Understanding the human conflict processing network: A review of the literature on direct neural recordings during performance of a modified stroop task.

The Stroop Task is a well-known neuropsychological task developed to investigate conflict processing in the human brain. Our group has utilized direct intracranial neural recordings in various brain regions during performance of a modified color-word Stroop Task to gain a mechanistic understanding of non-emotional human conflict processing. The purpose of this review article is to: 1) synthesize our own studies into a model of human conflict processing, 2) review the current literature on the Stroop Task and other conflict tasks to put our research in context, and 3) describe how these studies define a network in conflict processing. The figures presented are reprinted from our prior publications and key publications referenced in the manuscript. We summarize all studies to date that employ invasive intracranial recordings in humans during performance of conflict-inducing tasks. For our own studies, we analyzed local field potentials (LFPs) from patients with implanted stereotactic electroencephalography (SEEG) electrodes, and we observed intracortical oscillation patterns as well as intercortical temporal relationships in the hippocampus, amygdala, and orbitofrontal cortex (OFC) during the cue-processing phase of a modified Stroop Task. Our findings suggest that non-emotional human conflict processing involves modulation across multiple frequency bands within and between brain structures.

Primary somatosensory cortex organization for engineering artificial somatosensation.

Somatosensory deficits from stroke, spinal cord injury, or other neurologic damage can lead to a significant degree of functional impairment. The primary (SI) and secondary (SII) somatosensory cortices encode information in a medial to lateral organization. SI is generally organized topographically, with more discrete cortical representations of specific body regions. SII regions corresponding to anatomical areas are less discrete and may represent a more functional rather than topographic organization. Human somatosensory research continues to map cortical areas of sensory processing with efforts primarily focused on hand and upper extremity information in SI. However, research into SII and other body regions is lacking. In this review, we synthesize the current state of knowledge regarding the cortical organization of human somatosensation and discuss potential applications for brain computer interface. In addition to accurate individualized mapping of cortical somatosensation, further research is required to uncover the neurophysiological mechanisms of how somatosensory information is encoded in the cortex.

Stereotactic Frame-Based Electrode Insertion: The Accuracy of Increasingly Oblique Insertion Angles.

AIM: To investigate the relationship between planned drill approach angle and angular deviation of the stereotactically placed intracranial electrode tips. MATERIAL AND METHODS: Stereotactic electrode implantation was performed in 13 patients with drug resistant epilepsy. A total of 136 electrodes were included in our analysis. Stereotactic targets were planned on pre-operative magnetic resonance imaging (MRI) scans and implantation was carried out using a Cosman-Roberts-Wells stereotactic frame with the Ad-Tech drill guide and electrodes. Post implant electrode angles in the axial, coronal, and sagittal planes were determined from post-operative computerized tomography (CT) scans and compared with planned angles using Bland-Altman plots and linear regression. RESULTS: Qualitative assessment of correlation plots between planned and actual angles demonstrated a linear relationship for axial, coronal, and sagittal planes, with no overt angular deflection for any magnitude of the planned angle. CONCLUSION: The accuracy of CRW frame-based electrode placement using the Ad-Tech drill guide and electrodes is not significantly affected by the magnitude of the planning angle. Based on our results, oblique electrode insertion is a safe and accurate procedure.

Suppression of cortical electrostimulation artifacts using pre-whitening and null projection.

Objective.Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers. While front-end hardware techniques can alleviate this problem, residual artifacts generally persist and must be suppressed by back-end methods.Approach.We have developed a technique based on pre-whitening and null projection (PWNP) and tested its ability to suppress stimulation artifacts in electroencephalogram (EEG), electrocorticogram (ECoG) and microelectrode array (MEA) signals from five human subjects.Main results.In EEG signals contaminated by narrow-band stimulation artifacts, the PWNP method achieved average artifact suppression between 32 and 34 dB, as measured by an increase in signal-to-interference ratio. In ECoG and MEA signals contaminated by broadband stimulation artifacts, our method suppressed artifacts by 78%-80% and 85%, respectively, as measured by a reduction in interference index. When compared to independent component analysis, which is considered the state-of-the-art technique for artifact suppression, our method achieved superior results, while being significantly easier to implement.Significance.PWNP can potentially act as an efficient method of artifact suppression to enable simultaneous stimulation and recording in bi-directional BCIs to biomimetically restore motor function.

