Spatiotemporal Dynamics of Successive Activations across the Human Brain during Simple Arithmetic Processing

Previous neuroimaging studies have offered unique insights about the spatial organization of activations and deactivations across the brain; however, these were not powered to explore the exact timing of events at the subsecond scale combined with a precise anatomical source of information at the level of individual brains. As a result, we know little about the order of engagement across different brain regions during a given cognitive task. Using experimental arithmetic tasks as a prototype for human-unique symbolic processing, we recorded directly across 10,076 brain sites in 85 human subjects (52% female) using the intracranial electroencephalography. Our data revealed a remarkably distributed change of activity in almost half of the sampled sites. In each activated brain region, we found juxtaposed neuronal populations preferentially responsive to either the target or control conditions, arranged in an anatomically orderly manner. Notably, an orderly successive activation of a set of brain regions-anatomically consistent across subjects-was observed in individual brains. The temporal order of activations across these sites was replicable across subjects and trials. Moreover, the degree of functional connectivity between the sites decreased as a function of temporal distance between regions, suggesting that the information is partially leaked or transformed along the processing chain. Our study complements prior imaging studies by providing hitherto unknown information about the timing of events in the brain during arithmetic processing. Such findings can be a basis for developing mechanistic computational models of human-specific cognitive symbolic systems.

Data Processing Techniques Impact Quantification of Cortico-Cortical Evoked Potentials

BACKGROUND

Cortico-cortical evoked potentials (CCEPs) are a common tool for probing effective connectivity in intracranial human electrophysiology. As with all human electrophysiology data, CCEP data are highly susceptible to noise. To address noise, filters and re-referencing are often applied to CCEP data, but different processing strategies are used from study to study.

NEW METHOD

We systematically compare how common average re-referencing and filtering CCEP data impacts quantification.

RESULTS

We show that common average re-referencing and filters, particularly filters that cut out more frequencies, can significantly impact the quantification of CCEP magnitude and morphology. We identify that high cutoff high pass filters (> 0.5Hz), low cutoff low pass filters (< 200Hz), and common average re-referencing impact quantification across subjects. However, we also demonstrate that the presence of noise may impact CCEP quantification, and preprocessing is necessary to mitigate this. We show that filtering is more effective than re-referencing or averaging across trials for reducing most common types of noise.

COMPARISON WITH EXISTING METHODS

These results suggest that existing CCEP processing methods must be applied with care to maximize noise reduction and minimize changes to the data. We do not test every available processing strategy; rather we demonstrate that processing can influence the results of CCEP studies. We emphasize the importance of reporting all processing methods, particularly re-referencing methods.

CONCLUSIONS

We propose a general framework for choosing an appropriate processing pipeline for CCEP data, taking into consideration the noise levels of a specific dataset. We suggest that minimal gentle filtering is preferable.

More widespread and rigid neuronal representation of reward expectation underlies impulsive choices

Impulsive choices prioritize smaller, more immediate rewards over larger, delayed, or potentially uncertain rewards. Impulsive choices are a critical aspect of substance use disorders and maladaptive decision-making across the lifespan. Here, we sought to understand the neuronal underpinnings of expected reward and risk estimation on a trial-by-trial basis during impulsive choices. To do so, we acquired electrical recordings from the human brain while participants carried out a risky decision-making task designed to measure choice impulsivity. Behaviorally, we found a reward-accuracy tradeoff, whereby more impulsive choosers were more accurate at the task, opting for a more immediate reward while compromising overall task performance. We then examined how neuronal populations across frontal, temporal, and limbic brain regions parametrically encoded reinforcement learning model variables, namely reward and risk expectation and surprise, across trials. We found more widespread representations of reward value expectation and prediction error in more impulsive choosers, whereas less impulsive choosers preferentially represented risk expectation. A regional analysis of reward and risk encoding highlighted the anterior cingulate cortex for value expectation, the anterior insula for risk expectation and surprise, and distinct regional encoding between impulsivity groups. Beyond describing trial-by-trial population neuronal representations of reward and risk variables, these results suggest impaired inhibitory control and model-free learning underpinnings of impulsive choice. These findings shed light on neural processes underlying reinforced learning and decision-making in uncertain environments and how these processes may function in psychiatric disorders.

Light and the Brain: A Clinical Case Depicting the Effects of Light on Brainwaves and Possible Presence of Plasma-like Brain Energy

Light is an electromagnetic radiation that has visible and invisible wavelength spectrums. Visible light can only be detected by the eyes through the optic pathways. With the presence of the scalp, cranium, and meninges, the brain is seen as being protected from direct exposure to light. For that reason, the brain can be viewed as a black body lying inside a black box. In physics, a black body tends to be in thermal equilibrium with its environment and can tightly regulate its temperature via thermodynamic principles. Therefore, a healthy brain inside a black box should not be exposed to light. On the contrary, photobiomodulation, a form of light therapy for the brain, has been shown to have beneficial effects on some neurological conditions. The proposed underlying mechanisms are multiple. Herein, we present our intraoperative findings of rapid electrocorticographic brainwave changes when the brain was shone directly with different wavelengths of light during awake brain surgery. Our findings provide literature evidence for light's ability to influence human brain energy and function. Our proposed mechanism for these rapid changes is the presence of plasma-like energy inside the brain, which causes fast brain activities that are akin to lightning strikes.

Timing and location of speech errors induced by direct cortical stimulation

Cortical regions supporting speech production are commonly established using neuroimaging techniques in both research and clinical settings. However, for neurosurgical purposes, structural function is routinely mapped peri-operatively using direct electrocortical stimulation. While this method is the gold standard for identification of eloquent cortical regions to preserve in neurosurgical patients, there is lack of specificity of the actual underlying cognitive processes being interrupted. To address this, we propose mapping the temporal dynamics of speech arrest across peri-sylvian cortices by quantifying the latency between stimulation and speech deficits. In doing so, we are able to substantiate hypotheses about distinct region-specific functional roles (e.g. planning versus motor execution). In this retrospective observational study, we analysed 20 patients (12 female; age range 14-43) with refractory epilepsy who underwent continuous extra-operative intracranial EEG monitoring of an automatic speech task during clinical bedside language mapping. Latency to speech arrest was calculated as time from stimulation onset to speech arrest onset, controlling for individual speech rate. Most instances of motor-based arrest (87.5% of 96 instances) were in sensorimotor cortex with mid-range latencies to speech arrest with a distributional peak at 0.47 s. Speech arrest occurred in numerous regions, with relatively short latencies in supramarginal gyrus (0.46 s), superior temporal gyrus (0.51 s) and middle temporal gyrus (0.54 s), followed by relatively long latencies in sensorimotor cortex (0.72 s) and especially long latencies in inferior frontal gyrus (0.95 s). Non-parametric testing for speech arrest revealed that region predicted latency; latencies in supramarginal gyrus and in superior temporal gyrus were shorter than in sensorimotor cortex and in inferior frontal gyrus. Sensorimotor cortex is primarily responsible for motor-based arrest. Latencies to speech arrest in supramarginal gyrus and superior temporal gyrus (and to a lesser extent middle temporal gyrus) align with latencies to motor-based arrest in sensorimotor cortex. This pattern of relatively quick cessation of speech suggests that stimulating these regions interferes with the outgoing motor execution. In contrast, the latencies to speech arrest in inferior frontal gyrus and in ventral regions of sensorimotor cortex were significantly longer than those in temporoparietal regions. Longer latencies in the more frontal areas (including inferior frontal gyrus and ventral areas of precentral gyrus and postcentral gyrus) suggest that stimulating these areas interrupts a higher-level speech production process involved in planning. These results implicate the ventral specialization of sensorimotor cortex (including both precentral and postcentral gyri) for speech planning above and beyond motor execution.

Multiplexed Surface Electrode Arrays Based on Metal Oxide Thin-Film Electronics for High-Resolution Cortical Mapping

Electrode grids are used in neuroscience research and clinical practice to record electrical activity from the surface of the brain. However, existing passive electrocorticography (ECoG) technologies are unable to offer both high spatial resolution and wide cortical coverage, while ensuring a compact acquisition system. The electrode count and density are restricted by the fact that each electrode must be individually wired. This work presents an active micro-electrocorticography (µECoG) implant that tackles this limitation by incorporating metal oxide thin-film transistors (TFTs) into a flexible electrode array, allowing to address multiple electrodes through a single shared readout line. By combining the array with an incremental-ΔΣ readout integrated circuit (ROIC), the system is capable of recording from up to 256 electrodes virtually simultaneously, thanks to the implemented 16:1 time-division multiplexing scheme, offering lower noise levels than existing active µECoG arrays. In vivo validation is demonstrated acutely in mice by recording spontaneous activity and somatosensory evoked potentials over a cortical surface of ≈8×8 mm2 . The proposed neural interface overcomes the wiring bottleneck limiting ECoG arrays, holding promise as a powerful tool for improved mapping of the cerebral cortex and as an enabling technology for future brain-machine interfaces.

