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BackgroundDomoic acid (DA) is a naturally occurring neurotoxin harmful to marine animals and humans. California sea lions exposed to DA in prey during algal blooms along the Pacific coast exhibit significant neurological symptoms, including epilepsy with hippocampal atrophy.ObservationsHere the authors describe a xenotransplantation procedure to deliver interneuron progenitor cells into the damaged hippocampus of an epileptic sea lion with suspected DA toxicosis. The sea lion has had no evidence of seizures after the procedure, and clinical measures of well-being, including weight and feeding habits, have stabilized.LessonsThese preliminary results suggest xenotransplantation has improved the quality of life for this animal and holds tremendous therapeutic promise.

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.

In the changing and demanding university context, various situations are experienced wherein abilities to maintain motivation and activate problem solving could be relevant in students' adjustment. Beyond the widely analyzed role of academic motivation, this study focused on the added value of social problem-solving ability in student adjustment in the academic context. Analyses based on the responses obtained from 253 students (197 women and 56 men) indicated the significant role of social problem-solving ability in student adjustment, with a small additional amount (f.sup.2 = .09) 9% of variance in life satisfaction and medium additional amount (f.sup.2 = .17) 15% of variance in depressive symptoms, beyond academic motivation. In particular, negative problem orientation was an important predictor of depressive symptoms ([beta] = .41, p < .001) and life satisfaction ([beta] = - .26, p < .001); however, positive problem orientation was only an important predictor of life satisfaction ([beta] = .21, p < .01). This study also showed the predictive role of the value, expectancy, and affection components of motivation in student adjustment. Overall, the findings highlight the relevance of training in problem-solving orientation and motivational components to improve college students' general well-being., Author(s): Amaia de la Fuente [sup.1] , Olga Cardeñoso [sup.1] , Edward C. Chang [sup.2] , Abigael G. Lucas [sup.2] , Mingqi Li [sup.3] , Olivia D. Chang [sup.2] Author [...]

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.

Neuroprostheses have the potential to restore communication to people who cannot speak or type due to paralysis. However, it is unclear if silent attempts to speak can be used to control a communication neuroprosthesis. Here, we translated direct cortical signals in a clinical-trial participant (ClinicalTrials.gov; NCT03698149) with severe limb and vocal-tract paralysis into single letters to spell out full sentences in real time. We used deep-learning and language-modeling techniques to decode letter sequences as the participant attempted to silently spell using code words that represented the 26 English letters (e.g. "alpha" for "a"). We leveraged broad electrode coverage beyond speech-motor cortex to include supplemental control signals from hand cortex and complementary information from low- and high-frequency signal components to improve decoding accuracy. We decoded sentences using words from a 1,152-word vocabulary at a median character error rate of 6.13% and speed of 29.4 characters per minute. In offline simulations, we showed that our approach generalized to large vocabularies containing over 9,000 words (median character error rate of 8.23%). These results illustrate the clinical viability of a silently controlled speech neuroprosthesis to generate sentences from a large vocabulary through a spelling-based approach, complementing previous demonstrations of direct full-word decoding.

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.

To achieve optimal survival and quality of life outcomes in patients with glioma, the extent of tumor resection must be maximized without causing injury to eloquent structures. Preservation of language function is of particular importance to patients and requires careful mapping to reveal the locations of cortical language hubs and their structural and functional connections. Within this language network, accurate mapping of eloquent white matter tracts is critical, given the high risk of permanent neurological impairment if they are injured during surgery. In this review, we start by describing the clinical implications of gliomas involving white matter language tracts. Next, we highlight the advantages and limitations of methods commonly used to identify these tracts during surgery including structural imaging techniques, functional imaging, non-invasive stimulation, and finally, awake craniotomy. We provide a rationale for combining these complementary techniques as part of a multimodal mapping paradigm to optimize postoperative language outcomes. Next, we review local and long-range adaptations that take place as the language network undergoes remodeling after tumor growth and surgical resection. We discuss the probable cellular mechanisms underlying this plasticity with emphasis on the white matter, which until recently was thought to have a limited role in adults. Finally, we provide an overview of emerging developments in targeting the glioma-neuronal network interface to achieve better disease control and promote recovery after injury.

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.

Deep brain stimulation is a promising treatment for neuropsychiatric conditions such as major depression. It could be optimized by identifying neural biomarkers that trigger therapy selectively when symptom severity is elevated. We developed an approach that first used multi-day intracranial electrophysiology and focal electrical stimulation to identify a personalized symptom-specific biomarker and a treatment location where stimulation improved symptoms. We then implanted a chronic deep brain sensing and stimulation device and implemented a biomarker-driven closed-loop therapy in an individual with depression. Closed-loop therapy resulted in a rapid and sustained improvement in depression. Future work is required to determine if the results and approach of this n-of-1 study generalize to a broader population.