Neural representations of economic decision variables in human posterior parietal cortex.

Decision making has been intensively studied in the posterior parietal cortex in non-human primates on a single neuron level. In humans decision making has mainly been studied with psychophysical tools or with fMRI. Here, we investigated how single neurons from human posterior parietal cortex represent numeric values informing future decisions during a complex two-player game. The tetraplegic study participant was implanted with a Utah electrode array in the anterior intraparietal area (AIP). We played a simplified variant of Black Jack with the participant while neuronal data was recorded. During the game two players are presented with numbers which are added up. Each time a number is presented the player has to decide to proceed or to stop. Once the first player stops or the score reaches a limit the turn passes on to the second player who tries to beat the score of the first player. Whoever is closer to the limit (without overshooting) wins the game. We found that many AIP neurons selectively responded to the face value of the presented number. Other neurons tracked the cumulative score or were selectively active for the upcoming decision of the study participant. Interestingly, some cells also kept track of the opponent's score. Our findings show that parietal regions engaged in hand action control also represent numbers and their complex transformations. This is also the first demonstration of complex economic decisions being possible to track in single neuron activity in human AIP. Our findings show how tight are the links between parietal neural circuits underlying hand control, numerical cognition and complex decision-making.

A review of neurophysiological effects and efficiency of waveform parameters in deep brain stimulation.

Neurostimulation has diverse clinical applications and potential as a treatment for medically refractory movement disorders, epilepsy, and other neurological disorders. However, the parameters used to program electrodes-polarity, pulse width, amplitude, and frequency-and how they are adjusted have remained largely untouched since the 1970 s. This review summarizes the state-of-the-art in Deep Brain Stimulation (DBS) and highlights the need for further research to uncover the physiological mechanisms of neurostimulation. We focus on studies that reveal the potential for clinicians to use waveform parameters to selectively stimulate neural tissue for therapeutic benefit, while avoiding activating tissue associated with adverse effects. DBS uses cathodic monophasic rectangular pulses with passive recharging in clinical practice to treat neurological conditions such as Parkinson's Disease. However, research has shown that stimulation efficiency can be improved, and side effects reduced, through modulating parameters and adding novel waveform properties. These developments can prolong implantable pulse generator lifespan, reducing costs and surgery-associated risks. Waveform parameters can stimulate neurons based on axon orientation and intrinsic structural properties, providing clinicians with more precise targeting of neural pathways. These findings could expand the spectrum of diseases treatable with neuromodulation and improve patient outcomes.

S1 represents multisensory contexts and somatotopic locations within and outside the bounds of the cortical homunculus.

Recent literature suggests that tactile events are represented in the primary somatosensory cortex (S1) beyond its long-established topography; in addition, the extent to which S1 is modulated by vision remains unclear. To better characterize S1, human electrophysiological data were recorded during touches to the forearm or finger. Conditions included visually observed physical touches, physical touches without vision, and visual touches without physical contact. Two major findings emerge from this dataset. First, vision strongly modulates S1 area 1, but only if there is a physical element to the touch, suggesting that passive touch observation is insufficient to elicit neural responses. Second, despite recording in a putative arm area of S1, neural activity represents both arm and finger stimuli during physical touches. Arm touches are encoded more strongly and specifically, supporting the idea that S1 encodes tactile events primarily through its topographic organization but also more generally, encompassing other areas of the body.

Baseline hippocampal beta band power is lower in the presence of movement uncertainty.

