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Glioblastoma is a clinically and molecularly heterogeneous disease, and new predictive biomarkers are needed to identify those patients most likely to respond to specific treatments. Through prospective genomic profiling of 459 consecutive primary treatment-naïve IDH-wildtype glioblastomas in adults, we identified a unique subgroup (2%, 9/459) defined by somatic hypermutation and DNA replication repair deficiency due to biallelic inactivation of a canonical mismatch repair gene. The deleterious mutations in mismatch repair genes were often present in the germline in the heterozygous state with somatic inactivation of the remaining allele, consistent with glioblastomas arising due to underlying Lynch syndrome. A subset of tumors had accompanying proofreading domain mutations in the DNA polymerase POLE and resultant "ultrahypermutation". The median age at diagnosis was 50 years (range 27-78), compared with 63 years for the other 450 patients with conventional glioblastoma (p

The amplitude envelope of speech is crucial for accurate comprehension. Considered a key stage in speech processing, the phase of neural activity in the theta-delta bands (1-10 Hz) tracks the phase of the speech amplitude envelope during listening. However, the mechanisms underlying this envelope representation have been heavily debated. A dominant model posits that envelope tracking reflects entrainment of endogenous low-frequency oscillations to the speech envelope. Alternatively, envelope tracking reflects a series of evoked responses to acoustic landmarks within the envelope. It has proven challenging to distinguish these two mechanisms. To address this, we recorded MEG while participants (n = 12, 6 female) listened to natural speech, and compared the neural phase patterns to the predictions of two computational models: an oscillatory entrainment model and a model of evoked responses to peaks in the rate of envelope change. Critically, we also presented speech at slowed rates, where the spectro-temporal predictions of the two models diverge. Our analyses revealed transient theta phase-locking in regular speech, as predicted by both models. However, for slow speech, we found transient theta and delta phase-locking, a pattern that was fully compatible with the evoked response model but could not be explained by the oscillatory entrainment model. Furthermore, encoding of acoustic edge magnitudes was invariant to contextual speech rate, demonstrating speech rate normalization of acoustic edge representations. Together, our results suggest that neural phase-locking to the speech envelope is more likely to reflect discrete representation of transient information rather than oscillatory entrainment.SIGNIFICANCE STATEMENT This study probes a highly debated topic in speech perception: the neural mechanisms underlying the cortical representation of the temporal envelope of speech. It is well established that the slow intensity profile of the speech signal, its envelope, elicits a robust brain response that "tracks" these envelope fluctuations. The oscillatory entrainment model posits that envelope tracking reflects phase alignment of endogenous neural oscillations. Here the authors provide evidence for a distinct mechanism. They show that neural speech envelope tracking arises from transient evoked neural responses to rapid increases in the speech envelope. Explicit computational modeling provides direct and compelling evidence that evoked responses are the primary mechanism underlying cortical speech envelope representations, with no evidence for oscillatory entrainment.

ObjectiveElectrocortical stimulation mapping (ECS) is widely used to identify essential language areas, but sentence-level processing has rarely been investigated.MethodsWhile undergoing awake surgery in the dominant left hemisphere, 6 subjects were asked to comprehend sentences varying in their demands on syntactic processing.ResultsIn all 6 subjects, stimulation of the inferior frontal gyrus disrupted comprehension of passive sentences, which critically depend on syntactic processing to correctly assign grammatical roles, without disrupting comprehension of simpler tasks. In 4 of the 6 subjects, these sites were localized to the pars opercularis. Sentence comprehension was also disrupted by stimulation of other perisylvian sites, but in a more variable manner.ConclusionsThese findings suggest that there may be language regions that differentially contribute to sentence processing and which therefore are best identified using sentence-level tasks. The functional consequences of resecting these sites remain to be investigated.

PurposeIn patients with diffuse low-grade glioma (LGG), the extent of surgical tumor resection (EOR) has a controversial role, in part because a randomized clinical trial with different levels of EOR is not feasible.MethodsIn a 20-year retrospective cohort of 392 patients with IDH-mutant grade 2 glioma, we analyzed the combined effects of volumetric EOR and molecular and clinical factors on overall survival (OS) and progression-free survival by recursive partitioning analysis. The OS results were validated in two external cohorts (n = 365). Propensity score analysis of the combined cohorts (n = 757) was used to mimic a randomized clinical trial with varying levels of EOR.ResultsRecursive partitioning analysis identified three survival risk groups. Median OS was shortest in two subsets of patients with astrocytoma: those with postoperative tumor volume (TV) > 4.6 mL and those with preoperative TV > 43.1 mL and postoperative TV ≤ 4.6 mL. Intermediate OS was seen in patients with astrocytoma who had chemotherapy with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL in addition to oligodendroglioma patients with either preoperative TV > 43.1 mL and residual TV ≤ 4.6 mL or postoperative residual volume > 4.6 mL. Longest OS was seen in astrocytoma patients with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL who received no chemotherapy and oligodendroglioma patients with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL. EOR ≥ 75% improved survival outcomes, as shown by propensity score analysis.ConclusionAcross both subtypes of LGG, EOR beginning at 75% improves OS while beginning at 80% improves progression-free survival. Nonetheless, maximal resection with preservation of neurological function remains the treatment goal. Our findings have implications for surgical strategies for LGGs, particularly oligodendroglioma.

BackgroundWhile genetic alterations in brain metastases (BMs) have been previously explored, there are limited data examining their association with recurrence after surgical resection. This study aimed to identify genetic alterations within BMs associated with CNS recurrence after surgery across multiple cancer types.MethodsA retrospective, single-center study was conducted with patients who underwent resection of a BM with available clinical and gene sequencing data available. Local and remote CNS recurrence were the primary study outcomes. Next-generation sequencing of the coding regions in over 500 oncogenes was performed in brain metastasis specimens. Cox proportional hazards analyses were performed to identify clinical features and genomic alterations associated with CNS recurrence.ResultsA total of 90 patients undergoing resection of 91 BMs composed the cohort. Genes most frequently mutated in the cohort included TP53 (64%), CDKN2A (37%), TERT (29%), CDKN2B (23%), NF1 (14%), KRAS (14%), and PTEN (13%), all of which occurred across multiple cancer types. CDKN2A/B co-deletion was seen in 21 (23.1%) brain metastases across multiple cancer types. In multivariate Cox proportional hazard analyses including patient, tumor, and treatment factors, CDKN2A/B co-deletion in the brain metastasis was associated with increased risk of local (HR 4.07, 95% CI 1.32-12.54, P = 0.014) and remote (HR 2.28, 95% CI 1.11-4.69, P = 0.025) CNS progression. Median survival and length of follow-up were not different based on CDKN2A/B mutation status.ConclusionsCDKN2A/B co-deletion detected in BMs is associated with increased CNS recurrence after surgical resection. Additional work is needed to determine whether more aggressive treatment in patients with this mutation may improve outcomes.