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.

Direct electrical stimulation, the transient 'lesional' method probing brain function, has been utilized in identifying the language cortex and preserving language function during epilepsy and neuro-oncological surgeries for about a century. However, comparison of functional maps of the language cortex across languages/continents based on cortical stimulation remains unclear. We conducted a retrospective multicentre study including four cohorts of direct electrical stimulation mapping from four centres across three continents, where three indigenous languages (English, French and Mandarin) are spoken. All subjects performed the two most common language tasks: number counting and picture naming during stimulation. All language sites were recorded and normalized to the same brain template. Next, Spearman's correlation analysis was performed to explore the consistency of the distributions of the language cortex across centres, a kernel density estimation to localize the peak coordinates, and a hierarchical cluster analysis was performed to detect the crucial epicenters. A total of 598 subjects with 917 speech arrest sites (complete interruption of ongoing counting) and 423 anomia sites (inability to name or misnaming) were included. Different centres presented highly consistent distribution patterns for speech arrest (Spearman's coefficient r ranged from 0.60 to 0.85, all pair-wise correlations P

Speech perception is thought to rely on a cortical feedforward serial transformation of acoustic into linguistic representations. Using intracranial recordings across the entire human auditory cortex, electrocortical stimulation, and surgical ablation, we show that cortical processing across areas is not consistent with a serial hierarchical organization. Instead, response latency and receptive field analyses demonstrate parallel and distinct information processing in the primary and nonprimary auditory cortices. This functional dissociation was also observed where stimulation of the primary auditory cortex evokes auditory hallucination but does not distort or interfere with speech perception. Opposite effects were observed during stimulation of nonprimary cortex in superior temporal gyrus. Ablation of the primary auditory cortex does not affect speech perception. These results establish a distributed functional organization of parallel information processing throughout the human auditory cortex and demonstrate an essential independent role for nonprimary auditory cortex in speech processing.

Since the early descriptions of language function based on observations of patients with language deficits by Broca and Wernicke, neurosurgeons have been focused on characterizing the anatomic regions necessary for language perception and production, and preserving these structures during surgery to minimize patient deficits post operatively. In this supplementary issue on awake intraoperative mapping, we review language processing across multiple domains, highlighting key advances in direct electrical stimulation of different cortical and subcortical regions involved in naming, repetition, reading, writing, and syntax. We then discuss different intraoperative tasks for assessing the function of a given area and avoiding injury to critical, eloquent regions.

Objective.Intracranial neural recordings and electrical stimulation are tools used in an increasing range of applications, including intraoperative clinical mapping and monitoring, therapeutic neuromodulation, and brain computer interface control and feedback. However, many of these applications suffer from a lack of spatial specificity and localization, both in terms of sensed neural signal and applied stimulation. This stems from limited manufacturing processes of commercial-off-the-shelf (COTS) arrays unable to accommodate increased channel density, higher channel count, and smaller contact size.Approach.Here, we describe a manufacturing and assembly approach using thin-film microfabrication for 32-channel high density subdural micro-electrocorticography (µECoG) surface arrays (contacts 1.2 mm diameter, 2 mm pitch) and intracranial electroencephalography (iEEG) depth arrays (contacts 0.5 mm × 1.5 mm, pitch 0.8 mm × 2.5 mm). Crucially, we tackle the translational hurdle and test these arrays during intraoperative studies conducted in four humans under regulatory approval.Main results.We demonstrate that the higher-density contacts provide additional unique information across the recording span compared to the density of COTS arrays which typically have electrode pitch of 8 mm or greater; 4 mm in case of specially ordered arrays. Our intracranial stimulation study results reveal that refined spatial targeting of stimulation elicits evoked potentials with differing spatial spread.Significance.Thin-film,μECoG and iEEG depth arrays offer a promising substrate for advancing a number of clinical and research applications reliant on high-resolution neural sensing and intracranial stimulation.

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.).

The hippocampus is diversely interconnected with other brain systems along its axis. Cycles of theta-frequency activity are believed to propagate from the septal to temporal pole, yet it is unclear how this one-way route supports the flexible cognitive capacities of this structure. We leveraged novel thin-film microgrid arrays conformed to the human hippocampal surface to track neural activity two-dimensionally in vivo. All oscillation frequencies identified between 1-15 Hz propagated across the tissue. Moreover, they dynamically shifted between two roughly opposite directions oblique to the long axis. This predominant propagation axis was mirrored across participants, hemispheres, and consciousness states. Directionality was modulated in a participant who performed a behavioral task, and it could be predicted by wave amplitude topography over the hippocampal surface. Our results show that propagation directions may thus represent distinct meso-scale network computations, operating along versatile spatiotemporal processing routes across the hippocampal body.

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.