Objective.This study aimed to characterize hippocampal neural signatures of uncertainty by measuring beta band power in the period prior to movement cue.Approach. Participants with epilepsy were implanted with hippocampal depth electrodes for stereo electroencephalographic (SEEG) monitoring. Hippocampal beta (13-30 Hz) power changes have been observed during motor tasks such as the direct reach (DR) and Go/No-Go (GNG) tasks. The primary difference between the tasks is the presence of uncertainty about whether movement should be executed. Previous research on cortical responses to uncertainty has found that baseline beta power changes with uncertainty. SEEG data were sampled throughout phases of the DR and GNG tasks. Beta-band power during the fixation phase was compared between the DR and GNG task using a Wilcoxon rank sum test. This unpaired test was also used to analyze response times from cue to task completion between tasks.Main results.Eight patients who performed both reaching tasks were analyzed in this study. Movement response times in the GNG task were on average 210 milliseconds slower than in the DR task. All patients exhibited a significantly increased response latency in the GNG task compared to the DR task (Wilcoxon rank-sum p-value < 0.001). Six out of eight patients demonstrated statistically significant differences in beta power in single hippocampal contacts between the fixation phases of the GNG and DR tasks. At the group level, baseline beta power was significantly lower in the GNG task than in the DR task (Wilcoxon rank-sum p-value < 0.001).Significance. This novel study found that, in the presence of task uncertainty, baseline beta power in the hippocampus is lower than in its absence. This finding implicates movement uncertainty as an important factor in baseline hippocampal beta power during movement preparation.

Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human.

The cortical grasp network encodes planning and execution of grasps and processes spoken and written aspects of language. High-level cortical areas within this network are attractive implant sites for brain-machine interfaces (BMIs). While a tetraplegic patient performed grasp motor imagery and vocalized speech, neural activity was recorded from the supramarginal gyrus (SMG), ventral premotor cortex (PMv), and somatosensory cortex (S1). In SMG and PMv, five imagined grasps were well represented by firing rates of neuronal populations during visual cue presentation. During motor imagery, these grasps were significantly decodable from all brain areas. During speech production, SMG encoded both spoken grasp types and the names of five colors. Whereas PMv neurons significantly modulated their activity during grasping, SMG's neural population broadly encoded features of both motor imagery and speech. Together, these results indicate that brain signals from high-level areas of the human cortex could be used for grasping and speech BMI applications.

Neuromodulation in Beta-Band Power Between Movement Execution and Inhibition in the Human Hippocampus.

INTRODUCTION: The hippocampus is thought to be involved in movement, but its precise role in movement execution and inhibition has not been well studied. Previous work with direct neural recordings has found beta-band (13-30 Hz) modulation in both movement execution and inhibition throughout the motor system, but the role of beta-band modulation in the hippocampus during movement inhibition is not well understood. Here, we perform a Go/No-Go reaching task in ten patients with medically refractory epilepsy to study human hippocampal beta-power changes during movement. MATERIALS AND METHODS: Ten epilepsy patients (5 female; ages 21-46) were implanted with intracranial depth electrodes for seizure monitoring and localization. Local field potentials were sampled at 2000 Hz during a Go/No-Go movement task. Comparison of beta-band power between Go and No-Go conditions was conducted using Wilcoxon signed-rank hypothesis testing for each patient. Sub-analyses were conducted to assess differences in the anterior vs posterior contacts, ipsilateral vs contralateral contacts, and male vs female beta-power values. RESULTS: Eight out of ten patients showed significant beta-power decreases during the Go movement response (p < 0.05) compared to baseline. Eight out of ten patients also showed significant beta-power increases in the No-Go condition, occurring in the absence of movement. No significant differences were noted between ipsilateral vs contralateral contacts nor in anterior vs posterior hippocampal contacts. Female participants had a higher task success rate than males and had significantly greater beta-power increases in the No-Go condition (p < 0.001). CONCLUSION: These findings indicate that increases in hippocampal beta power are associated with movement inhibition. To the best of our knowledge, this study is the first to report this phenomenon in the human hippocampus. The beta band may represent a state-change signal involved in motor processing. Future focus on the beta band in understanding human motor and impulse control will be vital.