Background and objectivesWhile somatic mutations have been well-studied in cancer, their roles in other complex traits are much less understood. Our goal is to identify somatic variants that may contribute to the formation of saccular cerebral aneurysms.MethodsWe performed whole-exome sequencing on aneurysm tissues and paired peripheral blood. RNA sequencing and the CRISPR/Cas9 system were then used to perform functional validation of our results.ResultsSomatic variants involved in supervillin (SVIL) or its regulation were found in 17% of aneurysm tissues. In the presence of a mutation in the SVIL gene, the expression level of SVIL was downregulated in the aneurysm tissue compared with normal control vessels. Downstream signaling pathways that were induced by knockdown of SVIL via the CRISPR/Cas9 system in vascular smooth muscle cells (vSMCs) were determined by evaluating changes in gene expression and protein kinase phosphorylation. We found that SVIL regulated the phenotypic modulation of vSMCs to the synthetic phenotype via Krüppel-like factor 4 and platelet-derived growth factor and affected cell migration of vSMCs via the RhoA/ROCK pathway.DiscussionWe propose that somatic variants form a novel mechanism for the development of cerebral aneurysms. Specifically, somatic variants in SVIL result in the phenotypic modulation of vSMCs, which increases the susceptibility to aneurysm formation. This finding suggests a new avenue for the therapeutic intervention and prevention of cerebral aneurysms.

Classical models have traditionally focused on the left posterior inferior frontal gyrus (Broca's area) as a key region for motor planning of speech production. However, converging evidence suggests that it is not critical for either speech motor planning or execution. Alternative cortical areas supporting high-level speech motor planning have yet to be defined. In this review, we focus on the precentral gyrus, whose role in speech production is often thought to be limited to lower-level articulatory muscle control. In particular, we highlight neurosurgical investigations that have shed light on a cortical region anatomically located near the midpoint of the precentral gyrus, hence called the middle precentral gyrus (midPrCG). The midPrCG is functionally located between dorsal hand and ventral orofacial cortical representations and exhibits unique sensorimotor and multisensory functions relevant for speech processing. This includes motor control of the larynx, auditory processing, as well as a role in reading and writing. Furthermore, direct electrical stimulation of midPrCG can evoke complex movements, such as vocalization, and selective injury can cause deficits in verbal fluency, such as pure apraxia of speech. Based on these findings, we propose that midPrCG is essential to phonological-motoric aspects of speech production, especially syllabic-level speech sequencing, a role traditionally ascribed to Broca's area. The midPrCG is a cortical brain area that should be included in contemporary models of speech production with a unique role in speech motor planning and execution.

BackgroundGenomic profiling studies of diffuse gliomas have led to new improved classification schemes that better predict patient outcomes compared to conventional histomorphology alone. One example is the recognition that patients with IDH-wildtype diffuse astrocytic gliomas demonstrating lower-grade histologic features but genomic and/or epigenomic profile characteristic of glioblastoma typically have poor outcomes similar to patients with histologically diagnosed glioblastoma. Here we sought to determine the clinical impact of prospective genomic profiling for these IDH-wildtype diffuse astrocytic gliomas lacking high-grade histologic features but with molecular profile of glioblastoma.MethodsClinical management and outcomes were analyzed for 38 consecutive adult patients with IDH-wildtype diffuse astrocytic gliomas lacking necrosis or microvascular proliferation on histologic examination that were genomically profiled on a prospective clinical basis revealing criteria for an integrated diagnosis of "diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV" per cIMPACT-NOW criteria.ResultsWe identified that this diagnosis consists of two divergent clinical scenarios based on integration of radiologic, histologic, and genomic features that we term "early/evolving" and "undersampled" glioblastoma, IDH-wildtype. We found that prospective genomically guided identification of early/evolving and undersampled IDH-wildtype glioblastoma resulted in more aggressive patient management and improved clinical outcomes compared to a biologically matched historical control patient cohort receiving standard-of-care therapy based on histomorphologic diagnosis alone.ConclusionsThese results support routine use of genomic and/or epigenomic profiling to accurately classify glial neoplasms, as these assays not only improve diagnostic classification but critically lead to more appropriate patient management that can improve clinical outcomes.

ObjectiveInterfacility transfers represent a large proportion of neurosurgical admissions to tertiary care centers each year. In this study, the authors examined the impact of the COVID-19 pandemic on the number of transfers, timing of transfers, demographic profile of transfer patients, and clinical outcomes including rates of surgical intervention.MethodsA retrospective review of neurosurgical transfer patients at a single tertiary center was performed. Patients transferred from April to November 2020 (the "COVID Era") were compared with an institutional database of transfer patients collected before the COVID-19 pandemic (the "Pre-COVID Era"). During the COVID Era, both emergent and nonemergent neurosurgical services had resumed. A comparison of demographic and clinical factors between the 2 cohorts was performed.ResultsA total of 674 patients were included in the study (331 Pre-COVID and 343 COVID-Era patients). Overall, there was no change in the average monthly number of transfers (P = 0.66) or in the catchment area of referral hospitals. However, COVID-Era patients were more likely to be uninsured (1% vs. 4%), had longer transfer times (COVID vs. Pre-COVID Era: 18 vs. 9 hours; P < 0.001), required higher rates of surgical intervention (63% vs. 50%, P = 0.001), had higher rates of spine pathology (17% vs. 10%), and less frequently were admitted to the intensive care unit (34% vs. 52%, P < 0.001). Overall, COVID-Era patients did not experience delays to surgical intervention (3.1 days vs. 3.6 days, P = 0.2). When analyzing the subgroup of COVID-Era patients, COVID infection status did not impact the time of transfer or rates of operation, although COVID-infected patients experienced a longer time to surgery after admission (14 vs. 2.9 days, P < 0.001).ConclusionThe COVID-19 pandemic did not reduce the number of monthly transfers, operation rates, or catchment area for transfer patients. Transfer rates of uninsured patients increased during the COVID Era, potentially reflecting changes in access to community neurosurgery care. Shorter time to surgery seen in COVID-Era patients possibly reflects institutional policies that improved operating room efficiency to compensate for surgical backlogs. COVID status affeted time to surgery, reflecting the preoperative care that these patients require before intervention.

Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (

ObjectiveDespite the overall success of responsive neurostimulation (RNS) therapy for drug-resistant focal epilepsy, clinical outcomes in individuals vary significantly and are hard to predict. Biomarkers that indicate the clinical efficacy of RNS-ideally before device implantation-are critically needed, but challenges include the intrinsic heterogeneity of the RNS patient population and variability in clinical management across epilepsy centers. The aim of this study is to use a multicenter dataset to evaluate a candidate biomarker from intracranial electroencephalographic (iEEG) recordings that predicts clinical outcome with subsequent RNS therapy.MethodsWe assembled a federated dataset of iEEG recordings, collected prior to RNS implantation, from a retrospective cohort of 30 patients across three major epilepsy centers. Using ictal iEEG recordings, each center independently calculated network synchronizability, a candidate biomarker indicating the susceptibility of epileptic brain networks to RNS therapy.ResultsIctal measures of synchronizability in the high-γ band (95-105 Hz) significantly distinguish between good and poor RNS responders after at least 3 years of therapy under the current RNS therapy guidelines (area under the curve = .83). Additionally, ictal high-γ synchronizability is inversely associated with the degree of therapeutic response.SignificanceThis study provides a proof-of-concept roadmap for collaborative biomarker evaluation in federated data, where practical considerations impede full data sharing across centers. Our results suggest that network synchronizability can help predict therapeutic response to RNS therapy. With further validation, this biomarker could facilitate patient selection and help avert a costly, invasive intervention in patients who are unlikely to benefit.

