz) activity across the lateral hemisphere in less than 1 sec. The sequence demonstrated concurrent regional sensory processing of speech syllables in the posterior superior temporal gyrus (STG) and speech motor cortex, and then transitioned to sequential task-dependent processing from prefrontal cortex (PFC), to the final motor response in the hand sensorimotor cortex. STG activation was modestly enhanced for target over nontarget sounds, supporting a selective gain mechanism in early sensory processing, whereas PFC was entirely selective to targets, supporting its role in guiding response behavior. These results reveal that target detection is not a single cognitive event, but rather a process of progressive target selectivity that involves large-scale rapid parallel and serial processing in sensory, cognitive, and motor structures to support goal-directed human behavior.

Single-trial speech suppression of auditory cortex activity in humans.

Authors:

• Adeen Flinker

• Edward F. Chang

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Nathan E. Crone

• Robert T. Knight

Date: 2010

PubMed: 21148003

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Abstract:

The human auditory cortex is engaged in monitoring the speech of interlocutors as well as self-generated speech. During vocalization, auditory cortex activity is reported to be suppressed, an effect often attributed to the influence of an efference copy from motor cortex. Single-unit studies in non-human primates have demonstrated a rich dynamic range of single-trial auditory responses to self-speech consisting of suppressed, nonsuppressed and excited auditory neurons. However, human research using noninvasive methods has only reported suppression of averaged auditory cortex responses to self-generated speech. We addressed this discrepancy by recording electrocorticographic activity from neurosurgical subjects performing auditory repetition tasks. We observed that the degree of suppression varied across different regions of auditory cortex, revealing a variety of suppressed and nonsuppressed responses during vocalization. Importantly, single-trial high-gamma power (γ(High), 70-150 Hz) robustly tracked individual auditory events and exhibited stable responses across trials for suppressed and nonsuppressed regions.

Categorical speech representation in the human superior temporal gyrus

Authors:

• Edward F. Chang

• Jochem W. Rieger

• Keith Johnson

• Mitchel S. Berger

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2010

DOI: 10.1038/nn.264

PubMed: 20890293

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Abstract:

Speech perception requires the rapid and effortless extraction of meaningful phonetic information from a highly variable acoustic signal. A powerful example of this phenomenon is categorical speech perception, in which a continuum of acoustically varying sounds is transformed into perceptually distinct phoneme categories. We found that the neural representation of speech sounds is categorically organized in the human posterior superior temporal gyrus. Using intracranial high-density cortical surface arrays, we found that listening to synthesized speech stimuli varying in small and acoustically equal steps evoked distinct and invariant cortical population response patterns that were organized by their sensitivities to critical acoustic features. Phonetic category boundaries were similar between neurometric and psychometric functions. Although speech-sound responses were distributed, spatially discrete cortical loci were found to underlie specific phonetic discrimination. Our results provide direct evidence for acoustic-to–higher order phonetic level encoding of speech sounds in human language receptive cortex.

Categorical speech representation in human superior temporal gyrus

Authors:

• Edward F. Chang

• Jochem W. Rieger

• Keith Johnson

• Mitchel S. Berger

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2010

PubMed: 20890293

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Abstract:

Speech perception requires the rapid and effortless extraction of meaningful phonetic information from a highly variable acoustic signal. A powerful example of this phenomenon is categorical speech perception, in which a continuum of acoustically varying sounds is transformed into perceptually distinct phoneme categories. We found that the neural representation of speech sounds is categorically organized in the human posterior superior temporal gyrus. Using intracranial high-density cortical surface arrays, we found that listening to synthesized speech stimuli varying in small and acoustically equal steps evoked distinct and invariant cortical population response patterns that were organized by their sensitivities to critical acoustic features. Phonetic category boundaries were similar between neurometric and psychometric functions. Although speech-sound responses were distributed, spatially discrete cortical loci were found to underlie specific phonetic discrimination. Our results provide direct evidence for acoustic-to–higher order phonetic level encoding of speech sounds in human language receptive cortex.

Categorical speech representation in human superior temporal gyrus

Authors:

• Edward F. Chang

• Jochem W. Rieger

• Keith Johnson

• Mitchel S. Berger

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2010

PubMed: 20890293

View PDF

Abstract:

Speech perception requires the rapid and effortless extraction of meaningful phonetic information from a highly variable acoustic signal. A powerful example of this phenomenon is categorical speech perception, in which a continuum of acoustically varying sounds is transformed into perceptually distinct phoneme categories. We found that the neural representation of speech sounds is categorically organized in the human posterior superior temporal gyrus. Using intracranial high-density cortical surface arrays, we found that listening to synthesized speech stimuli varying in small and acoustically equal steps evoked distinct and invariant cortical population response patterns that were organized by their sensitivities to critical acoustic features. Phonetic category boundaries were similar between neurometric and psychometric functions. Although speech-sound responses were distributed, spatially discrete cortical loci were found to underlie specific phonetic discrimination. Our results provide direct evidence for acoustic-to–higher order phonetic level encoding of speech sounds in human language receptive cortex.