Theta low-gamma phase amplitude coupling in the human orbitofrontal cortex increases during a conflict-processing task.

Objective. The human orbitofrontal cortex (OFC) is involved in automatic response inhibition and conflict processing, but the mechanism of frequency-specific power changes that control these functions is unknown. Theta and gamma activity have been independently observed in the OFC during conflict processing, while theta-gamma interactions in other brain areas have been noted primarily in studies of memory. Within the OFC, it is possible that theta-gamma phase amplitude coupling (PAC) drives conflict processing. This study aims to characterize the coupled relationship between theta and gamma frequency bands in the OFC during conflict processing using a modified Stroop task.Approach. Eight epilepsy patients implanted with OFC stereotactic electroencephalography electrodes participated in a color-word modified Stroop task. PAC between theta phase and gamma amplitude was assessed to determine the timing and magnitude of neural oscillatory changes. Group analysis was conducted using a non-parametric cluster-permutationt-test on coherence values.Main results.Theta-low gamma (LG) PAC significantly increased in five out of eight patients during successful trials of the incongruent condition compared with the congruent condition. Significant increases in theta-LG PAC were most prominent during cue processing 200-800 ms after cue presentation. On group analysis, trial-averaged mean theta-LG PAC was statistically significantly greater in the incongruent condition compared to the congruent condition (p< 0.001, Cohen'sd= 0.51).Significance.For the first time, we report that OFC theta phase and LG amplitude coupling increases during conflict resolution. Given the delayed onset after cue presentation, OFC theta-LG PAC may contribute to conflict processing after conflict detection and before motor response. This explanation follows the hypothesis that global theta waves modulate local gamma signals. Understanding this relationship within the OFC will help further elucidate the neural mechanisms of human conflict resolution.

Exploring Cognition with Brain-Machine Interfaces.

Traditional brain-machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials. These signals are consistent with small regions of cortex having a diverse role in cognitive aspects of movement control and body monitoring, including sensorimotor integration, planning, trajectory representation, somatosensation, action semantics, learning, and decision making. These variables are encoded within the same population of cells using structured representations that bind related sensory and motor variables, an architecture termed partially mixed selectivity. Diverse cognitive signals provide complementary information to traditional motor commands to enable more natural and intuitive control of external devices.

Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research.

Introduction: Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Methods: A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator. Subsequently, the stimulator was tested in an epilepsy patient with subcortical electrocorticographic (ECoG) implants covering the sensorimotor cortex to assess its ability to elicit equivalent responses as the FDA-approved counterpart. Additional safety features (impedance monitoring, artifact mitigation, and passive and active charge balancing mechanisms) were also implemeneted and tested in phantom brain tissue. Finally, concurrent operation with interleaved stimulation and BCI decoding was tested in a phantom brain as a proof-of-concept operation of BD-BCI system. Results: The benchtop prototype BD-BCI stimulator's basic output features (current amplitude, pulse frequency, pulse width, train duration) were validated by demonstrating the output-equivalency to an FDA-approved commercial cortical electrical stimulator (R 2 > 0.99). Charge-neutral stimulation was demonstrated with pulse-width modulation-based correction algorithm preventing steady state voltage deviation. Artifact mitigation achieved a 64.5% peak voltage reduction. Highly accurate impedance monitoring was achieved with R 2 > 0.99 between measured and actual impedance, which in-turn enabled accurate charge density monitoring. An online BCI decoding accuracy of 93.2% between instructional cues and decoded states was achieved while delivering interleaved stimulation. The brain stimulation mapping via ECoG grids in an epilepsy patient showed that the two stimulators elicit equivalent responses. Significance: This study demonstrates clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system. This low-cost BD-BCI system is safe and readily applicable as a testbed for BD-BCI research. In particular, it provides an all-inclusive hardware platform that approximates the limitations in a near-future implantable BD-BCI. This successful benchtop/human validation of the programmable electrical stimulator in a BD-BCI system is a critical milestone toward fully-implantable BD-BCI systems.

Amygdaloid theta-band power increases during conflict processing in humans.