Neurophysiological studies in humans and nonhuman primates have revealed movement representations in both the contralateral and ipsilateral hemispheres. Inspired by clinical observations, we ask if this bilateral representation differs for the left and right hemispheres. Electrocorticography was recorded in human participants during an instructed-delay reaching task, with movements produced with either the contralateral or ipsilateral arm. Using a cross-validated kinematic encoding model, we found stronger bilateral encoding in the left hemisphere, an effect that was present during preparation and was amplified during execution. Consistent with this asymmetry, we also observed better across-arm generalization in the left hemisphere, indicating similar neural representations for right and left arm movements. Notably, these left hemisphere electrodes were centered over premotor and parietal regions. The more extensive bilateral encoding in the left hemisphere adds a new perspective to the pervasive neuropsychological finding that the left hemisphere plays a dominant role in praxis.

ObjectiveImpairments of speech are common in patients with glioma and negatively impact health-related quality of life (HRQoL). The benchmark for clinical assessments is task-based measures, which are not always feasible to administer and may miss essential components of HRQoL. In this study, the authors tested the hypothesis that variations in natural language (NL) correlate with HRQoL in a pattern distinct from task-based measures of language performance.MethodsNL use was assessed using audio samples collected unobtrusively from 18 patients with newly diagnosed low- and high-grade glioma. NL measures were calculated using manual segmentation and correlated with Quality of Life in Neurological Disorders (Neuro-QoL) outcomes. Spearman's rank-order correlation was used to determine relationships between Neuro-QoL scores and NL measures.ResultsThe distribution of NL measures across the entire patient cohort included a mean ± SD total time speaking of 11.5 ± 2.20 seconds, total number of words of 27.2 ± 4.44, number of function words of 10.9 ± 1.68, number of content words of 16.3 ± 2.91, and speech rate of 2.61 ± 0.20 words/second. Speech rate was negatively correlated with functional domains (rho = -0.62 and p = 0.007 for satisfaction with social roles; rho = -0.74 and p < 0.001 for participation in social roles) but positively correlated with impairment domains (rho = 0.58 and p = 0.009 for fatigue) of Neuro-QoL.ConclusionsAssessment of NL at the time of diagnosis may be a useful measure in the context of treatment planning and monitoring outcomes for adult patients with glioma.

Human speech perception results from neural computations that transform external acoustic speech signals into internal representations of words. The superior temporal gyrus (STG) contains the nonprimary auditory cortex and is a critical locus for phonological processing. Here, we describe how speech sound representation in the STG relies on fundamentally nonlinear and dynamical processes, such as categorization, normalization, contextual restoration, and the extraction of temporal structure. A spatial mosaic of local cortical sites on the STG exhibits complex auditory encoding for distinct acoustic-phonetic and prosodic features. We propose that as a population ensemble, these distributed patterns of neural activity give rise to abstract, higher-order phonemic and syllabic representations that support speech perception. This review presents a multi-scale, recurrent model of phonological processing in the STG, highlighting the critical interface between auditory and language systems.

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements.

Leveraging firsthand experience, BRAIN-funded investigators conducting intracranial human neuroscience research propose two fundamental ethical commitments: (1) maintaining the integrity of clinical care and (2) ensuring voluntariness. Principles, practices, and uncertainties related to these commitments are offered for future investigation.

Recent developments in the biology of malignant gliomas have demonstrated that glioma cells interact with neurons through both paracrine signaling and electrochemical synapses. Glioma-neuron interactions consequently modulate the excitability of local neuronal circuits, and it is unclear the extent to which glioma-infiltrated cortex can meaningfully participate in neural computations. For example, gliomas may result in a local disorganization of activity that impedes the transient synchronization of neural oscillations. Alternatively, glioma-infiltrated cortex may retain the ability to engage in synchronized activity in a manner similar to normal-appearing cortex but exhibit other altered spatiotemporal patterns of activity with subsequent impact on cognitive processing. Here, we use subdural electrocorticography to sample both normal-appearing and glioma-infiltrated cortex during speech. We find that glioma-infiltrated cortex engages in synchronous activity during task performance in a manner similar to normal-appearing cortex but recruits a diffuse spatial network. On a temporal scale, we show that signals from glioma-infiltrated cortex have decreased entropy, which may affect its ability to encode information during nuanced tasks such as production of monosyllabic versus polysyllabic words. Furthermore, we show that temporal decoding strategies for distinguishing monosyllabic from polysyllabic words were feasible for signals arising from normal-appearing cortex but not from glioma-infiltrated cortex. These findings inform our understanding of cognitive processing in chronic disease states and have implications for neuromodulation and prosthetics in patients with malignant gliomas.

There has been a growing interest in improving the informed consent process to ensure patients truly understand the benefits, risks, and alternatives of their procedures. Herein, we sought to describe the production of an educational video to supplement the traditional rhinoplasty informed consent process. Additionally, we evaluate satisfaction and risk recall among prospective rhinoplasty patients who participated in the video-assisted informed consent process. One author attended 30 rhinoplasty consultations where informed consent was performed and generated 65 questions related to the benefits, risks, alternatives, and general knowledge of rhinoplasty operations. A video of the senior author answering these questions was filmed and edited to 25 minutes. Prospective rhinoplasty patients watched the video before their initial consultation and were asked to complete two surveys assessing their satisfaction with the video-assisted process as well as their ability to recall risks discussed in the video. Understandability and actionability of the video was assessed by three independent reviewers using the Patient Education Materials Assessment Tool. Postvideo surveys were completed by 40 patients. Patients strongly agreed that the video informed them about rhinoplasty risks and benefits (4.90/5.00), effectively answered their questions and/or concerns (4.78/5.00), and provided adequate information before surgery (4.85/5.00). Participants strongly recommended that all prospective patients watch the video prior to surgery (4.97/5.00). Participants on average correctly answered 4.00 ± 0.877 out of five risk recall questions. There was no statistically significant difference in risk recall performance between college graduates (4.19 ± 0.602) and those who did not graduate college (3.79 ± 1.08), p = 0.076. No significant correlation was found between patient age and recall performance (r = -0.011), p = 0.943. The overall mean understandability and actionability scores for the video were 100%. Video-assisted informed consent for rhinoplasty may enhance and overcome limitations to the traditional verbal consent process by ensuring comprehensive, standardized, and readily understandable information.

