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Speech requires successful information transfer within cortical-basal ganglia loop circuits to produce the desired acoustic output. For this reason, up to 90% of Parkinson’s disease patients experience impairments of speech articulation. Deep brain stimulation (DBS) is highly effective in controlling the symptoms of Parkinson’s disease, sometimes alongside speech improvement, but subthalamic nucleus (STN) DBS can also lead to decreases in semantic and phonological fluency. This paradox demands better understanding of the interactions between the cortical speech network and the STN, which can be investigated with intracranial EEG recordings collected during DBS implantation surgery. We analyzed the propagation of high-gamma activity between STN, superior temporal gyrus (STG), and ventral sensorimotor cortices during reading aloud via event-related causality, a method that estimates strengths and directionalities of neural activity propagation. We employed a newly developed bivariate smoothing model based on a two-dimensional moving average, which is optimal for reducing random noise while retaining a sharp step response, to ensure precise embedding of statistical significance in the time–frequency space. Sustained and reciprocal neural interactions between STN and ventral sensorimotor cortex were observed. Moreover, high-gamma activity propagated from the STG to the STN prior to speech onset. The strength of this influence was affected by the lexical status of the utterance, with increased activity propagation during word versus pseudoword reading. These unique data suggest a potential role for the STN in the feedforward control of speech.

ObjectiveWe evaluated whether the combination of epileptiform spikes and ripples (spike ripples) outperformed other leading biomarkers in identifying the epileptogenic zone across subjects in a multicenter international study.MethodsWe validated and applied an automated spike ripple detector on intracranial EEG recordings in subjects from 4 centers who subsequently underwent surgical resection with known 1-year seizure outcomes. We evaluated the spike ripple rate in subjects cured after resection (ILAE 1 outcome) and those with persistent seizures (ILAE 2-5) across sites and recording types. We also evaluated spike, wideband HFO (80-500 Hz), fast ripple (250-500 Hz), and ripple (80-250 Hz) rates using validated automated detectors. The proportion of resected events was computed and compared across subject outcomes and biomarkers.Results109 subjects were included. The majority of spike ripples were removed in subjects with ILAE 1 outcome (p = 1e-6), and this was qualitatively observed across the four sites (p = 0.032, p = 0.092, p = 0.0005, p = 0.003) and the two electrode types (p = 0.01, p = 7e-6). A higher proportion of spike ripples were removed in subjects with ILAE 1 outcomes compared to ILAE 2-5 outcomes (p = 0.02). Among ILAE 1 subjects, the proportion of spike ripples removed was higher than the proportion of spikes (p = 0.0004), wideband HFOs (p = 0.0004), fast ripples (p = 0.008), and ripples (p = 0.008) removed. At the individual level, more subjects with ILAE 1 outcome had the majority of spike ripples removed (40/48, 83%) than spikes (69%, p = 0.04), wideband HFOs (63%, p = 0.009), fast ripples (36%, p = 2e-5), or ripples (45%, p = 0.0007) removed.InterpretationWhen surgical resection was successful, the majority of spike ripples were removed. Automatically detected spike ripples have improved specificity for epileptogenic tissue compared to spikes, wideband HFOs, fast ripples, and ripples.

SummarySubanesthetic doses of ketamine produce rapid and sustained anti-depressant effects in patients with treatment-resistant depression. Unfortunately, the usefulness of ketamine as a treatment is limited by its potential for abuse because of psychotropic side effects such as dissociation. Understanding the brain dynamics and the neural circuits involved in ketamine’s effects could lend insight into improved therapies for depression with fewer adverse effects. It is believed that ketamine acts via NMDA receptor and hyperpolarization-activated cyclic nucleotide-gated 1 (HCN1) channels to produce changes in oscillatory brain dynamics. Here we show, in humans, a detailed description of the principal oscillatory changes in cortical and subcortical structures by administration of a subanesthetic dose of ketamine. Using recordings from intracranial electrodes, we found that ketamine increased gamma oscillations within prefrontal cortical areas and the hippocampus--structures previously implicated in ketamine’s antidepressant effects. Furthermore, our studies provide direct evidence of a ketamine-induced 3 Hz oscillation in posteromedial cortex that has been proposed as a mechanism for its dissociative effects. By analyzing changes in neural oscillations after the addition of propofol, whose GABAergic activity antagonizes ketamine’s NMDA-mediated disinhibition alongside a shared HCN1 inhibitory effect, we identified brain dynamics that could be attributed to NMDA-mediated disinhibition versus HCN1 inhibition. Overall, our results imply that ketamine engages different neural circuits in distinct frequency-dependent patterns of activity to produce its antidepressant and dissociative sensory effects. These insights may help guide the development of novel brain dynamic biomarkers and therapeutics for depression.