Sub-centimeter language organization in the human temporal lobe

Authors:

• Adeen Flinker

• Edward F. Chang

• Nicholas M. Barbaro

• Mitchel S. Berger

• Robert T. Knight

Date: 2010

DOI: 10.1016/j.bandl.2010.09.009

PubMed: 20961611

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Abstract:

The human temporal lobe is well known to be critical for language comprehension. Previous physiological research has focused mainly on non-invasive neuroimaging and electrophysiological techniques with each approach requiring averaging across many trials and subjects. The results of these studies have implicated extended anatomical regions in peri-sylvian cortex in speech perception. These non-invasive studies typically report a spatially homogenous functional pattern of activity across several centimeters of cortex. We examined the spatiotemporal dynamics of word processing using electrophysiological signals acquired from high-density electrode arrays (4mm spacing) placed directly on the human temporal lobe. Electrocorticographic (ECoG) activity revealed a rich mosaic of language activity, which was functionally distinct at four mm separation. Cortical sites responding specifically to word and not phoneme stimuli were surrounded by sites that responded to both words and phonemes. Other sub-regions of the temporal lobe responded robustly to self-produced speech and minimally to external stimuli while surrounding sites at 4mm distance exhibited an inverse pattern of activation. These data provide evidence for temporal lobe specificity to words as well as self-produced speech. Furthermore, the results provide evidence that cortical processing in the temporal lobe is not spatially homogenous over centimeters of cortex. Rather, language processing is supported by independent and spatially distinct functional sub-regions of cortex at a resolution of at least 4mm.

Cortical spatiotemporal dynamics underlying phonological target detection in humans

Authors:

• Edward F. Chang

• Erik Edwards

• Srikantan S. Nagarajan

• Noa Fogelson

• Sarang S. Dalal

• Ryan T. Canolty

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2010

DOI: 10.1162/jocn.2010.21466

PubMed: 20465359

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Abstract:

Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential recordings during this task revealed a highly ordered temporal progression of high gamma (HG, 70–200 Hz) activity across the lateral hemisphere in less than 1 sec. The sequence demonstrated concurrent regional sensory processing of speech syllables in the posterior superior temporal gyrus (STG) and speech motor cortex, and then transitioned to sequential task-dependent processing from prefrontal cortex (PFC), to the final motor response in the hand sensorimotor cortex. STG activation was modestly enhanced for target over nontarget sounds, supporting a selective gain mechanism in early sensory processing, whereas PFC was entirely selective to targets, supporting its role in guiding response behavior. These results reveal that target detection is not a single cognitive event, but rather a process of progressive target selectivity that involves large-scale rapid parallel and serial processing in sensory, cognitive, and motor structures to support goal-directed human behavior.

Cortical representation of ipsilateral arm movements in monkey and man

Authors:

• Karunesh Ganguly

• Lavi Secundo

• Gireeja Ranade

• Amy Orsborn

• Edward F. Chang

• Dragan F. Dimitrov

• Johnathan D. Wallis

• Nicholas M. Barbaro

• Robert T. Knight

• Jose M. Carmena

Date: 2009

DOI: 10.1523/JNEUROSCI.2471-09.2009

PubMed: 19828809

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Abstract:

A fundamental organizational principle of the primate motor system is cortical control of contralateral limb movements. Motor areas also appear to play a role in the control of ipsilateral limb movements. Several studies in monkeys have shown that individual neurons in primary motor cortex (M1) may represent, on average, the direction of movements of the ipsilateral arm. Given the increasing body of evidence demonstrating that neural ensembles can reliably represent information with a high temporal resolution, here we characterize the distributed neural representation of ipsilateral upper limb kinematics in both monkey and man. In two macaque monkeys trained to perform center-outreaching movements, we found thatthe ensemble spiking activity in M1 could continuously representipsilateral limb position. Interestingly, this representation was more correlated with joint angles than hand position. Using bilateral electromyography recordings, we excluded the possibility that postural or mirror movements could exclusively account for these findings. In addition, linear methods could decode limb position from cortical field potentials in both monkeys. We also found that M1 spiking activity could control a biomimetic brain–machine interface reflecting ipsilateral kinematics. Finally, we recorded cortical field potentials from three human subjects and also consistently found evidence of a neural representation for ipsilateral movement parameters. Together, our results demonstrate the presence of a high-fidelity neural representation for ipsilateral movement and illustrates that it can be successfully incorporated into a brain–machine interface.