The present study drew on the act-frequency approach to study eating disturbances by modifying the items of the Eating Expectancy Inventory (EEI) and Thinness and Restricting Expectancy Inventory (TREI) to their frequency versions, namely, EEI-F and TREI-F. In Study 1, a total of 354 young females completed the EEI-F and TREI-F for factor analysis. In Study 2, to assess for construct validity and predictive utility, an independent sample of 241 young females completed a test battery including the EEI-F, TREI-F, and measures of eating disturbances. In Study 1, results from an exploratory factor analysis indicated a one-factor solution for both EEI-F and TREI-F that account for 65.65% and 72.97% of the common variance, respectively. In Study 2, both measures were found to possess good test-retest reliability (11-week) in a subset sample of participants from Study 1. Moreover, in support for construct validity, we found both EEI-F and TREI-F scores were positively associated with scores on measures of eating disturbances (i.e., drive for thinness, bulimic symptoms). Finally, in support of utility, frequency of eating and thinness expectancies predicted eating disturbances above and beyond general attitudes associated with eating and thinness expectancies (measured by the EEI and TREI). Overall, the present findings provide promising evidence for the validity, reliability, and utility of the EEI-F and TREI-F as reliable, valid, and useful measures of frequency of eating and thinness expectancies in young females. Implications for the theory and clinical assessments were discussed., Author(s): Mingqi Li [sup.1] , Edward C. Chang [sup.2] Author Affiliations: (1) grid.254920.8, 0000 0001 0707 2013, Department of Psychology, DePaul University, , 2219 North Kenmore Avenue, 60614, Chicago, IL, [...]

Drawing upon the broaden-and-build model and self-determination theory, the present study examined whether and how the fulfillment of basic psychological needs (i.e., autonomy, competence, & relatedness) might mediate the relationship between positive affectivity and distinctive positive outcomes (i.e., life satisfaction, self-esteem, & academic performance) in a sample of 320 (202 females) Chinese adolescents using a six-months' prospective design. Results showed that positive affectivity was positively associated with all basic psychological needs and positive outcomes. Furthermore, results obtained from conducting mediation analyses indicated that competence mediated the link between positive affectivity and subsequent levels of self-esteem, while relatedness mediated the link between positive affectivity and subsequent levels of life satisfaction, and autonomy did not emerge as a significant mediator for any of the positive outcomes studied. Overall, the current study integrated the basic psychological needs theory into the framework of the broaden-and-build model, identifying the unique contribution of the needs in the link between positive affectivity and positive outcomes in Chinese adolescents., Author(s): Jianjie Xu [sup.1] , Edward C. Chang [sup.2] , Claire J. Novak [sup.2] , Jingyi Shen [sup.1] , Shaoying Zheng [sup.1] , Yinan Wang [sup.3] , Nan Zhou [sup.4] [...]

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.

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.

ObjectiveSurgical site infection (SSI) is a complication linked to increased costs and length of hospital stay. Prevention of SSI is important to reduce its burden on individual patients and the healthcare system. The authors aimed to assess the efficacy of preoperative chlorhexidine gluconate (CHG) showers on SSI rates following cranial surgery.MethodsIn November 2013, a preoperative CHG shower protocol was implemented at the authors' institution. A total of 3126 surgical procedures were analyzed, encompassing a time frame from April 2012 to April 2016. Cohorts before and after implementation of the CHG shower protocol were evaluated for differences in SSI rates.ResultsThe overall SSI rate was 0.6%. No significant differences (p = 0.11) were observed between the rate of SSI of the 892 patients in the preimplementation cohort (0.2%) and that of the 2234 patients in the postimplementation cohort (0.8%). Following multivariable analysis, implementation of preoperative CHG showers was not associated with decreased SSI (adjusted OR 2.96, 95% CI 0.67-13.1; p = 0.15).ConclusionsThis is the largest study, according to sample size, to examine the association between CHG showers and SSI following craniotomy. CHG showers did not significantly alter the risk of SSI after a cranial procedure.

Direct electrical stimulation of the brain is the gold standard technique used to define functional-anatomical relationships during neurosurgical procedures. Areas that respond to stimulation are considered "critical nodes" of circuits that must remain intact for the subject to maintain the ability to perform certain functions, like moving and speaking. Despite its routine use, the neurophysiology underlying downstream motor responses to electrical stimulation of the brain, such as muscle contraction or movement arrest, is poorly understood. Furthermore, varying and sometimes counterintuitive responses can be seen depending on how and where the stimulation is applied, even within the human primary motor cortex. Therefore, here we review relevant neuroanatomy of the human motor system, provide a brief historical perspective on electrical brain stimulation, explore mechanistic variations in stimulation applications, examine neurophysiological properties of different parts of the motor system, and suggest areas of future research that can promote a better understanding of the interaction between electrical stimulation of the brain and its function.

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.