Intraoperative application and early experience with novel high-resolution, high-channel-count thin-film electrodes for human microelectrocorticography

OBJECTIVE

The study objective was to evaluate intraoperative experience with newly developed high-spatial-resolution microelectrode grids composed of poly(3,4-ethylenedioxythiophene) with polystyrene sulfonate (PEDOT:PSS), and those composed of platinum nanorods (PtNRs).

METHODS

A cohort of patients who underwent craniotomy for pathological tissue resection and who had high-spatial-resolution microelectrode grids placed intraoperatively were evaluated. Patient demographic and baseline clinical variables as well as relevant microelectrode grid characteristic data were collected. The primary and secondary outcome measures of interest were successful microelectrode grid utilization with usable resting-state or task-related data, and grid-related adverse intraoperative events and/or grid dysfunction.

RESULTS

Included in the analysis were 89 cases of patients who underwent a craniotomy for resection of neoplasms (n = 58) or epileptogenic tissue (n = 31). These cases accounted for 94 grids: 58 PEDOT:PSS and 36 PtNR grids. Of these 94 grids, 86 were functional and used successfully to obtain cortical recordings from 82 patients. The mean cortical grid recording duration was 15.3 ± 1.15 minutes. Most recordings in patients were obtained during experimental tasks (n = 52, 58.4%), involving language and sensorimotor testing paradigms, or were obtained passively during resting state (n = 32, 36.0%). There were no intraoperative adverse events related to grid placement. However, there were instances of PtNR grid dysfunction (n = 8) related to damage incurred by suboptimal preoperative sterilization (n = 7) and improper handling (n = 1); intraoperative recordings were not performed. Vaporized peroxide sterilization was the most optimal sterilization method for PtNR grids, providing a significantly greater number of usable channels poststerilization than did steam-based sterilization techniques (median 905.0 [IQR 650.8-935.5] vs 356.0 [IQR 18.0-597.8], p = 0.0031).

CONCLUSIONS

High-spatial-resolution microelectrode grids can be readily incorporated into appropriately selected craniotomy cases for clinical and research purposes. Grids are reliable when preoperative handling and sterilization considerations are accounted for. Future investigations should compare the diagnostic utility of these high-resolution grids to commercially available counterparts and assess whether diagnostic discrepancies relate to clinical outcomes.

Intraoperative ECoG in bottom-of-the-sulcus syndrome using a novel flexible strip electrode

The recording of epileptiform discharges from bottom-of-sulcus focal cortical dysplasia (BOSD) is often difficult during intraoperative electrocorticography (ECoG) due to the deep localization. We describe the use in this scenario of a new-generation electrode strip with high flexibility, easily adapted to cortical gyri and sulci. A right-handed 20-year-old male with drug-resistant focal epilepsy due to BOSD of the inferior frontal gyrus and daily focal aware seizures was evaluated for epilepsy surgery. Based on electroclinical and neuroimaging results, a focal cortectomy guided by ECoG was proposed. ECoG recordings were performed with new-generation cortical strips (Wise Cortical Strip; WCS®) and standard cortical strips. ECoG, performed on the convexity of the frontal cortical surface, recorded only sporadic spikes with both types of strips. Then, after microsurgical trans-sulcal dissection, WCS was molded along the sulcal surface of the suspected BOSD based on 3D-imaging reconstruction, showing continuous/subcontinuous 3-4-Hz rhythmic spike activity from the deepest electrode. Registration after resection of the BOSD did not show any epileptiform activity. Pathology showed dysmorphic neurons and gliosis. No surgical complications occurred. The patient is seizure-free after 12 months. This single case experience shows that highly flexible electrode strips with adaptability to cortical gyrations can identify IEDs originating from deep location and could therefore be useful in cases of bottom of the sulcus dysplasia.

Intraoperative language mapping guided by real-time visualization of gamma band modulation electrocorticograms: Case report and proof of concept

Background

Electrocorticography (ECoG) language mapping is often performed extraoperatively, frequently involves offline processing, and relationships with direct cortical stimulation (DCS) remain variable. We sought to determine the feasibility and preliminary utility of an intraoperative language mapping approach guided by real-time visualization of electrocorticograms.

Methods

A patient with astrocytoma underwent awake craniotomy with intraoperative language mapping, utilizing a dual iPad stimulus presentation system coupled to a real-time neural signal processing platform capable of both ECoG recording and delivery of DCS. Gamma band modulations in response to 4 language tasks at each electrode were visualized in real-time. Next, DCS was conducted for each neighboring electrode pair during language tasks.

Results

All language tasks resulted in strongest heat map activation at an electrode pair in the anterior to mid superior temporal gyrus. Consistent speech arrest during DCS was observed for Object and Action naming tasks at these same electrodes, indicating good correspondence with ECoG heat map recordings. This region corresponded well with posterior language representation via preoperative functional MRI.

Conclusions

Intraoperative real-time visualization of language task-based ECoG gamma band modulation is feasible and may help identify targets for DCS. If validated, this may improve the efficiency and accuracy of intraoperative language mapping.

Auditory prediction and prediction error responses evoked through a novel cascade roving paradigm: a human ECoG study

Auditory sensory processing is assumed to occur in a hierarchical structure including the primary auditory cortex (A1), superior temporal gyrus, and frontal areas. These areas are postulated to generate predictions for incoming stimuli, creating an internal model of the surrounding environment. Previous studies on mismatch negativity have indicated the involvement of the superior temporal gyrus in this processing, whereas reports have been mixed regarding the contribution of the frontal cortex. We designed a novel auditory paradigm, the "cascade roving" paradigm, which incorporated complex structures (cascade sequences) into a roving paradigm. We analyzed electrocorticography data from six patients with refractory epilepsy who passively listened to this novel auditory paradigm and detected responses to deviants mainly in the superior temporal gyrus and inferior frontal gyrus. Notably, the inferior frontal gyrus exhibited broader distribution and sustained duration of deviant-elicited responses, seemingly differing in spatio-temporal characteristics from the prediction error responses observed in the superior temporal gyrus, compared with conventional oddball paradigms performed on the same participants. Moreover, we observed that the deviant responses were enhanced through stimulus repetition in the high-gamma range mainly in the superior temporal gyrus. These features of the novel paradigm may aid in our understanding of auditory predictive coding.

Timing and location of speech errors induced by direct cortical stimulation

Cortical regions supporting speech production are commonly established using neuroimaging techniques in both research and clinical settings. However, for neurosurgical purposes, structural function is routinely mapped peri-operatively using direct electrocortical stimulation. While this method is the gold standard for identification of eloquent cortical regions to preserve in neurosurgical patients, there is lack of specificity of the actual underlying cognitive processes being interrupted. To address this, we propose mapping the temporal dynamics of speech arrest across peri-sylvian cortices by quantifying the latency between stimulation and speech deficits. In doing so, we are able to substantiate hypotheses about distinct region-specific functional roles (e.g., planning versus motor execution). In this retrospective observational study, we analyzed 20 patients (12 female; age range 14-43) with refractory epilepsy who underwent continuous extra-operative intracranial EEG monitoring of an automatic speech task during clinical bedside language mapping. Latency to speech arrest was calculated as time from stimulation onset to speech arrest onset, controlling for individual speech rate. Most instances of motor-based arrest (87.5% of 96 instances) were in sensorimotor cortex with mid-range latencies to speech arrest with a distributional peak at 0.47 seconds. Speech arrest occurred in numerous regions, with relatively short latencies in supramarginal gyrus (0.46 seconds), superior temporal gyrus (0.51 seconds), and middle temporal gyrus (0.54 seconds), followed by relatively long latencies in sensorimotor cortex (0.72 seconds) and especially long latencies in inferior frontal gyrus (0.95 seconds). Nonparametric testing for speech arrest revealed that region predicted latency; latencies in supramarginal gyrus and in superior temporal gyrus were shorter than in sensorimotor cortex and in inferior frontal gyrus. Sensorimotor cortex is primarily responsible for motor-based arrest. Latencies to speech arrest in supramarginal gyrus and superior temporal gyrus (and to a lesser extent middle temporal gyrus) align with latencies to motor-based arrest in sensorimotor cortex. This pattern of relatively quick cessation of speech suggests that stimulating these regions interferes with the outgoing motor execution. In contrast, the latencies to speech arrest in inferior frontal gyrus and in ventral regions of sensorimotor cortex were significantly longer than those in temporoparietal regions. Longer latencies in the more frontal areas (including inferior frontal gyrus and ventral areas of precentral gyrus and postcentral gyrus) suggest that stimulating these areas interrupts a higher-level speech production process involved in planning. These results implicate the ventral specialization of sensorimotor cortex (including both precentral and postcentral gyri) for speech planning above and beyond motor execution.