HYPOTHESIS: Among other functions, mucins hydrate and protect biological interfaces from mechanical challenges. Mucins also attract interest as biocompatible coatings with excellent lubrication performance. Therefore, it is of high interest to understand the structural response of mucin films to mechanical challenges. We hypothesized that this could be done with Neutron Reflectometry using a novel sample environment where mechanical confinement is achieved by inflating a membrane against the films. EXPERIMENTS: Oral MUC5B mucin films were investigated by Force Microscopy/Spectroscopy and Neutron Reflectometry both at solid-liquid interfaces and under mechanical confinement. FINDINGS: NR indicated that MUC5B films were almost completely compressed and dehydrated when confined at 1 bar. This was supported by Force Microscopy/Spectroscopy investigations. Force Spectroscopy also indicated that MUC5B films could withstand mechanical confinement by means of steric interactions for pressures lower than ∼ 0.5 bar i.e., mucins could protect interfaces from mechanical challenges of this magnitude while keeping them hydrated. To investigate mucin films under these pressures by means of the employed sample environment for NR, further technological developments are needed. The most critical would be identifying or developing more flexible membranes that would still meet certain requirements like chemical homogeneity and very low roughness.

Consciousness is not explained by a single mechanism, rather it involves multiple specialized neural systems overlapping in space and time. We hypothesize that synergistic, large-scale subcortical and cortical attention and signal processing networks encode conscious experiences. To identify brain activity in conscious perception without overt report, we classified visual stimuli as perceived or not using eye measurements. Report-independent event-related potentials and functional magnetic resonance imaging (fMRI) signals both occurred at early times after stimuli. Direct recordings revealed a novel thalamic awareness potential linked to conscious visual perception based on report. fMRI showed thalamic and cortical detection, arousal, attentional salience, task-positive, and default mode networks were involved independent of overt report. These findings identify a specific sequence of neural mechanisms in human conscious visual perception.One-Sentence SummaryHuman conscious visual perception engages large-scale subcortical and cortical networks even without overt report.

Speaking precisely is important for effective verbal communication, and articulatory gain is one component of speech motor control that contributes to achieving this goal. Given that the basal ganglia have been proposed to regulate the speed and size of limb movement, that is, movement gain, we explored the basal ganglia contribution to articulatory gain, through local field potentials (LFP) recorded simultaneously from the subthalamic nucleus (STN), precentral gyrus, and postcentral gyrus. During STN deep brain stimulation implantation for Parkinson’s disease, participants read aloud consonant-vowel-consonant syllables. Articulatory gain was indirectly assessed using the F2 Ratio, an acoustic measurement of the second formant frequency of/i/vowels divided by/u/vowels. Mixed effects models demonstrated that the F2 Ratio correlated with alpha and theta activity in the precentral gyrus and STN. No correlations were observed for the postcentral gyrus. Functional connectivity analysis revealed that higher phase locking values for beta activity between the STN and precentral gyrus were correlated with lower F2 Ratios, suggesting that higher beta synchrony impairs articulatory precision. Effects were not related to disease severity. These data suggest that articulatory gain is encoded within the basal ganglia-cortical loop.

Epilepsy is a chronic brain disorder, and for at least one- third of epilepsy patients, medications do not adequately control seizures and surgery is the only potential cure. An automated seizure detector that requires a short period of normal EEG would shorten the seizure monitoring durations, decrease the need for manual assessment of large amount of recorded EEG data, and accordingly assist the neurologists focus on improving quality of care. In this work, we propose a novel approach based on the extended cumulative sum test to detect seizures using intracranial EEG. Different than the existing machine learning approaches, this method requires only a short period of normal EEG for training. In addition to a new proposed feature based on partial directed coherence and random graph theory, in this work, previously developed features used to characterize seizures are used as features in cumulative sum test for seizure detection. A total of 33 intracranial EEG recordings collected from a total of 9 patients corresponding to three different datasets have been used for the analysis purposes: (i) the first dataset includes 11 recorded EEG files (~12.5 min) from 4 patients; (ii) the second dataset includes 20 recorded EEG files (~30 min) from 4 patients; and (iii) two 24-hour long EEG files from a single patient. The proposed detector achieved a mean sensitivity and mean specificity for the first (0.77, 0.86), second (0.88, 0.9) and third datasets (0.92, 0.94) respectively. Statistical detection of seizures has shown success in detecting seizures without the need for highly customizable parameters or previously labelled EEG data. The proposed method could be used in real-time at hospital settings with a minimum requirement of training data.

Many language functions are traditionally assigned to cortical brain areas, leaving the contributions of subcortical structures to language processing largely unspecified. The present study examines a potential role of the subthalamic nucleus (STN) in lexical processing, specifically, reading aloud of words (e.g., 'fate') and pseudowords (e.g., 'fape'). We recorded local field potentials simultaneously from the STN and the cortex (precentral, postcentral, and superior temporal gyri) of 13 people with Parkinson's disease undergoing awake deep brain stimulation and compared STN's lexicality-related neural activity with that of the cortex. Both STN and cortical activity demonstrated significant task-related modulations, but the lexicality effects were different in the two brain structures. In the STN, an increase in gamma band activity (31-70 Hz) was present in pseudoword trials compared to word trials during subjects' spoken response. In the cortex, a greater decrease in beta band activity (12-30 Hz) was observed for pseudowords in the precentral gyrus. Additionally, 11 individual cortical sites showed lexicality effects with varying temporal and topographic characteristics in the alpha and beta frequency bands. These findings suggest that the STN and the sampled cortical regions are involved differently in the processing of lexical distinctions.