Adults can learn to identify nonnative speech sounds with training, albeit with substantial variability in learning behavior. Increases in behavioral accuracy are associated with increased separability for sound representations in cortical speech areas. However, it remains unclear whether individual auditory neural populations all show the same types of changes with learning, or whether there are heterogeneous encoding patterns. Here, we used high-resolution direct neural recordings to examine local population response patterns, while native English listeners learned to recognize unfamiliar vocal pitch patterns in Mandarin Chinese tones. We found a distributed set of neural populations in bilateral superior temporal gyrus and ventrolateral frontal cortex, where the encoding of Mandarin tones changed throughout training as a function of trial-by-trial accuracy ("learning effect"), including both increases and decreases in the separability of tones. These populations were distinct from populations that showed changes as a function of exposure to the stimuli regardless of trial-by-trial accuracy. These learning effects were driven in part by more variable neural responses to repeated presentations of acoustically identical stimuli. Finally, learning effects could be predicted from speech-evoked activity even before training, suggesting that intrinsic properties of these populations make them amenable to behavior-related changes. Together, these results demonstrate that nonnative speech sound learning involves a wide array of changes in neural representations across a distributed set of brain regions.

BackgroundTechnology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of such patients may represent an advancement over existing methods for assisted communication.MethodsWe implanted a subdural, high-density, multielectrode array over the area of the sensorimotor cortex that controls speech in a person with anarthria (the loss of the ability to articulate speech) and spastic quadriparesis caused by a brain-stem stroke. Over the course of 48 sessions, we recorded 22 hours of cortical activity while the participant attempted to say individual words from a vocabulary set of 50 words. We used deep-learning algorithms to create computational models for the detection and classification of words from patterns in the recorded cortical activity. We applied these computational models, as well as a natural-language model that yielded next-word probabilities given the preceding words in a sequence, to decode full sentences as the participant attempted to say them.ResultsWe decoded sentences from the participant's cortical activity in real time at a median rate of 15.2 words per minute, with a median word error rate of 25.6%. In post hoc analyses, we detected 98% of the attempts by the participant to produce individual words, and we classified words with 47.1% accuracy using cortical signals that were stable throughout the 81-week study period.ConclusionsIn a person with anarthria and spastic quadriparesis caused by a brain-stem stroke, words and sentences were decoded directly from cortical activity during attempted speech with the use of deep-learning models and a natural-language model. (Funded by Facebook and others; ClinicalTrials.gov number, NCT03698149.).

ObjectiveIntracranial electroencephalography (ICEEG) recordings are performed for seizure localization in medically refractory epilepsy. Signal quantifications such as frequency power can be projected as heatmaps on personalized three-dimensional (3D) reconstructed cortical surfaces to distill these complex recordings into intuitive cinematic visualizations. However, simultaneously reconciling deep recording locations and reliably tracking evolving ictal patterns remain significant challenges.MethodsWe fused oblique magnetic resonance imaging (MRI) slices along depth probe trajectories with cortical surface reconstructions and projected dynamic heatmaps using a simple mathematical metric of epileptiform activity (line-length). This omni-planar and surface casting of epileptiform activity approach (OPSCEA) thus illustrated seizure onset and spread among both deep and superficial locations simultaneously with minimal need for signal processing supervision. We utilized the approach on 41 patients at our center implanted with grid, strip, and/or depth electrodes for localizing medically refractory seizures. Peri-ictal data were converted into OPSCEA videos with multiple 3D brain views illustrating all electrode locations. Five people of varying expertise in epilepsy (medical student through epilepsy attending level) attempted to localize the seizure-onset zones.ResultsWe retrospectively compared this approach with the original ICEEG study reports for validation. Accuracy ranged from 73.2% to 97.6% for complete or overlapping onset lobe(s), respectively, and ~56.1% to 95.1% for the specific focus (or foci). Higher answer certainty for a given case predicted better accuracy, and scorers had similar accuracy across different training levels.SignificanceIn an era of increasing stereo-EEG use, cinematic visualizations fusing omni-planar and surface functional projections appear to provide a useful adjunct for interpreting complex intracranial recordings and subsequent surgery planning.

Deep brain stimulation is a promising treatment for severe depression, but lack of efficacy in randomized trials raises questions regarding anatomical targeting. We implanted multi-site intracranial electrodes in a severely depressed patient and systematically assessed the acute response to focal electrical neuromodulation. We found an elaborate repertoire of distinctive emotional responses that were rapid in onset, reproducible, and context and state dependent. Results provide proof of concept for personalized, circuit-specific medicine in psychiatry.

Vision is the primary sense humans use to evaluate and respond to threats. Understanding the biological underpinnings of the human threat response has been hindered by lack of realistic in-lab threat paradigms. We established an immersive virtual reality (VR) platform to simultaneously measure behavior, physiological state, and neural activity from the human brain using chronically implanted electrodes. Subjects with high anxiety showed increased visual scanning in response to threats as compared to healthy controls. In both healthy and anxious subjects, the amount of scanning behavior correlated with the magnitude of physiological arousal, suggesting that visual scanning behavior is directly linked to internal state. Intracranial electroencephalography (iEEG) recordings from three subjects suggested that high-frequency gamma activity in the insula positively correlates with physiological arousal induced by visual threats and that low-frequency theta activity in the orbitofrontal cortex (OFC) negatively correlates with physiological arousal induced by visual threats. These findings reveal a key role of eye movements and suggest that distinct insula and OFC activation dynamics may be important for detecting and adjusting human stress in response to visually perceived threats.

Closed-loop neurostimulation is a promising therapy being tested and clinically implemented in a growing number of neurological and psychiatric indications. This therapy is enabled by chronically implanted, bidirectional devices including the Medtronic Summit RC+S system. In order to successfully optimize therapy for patients implanted with these devices, analyses must be conducted offline on the recorded neural data, in order to inform optimal sense and stimulation parameters. The file format, volume, and complexity of raw data from these devices necessitate conversion, parsing, and time reconstruction ahead of time-frequency analyses and modeling common to standard neuroscientific analyses. Here, we provide an open-source toolbox written in Matlab which takes raw files from the Summit RC+S and transforms these data into a standardized format amenable to conventional analyses. Furthermore, we provide a plotting tool which can aid in the visualization of multiple data streams and sense, stimulation, and therapy settings. Finally, we describe an analysis module which replicates RC+S on-board power computations, a functionality which can accelerate biomarker discovery. This toolbox aims to accelerate the research and clinical advances made possible by longitudinal neural recordings and adaptive neurostimulation in people with neurological and psychiatric illnesses.

Languages can use a common repertoire of vocal sounds to signify distinct meanings. In tonal languages, such as Mandarin Chinese, pitch contours of syllables distinguish one word from another, whereas in non-tonal languages, such as English, pitch is used to convey intonation. The neural computations underlying language specialization in speech perception are unknown. Here, we use a cross-linguistic approach to address this. Native Mandarin- and English- speaking participants each listened to both Mandarin and English speech, while neural activity was directly recorded from the non-primary auditory cortex. Both groups show language-general coding of speaker-invariant pitch at the single electrode level. At the electrode population level, we find language-specific distribution of cortical tuning parameters in Mandarin speakers only, with enhanced sensitivity to Mandarin tone categories. Our results show that speech perception relies upon a shared cortical auditory feature processing mechanism, which may be tuned to the statistics of a given language.