Benefits of sharing neurophysiology data from the BRAIN Initiative Research Opportunities in Humans Consortium

Sharing human brain data can yield scientific benefits, but because of various disincentives, only a fraction of these data is currently shared. We profile three successful data-sharing experiences from the NIH BRAIN Initiative Research Opportunities in Humans (ROH) Consortium and demonstrate benefits to data producers and to users.

Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review

STUDY DESIGN

Systematic review of the literature.

OBJECTIVES

In recent years, brain-computer interface (BCI) has emerged as a potential treatment for patients with spinal cord injury (SCI). This is the first systematic review of the literature on invasive closed-loop BCI technologies for the treatment of SCI in humans.

MATERIALS AND METHODS

A comprehensive search of PubMed MEDLINE, Web of Science, and Ovid EMBASE was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

Of 8316 articles collected, 19 studies met all the inclusion criteria. Data from 21 patients were extracted from these studies. All patients sustained a cervical SCI and were treated using either a BCI with intracortical microelectrode arrays (n = 18, 85.7%) or electrocorticography (n = 3, 14.3%). To decode these neural signals, machine learning and statistical models were used: support vector machine in eight patients (38.1%), linear estimator in seven patients (33.3%), Hidden Markov Model in three patients (14.3%), and other in three patients (14.3%). As the outputs, ten patients (47.6%) underwent noninvasive functional electrical stimulation (FES) with a cuff; one (4.8%) had an invasive FES with percutaneous stimulation, and ten (47.6%) used an external device (neuroprosthesis or virtual avatar). Motor function was restored in all patients for each assigned task. Clinical outcome measures were heterogeneous across all studies.

CONCLUSIONS

Invasive techniques of BCI show promise for the treatment of SCI, but there is currently no technology that can restore complete functional autonomy in patients with SCI. The current techniques and outcomes of BCI vary greatly. Because invasive BCIs are still in the early stages of development, further clinical studies should be conducted to optimize the prognosis for patients with SCI.

Epileptic versus neuro-oncological focus of management in pediatric patients with concurrent primary brain lesion and seizures: a systematic review

OBJECTIVE

Seizures can be a debilitating manifestation of underlying neoplastic intracranial pathology. Existing literature offers a paucity of scientific consensus regarding risk factors, seizure semiology, operative techniques, and tumor characteristics in pediatric patients with a concurrent diagnosis of primary intracranial neoplasm and seizures. To address the limited evidence in current literature, the authors systematically reviewed published literature on current clinical characteristics and management strategies for patients presenting concurrently with seizures and a newly diagnosed brain lesion, while aiming to synthesize a potential management protocol or set of recommendations for these patients.

METHODS

An initial search revealed 792 papers, of which 196 studies were excluded, leaving 596 studies available for abstract review. After further stratification, 546 studies were eliminated, leaving 50 studies for eligibility assessment. Of the 50 studies, 12 met the criteria for outcome extraction.

RESULTS

The results indicate that patients with a mean age of 9 years with a newly diagnosed brain tumor and presenting symptoms of seizure are likely to present with daily seizures of the complex partial subtype, with the most likely primary epileptogenic and neoplastic foci occurring in the temporal lobe. The most common tumor subtypes were low-grade gliomas, ganglioglioma, dysembryoplastic neuroepithelial tumor, or astrocytoma. With the aim of gross-total resection, 77.54% of patients are likely to achieve seizure freedom.

CONCLUSIONS

This study highlights the demographic, clinical, seizure, tumor, and postoperative outcomes for pediatric patients presenting with a primary brain tumor and concurrent seizures. Further prospective multicenter studies are necessary to understand and compare varying treatment approaches and to develop standardized guidelines for these patients, with the goal of optimizing neuro-oncological and seizure-related outcomes.

Can we improve electrocorticography using a circular grid array in brain tumor surgery?

Intraoperative electrocorticography (iECoG) is used as an adjunct to localize the epileptogenic zone during surgical resection of brain tumors in patients with focal epilepsies. It also enables monitoring of after-discharges and seizures with EEG during functional brain mapping with electrical stimulation. When seizures or after-discharges are present, they complicate accurate interpretation of the mapping strategy to outline the brain's eloquent function and can affect the surgical procedure. Recurrent seizures during surgery requires urgent treatment and, when occurring during awake craniotomy, often leads to premature termination of brain mapping due to post-ictal confusion or sedation from acute rescue therapy. There are mixed results in studies on efficacy with iECoG in patients with epilepsy and brain tumors influencing survival and functional outcomes following surgery. Commercially available electrode arrays have inherent limitations. These could be improved with customization potentially leading to greater precision in safe and maximal resection of brain tumors. Few studies have assessed customized electrode grid designs as an alternative to commercially available products. Higher density electrode grids with intercontact distances less than 1 cm improve spatial delineation of electrophysiologic sources, including epileptiform activity, electrographic seizures, and afterdischarges on iECoG during functional brain mapping. In response to the shortcomings of current iECoG grid technologies, we designed and developed a novel higher-density hollow circular electrode grid array. The 360-degree iECoG monitoring capability allows continuous EEG recording during surgical intervention through the aperture with and without electrical stimulation mapping. Compared with linear strip electrodes that are commonly used for iECoG during surgery, the circular grid demonstrates significant benefits in brain tumor surgery. This includes quicker recovery of post-operative motor deficits (2.4 days versus 9 days, p = 0.05), more extensive tumor resection (92.0% versus 77.6%, p = 0.003), lesser reduction in Karnofsky Performance scale postoperatively (-2 versus -11.6, p = 0.007), and more sensitivity to recording afterdischarges. In this narrative review, we discuss the advantages and disadvantages of commercially available recording devices in the operating room and focus on the usefulness of the higher-density circular grid.

Mapping information flow between the inferotemporal and prefrontal cortices via neural oscillations in memory retrieval and maintenance

Interaction between the inferotemporal (ITC) and prefrontal (PFC) cortices is critical for retrieving information from memory and maintaining it in working memory. Neural oscillations provide a mechanism for communication between brain regions. However, it remains unknown how information flow via neural oscillations is functionally organized in these cortices during these processes. In this study, we apply Granger causality analysis to electrocorticographic signals from both cortices of monkeys performing visual association tasks to map information flow. Our results reveal regions within the ITC where information flow to and from the PFC increases via specific frequency oscillations to form clusters during memory retrieval and maintenance. Theta-band information flow in both directions increases in similar regions in both cortices, suggesting reciprocal information exchange in those regions. These findings suggest that specific subregions function as nodes in the memory information-processing network between the ITC and the PFC.

Distributed feedforward and feedback cortical processing supports human speech production

Speech production is a complex human function requiring continuous feedforward commands together with reafferent feedback processing. These processes are carried out by distinct frontal and temporal cortical networks, but the degree and timing of their recruitment and dynamics remain poorly understood. We present a deep learning architecture that translates neural signals recorded directly from the cortex to an interpretable representational space that can reconstruct speech. We leverage learned decoding networks to disentangle feedforward vs. feedback processing. Unlike prevailing models, we find a mixed cortical architecture in which frontal and temporal networks each process both feedforward and feedback information in tandem. We elucidate the timing of feedforward and feedback-related processing by quantifying the derived receptive fields. Our approach provides evidence for a surprisingly mixed cortical architecture of speech circuitry together with decoding advances that have important implications for neural prosthetics.

