A Phase 1 Assessment of the Safety, Tolerability, Pharmacokinetics and Pharmacodynamics of (2R,6R)-Hydroxynorketamine in Healthy Volunteers.

(R,S)-Ketamine (ketamine) is a dissociative anesthetic that also possesses analgesic and antidepressant activity. Undesirable dissociative side effects and misuse potential limit expanded use of ketamine in several mental health disorders despite promising clinical activity and intensifying medical need. (2R,6R)-Hydroxynorketamine (RR-HNK) is a metabolite of ketamine that lacks anesthetic and dissociative activity but maintains antidepressant and analgesic activity in multiple preclinical models. To enable future assessments in selected human indications, we report the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of RR-HNK in a Phase 1 study in healthy volunteers (NCT04711005). A six-level single-ascending dose (SAD) (0.1-4 mg/kg) and a two-level multiple ascending dose (MAD) (1 and 2 mg/kg) study was performed using a 40-minute IV administration emulating the common practice for ketamine administration for depression. Safety assessments showed RR-HNK possessed a minimal adverse event profile and no serious adverse events at all doses examined. Evaluations of dissociation and sedation demonstrated that RR-HNK did not possess anesthetic or dissociative characteristics in the doses examined. RR-HNK PK parameters were measured in both the SAD and MAD studies and exhibited dose-proportional increases in exposure. Quantitative electroencephalography (EEG) measurements collected as a PD parameter based on preclinical findings and ketamine's established effect on gamma-power oscillations demonstrated increases of gamma power in some participants at the lower/mid-range doses examined. Cerebrospinal fluid examination confirmed RR-HNK exposure within the central nervous system (CNS). Collectively, these data demonstrate RR-HNK is well tolerated with an acceptable PK profile and promising PD outcomes to support the progression into Phase 2.

High-resolution neural recordings improve the accuracy of speech decoding.

Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life. One solution to restore communication is to decode signals directly from the brain to enable neural speech prostheses. However, decoding has been limited by coarse neural recordings which inadequately capture the rich spatio-temporal structure of human brain signals. To resolve this limitation, we performed high-resolution, micro-electrocorticographic (µECoG) neural recordings during intra-operative speech production. We obtained neural signals with 57× higher spatial resolution and 48% higher signal-to-noise ratio compared to macro-ECoG and SEEG. This increased signal quality improved decoding by 35% compared to standard intracranial signals. Accurate decoding was dependent on the high-spatial resolution of the neural interface. Non-linear decoding models designed to utilize enhanced spatio-temporal neural information produced better results than linear techniques. We show that high-density µECoG can enable high-quality speech decoding for future neural speech prostheses.

Flexible, high-resolution cortical arrays with large coverage capture microscale high-frequency oscillations in patients with epilepsy.

OBJECTIVE: Effective surgical treatment of drug-resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High-frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intracranial electrode arrays may limit the accurate capture of HFO activity. In this study, we sought to characterize microscale HFO activity captured on thin, flexible microelectrocorticographic (µECoG) arrays, which provide high spatial resolution over large cortical surface areas. METHODS: We used novel liquid crystal polymer thin-film µECoG arrays (.76-1.72-mm intercontact spacing) to capture HFOs in eight intraoperative recordings from seven patients with epilepsy. We identified ripple (80-250 Hz) and fast ripple (250-600 Hz) HFOs using a common energy thresholding detection algorithm along with two stages of artifact rejection. We visualized microscale subregions of HFO activity using spatial maps of HFO rate, signal-to-noise ratio, and mean peak frequency. We quantified the spatial extent of HFO events by measuring covariance between detected HFOs and surrounding activity. We also compared HFO detection rates on microcontacts to simulated macrocontacts by spatially averaging data. RESULTS: We found visually delineable subregions of elevated HFO activity within each µECoG recording. Forty-seven percent of HFOs occurred on single 200-µm-diameter recording contacts, with minimal high-frequency activity on surrounding contacts. Other HFO events occurred across multiple contacts simultaneously, with covarying activity most often limited to a .95-mm radius. Through spatial averaging, we estimated that macrocontacts with 2-3-mm diameter would only capture 44% of the HFOs detected in our µECoG recordings. SIGNIFICANCE: These results demonstrate that thin-film microcontact surface arrays with both highresolution and large coverage accurately capture microscale HFO activity and may improve the utility of HFOs to localize the EZ for treatment of drug-resistant epilepsy.