Vagus nerve stimulation (VNS) is being used increasingly to treat a wide array of diseases and disorders. This growth is driven in part by the putative ability to stimulate the nerve non-invasively. Despite decades of use and a rapidly expanding application space, we lack a complete understanding of the acute effects of VNS on human cortical neurophysiology. Here, we investigated cortical responses to sub-perceptual threshold cervical implanted (iVNS) and transcutaneous auricular (taVNS) vagus nerve stimulation using intracranial neurophysiological recordings in human epilepsy patients. To understand the areas that are modulated by VNS and how they differ depending on invasiveness and stimulation parameters, we compared VNS-evoked neural activity across a range of stimulation modalities, frequencies, and amplitudes. Using comparable stimulation parameters, both iVNS and taVNS caused subtle changes in low-frequency power across broad cortical networks, which were not the same across modalities and were highly variable across participants. However, within at least some individuals, it may be possible to elicit similar responses across modalities using distinct sets of stimulation parameters. These results demonstrate that both invasive and non-invasive VNS cause evoked changes in activity across a set of highly distributed cortical networks that are relevant to a diverse array of clinical, rehabilitative, and enhancement applications.

The anterior cingulate cortex (ACC) has been extensively implicated in the functional brain network underlying chronic pain. Electrical stimulation of the ACC has been proposed as a therapy for refractory chronic pain, although, mechanisms of therapeutic action are still unclear. As stimulation of the ACC has been reported to produce many different behavioral and perceptual responses, this region likely plays a varied role in sensory and emotional integration as well as modulating internally generated perceptual states. In this case series, we report the emergence of subjective musical hallucinations (MH) after electrical stimulation of the ACC in two patients with refractory chronic pain. In an N-of-1 analysis from one patient, we identified neural activity (local field potentials) that distinguish MH from both the non-MH condition and during a task involving music listening. Music hallucinations were associated with reduced alpha band activity and increased gamma band activity in the ACC. Listening to similar music was associated with different changes in ACC alpha and gamma power, extending prior results that internally generated perceptual phenomena are supported by circuits in the ACC. We discuss these findings in the context of phantom perceptual phenomena and posit a framework whereby chronic pain may be interpreted as a persistent internally generated percept.

Objective: Anxiety and depression are prominent non-motor symptoms of Parkinson's disease (PD), but their pathophysiology remains unclear. We sought to understand their neurophysiological correlates from chronic invasive recordings of the prefrontal cortex (PFC). Methods: We studied four patients undergoing deep brain stimulation (DBS) for their motor signs, who had comorbid mild to moderate anxiety and/or depressive symptoms. In addition to their basal ganglia leads, we placed a permanent prefrontal subdural 4-contact lead. These electrodes were attached to an investigational pulse generator with the capability to sense and store field potential signals, as well as deliver therapeutic neurostimulation. At regular intervals over 3-5 months, participants paired brief invasive neural recordings with self-ratings of symptoms related to depression and anxiety. Results: Mean age was 61 ± 7 years, mean disease duration was 11 ± 8 years and a mean Unified Parkinson's Disease Rating Scale, with part III (UPDRS-III) off medication score of 37 ± 13. Mean Beck Depression Inventory (BDI) score was 14 ± 5 and Beck Anxiety Index was 16.5 ± 5. Prefrontal cortex spectral power in the beta band correlated with patient self-ratings of symptoms of depression and anxiety, with r-values between 0.31 and 0.48. Mood scores showed negative correlation with beta spectral power in lateral locations, and positive correlation with beta spectral power in a mesial recording location, consistent with the dichotomous organization of reward networks in PFC. Interpretation: These findings suggest a physiological basis for anxiety and depression in PD, which may be useful in the development of neurostimulation paradigms for these non-motor disease features.

Major depressive disorder is a common and disabling disorder with high rates of treatment resistance. Evidence suggests it is characterized by distributed network dysfunction that may be variable across patients, challenging the identification of quantitative biological substrates. We carried out this study to determine whether application of a novel computational approach to a large sample of high spatiotemporal resolution direct neural recordings in humans could unlock the functional organization and coordinated activity patterns of depression networks. This group level analysis of depression networks from heterogenous intracranial recordings was possible due to application of a correlational model-based method for inferring whole-brain neural activity. We then applied a network framework to discover brain dynamics across this model that could classify depression. We found a highly distributed pattern of neural activity and connectivity across cortical and subcortical structures that was present in the majority of depressed subjects. Furthermore, we found that this depression signature consisted of two subnetworks across individuals. The first was characterized by left temporal lobe hypoconnectivity and pathological beta activity. The second was characterized by a hypoactive, but hyperconnected left frontal cortex. These findings have applications toward personalization of therapy.

ObjectiveTo develop a Dissociative Seizures Likelihood Score (DSLS), which is a comprehensive, evidence-based tool using information available during the first outpatient visit to identify patients with "probable" dissociative seizures (DS) to allow early triage to more extensive diagnostic assessment.MethodsBased on data from 1616 patients with video-electroencephalography (vEEG) confirmed diagnoses, we compared the clinical history from a single neurology interview of patients in five mutually exclusive groups: epileptic seizures (ES), DS, physiologic nonepileptic seizure-like events (PSLE), mixed DS plus ES, and inconclusive monitoring. We used data-driven methods to determine the diagnostic utility of 76 features from retrospective chart review and applied this model to prospective interviews.ResultsThe DSLS using recursive feature elimination (RFE) correctly identified 77% (95% confidence interval (CI), 74-80%) of prospective patients with either ES or DS, with a sensitivity of 74% and specificity of 84%. This accuracy was not significantly inferior than neurologists' impression (84%, 95% CI: 80-88%) and the kappa between neurologists' and the DSLS was 21% (95% CI: 1-41%). Only 3% of patients with DS were missed by both the fellows and our score (95% CI 0-11%).SignificanceThe evidence-based DSLS establishes one method to reliably identify some patients with probable DS using clinical history. The DSLS supports and does not replace clinical decision making. While not all patients with DS can be identified by clinical history alone, these methods combined with clinical judgement could be used to identify patients who warrant further diagnostic assessment at a comprehensive epilepsy center.