Lateralization and Time-Course of Cortical Phonological Representations during Syllable Production

Spoken language contains information at a broad range of timescales, from phonetic distinctions on the order of milliseconds to semantic contexts which shift over seconds to minutes. It is not well understood how the brain's speech production systems combine features at these timescales into a coherent vocal output. We investigated the spatial and temporal representations in cerebral cortex of three phonological units with different durations: consonants, vowels, and syllables. Electrocorticography (ECoG) recordings were obtained from five participants while speaking single syllables. We developed a novel clustering and Kalman filter-based trend analysis procedure to sort electrodes into temporal response profiles. A linear discriminant classifier was used to determine how strongly each electrode's response encoded phonological features. We found distinct time-courses of encoding phonological units depending on their duration: consonants were represented more during speech preparation, vowels were represented evenly throughout trials, and syllables during production. Locations of strongly speech-encoding electrodes (the top 30% of electrodes) likewise depended on phonological element duration, with consonant-encoding electrodes left-lateralized, vowel-encoding hemispherically balanced, and syllable-encoding right-lateralized. The lateralization of speech-encoding electrodes depended on onset time, with electrodes active before or after speech production favoring left hemisphere and those active during speech favoring the right. Single-electrode speech classification revealed cortical areas with preferential encoding of particular phonemic elements, including consonant encoding in the left precentral and postcentral gyri and syllable encoding in the right middle frontal gyrus. Our findings support neurolinguistic theories of left hemisphere specialization for processing short-timescale linguistic units and right hemisphere processing of longer-duration units.

Improving Neurotrauma by Depolarization Inhibition With Combination Therapy: A Phase 2 Randomized Feasibility Trial

BACKGROUND AND OBJECTIVES

Spreading depolarizations (SDs) are a pathological mechanism that mediates lesion development in cerebral gray matter. They occur in ∼60% of patients with severe traumatic brain injury (TBI), often in recurring and progressive patterns from days 0 to 10 after injury, and are associated with worse outcomes. However, there are no protocols or trials suggesting how SD monitoring might be incorporated into clinical management. The objective of this protocol is to determine the feasibility and efficacy of implementing a treatment protocol for intensive care of patients with severe TBI that is guided by electrocorticographic monitoring of SDs.

METHODS

Patients who undergo surgery for severe TBI with placement of a subdural electrode strip will be eligible for enrollment. Those who exhibit SDs on electrocorticography during intensive care will be randomized 1:1 to either (1) standard care that is blinded to the further course of SDs or (2) a tiered intervention protocol based on efficacy to suppress further SDs. Interventions aim to block the triggering and propagation of SDs and include adjusted targets for management of blood pressure, CO 2 , temperature, and glucose, as well as ketamine pharmacotherapy up to 4 mg/kg/ hour. Interventions will be escalated and de-escalated depending on the course of SD pathology.

EXPECTED OUTCOMES

We expect to demonstrate that electrocorticographic monitoring of SDs can be used as a real- time diagnostic in intensive care that leads to meaningful changes in patient management and a reduction in secondary injury, as compared with standard care, without increasing medical complications or adverse events.

DISCUSSION

This trial holds potential for personalization of intensive care management by tailoring therapies based on monitoring and confirmation of the targeted neuronal mechanism of SD. Results are expected to validate the concept of this approach, inform refinement of the treatment protocol, and lead to larger-scale trials.

Chronic subdural electrocorticography in nonhuman primates by an implantable wireless device for brain-machine interfaces

Background

Subdural electrocorticography (ECoG) signals have been proposed as a stable, good-quality source for brain-machine interfaces (BMIs), with a higher spatial and temporal resolution than electroencephalography (EEG). However, long-term implantation may lead to chronic inflammatory reactions and connective tissue encapsulation, resulting in a decline in signal recording quality. However, no study has reported the effects of the surrounding tissue on signal recording and device functionality thus far.

Methods

In this study, we implanted a wireless recording device with a customized 32-electrode-ECoG array subdurally in two nonhuman primates for 15 months. We evaluated the neural activities recorded from and wirelessly transmitted to the devices and the chronic tissue reactions around the electrodes. In addition, we measured the gain factor of the newly formed ventral fibrous tissue in vivo.

Results

Time-frequency analyses of the acute and chronic phases showed similar signal features. The average root mean square voltage and power spectral density showed relatively stable signal quality after chronic implantation. Histological examination revealed thickening of the reactive tissue around the electrode array; however, no evident inflammation in the cortex. From gain factor analysis, we found that tissue proliferation under electrodes reduced the amplitude power of signals.

Conclusion

This study suggests that subdural ECoG may provide chronic signal recordings for future clinical applications and neuroscience research. This study also highlights the need to reduce proliferation of reactive tissue ventral to the electrodes to enhance long-term stability.

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.

Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models

Objective.Development of brain-computer interface (BCI) technology is key for enabling communication in individuals who have lost the faculty of speech due to severe motor paralysis. A BCI control strategy that is gaining attention employs speech decoding from neural data. Recent studies have shown that a combination of direct neural recordings and advanced computational models can provide promising results. Understanding which decoding strategies deliver best and directly applicable results is crucial for advancing the field.Approach.In this paper, we optimized and validated a decoding approach based on speech reconstruction directly from high-density electrocorticography recordings from sensorimotor cortex during a speech production task.Main results.We show that (1) dedicated machine learning optimization of reconstruction models is key for achieving the best reconstruction performance; (2) individual word decoding in reconstructed speech achieves 92%-100% accuracy (chance level is 8%); (3) direct reconstruction from sensorimotor brain activity produces intelligible speech.Significance.These results underline the need for model optimization in achieving best speech decoding results and highlight the potential that reconstruction-based speech decoding from sensorimotor cortex can offer for development of next-generation BCI technology for communication.

High gamma coherence between task-responsive sensory-motor cortical regions in a motor reaction-time task

Electrical activity at high gamma frequencies (70-170 Hz) is thought to reflect the activity of small cortical ensembles. For example, high gamma activity (often quantified by spectral power) can increase in sensory-motor cortex in response to sensory stimuli or movement. On the other hand, synchrony of neural activity between cortical areas (often quantified by coherence) has been hypothesized as an important mechanism for inter-areal communication, thereby serving functional roles in cognition and behavior. Currently, high gamma activity has primarily been studied as a local amplitude phenomenon. We investigated the synchronization of high gamma activity within sensory-motor cortex and the extent to which underlying high gamma activity can explain coherence during motor tasks. We characterized high gamma coherence in sensory-motor networks and the relationship between coherence and power by analyzing electrocorticography (ECoG) data from human subjects as they performed a motor response to sensory cues. We found greatly increased high gamma coherence during the motor response compared with the sensory cue. High gamma power poorly predicted high gamma coherence, but the two shared a similar time course. However, high gamma coherence persisted longer than high gamma power. The results of this study suggest that high gamma coherence is a physiologically distinct phenomenon during a sensory-motor task, the emergence of which may require active task participation.NEW & NOTEWORTHY Motor action after auditory stimulus elicits high gamma responses in sensory-motor and auditory cortex, respectively. We show that high gamma coherence reliably and greatly increased during motor response, but not after auditory stimulus. Underlying high gamma power could not explain high gamma coherence. Our results indicate that high gamma coherence is a physiologically distinct sensory-motor phenomenon that may serve as an indicator of increased synaptic communication on short timescales (∼1 s).

Analogous cortical reorganization accompanies entry into states of reduced consciousness during anesthesia and sleep

Theories of consciousness suggest that brain mechanisms underlying transitions into and out of unconsciousness are conserved no matter the context or precipitating conditions. We compared signatures of these mechanisms using intracranial electroencephalography in neurosurgical patients during propofol anesthesia and overnight sleep and found strikingly similar reorganization of human cortical networks. We computed the "effective dimensionality" of the normalized resting state functional connectivity matrix to quantify network complexity. Effective dimensionality decreased during stages of reduced consciousness (anesthesia unresponsiveness, N2 and N3 sleep). These changes were not region-specific, suggesting global network reorganization. When connectivity data were embedded into a low-dimensional space in which proximity represents functional similarity, we observed greater distances between brain regions during stages of reduced consciousness, and individual recording sites became closer to their nearest neighbors. These changes corresponded to decreased differentiation and functional integration and correlated with decreases in effective dimensionality. This network reorganization constitutes a neural signature of states of reduced consciousness that is common to anesthesia and sleep. These results establish a framework for understanding the neural correlates of consciousness and for practical evaluation of loss and recovery of consciousness.