Intraoperative microseizure detection using a high-density micro-electrocorticography electrode array.

One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30-70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, subdural electrode arrays with hundreds of microelectrodes over a 100-1000 mm2 area to enable high-resolution mapping of neural activity. Here, we used these high-density arrays to study microscale properties of human epileptiform activity. We performed intraoperative micro-electrocorticographic recordings in nine patients with epilepsy. In addition, we recorded from four patients with movement disorders undergoing deep brain stimulator implantation as non-epileptic controls. A board-certified epileptologist identified microseizures, which resembled electrographic seizures normally observed with clinical macroelectrodes. Recordings in epileptic patients had a significantly higher microseizure rate (2.01 events/min) than recordings in non-epileptic subjects (0.01 events/min; permutation test, P = 0.0068). Using spatial averaging to simulate recordings from larger electrode contacts, we found that the number of detected microseizures decreased rapidly with increasing contact diameter and decreasing contact density. In cases in which microseizures were spatially distributed across multiple channels, the approximate onset region was identified. Our results suggest that micro-electrocorticographic electrode arrays with a high density of contacts and large coverage are essential for capturing microseizures in epilepsy patients and may be beneficial for localizing epileptogenic tissue to plan surgery or target brain stimulation.

Flexible, high-resolution thin-film electrodes for human and animal neural research.

Objective.Brain functions such as perception, motor control, learning, and memory arise from the coordinated activity of neuronal assemblies distributed across multiple brain regions. While major progress has been made in understanding the function of individual neurons, circuit interactions remain poorly understood. A fundamental obstacle to deciphering circuit interactions is the limited availability of research tools to observe and manipulate the activity of large, distributed neuronal populations in humans. Here we describe the development, validation, and dissemination of flexible, high-resolution, thin-film (TF) electrodes for recording neural activity in animals and humans.Approach.We leveraged standard flexible printed-circuit manufacturing processes to build high-resolution TF electrode arrays. We used biocompatible materials to form the substrate (liquid crystal polymer; LCP), metals (Au, PtIr, and Pd), molding (medical-grade silicone), and 3D-printed housing (nylon). We designed a custom, miniaturized, digitizing headstage to reduce the number of cables required to connect to the acquisition system and reduce the distance between the electrodes and the amplifiers. A custom mechanical system enabled the electrodes and headstages to be pre-assembled prior to sterilization, minimizing the setup time required in the operating room. PtIr electrode coatings lowered impedance and enabled stimulation. High-volume, commercial manufacturing enables cost-effective production of LCP-TF electrodes in large quantities.Main Results. Our LCP-TF arrays achieve 25× higher electrode density, 20× higher channel count, and 11× reduced stiffness than conventional clinical electrodes. We validated our LCP-TF electrodes in multiple human intraoperative recording sessions and have disseminated this technology to >10 research groups. Using these arrays, we have observed high-frequency neural activity with sub-millimeter resolution.Significance.Our LCP-TF electrodes will advance human neuroscience research and improve clinical care by enabling broad access to transformative, high-resolution electrode arrays.

Sufficient sampling for kriging prediction of cortical potential in rat, monkey, and human µECoG.

Objective. Large channel count surface-based electrophysiology arrays (e.g. µECoG) are high-throughput neural interfaces with good chronic stability. Electrode spacing remains ad hoc due to redundancy and nonstationarity of field dynamics. Here, we establish a criterion for electrode spacing based on the expected accuracy of predicting unsampled field potential from sampled sites.Approach. We applied spatial covariance modeling and field prediction techniques based on geospatial kriging to quantify sufficient sampling for thousands of 500 ms µECoG snapshots in human, monkey, and rat. We calculated a probably approximately correct (PAC) spacing based on kriging that would be required to predict µECoG fields at≤10% error for most cases (95% of observations).Main results. Kriging theory accurately explained the competing effects of electrode density and noise on predicting field potential. Across five frequency bands from 4-7 to 75-300 Hz, PAC spacing was sub-millimeter for auditory cortex in anesthetized and awake rats, and posterior superior temporal gyrus in anesthetized human. At 75-300 Hz, sub-millimeter PAC spacing was required in all species and cortical areas.Significance. PAC spacing accounted for the effect of signal-to-noise on prediction quality and was sensitive to the full distribution of non-stationary covariance states. Our results show that µECoG arrays should sample at sub-millimeter resolution for applications in diverse cortical areas and for noise resilience.