ObjectiveA fundamental question in epilepsy surgery is how to delineate the margins of cortex that must be resected to result in seizure freedom. Whether and which areas showing seizure activity early in ictus must be removed to avoid postoperative recurrence of seizures is an area of ongoing research. Seizure spread dynamics in the initial seconds of ictus are often correlated with postoperative outcome; there is neither a consensus definition of early spread nor a concise summary of the existing literature linking seizure spread to postsurgical seizure outcomes. The present study is intended to summarize the literature that links seizure spread to postoperative seizure outcome and to provide a framework for quantitative assessment of early seizure spread.MethodsA systematic review was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A Medline search identified clinical studies reporting data on seizure spread measured by intracranial electrodes, having at least 10 subjects and reporting at least 1-year postoperative outcome in the English literature from 1990 to 2019. Studies were evaluated regarding support for a primary hypothesis: Areas of early seizure spread represent cortex with seizure-generating potential.ResultsThe search yielded 4562 studies: 15 studies met inclusion criteria and 7 studies supported the primary hypothesis. The methods and metrics used to describe seizure spread were heterogenous. The timeframe of seizure spread associated with seizure outcome ranged from 1-14 seconds, with large, well-designed, retrospective studies pointing to 3-10 seconds as most likely to provide meaningful correlates of postoperative seizure freedom.SignificanceThe complex correlation between electrophysiologic seizure spread and the potential for seizure generation needs further elucidation. Prospective cohort studies or trials are needed to evaluate epilepsy surgery targeting cortex involved in the first 3-10 seconds of ictus.

ObjectiveThe RNS System is a direct brain-responsive neurostimulation system that is US Food and Drug Administration-approved for adults with medically intractable focal onset seizures based on safety and effectiveness data from controlled clinical trials. The purpose of this study was to retrospectively evaluate the real-world safety and effectiveness of the RNS System.MethodsEight comprehensive epilepsy centers conducted a chart review of patients treated with the RNS System for at least 1 year, in accordance with the indication for use. Data included device-related serious adverse events and the median percent change in disabling seizure frequency from baseline at years 1, 2, and 3 of treatment and at the most recent follow-up.ResultsOne hundred fifty patients met the criteria for analysis. The median reduction in seizures was 67% (interquartile range [IQR] = 33%-93%, n = 149) at 1 year, 75% (IQR = 50%-94%, n = 93) at 2 years, 82% (IQR = 50%-96%, n = 38) at ≥3 years, and 74% (IQR = 50%-96%, n = 150) at last follow-up (mean = 2.3 years). Thirty-five percent of patients had a ≥90% seizure frequency reduction, and 18% of patients reported being clinically seizure-free at last follow-up. Seizure frequency reductions were similar regardless of patient age, age at epilepsy onset, duration of epilepsy, seizure onset in mesial temporal or neocortical foci, magnetic resonance imaging findings, prior intracranial monitoring, prior epilepsy surgery, or prior vagus nerve stimulation treatment. The infection rate per procedure was 2.9% (6/150 patients); five of the six patients had an implant site infection, and one had osteomyelitis. Lead revisions were required in 2.7% (4/150), and 2.0% (3/150) of patients had a subdural hemorrhage, none of which had long-lasting neurological consequences.SignificanceIn this real-world experience, safety was similar and clinical seizure outcomes exceeded those of the prospective clinical trials, corroborating effectiveness of this therapy and suggesting that clinical experience has informed more effective programming.

A decade after speech was first decoded from human brain signals, accuracy and speed remain far below that of natural speech. Here we show how to decode the electrocorticogram with high accuracy and at natural-speech rates. Taking a cue from recent advances in machine translation, we train a recurrent neural network to encode each sentence-length sequence of neural activity into an abstract representation, and then to decode this representation, word by word, into an English sentence. For each participant, data consist of several spoken repeats of a set of 30-50 sentences, along with the contemporaneous signals from ~250 electrodes distributed over peri-Sylvian cortices. Average word error rates across a held-out repeat set are as low as 3%. Finally, we show how decoding with limited data can be improved with transfer learning, by training certain layers of the network under multiple participants' data.

ObjectivesAdult patients with epilepsy have an increased prevalence of major depressive disorder (MDD). Intracranial EEG (iEEG) captured during extended inpatient monitoring of patients with treatment-resistant epilepsy offers a particularly promising method to study MDD networks in epilepsy.MethodsThe authors used 24 hours of resting-state iEEG to examine the neural activity patterns within corticolimbic structures that reflected the presence of depressive symptoms in 13 adults with medication-refractory epilepsy. Principal component analysis was performed on the z-scored mean relative power in five standard frequency bands averaged across electrodes within a region.ResultsPrincipal component 3 was a statistically significant predictor of the presence of depressive symptoms (R2=0.35, p=0.014). A balanced logistic classifier model using principal component 3 alone correctly classified 78% of patients as belonging to the group with a high burden of depressive symptoms or a control group with minimal depressive symptoms (sensitivity, 75%; specificity, 80%; area under the curve=0.8, leave-one-out cross validation). Classification was dependent on beta power throughout the corticolimbic network and low-frequency cingulate power.ConclusionsThese finding suggest, for the first time, that neural features across circuits involved in epilepsy may distinguish patients who have depressive symptoms from those who do not. Larger studies are required to validate these findings and to assess their diagnostic utility in MDD.

Intracranial electroencephalography (IEEG) involves recording from electrodes placed directly onto the cortical surface or deep brain locations. It is performed on patients with medically refractory epilepsy, undergoing pre-surgical seizure localization. IEEG recordings, combined with advancements in computational capacity and analysis tools, have accelerated cognitive neuroscience. This Perspective describes a potential pitfall latent in many of these recordings by virtue of the subject population-namely interictal epileptiform discharges (IEDs), which can cause spurious results due to the contamination of normal neurophysiological signals by pathological waveforms related to epilepsy. We first discuss the nature of IED hazards, and why they deserve the attention of neurophysiology researchers. We then describe four general strategies used when handling IEDs (manual identification, automated identification, manual-automated hybrids, and ignoring by leaving them in the data), and discuss their pros, cons, and contextual factors. Finally, we describe current practices of human neurophysiology researchers worldwide based on a cross-sectional literature review and a voluntary survey. We put these results in the context of the listed strategies and make suggestions on improving awareness and clarity of reporting to enrich both data quality and communication in the field.

Aphasia classifications and specialized language batteries differ across the fields of neurodegenerative disorders and lesional brain injuries, resulting in difficult comparisons of language deficits across etiologies. In this study, we present a simplified framework, in which a widely-used aphasia battery captures clinical clusters across disease etiologies and provides a quantitative and visual method to characterize and track patients over time. The framework is used to evaluate populations representing three disease etiologies: stroke, primary progressive aphasia (PPA), and post-operative aphasia. A total of 330 patients across three populations with cerebral injury leading to aphasia were investigated, including 76 patients with stroke, 107 patients meeting criteria for PPA, and 147 patients following left hemispheric resective surgery. Western Aphasia Battery (WAB) measures (Information Content, Fluency, answering Yes/No questions, Auditory Word Recognition, Sequential Commands, and Repetition) were collected across the three populations and analyzed to develop a multi-dimensional aphasia model using dimensionality reduction techniques. Two orthogonal dimensions were found to explain 87% of the variance across aphasia phenotypes and three disease etiologies. The first dimension reflects shared weighting across aphasia subscores and correlated with aphasia severity. The second dimension incorporates fluency and comprehension, thereby separating Wernicke's from Broca's aphasia, and the non-fluent/agrammatic from semantic PPA variants. Clusters representing clinical classifications, including late PPA presentations, were preserved within the two-dimensional space. Early PPA presentations were not classifiable, as specialized batteries are needed for phenotyping. Longitudinal data was further used to visualize the trajectory of aphasias during recovery or disease progression, including the rapid recovery of post-operative aphasic patients. This method has implications for the conceptualization of aphasia as a spectrum disorder across different disease etiology and may serve as a framework to track the trajectories of aphasia progression and recovery.