The amygdala is a medial temporal lobe structure known to be involved in processing emotional conflict. However, its role in processing non-emotional conflict is not well understood. Previous studies have utilized the Stroop Task to examine brain modulation of humans under the color-word conflict scenario, which is non-emotional conflict processing, and found hippocampal theta-band (4-7 Hz) modulation. This study aims to survey amygdaloid theta power changes during non-emotional conflict processing using intracranial depth electrodes in nine epileptic patients (3 female; age 20-62). All patients were asked to perform a modified Stroop task. During task performance, local field potential (LFP) data was recorded from macro contacts sampled at 2 K Hz and used for analysis. Mean theta power change from baseline was compared between the incongruent and congruent task condition groups using a paired sample t-test. Seven patients were available for analysis after artifact exclusion. In five out of seven patients, statistically significant increases in theta-band power from baseline were noted during the incongruent task condition (paired sample t-test p < 0.001), including one patient exhibiting theta power increases in both task conditions. Average response time was 1.07 s (failure trials) and 1.04 s (success trials). No speed-accuracy tradeoff was noted in this analysis. These findings indicate that human amygdaloid theta-band modulation may play a role in processing non-emotional conflict. It builds directly upon work suggesting that the amygdala processes emotional conflict and provides a neurophysiological mechanism for non-emotional conflict processing as well.

Neuropathological effects of chronically implanted, intracortical microelectrodes in a tetraplegic patient.

Objective.Intracortical microelectrode arrays (MEA) can be used as part of a brain-machine interface system to provide sensory feedback control of an artificial limb to assist persons with tetraplegia. Variability in functionality of electrodes has been reported but few studies in humans have examined the impact of chronic brain tissue responses revealed postmortem on electrode performancein vivo. Approach.In a tetraplegic man, recording MEAs were implanted into the anterior intraparietal area and Brodmann's area 5 (BA5) of the posterior parietal cortex and a recording and stimulation array was implanted in BA1 of the primary somatosensory cortex (S1). The participant expired from unrelated causes seven months after MEA implantation. The underlying tissue of two of the three devices was processed for histology and electrophysiological recordings were assessed.Main results.Recordings of neuronal activity were obtained from all three MEAs despite meningeal encapsulation. However, the S1 array had a greater encapsulation, yielded lower signal quality than the other arrays and failed to elicit somatosensory percepts with electrical stimulation. Histological examination of tissues underlying S1 and BA5 implant sites revealed localized leptomeningeal proliferation and fibrosis, lymphocytic infiltrates, astrogliosis, and foreign body reaction around the electrodes. The BA5 recording site showed focal cerebral microhemorrhages and leptomeningeal vascular ectasia. The S1 site showed focal tissue damage including vascular recanalization, neuronal loss, and extensive subcortical white matter necrosis. The tissue response at the S1 site included hemorrhagic-induced injury suggesting a likely mechanism for reduced function of the S1 implant.Significance.Our findings are similar to those from animal studies with chronic intracortical implants and suggest that vascular disruption and microhemorrhage during device implantation are important contributors to overall array and individual electrode performance and should be a topic for future device development to mitigate tissue responses. Neurosurgical considerations are also discussed.

Hippocampal and Orbitofrontal Theta Band Coherence Diminishes During Conflict Resolution.