Cortical control of posture in fine motor skills: evidence from inter-utterance rest position

The vocal tract continuously employs tonic muscle activity in the maintenance of postural configurations. Gamma-band activity in the sensorimotor cortex underlies transient movements during speech production, yet little is known about the neural control of postural states in the vocal tract. Simultaneously, there is evidence that sensorimotor beta-band activations contribute to a system of inhibition and state maintenance that is integral to postural control in the body. Here we use electrocorticography to assess the contribution of sensorimotor beta-band activity during speech articulation and postural maintenance, and demonstrate that beta-band activity corresponds to the inhibition of discrete speech movements and the maintenance of tonic postural states in the vocal tract. Our findings identify consistencies between the neural control of posture in speech and what is previously reported in gross motor contexts, providing support for a unified theory of postural control across gross and fine motor skills.

Human upper extremity motor cortex activity shows distinct oscillatory signatures for stereotyped arm and leg movements

Introduction

Stepping and arm swing are stereotyped movements that require coordination across multiple muscle groups. It is not known whether the encoding of these stereotyped movements in the human primary motor cortex is confined to the limbs' respective somatotopy.

Methods

We recorded subdural electrocorticography activities from the hand/arm area in the primary motor cortex of 6 subjects undergoing deep brain stimulation surgery for essential tremor and Parkinson's disease who performed stepping (all patients) and arm swing (n = 3 patients) tasks.

Results

We show stepping-related low frequency oscillations over the arm area. Furthermore, we show that this oscillatory activity is separable, both in frequency and spatial domains, from gamma band activity changes that occur during arm swing.

Discussion

Our study contributes to the growing body of evidence that lower extremity movement may be more broadly represented in the motor cortex, and suggest that it may represent a way to coordinate stereotyped movements across the upper and lower extremities.

Characterization of High-Gamma Activity in Electrocorticographic Signals

Introduction

Electrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information.

Methods

To address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA.

Results

The high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks.

Discussion

This study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies.

Continuous synthesis of artificial speech sounds from human cortical surface recordings during silent speech production

Objective. Brain-computer interfaces can restore various forms of communication in paralyzed patients who have lost their ability to articulate intelligible speech. This study aimed to demonstrate the feasibility of closed-loop synthesis of artificial speech sounds from human cortical surface recordings during silent speech production.Approach. Ten participants with intractable epilepsy were temporarily implanted with intracranial electrode arrays over cortical surfaces. A decoding model that predicted audible outputs directly from patient-specific neural feature inputs was trained during overt word reading and immediately tested with overt, mimed and imagined word reading. Predicted outputs were later assessed objectively against corresponding voice recordings and subjectively through human perceptual judgments.Main results. Artificial speech sounds were successfully synthesized during overt and mimed utterances by two participants with some coverage of the precentral gyrus. About a third of these sounds were correctly identified by naïve listeners in two-alternative forced-choice tasks. A similar outcome could not be achieved during imagined utterances by any of the participants. However, neural feature contribution analyses suggested the presence of exploitable activation patterns during imagined speech in the postcentral gyrus and the superior temporal gyrus. In future work, a more comprehensive coverage of cortical surfaces, including posterior parts of the middle frontal gyrus and the inferior frontal gyrus, could improve synthesis performance during imagined speech.Significance.As the field of speech neuroprostheses is rapidly moving toward clinical trials, this study addressed important considerations about task instructions and brain coverage when conducting research on silent speech with non-target participants.

Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities

In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses.

Concurrent decoding of distinct neurophysiological fingerprints of tremor and bradykinesia in Parkinson's disease

Parkinson's disease (PD) is characterized by distinct motor phenomena that are expressed asynchronously. Understanding the neurophysiological correlates of these motor states could facilitate monitoring of disease progression and allow improved assessments of therapeutic efficacy, as well as enable optimal closed-loop neuromodulation. We examined neural activity in the basal ganglia and cortex of 31 subjects with PD during a quantitative motor task to decode tremor and bradykinesia - two cardinal motor signs of PD - and relatively asymptomatic periods of behavior. Support vector regression analysis of microelectrode and electrocorticography recordings revealed that tremor and bradykinesia had nearly opposite neural signatures, while effective motor control displayed unique, differentiating features. The neurophysiological signatures of these motor states depended on the signal type and location. Cortical decoding generally outperformed subcortical decoding. Within the subthalamic nucleus (STN), tremor and bradykinesia were better decoded from distinct subregions. These results demonstrate how to leverage neurophysiology to more precisely treat PD.

Accurate Deep Brain Stimulation Lead Placement Concurrent With Research Electrocorticography

BACKGROUND

Using electrocorticography for research (R-ECoG) during deep brain stimulation (DBS) surgery has advanced our understanding of human cortical-basal ganglia neurophysiology and mechanisms of therapeutic circuit modulation. The safety of R-ECoG has been established, but potential effects of temporary ECoG strip placement on targeting accuracy have not been reported.

OBJECTIVE

To determine whether temporary subdural electrode strip placement during DBS implantation surgery affects lead implantation accuracy.

METHODS

Twenty-four consecutive patients enrolled in a prospective database who underwent awake DBS surgery were identified. Ten of 24 subjects participated in R-ECoG. Lead locations were determined after fusing postoperative computed tomography scans into the surgical planning software. The effect of brain shift was quantified using Lead-DBS and analyzed in a mixed-effects model controlling for time interval to postoperative computed tomography. Targeting accuracy was reported as radial and Euclidean distance errors and compared with Mann-Whitney tests.

RESULTS

Neither radial error nor Euclidean distance error differed significantly between R-ECoG participants and nonparticipants. Pneumocephalus volume did not differ between the 2 groups, but brain shift was slightly greater with R-ECoG. Pneumocephalus volume correlated with brain shift, but neither of these measures significantly correlated with Euclidean distance error. There were no complications in either group.

CONCLUSION

In addition to an excellent general safety profile as has been reported previously, these results suggest that performing R-ECoG during DBS implantation surgery does not affect the accuracy of lead placement.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

Nine decades of electrocorticography: A comparison between epidural and subdural recordings

In recent years, electrocorticography (ECoG) has arisen as a neural signal recording tool in the development of clinically viable neural interfaces. ECoG electrodes are generally placed below the dura mater (subdural) but can also be placed on top of the dura (epidural). In deciding which of these modalities best suits long-term implants, complications and signal quality are important considerations. Conceptually, epidural placement may present a lower risk of complications as the dura is left intact but also a lower signal quality due to the dura acting as a signal attenuator. The extent to which complications and signal quality are affected by the dura, however, has been a matter of debate. To improve our understanding of the effects of the dura on complications and signal quality, we conducted a literature review. We inventorized the effect of the dura on signal quality, decodability and longevity of acute and chronic ECoG recordings in humans and non-human primates. Also, we compared the incidence and nature of serious complications in studies that employed epidural and subdural ECoG. Overall, we found that, even though epidural recordings exhibit attenuated signal amplitude over subdural recordings, particularly for high-density grids, the decodability of epidural recorded signals does not seem to be markedly affected. Additionally, we found that the nature of serious complications was comparable between epidural and subdural recordings. These results indicate that both epidural and subdural ECoG may be suited for long-term neural signal recordings, at least for current generations of clinical and high-density ECoG grids.

Reflection of the Ictal Electrocorticographic Discharges Confined to the Medial Temporal Lobe to the Scalp-Recorded Electroencephalogram

Objective: Previous reports on the simultaneous recording of electroencephalography (EEG) and electrocorticography (ECoG) have demonstrated that, in patients with temporal lobe epilepsy (TLE), ictal ECoG discharges with an amplitude as high as 1000 μV originating from the medial temporal lobe could not be recorded on EEG. In contrast, ictal EEG discharges were recorded after ictal ECoG discharges propagated to the lateral temporal lobe. Here, we report a case of TLE in which the ictal EEG discharges, corresponding to ictal ECoG discharges confined to the medial temporal lobe, were recorded. Case report: In the present case, ictal EEG discharges were hardly recognized when the amplitude of the ECoG discharges was less than 1500 μV. During the evolution and burst suppression phase, corresponding to highly synchronized ECoG discharges with amplitudes greater than 1500 to 2000 μV, rhythmic negative waves with the same frequency were clearly recorded both on the lateral temporal lobe and scalp. The amplitude of the lateral temporal ECoG was approximately one-tenth of that of the medial temporal ECoG. The amplitude of the scalp EEG was approximately one-tenth of that of the lateral temporal ECoG. Conclusions: Highly synchronized ictal ECoG discharges with high amplitude of greater than 1500 to 2000 μV in the medial temporal lobe could be recorded on the scalp as ictal EEG discharges via volume conduction.