The cost-effectiveness and benefit of many diagnostic tests used in the presurgical evaluation for persons with epilepsy is for the most part uncertain as is their influence on decision-making. The options we have at our disposal are ever increasing. Advanced imaging modalities aim to improve surgical candidacy by helping us better define the epileptogenic zone and optimize surgical planning. However, judicious use is important. Randomized controlled trials delineating which mode of investigation is superior are lacking. Presurgical tests do have incremental value by increasing surgical candidacy and refining surgical planning. The yield of additional imaging will increase with complex localization. However, every case must be tailored by hypothesis, cost, and accessibility. Future studies using a quantitative cost-benefit framework are needed to determine the cost-effectiveness of advanced diagnostic tests (beyond magnetic resonance imaging) in the presurgical evaluation of those with epilepsy.

In speech, listeners extract continuously-varying spectrotemporal cues from the acoustic signal to perceive discrete phonetic categories. Spectral cues are spatially encoded in the amplitude of responses in phonetically-tuned neural populations in auditory cortex. It remains unknown whether similar neurophysiological mechanisms encode temporal cues like voice-onset time (VOT), which distinguishes sounds like /b/ and/p/. We used direct brain recordings in humans to investigate the neural encoding of temporal speech cues with a VOT continuum from /ba/ to /pa/. We found that distinct neural populations respond preferentially to VOTs from one phonetic category, and are also sensitive to sub-phonetic VOT differences within a population's preferred category. In a simple neural network model, simulated populations tuned to detect either temporal gaps or coincidences between spectral cues captured encoding patterns observed in real neural data. These results demonstrate that a spatial/amplitude neural code underlies the cortical representation of both spectral and temporal speech cues.

The most salient acoustic features in speech are the modulations in its intensity, captured by the amplitude envelope. Perceptually, the envelope is necessary for speech comprehension. Yet, the neural computations that represent the envelope and their linguistic implications are heavily debated. We used high-density intracranial recordings, while participants listened to speech, to determine how the envelope is represented in human speech cortical areas on the superior temporal gyrus (STG). We found that a well-defined zone in middle STG detects acoustic onset edges (local maxima in the envelope rate of change). Acoustic analyses demonstrated that timing of acoustic onset edges cues syllabic nucleus onsets, while their slope cues syllabic stress. Synthesized amplitude-modulated tone stimuli showed that steeper slopes elicited greater responses, confirming cortical encoding of amplitude change, not absolute amplitude. Overall, STG encoding of the timing and magnitude of acoustic onset edges underlies the perception of speech temporal structure.

A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear transformations between neural features and features of the sensory stimuli or motor task. While successful in some early sensory processing areas, linear mappings are unlikely to be ideal tools for elucidating nonlinear, hierarchical representations of higher-order brain areas during complex tasks, such as the production of speech by humans. Here, we apply deep networks to predict produced speech syllables from a dataset of high gamma cortical surface electric potentials recorded from human sensorimotor cortex. We find that deep networks had higher decoding prediction accuracy compared to baseline models. Having established that deep networks extract more task relevant information from neural data sets relative to linear models (i.e., higher predictive accuracy), we next sought to demonstrate their utility as a data analysis tool for neuroscience. We first show that deep network's confusions revealed hierarchical latent structure in the neural data, which recapitulated the underlying articulatory nature of speech motor control. We next broadened the frequency features beyond high-gamma and identified a novel high-gamma-to-beta coupling during speech production. Finally, we used deep networks to compare task-relevant information in different neural frequency bands, and found that the high-gamma band contains the vast majority of information relevant for the speech prediction task, with little-to-no additional contribution from lower-frequency amplitudes. Together, these results demonstrate the utility of deep networks as a data analysis tool for basic and applied neuroscience.

ObjectiveTo determine whether a less-invasive approach to surgery for medically refractory temporal lobe epilepsy is associated with lower health care costs and costs of lost productivity over time, compared to open surgery.MethodsWe compared direct medical costs and indirect productivity costs associated with treatment with stereotactic radiosurgery (SRS) or anterior temporal lobectomy (ATL) in the ROSE (Radiosurgery or Open Surgery for Epilepsy) trial. Health care use was abstracted from hospital bills, the study database, and diaries in which participants recorded health care use and time lost from work while seeking care. Costs of use were calculated using a Medicare costing approach used in a prior study of the costs of ATL. The power of many analyses was limited by the sample size and data skewing.ResultsCombined treatment and follow-up costs (in thousands of US dollars) did not differ between SRS (n = 20, mean = $76.6, 95% confidence interval [CI] = 50.7-115.6) and ATL (n = 18, mean = $79.0, 95% CI = 60.09-103.8). Indirect costs also did not differ. More ATL than SRS participants were free of consciousness-impairing seizures in each year of follow-up (all P

The acoustic dimensions that distinguish speech sounds (like the vowel differences in "boot" and "boat") also differentiate speakers' voices. Therefore, listeners must normalize across speakers without losing linguistic information. Past behavioral work suggests an important role for auditory contrast enhancement in normalization: preceding context affects listeners' perception of subsequent speech sounds. Here, using intracranial electrocorticography in humans, we investigate whether and how such context effects arise in auditory cortex. Participants identified speech sounds that were preceded by phrases from two different speakers whose voices differed along the same acoustic dimension as target words (the lowest resonance of the vocal tract). In every participant, target vowels evoke a speaker-dependent neural response that is consistent with the listener's perception, and which follows from a contrast enhancement model. Auditory cortex processing thus displays a critical feature of normalization, allowing listeners to extract meaningful content from the voices of diverse speakers.

The human superior temporal gyrus (STG) is critical for extracting meaningful linguistic features from speech input. Local neural populations are tuned to acoustic-phonetic features of all consonants and vowels and to dynamic cues for intonational pitch. These populations are embedded throughout broader functional zones that are sensitive to amplitude-based temporal cues. Beyond speech features, STG representations are strongly modulated by learned knowledge and perceptual goals. Currently, a major challenge is to understand how these features are integrated across space and time in the brain during natural speech comprehension. We present a theory that temporally recurrent connections within STG generate context-dependent phonological representations, spanning longer temporal sequences relevant for coherent percepts of syllables, words, and phrases.