Speech fine structure contains critical temporal cues to support speech segmentation.

Segmenting the continuous speech stream into units for further perceptual and linguistic analyses is fundamental to speech recognition. The speech amplitude envelope (SE) has long been considered a fundamental temporal cue for segmenting speech. Does the temporal fine structure (TFS), a significant part of speech signals often considered to contain primarily spectral information, contribute to speech segmentation? Using magnetoencephalography, we show that the TFS entrains cortical responses between 3 and 6 Hz and demonstrate, using mutual information analysis, that (i) the temporal information in the TFS can be reconstructed from a measure of frame-to-frame spectral change and correlates with the SE and (ii) that spectral resolution is key to the extraction of such temporal information. Furthermore, we show behavioural evidence that, when the SE is temporally distorted, the TFS provides cues for speech segmentation and aids speech recognition significantly. Our findings show that it is insufficient to investigate solely the SE to understand temporal speech segmentation, as the SE and the TFS derived from a band-filtering method convey comparable, if not inseparable, temporal information. We argue for a more synthetic view of speech segmentation - the auditory system groups speech signals coherently in both temporal and spectral domains.

Manipulating stored phonological input during verbal working memory.

Verbal working memory (vWM) involves storing and manipulating information in phonological sensory input. An influential theory of vWM proposes that manipulation is carried out by a central executive while storage is performed by two interacting systems: a phonological input buffer that captures sound-based information and an articulatory rehearsal system that controls speech motor output. Whether, when and how neural activity in the brain encodes these components remains unknown. Here we read out the contents of vWM from neural activity in human subjects as they manipulated stored speech sounds. As predicted, we identified storage systems that contained both phonological sensory and articulatory motor representations. Unexpectedly, however, we found that manipulation did not involve a single central executive but rather involved two systems with distinct contributions to successful manipulation. We propose, therefore, that multiple subsystems comprise the central executive needed to manipulate stored phonological input for articulatory motor output in vWM.

I see what you are saying.

The motor cortex in the brain tracks lip movements to help with speech perception.

A kiss is not a kiss: visually evoked neuromagnetic fields reveal differential sensitivities to brief presentations of kissing couples.

With a few exceptions, the literature on face recognition and its neural basis derives from the presentation of single faces. However, in many ecologically typical situations, we see more than one face, in different communicative contexts. One of the principal ways in which we interact using our faces is kissing. Although there is no obvious taxonomy of kissing, we kiss in various interpersonal situations (greeting, ceremony, sex), with different goals and partners. Here, we assess the visual cortical responses elicited by viewing different couples kissing with different intents. The study thus lies at the nexus of face recognition, action recognition, and social neuroscience. Magnetoencephalography data were recorded from nine participants in a passive viewing paradigm. We presented images of couples kissing, with the images differing along two dimensions, kiss type and couple type. We quantified event-related field amplitudes and latencies. In each participant, the canonical sequence of event-related fields was observed, including an M100, an M170, and a later M400 response. The earliest two responses were significantly modulated in latency (M100) or amplitude (M170) by the sex composition of the images (with male-male and female-female pairings yielding faster latency M100 and larger amplitude M170 responses). In contrast, kiss type showed no modulation of any brain response. The early cortical-evoked fields that we typically associate with the presentation and analysis of single faces are differentially sensitive to complex social and action information in face pairs that are kissing. The early responses, typically associated with perceptual analysis, exhibit a consistent grouping and suggest a high and rapid sensitivity to the composition of the kissing pairs.

Sensory-motor transformations for speech occur bilaterally.