Machine Learning to Classify Relative Seizure Frequency From Chronic Electrocorticography

PURPOSE

Brain responsive neurostimulation (NeuroPace) treats patients with refractory focal epilepsy and provides chronic electrocorticography (ECoG). We explored how machine learning algorithms applied to interictal ECoG could assess clinical response to changes in neurostimulation parameters.

METHODS

We identified five responsive neurostimulation patients each with ≥200 continuous days of stable medication and detection settings (median, 358 days per patient). For each patient, interictal ECoG segments for each month were labeled as "high" or "low" to represent relatively high or low long-episode (i.e., seizure) count compared with the median monthly long-episode count. Power from six conventional frequency bands from four responsive neurostimulation channels were extracted as features. For each patient, five machine learning algorithms were trained on 80% of ECoG, then tested on the remaining 20%. Classifiers were scored by the area-under-the-receiver-operating-characteristic curve. We explored how individual circadian cycles of seizure activity could inform classifier building.

RESULTS

Support vector machine or gradient boosting models achieved the best performance, ranging from 0.705 (fair) to 0.892 (excellent) across patients. High gamma power was the most important feature, tending to decrease during low-seizure-frequency epochs. For two subjects, training on ECoG recorded during the circadian ictal peak resulted in comparable model performance, despite less data used.

CONCLUSIONS

Machine learning analysis on retrospective background ECoG can classify relative seizure frequency for an individual patient. High gamma power was the most informative, whereas individual circadian patterns of seizure activity can guide model building. Machine learning classifiers built on interictal ECoG may guide stimulation programming.

Brain-Computer interface control of stepping from invasive electrocorticography upper-limb motor imagery in a patient with quadriplegia

Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishing ambulation. Using brain-computer interfaces (BCI), patients may regain leg control using neural signals that actuate assistive devices. Here, we present a case of a subject with cervical SCI with an implanted electrocorticography (ECoG) device and determined whether the system is capable of motor-imagery-initiated walking in an assistive ambulator. Methods: A 24-year-old male subject with cervical SCI (C5 ASIA A) was implanted before the study with an ECoG sensing device over the sensorimotor hand region of the brain. The subject used motor-imagery (MI) to train decoders to classify sensorimotor rhythms. Fifteen sessions of closed-loop trials followed in which the subject ambulated for one hour on a robotic-assisted weight-supported treadmill one to three times per week. We evaluated the stability of the best-performing decoder over time to initiate walking on the treadmill by decoding upper-limb (UL) MI. Results: An online bagged trees classifier performed best with an accuracy of 84.15% averaged across 9 weeks. Decoder accuracy remained stable following throughout closed-loop data collection. Discussion: These results demonstrate that decoding UL MI is a feasible control signal for use in lower-limb motor control. Invasive BCI systems designed for upper-extremity motor control can be extended for controlling systems beyond upper extremity control alone. Importantly, the decoders used were able to use the invasive signal over several weeks to accurately classify MI from the invasive signal. More work is needed to determine the long-term consequence between UL MI and the resulting lower-limb control.

Less-invasive subdural electrocorticography for investigation of spreading depolarizations in patients with subarachnoid hemorrhage

Introduction

Wyler-strip electrodes for subdural electrocorticography (ECoG) are the gold standard for continuous bed-side monitoring of pathological cortical network events, such as spreading depolarizations (SD) and electrographic seizures. Recently, SD associated parameters were shown to be (1) a marker of early brain damage after aneurysmal subarachnoid hemorrhage (aSAH), (2) the strongest real-time predictor of delayed cerebral ischemia currently known, and (3) the second strongest predictor of patient outcome at 7 months. The strongest predictor of patient outcome at 7 months was focal brain damage segmented on neuroimaging 2 weeks after the initial hemorrhage, whereas the initial focal brain damage was inferior to the SD variables as a predictor for patient outcome. However, the implantation of Wyler-strip electrodes typically requires either a craniotomy or an enlarged burr hole. Neuromonitoring via an enlarged burr hole has been performed in only about 10% of the total patients monitored.

Methods

In the present pilot study, we investigated the feasibility of ECoG monitoring via a less invasive burrhole approach using a Spencer-type electrode array, which was implanted subdurally rather than in the depth of the parenchyma. Seven aSAH patients requiring extraventricular drainage (EVD) were included. For electrode placement, the burr hole over which the EVD was simultaneously placed, was used in all cases. After electrode implantation, continuous, direct current (DC)/alternating current (AC)-ECoG monitoring was performed at bedside in our Neurointensive Care unit. ECoGs were analyzed following the recommendations of the Co-Operative Studies on Brain Injury Depolarizations (COSBID).

Results

Subdural Spencer-type electrode arrays permitted high-quality ECoG recording. During a cumulative monitoring period of 1,194.5 hours and a median monitoring period of 201.3 (interquartile range: 126.1-209.4) hours per patient, 84 SDs were identified. Numbers of SDs, isoelectric SDs and clustered SDs per recording day, and peak total SD-induced depression duration of a recording day were not significantly different from the previously reported results of the prospective, observational, multicenter, cohort, diagnostic phase III trial, DISCHARGE-1. No adverse events related to electrode implantation were noted.

Discussion

In conclusion, our findings support the safety and feasibility of less-invasive subdural electrode implantation for reliable SD-monitoring.

Reliability of visual review of intracranial electroencephalogram in identifying the seizure onset zone: A systematic review and implications for the accuracy of automated methods

Visual review of intracranial electroencephalography (iEEG) is often an essential component for defining the zone of resection for epilepsy surgery. Unsupervised approaches using machine and deep learning are being employed to identify seizure onset zones (SOZs). This prompts a more comprehensive understanding of the reliability of visual review as a reference standard. We sought to summarize existing evidence on the reliability of visual review of iEEG in defining the SOZ for patients undergoing surgical workup and understand its implications for algorithm accuracy for SOZ prediction. We performed a systematic literature review on the reliability of determining the SOZ by visual inspection of iEEG in accordance with best practices. Searches included MEDLINE, Embase, Cochrane Library, and Web of Science on May 8, 2022. We included studies with a quantitative reliability assessment within or between observers. Risk of bias assessment was performed with QUADAS-2. A model was developed to estimate the effect of Cohen kappa on the maximum possible accuracy for any algorithm detecting the SOZ. Two thousand three hundred thirty-eight articles were identified and evaluated, of which one met inclusion criteria. This study assessed reliability between two reviewers for 10 patients with temporal lobe epilepsy and found a kappa of .80. These limited data were used to model the maximum accuracy of automated methods. For a hypothetical algorithm that is 100% accurate to the ground truth, the maximum accuracy modeled with a Cohen kappa of .8 ranged from .60 to .85 (F-2). The reliability of reviewing iEEG to localize the SOZ has been evaluated only in a small sample of patients with methodologic limitations. The ability of any algorithm to estimate the SOZ is notably limited by the reliability of iEEG interpretation. We acknowledge practical limitations of rigorous reliability analysis, and we propose design characteristics and study questions to further investigate reliability.

Enhanced phase-amplitude coupling of human electrocorticography selectively in the posterior cortical region during rapid eye movement sleep

The spatiotemporal dynamics of interaction between slow (delta or infraslow) waves and fast (gamma) activities during wakefulness and sleep are yet to be elucidated in human electrocorticography (ECoG). We evaluated phase-amplitude coupling (PAC), which reflects neuronal coding in information processing, using ECoG in 11 patients with intractable focal epilepsy. PAC was observed between slow waves of 0.5-0.6 Hz and gamma activities, not only during light sleep and slow-wave sleep (SWS) but even during wakefulness and rapid eye movement (REM) sleep. While PAC was high over a large region during SWS, it was stronger in the posterior cortical region around the temporoparietal junction than in the frontal cortical region during REM sleep. PAC tended to be higher in the posterior cortical region than in the frontal cortical region even during wakefulness. Our findings suggest that the posterior cortical region has a functional role in REM sleep and may contribute to the maintenance of the dreaming experience.