Verbal repetition requires the coordination of auditory, memory, linguistic, and motor systems. To date, the basic dynamics of neural information processing in this deceptively simple behavior are largely unknown. Here, we examined the neural processes underlying verbal repetition using focal interruption (electrocortical stimulation) in 58 patients undergoing awake craniotomies, and neurophysiological recordings (electrocorticography) in 8 patients while they performed a single word repetition task. Electrocortical stimulation revealed that sub-components of the left peri-Sylvian network involved in single word repetition could be differentially interrupted, producing transient perceptual deficits, paraphasic errors, or speech arrest. Electrocorticography revealed the detailed spatio-temporal dynamics of cortical activation, involving a highly-ordered, but overlapping temporal progression of cortical high gamma (75-150Hz) activity throughout the peri-Sylvian cortex. We observed functionally distinct serial and parallel cortical processing corresponding to successive stages of general auditory processing (posterior superior temporal gyrus), speech-specific auditory processing (middle and posterior superior temporal gyrus), working memory (inferior frontal cortex), and motor articulation (sensorimotor cortex). Together, these methods reveal the dynamics of coordinated activity across peri-Sylvian cortex during verbal repetition.

Cognitive models of depression suggest that depressed individuals exhibit a tendency to attribute negative meaning to neutral stimuli, and enhanced processing of mood-congruent stimuli. However, evidence thus far has been inconsistent. In this study, we sought to identify both differential interpretation of neutral information as well as emotion processing biases associated with depression. Fifty adult participants completed standardized mood-related questionnaires, a novel immediate mood scale questionnaire (IMS-12), and a novel task, Emotion Matcher, in which they were required to indicate whether pairs of emotional faces show the same expression or not. We found that overall success rate and reaction time on the Emotion Matcher task did not differ as a function of severity of depression. However, more depressed participants had significantly worse performance when presented with sad-neutral face pairs, as well as increased reaction times to happy-happy pairs. In addition, accuracy of the sad-neutral pairs was found to be significantly associated with depression severity in a regression model. Our study provides partial support for the mood-congruent hypothesis, revealing only a potential bias in interpretation of sad and neutral expressions, but not a general deficit in processing of facial expressions. The potential of such bias in serving as a predictor for depression should be further examined in future studies.

Technology that translates neural activity into speech would be transformative for people who are unable to communicate as a result of neurological impairments. Decoding speech from neural activity is challenging because speaking requires very precise and rapid multi-dimensional control of vocal tract articulators. Here we designed a neural decoder that explicitly leverages kinematic and sound representations encoded in human cortical activity to synthesize audible speech. Recurrent neural networks first decoded directly recorded cortical activity into representations of articulatory movement, and then transformed these representations into speech acoustics. In closed vocabulary tests, listeners could readily identify and transcribe speech synthesized from cortical activity. Intermediate articulatory dynamics enhanced performance even with limited data. Decoded articulatory representations were highly conserved across speakers, enabling a component of the decoder to be transferrable across participants. Furthermore, the decoder could synthesize speech when a participant silently mimed sentences. These findings advance the clinical viability of using speech neuroprosthetic technology to restore spoken communication.

BackgroundAlthough language deficits after awake brain surgery are usually milder than post-stroke, postoperative language assessments are needed to identify these. Follow-up of brain tumor patients in certain geographical regions can be difficult when most patients are not local and come from afar. We developed a short telephone-based test for pre- and postoperative language assessments.MethodsThe development of the TeleLanguage Test was based on the Dutch Linguistic Intraoperative Protocol and existing standardized English batteries. Two parallel versions were composed and tested in healthy native English speakers. Subsequently, the TeleLanguage Test was administered in a group of 14 tumor patients before surgery and at 1 week, 1 month, and 3 months after surgery. The test includes auditory comprehension, repetition, semantic selection, sentence or story completion, verbal naming, and fluency tests. It takes less than 20 minutes to administer.ResultsHealthy participants had no difficulty performing any of the language tests via the phone, attesting to the feasibility of a phone assessment. In the patient group, all TeleLanguage test scores significantly declined shortly after surgery with a recovery to preoperative levels at 3 months postsurgery for naming and fluency tasks and a recovery to normal levels for the other language tasks. Analysis of the in-person language assessments (until 1 month) revealed a similar profile.ConclusionThe use of the TeleLanguage battery to conduct language assessments from afar can provide convenience, might optimize patient care, and enables longitudinal clinical research. The TeleLanguage is a valid tool for various clinical and scientific purposes.

Electrocortical stimulation (ECS) mapping is routinely used to identify critical language sites before resective neurosurgery. The precise locations of these sites are highly variable across patients, occurring in the frontal, temporal, and parietal lobes-it is this variability that necessitates individual patient mapping. But why these particular anatomical sites are so privileged in each patient is unknown. We hypothesized that critical language sites have greater functional connectivity with nearby cortex than sites without critical functions, since they serve as central nodes within the language network. Functional connectivity across language, motor, and cleared sites was measured in 15 patients undergoing electrocortiographic (ECoG) mapping for epilepsy surgery. Critical language sites had significantly higher connectivity than sites without critical functions (P = 0.001), and this also held for motor sites (P = 0.022). These data support the hypothesis that critical language sites are highly connected within the local cortical network, perhaps explaining why their disruption with ECS leads to transient disturbances in language function. It is our hope that improved understanding of the mechanisms of ECS will permit improved surgical planning and perhaps contribute to the understanding of normal language physiology.

Despite many behavioral and neuroimaging investigations, it remains unclear how the human cortex represents spectrotemporal sound features during auditory imagery, and how this representation compares to auditory perception. To assess this, we recorded electrocorticographic signals from an epileptic patient with proficient music ability in 2 conditions. First, the participant played 2 piano pieces on an electronic piano with the sound volume of the digital keyboard on. Second, the participant replayed the same piano pieces, but without auditory feedback, and the participant was asked to imagine hearing the music in his mind. In both conditions, the sound output of the keyboard was recorded, thus allowing precise time-locking between the neural activity and the spectrotemporal content of the music imagery. This novel task design provided a unique opportunity to apply receptive field modeling techniques to quantitatively study neural encoding during auditory mental imagery. In both conditions, we built encoding models to predict high gamma neural activity (70-150 Hz) from the spectrogram representation of the recorded sound. We found robust spectrotemporal receptive fields during auditory imagery with substantial, but not complete overlap in frequency tuning and cortical location compared to receptive fields measured during auditory perception.

Auditory speech comprehension is the result of neural computations that occur in a broad network that includes the temporal lobe auditory cortex and the left inferior frontal cortex. It remains unclear how representations in this network differentially contribute to speech comprehension. Here, we recorded high-density direct cortical activity during a sine-wave speech (SWS) listening task to examine detailed neural speech representations when the exact same acoustic input is comprehended versus not comprehended. Listeners heard SWS sentences (pre-exposure), followed by clear versions of the same sentences, which revealed the content of the sounds (exposure), and then the same SWS sentences again (post-exposure). Across all three task phases, high-gamma neural activity in the superior temporal gyrus was similar, distinguishing different words based on bottom-up acoustic features. In contrast, frontal regions showed a more pronounced and sudden increase in activity only when the input was comprehended, which corresponded with stronger representational separability among spatiotemporal activity patterns evoked by different words. We observed this effect only in participants who were not able to comprehend the stimuli during the pre-exposure phase, indicating a relationship between frontal high-gamma activity and speech understanding. Together, these results demonstrate that both frontal and temporal cortical networks are involved in spoken language understanding, and that under certain listening conditions, frontal regions are involved in discriminating speech sounds.