OBJECTIVE: Coherence between the hippocampus and other brain structures has been shown with the theta frequency (3-8 Hz). Cortical decreases in theta coherence are believed to reflect response accuracy efficiency. However, the role of theta coherence during conflict resolution is poorly understood in noncortical areas. In this study, coherence between the hippocampus and orbitofrontal cortex (OFC) was measured during a conflict resolution task. Although both brain areas have been previously implicated in the Stroop task, their interactions are not well understood. METHODS: Nine patients were implanted with stereotactic electroencephalography contacts in the hippocampus and OFC. Local field potential data were sampled throughout discrete phases of a Stroop task. Coherence was calculated for hippocampal and OFC contact pairs, and coherence spectrograms were constructed for congruent and incongruent conditions. Coherence changes during cue processing were identified using a nonparametric cluster-permutation t test. Group analysis was conducted to compare overall theta coherence changes among conditions. RESULTS: In 6 of 9 patients, decreased theta coherence was observed only during the incongruent condition (P < 0.05). Congruent theta coherence did not change from baseline. Group analysis showed lower theta coherence for the incongruent condition compared with the congruent condition (P < 0.05). CONCLUSIONS: Theta coherence between the hippocampus and OFC decreased during conflict. This finding supports existing theories that theta coherence desynchronization contributes to improved response accuracy and processing efficiency during conflict resolution. The underlying theta coherence observed between the hippocampus and OFC during conflict may be distinct from its previously observed role in memory.

The Neurophysiological Representation of Imagined Somatosensory Percepts in Human Cortex.

Intracortical microstimulation (ICMS) in human primary somatosensory cortex (S1) has been used to successfully evoke naturalistic sensations. However, the neurophysiological mechanisms underlying the evoked sensations remain unknown. To understand how specific stimulation parameters elicit certain sensations we must first understand the representation of those sensations in the brain. In this study we record from intracortical microelectrode arrays implanted in S1, premotor cortex, and posterior parietal cortex of a male human participant performing a somatosensory imagery task. The sensations imagined were those previously elicited by ICMS of S1, in the same array of the same participant. In both spike and local field potential recordings, features of the neural signal can be used to classify different imagined sensations. These features are shown to be stable over time. The sensorimotor cortices only encode the imagined sensation during the imagery task, while posterior parietal cortex encodes the sensations starting with cue presentation. These findings demonstrate that different aspects of the sensory experience can be individually decoded from intracortically recorded human neural signals across the cortical sensory network. Activity underlying these unique sensory representations may inform the stimulation parameters for precisely eliciting specific sensations via ICMS in future work.SIGNIFICANCE STATEMENT Electrical stimulation of human cortex is increasingly more common for providing feedback in neural devices. Understanding the relationship between naturally evoked and artificially evoked neurophysiology for the same sensations will be important in advancing such devices. Here, we investigate the neural activity in human primary somatosensory, premotor, and parietal cortices during somatosensory imagery. The sensations imagined were those previously elicited during intracortical microstimulation (ICMS) of the same somatosensory electrode array. We elucidate the neural features during somatosensory imagery that significantly encode different aspects of individual sensations and demonstrate feature stability over almost a year. The correspondence between neurophysiology elicited with or without stimulation for the same sensations will inform methods to deliver more precise feedback through stimulation in the future.

Mapping of primary somatosensory cortex of the hand area using a high-density electrocorticography grid for closed-loop brain computer interface.

Objective.The ideal modality for generating sensation in sensorimotor brain computer interfaces (BCI) has not been determined. Here we report the feasibility of using a high-density 'mini'-electrocorticography (mECoG) grid in a somatosensory BCI system.Approach.Thirteen subjects with intractable epilepsy underwent standard clinical implantation of subdural electrodes for the purpose of seizure localization. An additional high-density mECoG grid was placed (Adtech, 8 by 8, 1.2 mm exposed, 3 mm center-to-center spacing) over the hand area of primary somatosensory cortex. Following implantation, cortical mapping was performed with stimulation parameters of frequency: 50 Hz, pulse-width: 250µs, pulse duration: 4 s, polarity: alternating, and current that ranged from 0.5 mA to 12 mA at the discretion of the epileptologist. Location of the evoked sensory percepts was recorded along with a description of the sensation. The hand was partitioned into 48 distinct boxes. A box was included if sensation was felt anywhere within the box.Main results.The percentage of the hand covered was 63.9% (± 34.4%) (mean ± s.d.). Mean redundancy, measured as electrode pairs stimulating the same box, was 1.9 (± 2.2) electrodes per box; and mean resolution, measured as boxes included per electrode pair stimulation, was 11.4 (± 13.7) boxes with 8.1 (± 10.7) boxes in the digits and 3.4 (± 6.0) boxes in the palm. Functional utility of the system was assessed by quantifying usable percepts. Under the strictest classification, 'dermatomally exclusive' percepts, the mean was 2.8 usable percepts per grid. Allowing 'perceptually unique' percepts at the same anatomical location, the mean was 5.5 usable percepts per grid.Significance.Compared to the small area of coverage and redundancy of a microelectrode system, or the poor resolution of a standard ECoG grid, a mECoG is likely the best modality for a somatosensory BCI system with good coverage of the hand and minimal redundancy.