Finger movement and coactivation predicted from intracranial brain activity using extended block-term tensor regression

Objective.We introduce extended Block-Term Tensor Regression (eBTTR), a novel regression method designed to account for the multilinear nature of human intracranial finger movement recordings.Approach.The proposed method relies on recursive Tucker decomposition combined with automatic component extraction.Main results.eBTTR outperforms state-of-the-art regression approaches, including multilinear and deep learning ones, in accurately predicting finger trajectories as well as unintentional finger coactivations.Significance.eBTTR rivals state-of-the-art approaches while being less computationally expensive which is an advantage when intracranial electrodes are implanted acutely, as part of the patient's presurgical workup, limiting time for decoder development and testing.

Timing matters: disentangling the neurocognitive sequence of mentalizing

A recent electrocorticographic study by Tan et al. makes an important contribution to understanding the processes involved in mentalizing by adding the temporal dimension to the brain network of mentalizing. Combined with multivariate methods, this approach has the potential to unveil the precise representations underlying mentalizing and their functional interplay.

Can hyperoxic stress cause susceptibility to acute seizure in the neonatal period?: a rat study

Objective: Preterm neonates encounter hyperoxia relatively early, and are more exposed to hyperoxic stress due to their insufficient antioxidant defense mechanisms. This study was planned around the hypothesis that this hyperoxic effect may cause a disposition to future acute seizures. Methods: This study was composed of two main groups Hyperoxy and Control (Room air with normal O2 levels) Groups. Group 1 - hyperoxia (Study): The experimental group consisted of premature newborn rats exposed to hyperoxia with their dams from birth to postnatal day 5. Group 2 - room air (Control): The group was not exposed to hyperoxia and housed the same room air and temperature as their dams. Female, Acute Epilepsy Female, Male, Acute Epilepsy Male, and a total of eight subgroups were formed in both the control and hyperoxia groups. When the rats were two months old, intracranial electrodes were attached to obtain electrocorticography (ECoG) recordings. Pre-model recordings were taken, after which an acute pentylenetetrazole (PTZ) model of absence seizure was induced by the intraperitoneal administration of PTZ at 50 mg/kg. ECoG records were examined using the PowerLab system for 180 min. Spike wave number and duration, Spike wave frequency and amplitude data were evaluated.Results: Seven female and three male rats were exposed to hyperoxia, and a control group of five female and three male rats were included in the study. The median interquartile range for spike wave latency in the hyperoxia and control groups were 1112 (644-1545) and 654 (408-1152), frequency 4476 (3120-7421) and 3934 (2264-4704), and amplitude data 0.68 (0.59-0.79) and 0.52 (0.37-0.67), respectively. Although a difference was observed in median values capable of constituting susceptibility to epilepsy, the difference was not statistically significant (p > 0.05). In terms of gender, spike-wave counts were significantly higher in female rats (p < 0.05). Females exposed to hyperoxia were more susceptible to epilepsy than both males and females in the control group (p < 0.05).Conclusion: Exposure to hyperoxia in the first days of life of premature neonates due to their susceptibility to oxidative stress and insufficient antioxidant mechanisms, can cause a disposition to acute seizures. As a result, females exposed to hyperoxia during the neonatal period may be prone to epilepsy in maturity.

Towards predicting ECoG-BCI performance: assessing the potential of scalp-EEG. J Neural Eng 2022;19:046045. [PMID: 35931055 DOI: 10.1088/1741-2552/ac8764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Objective. Implanted brain-computer interfaces (BCIs) employ neural signals to control a computer and may offer an alternative communication channel for people with locked-in syndrome (LIS). Promising results have been obtained using signals from the sensorimotor (SM) area. However, in earlier work on home-use of an electrocorticography (ECoG)-based BCI by people with LIS, we detected differences in ECoG-BCI performance, which were related to differences in the modulation of low frequency band (LFB) power in the SM area. For future clinical implementation of ECoG-BCIs, it will be crucial to determine whether reliable performance can be predicted before electrode implantation. To assess if non-invasive scalp-electroencephalography (EEG) could serve such prediction, we here investigated if EEG can detect the characteristics observed in the LFB modulation of ECoG signals.Approach. We included three participants with LIS of the earlier study, and a control group of 20 healthy participants. All participants performed a Rest task, and a Movement task involving actual (healthy) or attempted (LIS) hand movements, while their EEG signals were recorded.Main results.Data of the Rest task was used to determine signal-to-noise ratio, which showed a similar range for LIS and healthy participants. Using data of the Movement task, we selected seven EEG electrodes that showed a consistent movement-related decrease in beta power (13-30 Hz) across healthy participants. Within the EEG recordings of this subset of electrodes of two LIS participants, we recognized the phenomena reported earlier for the LFB in their ECoG recordings. Specifically, strong movement-related beta band suppression was observed in one, but not the other, LIS participant, and movement-related alpha band (8-12 Hz) suppression was practically absent in both. Results of the third LIS participant were inconclusive due to technical issues with the EEG recordings.Significance. Together, these findings support a potential role for scalp EEG in the presurgical assessment of ECoG-BCI candidates.

Passive localization of the central sulcus during sleep based on intracranial EEG

We test the performance of a novel operator-independent EEG-based method for passive identification of the central sulcus (CS) and sensorimotor (SM) cortex. We studied seven patients with intractable epilepsy undergoing intracranial EEG (icEEG) monitoring, in whom CS localization was accomplished by standard methods. Our innovative approach takes advantage of intrinsic properties of the primary motor cortex (MC), which exhibits enhanced icEEG band-power and coherence across the CS. For each contact, we computed a composite power, coherence, and entropy values for activity in the high gamma band (80-115) Hz of 6-10 min of NREM sleep. Statistically transformed EEG data values that did not reach a threshold (th) were set to 0. We computed a metric M based on the transformed values and the mean Euclidian distance of each contact from contacts with Z-scores higher than 0. The last step was implemented to accentuate local network activity. The SM cortex exhibited higher EEG-band-power than non-SM cortex (P < 0.0002). There was no significant difference between the motor/premotor and sensory cortices (P < 0.47). CS was localized in all patients with 0.4 < th < 0.6. The primary hand and leg motor areas showed the highest metric values followed by the tongue motor area. Higher threshold values were specific (94%) for the anterior bank of the CS but not sensitive (42%). Intermediate threshold values achieved an acceptable trade-off (0.4: 89% specific and 70% sensitive).

Stability and Effect of Parkinsonian State on Deep Brain Stimulation Cortical Evoked Potentials

OBJECTIVES

To characterize and compare the stability of cortical potentials evoked by deep brain stimulation (DBS) of the subthalamic nucleus (STN) across the naïve, parkinsonian, and pharmacologically treated parkinsonian states. To advance cortical potentials as possible biomarkers for DBS programming.

MATERIALS AND METHODS

Serial electrocorticographic (ECoG) recordings were made more than nine months from a single non-human primate instrumented with bilateral ECoG grids spanning anterior parietal to prefrontal cortex. Cortical evoked potentials (CEPs) were generated through time-lock averaging of the ECoG recordings to DBS pulses delivered unilaterally in the STN region using a chronically implanted, six-contact, scaled DBS lead. Recordings were made across the naïve followed by mild and moderate parkinsonian conditions achieved by staged injections of the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxin. In addition to characterizing the spatial distribution and stability of the response within each state, changes in the amplitude and latency of CEP components as well as in the frequency content were examined in relation to parkinsonian severity and dopamine replacement.

RESULTS

In the naïve state, the STN DBS CEP presented as a multiphase response maximal over M1 cortex, with components attributable to physiological activity distinguishable from stimulus artifact as early as 0.45-0.75 msec poststimulation. When delivered using therapeutically effective parameters in the parkinsonian state, the CEP was highly stable across multiple recording sessions within each behavioral state. Across states, significant differences were present with respect to both the latency and amplitude of individual response components, with greater differences present for longer-latency components (all p < 0.05). Power spectral density analysis revealed a high-beta peak within the evoked response, with significant changes in power between disease states across multiple frequency bands.

CONCLUSIONS

Our findings underscore the spatiotemporal specificity and relative stability of the DBS-CEP associated with different disease states and with therapeutic benefit. DBS-CEP may be a viable biomarker for therapeutic programming.

Normalization of Aperiodic Electrocorticography Components Indicates Fine Motor Recovery After Sensory Cortical Stroke in Mice

BACKGROUND

Electrophysiological signatures of ischemic stroke might help to develop a deeper understanding of the mechanisms of recovery. However, to identify critical windows for novel treatment approaches, suitable readout parameters in vivo with the potential to close the gap between functional modifications within the peri-infarct cortex and behavioral outcome on the systems-level are still lacking.