Historically, the study of speech processing has emphasized a strong link between auditory perceptual input and motor production output. A kind of 'parity' is essential, as both perception- and production-based representations must form a unified interface to facilitate access to higher-order language processes such as syntax and semantics, believed to be computed in the dominant, typically left hemisphere. Although various theories have been proposed to unite perception and production, the underlying neural mechanisms are unclear. Early models of speech and language processing proposed that perceptual processing occurred in the left posterior superior temporal gyrus (Wernicke's area) and motor production processes occurred in the left inferior frontal gyrus (Broca's area). Sensory activity was proposed to link to production activity through connecting fibre tracts, forming the left lateralized speech sensory-motor system. Although recent evidence indicates that speech perception occurs bilaterally, prevailing models maintain that the speech sensory-motor system is left lateralized and facilitates the transformation from sensory-based auditory representations to motor-based production representations. However, evidence for the lateralized computation of sensory-motor speech transformations is indirect and primarily comes from stroke patients that have speech repetition deficits (conduction aphasia) and studies using covert speech and haemodynamic functional imaging. Whether the speech sensory-motor system is lateralized, like higher-order language processes, or bilateral, like speech perception, is controversial. Here we use direct neural recordings in subjects performing sensory-motor tasks involving overt speech production to show that sensory-motor transformations occur bilaterally. We demonstrate that electrodes over bilateral inferior frontal, inferior parietal, superior temporal, premotor and somatosensory cortices exhibit robust sensory-motor neural responses during both perception and production in an overt word-repetition task. Using a non-word transformation task, we show that bilateral sensory-motor responses can perform transformations between speech-perception- and speech-production-based representations. These results establish a bilateral sublexical speech sensory-motor system.

Visual input enhances selective speech envelope tracking in auditory cortex at a "cocktail party".

Our ability to selectively attend to one auditory signal amid competing input streams, epitomized by the "Cocktail Party" problem, continues to stimulate research from various approaches. How this demanding perceptual feat is achieved from a neural systems perspective remains unclear and controversial. It is well established that neural responses to attended stimuli are enhanced compared with responses to ignored ones, but responses to ignored stimuli are nonetheless highly significant, leading to interference in performance. We investigated whether congruent visual input of an attended speaker enhances cortical selectivity in auditory cortex, leading to diminished representation of ignored stimuli. We recorded magnetoencephalographic signals from human participants as they attended to segments of natural continuous speech. Using two complementary methods of quantifying the neural response to speech, we found that viewing a speaker's face enhances the capacity of auditory cortex to track the temporal speech envelope of that speaker. This mechanism was most effective in a Cocktail Party setting, promoting preferential tracking of the attended speaker, whereas without visual input no significant attentional modulation was observed. These neurophysiological results underscore the importance of visual input in resolving perceptual ambiguity in a noisy environment. Since visual cues in speech precede the associated auditory signals, they likely serve a predictive role in facilitating auditory processing of speech, perhaps by directing attentional resources to appropriate points in time when to-be-attended acoustic input is expected to arrive.

A mutual information analysis of neural coding of speech by low-frequency MEG phase information.

Recent work has implicated low-frequency (<20 Hz) neuronal phase information as important for both auditory (<10 Hz) and speech [theta (∼4-8 Hz)] perception. Activity on the timescale of theta corresponds linguistically to the average length of a syllable, suggesting that information within this range has consequences for segmentation of meaningful units of speech. Longer timescales that correspond to lower frequencies [delta (1-3 Hz)] also reflect important linguistic features-prosodic/suprasegmental-but it is unknown whether the patterns of activity in this range are similar to theta. We investigate low-frequency activity with magnetoencephalography (MEG) and mutual information (MI), an analysis that has not yet been applied to noninvasive electrophysiological recordings. We find that during speech perception each frequency subband examined [delta (1-3 Hz), theta(low) (3-5 Hz), theta(high) (5-7 Hz)] processes independent information from the speech stream. This contrasts with hypotheses that either delta and theta reflect their corresponding linguistic levels of analysis or each band is part of a single holistic onset response that tracks global acoustic transitions in the speech stream. Single-trial template-based classifier results further validate this finding: information from each subband can be used to classify individual sentences, and classifier results that utilize the combination of frequency bands provide better results than single bands alone. Our results suggest that during speech perception low-frequency phase of the MEG signal corresponds to neither abstract linguistic units nor holistic evoked potentials but rather tracks different aspects of the input signal. This study also validates a new method of analysis for noninvasive electrophysiological recordings that can be used to formally characterize information content of neural responses and interactions between these responses. Furthermore, it bridges results from different levels of neurophysiological study: small-scale multiunit recordings and local field potentials and macroscopic magneto/electrophysiological noninvasive recordings.