SpikeDeep-classifier: a deep-learning based fully automatic offline spike sorting algorithm.

Objective.Advancements in electrode design have resulted in micro-electrode arrays with hundreds of channels for single cell recordings. In the resulting electrophysiological recordings, each implanted electrode can record spike activity (SA) of one or more neurons along with background activity (BA). The aim of this study is to isolate SA of each neural source. This process is called spike sorting or spike classification. Advanced spike sorting algorithms are time consuming because of the human intervention at various stages of the pipeline. Current approaches lack generalization because the values of hyperparameters are not fixed, even for multiple recording sessions of the same subject. In this study, a fully automatic spike sorting algorithm called 'SpikeDeep-Classifier' is proposed. The values of hyperparameters remain fixed for all the evaluation data.Approach.The proposed approach is based on our previous study (SpikeDeeptector) and a novel background activity rejector (BAR), which are both supervised learning algorithms and an unsupervised learning algorithm (K-means). SpikeDeeptector and BAR are used to extract meaningful channels and remove BA from the extracted meaningful channels, respectively. The process of clustering becomes straight-forward once the BA is completely removed from the data. Then, K-means with a predefined maximum number of clusters is applied on the remaining data originating from neural sources only. Lastly, a similarity-based criterion and a threshold are used to keep distinct clusters and merge similar looking clusters. The proposed approach is called cluster accept or merge (CAOM) and it has only two hyperparameters (maximum number of clusters and similarity threshold) which are kept fixed for all the evaluation data after tuning.Main results.We compared the results of our algorithm with ground-truth labels. The algorithm is evaluated on data of human patients and publicly available labeled non-human primates (NHPs) datasets. The average accuracy of BAR on datasets of human patients is 92.3% which is further reduced to 88.03% after (K-means + CAOM). In addition, the average accuracy of BAR on a publicly available labeled dataset of NHPs is 95.40% which reduces to 86.95% after (K-mean + CAOM). Lastly, we compared the performance of the SpikeDeep-Classifier with two human experts, where SpikeDeep-Classifier has produced comparable results.Significance.The SpikeDeep-Classifier is evaluated on the datasets of multiple recording sessions of different species, different brain areas and different electrode types without further retraining. The results demonstrate that 'SpikeDeep-Classifier' possesses the ability to generalize well on a versatile dataset and henceforth provides a generalized and fully automated solution to offline spike sorting.Clinical trial registration numberThe clinical trial registration number for patients implanted with the Utah array isNCT 01849822.For the epilepsy patients, approval from the local ethics committee at the Ruhr-University Bochum, Germany, was obtained prior to implantation. The Clinical trial registration number for the epilepsy patients implanted with microwires is16-5670.

The human primary somatosensory cortex encodes imagined movement in the absence of sensory information.

Classical systems neuroscience positions primary sensory areas as early feed-forward processing stations for refining incoming sensory information. This view may oversimplify their role given extensive bi-directional connectivity with multimodal cortical and subcortical regions. Here we show that single units in human primary somatosensory cortex encode imagined reaches in a cognitive motor task, but not other sensory-motor variables such as movement plans or imagined arm position. A population reference-frame analysis demonstrates coding relative to the cued starting hand location suggesting that imagined reaching movements are encoded relative to imagined limb position. These results imply a potential role for primary somatosensory cortex in cognitive imagery, engagement during motor production in the absence of sensation or expected sensation, and suggest that somatosensory cortex can provide control signals for future neural prosthetic systems.