METHODS

Wild-type mice were trained in a skilled reaching task and underwent permanent distal medial cerebral artery occlusion or sham intervention. Functional deficits and their recovery were monitored both behaviorally and electrophysiologically recording multichannel electrocorticography from both hemispheres.

RESULTS

Ischemic strokes are located in sensory cortical areas. Affected mice presented fine motor deficits of their contralateral forepaw. Analyses of electrocorticography signals from awake animals demonstrated a modulation of the shape of power spectral density in the vicinity of the infarct. While power spectral density consists of both rhythmic oscillatory and nonrhythmic, aperiodic components, the alteration of spectrum shape was reflected in a transient increase of aperiodic exponents in the peri-infarct cortex. The relative power and frequency of slow oscillations remained unchanged. Exponents derived from motor areas significantly correlated with fine motor recovery, thus indicating functional modifications of neuronal activity.

CONCLUSIONS

Aperiodic spectral exponents exhibited a unique spatiotemporal profile in the mouse cortex after stroke and might complement future translational studies providing a dynamic link from pathophysiology to behavior.

Gamma Activation and Alpha Suppression within Human Auditory Cortex during a Speech Classification Task

The dynamics of information flow within the auditory cortical hierarchy associated with speech processing and the emergence of hemispheric specialization remain incompletely understood. To study these questions with high spatiotemporal resolution, intracranial recordings in 29 human neurosurgical patients of both sexes were obtained while subjects performed a semantic classification task. Neural activity was recorded from posteromedial portion of Heschl's gyrus (HGPM) and anterolateral portion of Heschl's gyrus (HGAL), planum temporale (PT), planum polare, insula, and superior temporal gyrus (STG). Responses to monosyllabic words exhibited early gamma power increases and a later suppression of alpha power, envisioned to represent feedforward activity and decreased feedback signaling, respectively. Gamma activation and alpha suppression had distinct magnitude and latency profiles. HGPM and PT had the strongest gamma responses with shortest onset latencies, indicating that they are the earliest auditory cortical processing stages. The origin of attenuated top-down influences in auditory cortex, as indexed by alpha suppression, was in STG and HGAL. Gamma responses and alpha suppression were typically larger to nontarget words than tones. Alpha suppression was uniformly greater to target versus nontarget stimuli. Hemispheric bias for words versus tones and for target versus nontarget words, when present, was left lateralized. Better task performance was associated with increased gamma activity in the left PT and greater alpha suppression in HGPM and HGAL bilaterally. The prominence of alpha suppression during semantic classification and its accessibility for noninvasive electrophysiologic studies suggests that this measure is a promising index of auditory cortical speech processing.SIGNIFICANCE STATEMENT Understanding the dynamics of cortical speech processing requires the use of active tasks. This is the first comprehensive intracranial electroencephalography study to examine cortical activity within the superior temporal plane, lateral superior temporal gyrus, and the insula during a semantic classification task. Distinct gamma activation and alpha suppression profiles clarify the functional organization of feedforward and feedback processing within the auditory cortical hierarchy. Asymmetries in cortical speech processing emerge at early processing stages. Relationships between cortical activity and task performance are interpreted in the context of current models of speech processing. Results lay the groundwork for iEEG studies using connectivity measures of the bidirectional information flow within the auditory processing hierarchy.

Simultaneous mnemonic and predictive representations in the auditory cortex

Recent studies have shown that stimulus history can be decoded via the use of broadband sensory impulses to reactivate mnemonic representations.^1-4. However, memories of previous stimuli can also be used to form sensory predictions about upcoming stimuli.^5,6 Predictive mechanisms allow the brain to create a probable model of the outside world, which can be updated when errors are detected between the model predictions and external inputs. ^7-10 Direct recordings in the auditory cortex of awake mice established neural mechanisms for how encoding mechanisms might handle working memory and predictive processes without "overwriting" recent sensory events in instances where predictive mechanisms are triggered by oddballs within a sequence.¹¹ However, it remains unclear whether mnemonic and predictive information can be decoded from cortical activity simultaneously during passive, implicit sequence processing, even in anesthetized models. Here, we recorded neural activity elicited by repeated stimulus sequences using electrocorticography (ECoG) in the auditory cortex of anesthetized rats, where events within the sequence (referred to henceforth as "vowels," for simplicity) were occasionally replaced with a broadband noise burst or omitted entirely. We show that both stimulus history and predicted stimuli can be decoded from neural responses to broadband impulses, at overlapping latencies but based on independent and uncorrelated data features. We also demonstrate that predictive representations are dynamically updated over the course of stimulation.

Pre- and Post-surgical Poor Seizure Control as Hallmark of Malignant Progression in Patients With Glioma?

Background

Regarding brain tumor-related epilepsy (BTRE), there is an increasing number of evidence about a relationship between epileptogenesis and oncogenesis. A recent study suggests a role of post-surgery seizure outcome on the survival of patients with low-grade glioma (LGG), underlying the need for a targeted and aggressive epilepsy treatment.

Objective

This study aims at investigating the possible correlation between pre- and post-surgical seizure control and tumor progression in patients who underwent surgery for LGG.

Methods

We performed a retrospective analysis of patients affected by LGGs and BTRE, in a single high-volume neurosurgical center. Seizure control was assessed before surgery and at 3 years of follow-up. Patients with histological progression in high-grade glioma (HGG) have been evaluated. Clinical features, pre-surgical electroencephalograms (EEGs), and electrocorticography (ECoG) have been analyzed.

Results

Among 154 subjects, we collected 32 patients who presented a tumor progression in HGG during the follow-up period. The majority had poor seizure control both pre- and post-surgery, never being in Engel class Ia throughout the whole history of their disease. Almost all patients with poor seizure control had pathological ECoG recording. Clinical features of seizures did not correlate with seizure outcome. On the univariate analysis, the age, the post-operative Engel class, and the extent of resection (EOR) were the prognostic factors significantly associated with oncological outcome; nevertheless, on multivariate analysis, Engel class significance was not confirmed, and the only predicting factor were age and EOR.

Conclusions

Although not confirmed on multivariate analysis, post-surgical seizure control could be a relevant factor to consider during follow-up of BRTE, in particular, when gross total resection is not achieved. Pathological findings on the ECoG may suggest a “hidden” propensity to malignant progression, strictly related to the persistent neuronal hyper-excitability. Further studies with longer follow-up period are needed to confirm our observations.

Cortical Complexity and Connectivity during Isoflurane-induced General Anesthesia: A Rat Study

OBJECTIVE

The investigation of neurophysiologic mechanisms of anesthetic drug-induced loss of consciousness (LOC) by using the entropy, complexity, and information integration theories at the mesoscopic level has been a hot topic in recent years. However, systematic research is still lacking.

APPROACH

We analyzed electrocorticography (ECoG) data recorded from nine rats during isoflurane-induced unconsciousness. To characterize the complexity and connectivity changes, we investigated ECoG power, symbolic dynamic-based entropy (i.e., permutation entropy (PE)), complexity (i.e., permutation Lempel-Ziv complexity (PLZC)), information integration (i.e., permutation cross mutual information (PCMI)), and PCMI-based cortical brain networks in the frontal, parietal, and occipital cortical regions.

MAIN RESULTS

Firstly, LOC was accompanied by a raised power in the ECoG beta (12-30 Hz) but a decreased power in the high gamma (55-95 Hz) frequency band in all three brain regions. Secondly, PE and PLZC showed similar change trends in the lower frequency band (0.1-45 Hz), declining after LOC (p<0.05) and increasing after recovery of consciousness (p<0.001). Thirdly, intra-frontal and inter-frontal-parietal PCMI declined after LOC, in both lower (0.1-45Hz) and higher frequency bands (55-95Hz) (p<0.001). Finally, the local network parameters of the nodal clustering coefficient and nodal efficiency in the frontal region decreased after LOC, in both the lower and higher frequency bands (p<0.05). Moreover, global network parameters of the normalized average clustering coefficient and small world index increased slightly after LOC in the lower frequency band. However, this increase was not statistically significant.

SIGNIFICANCE

The PE, PLZC, PCMI and PCMI-based brain networks are effective metrics for qualifying the effects of isoflurane.