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Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.

BACKGROUND: Fragile X syndrome (FXS) and autism spectrum disorder (ASD) are neurodevelopmental conditions that often have a substantial impact on daily functioning and quality of life. FXS is the most common cause of inherited intellectual disability (ID) and the most common monogenetic cause of ASD. Previous literature has shown that electrophysiological activity measured by electroencephalogram (EEG) during resting state is perturbated in FXS and ASD. However, whether electrophysiological profiles of participants with FXS and ASD are similar remains unclear. The aim of this study was to compare EEG alterations found in these two clinical populations presenting varying degrees of cognitive and behavioral impairments. METHODS: Resting state EEG signal complexity, alpha peak frequency (APF) and power spectral density (PSD) were compared between 47 participants with FXS (aged between 5-20), 49 participants with ASD (aged between 6-17), and 52 neurotypical (NT) controls with a similar age distribution using MANCOVAs with age as covariate when appropriate. MANCOVAs controlling for age, when appropriate, and nonverbal intelligence quotient (NVIQ) score were subsequently performed to determine the impact of cognitive functioning on EEG alterations. RESULTS: Our results showed that FXS participants manifested decreased signal complexity and APF compared to ASD participants and NT controls, as well as altered power in the theta, alpha and low gamma frequency bands. ASD participants showed exaggerated beta power compared to FXS participants and NT controls, as well as enhanced low and high gamma power compared to NT controls. However, ASD participants did not manifest altered signal complexity or APF. Furthermore, when controlling for NVIQ, results of decreased complexity in higher scales and lower APF in FXS participants compared to NT controls and ASD participants were not replicated. CONCLUSIONS: These findings suggest that signal complexity and APF might reflect cognitive functioning, while altered power in the low gamma frequency band might be associated with neurodevelopmental conditions, particularly FXS and ASD.

Alterations in functional connectivity (FC) have been observed in individuals with Alzheimers disease (AD) with elevated amyloid (Aβ) and tau. However, it is not yet known whether directed FC is already influenced by Aβ and tau load in cognitively healthy (CH) individuals. A 21-channel electroencephalogram (EEG) was used from 46 CHs classified based on cerebrospinal fluid (CSF) Aβ tau ratio: pathological (CH-PAT) or normal (CH-NAT). Directed FC was estimated with Partial Directed Coherence in frontal, temporal, parietal, central, and occipital regions. We also examined the correlations between directed FC and various functional metrics, including neuropsychology, cognitive reserve, MRI volumetrics, and heart rate variability between both groups. Compared to CH-NATs, the CH-PATs showed decreased FC from the temporal regions, indicating a loss of relative functional importance of the temporal regions. In addition, frontal regions showed enhanced FC in the CH-PATs compared to CH-NATs, suggesting neural compensation for the damage caused by the pathology. Moreover, CH-PATs showed greater FC in the frontal and occipital regions than CH-NATs. Our findings provide a useful and non-invasive method for EEG-based analysis to identify alterations in brain connectivity in CHs with a pathological versus normal CSF Aβ/tau.

Neural wearables can enable life-saving drowsiness and health monitoring for pilots and drivers. While existing in-cabin sensors may provide alerts, wearables can enable monitoring across more environments. Current neural wearables are promising but most require wet-electrodes and bulky electronics. This work showcases in-ear, dry-electrode earpieces used to monitor drowsiness with compact hardware. The employed system integrates additive-manufacturing for dry, user-generic earpieces, existing wireless electronics, and offline classification algorithms. Thirty-five hours of electrophysiological data were recorded across nine subjects performing drowsiness-inducing tasks. Three classifier models were trained with user-specific, leave-one-trial-out, and leave-one-user-out splits. The support-vector-machine classifier achieved an accuracy of 93.2% while evaluating users it has seen before and 93.3% when evaluating a never-before-seen user. These results demonstrate wireless, dry, user-generic earpieces used to classify drowsiness with comparable accuracies to existing state-of-the-art, wet electrode in-ear and scalp systems. Further, this work illustrates the feasibility of population-trained classification in future electrophysiological applications.

OBJECTIVE: ADHD is a prevalent neurodevelopmental disorder characterized by symptoms of inattention and hyperactivity-impulsivity. Impairments in executive functioning (EF) are central to models of ADHD, while alpha-band spectral power event-related decreases (ERD) have emerged as a putative electroencephalography (EEG) biomarker of EF in ADHD. Little is known about the roles of EF and alpha ERD and their interactions with symptoms of ADHD. METHOD: We estimated network models of ADHD symptoms and integrated alpha ERD measures into the symptom network. RESULTS: EF emerges as a bridge network node connecting alpha ERD and the hyperactivity/impulsivity and inattention symptoms. We found that EF most closely relates to a subset of symptoms, namely the motoric symptoms, seat (difficulty staying seated), and runs (running or climbing excessively). CONCLUSIONS: EF functions as a bridge node connecting alpha ERD and the ADHD symptom network. Motoric-type symptoms and EF deficits may constitute important nodes in the interplay between behavior/symptoms, cognition, and neurophysiological markers of ADHD.

The auditory steady state response (ASSR) arises when periodic sounds evoke stable responses in auditory networks that reflect the acoustic characteristics of the stimuli, such as the amplitude of the sound envelope. Larger for some stimulus rates than others, the ASSR in the human electroencephalogram (EEG) is notably maximal for sounds modulated in amplitude at 40 Hz. To investigate the local circuit underpinnings of the large ASSR to 40 Hz amplitude-modulated (AM) sounds, we acquired skull EEG and local field potential (LFP) recordings from primary auditory cortex (A1) in the rat during the presentation of 20, 30, 40, 50, and 80 Hz AM tones. 40 Hz AM tones elicited the largest ASSR from the EEG acquired above auditory cortex and the LFP acquired from each cortical layer in A1. The large ASSR in the EEG to 40 Hz AM tones was not due to larger instantaneous amplitude of the signals or to greater phase alignment of the LFP across the cortical layers. Instead, it resulted from decreased latency variability (or enhanced temporal consistency) of the 40 Hz response. Statistical models indicate the EEG signal was best predicted by LFPs in either the most superficial or deep cortical layers, suggesting deep layer coordinators of the ASSR. Overall, our results indicate that the recruitment of non-uniform but more temporally consistent responses across A1 layers underlie the larger ASSR to amplitude-modulated tones at 40 Hz.

BACKGROUND: In the United States, there are over seven million stroke survivors, with many facing gait impairments due to foot drop. This restricts their community ambulation and hinders functional independence, leading to several long-term health complications. Despite the best available physical therapy, gait function is incompletely recovered, and this occurs mainly during the acute phase post-stroke. Therapeutic options are limited currently. Novel therapies based on neurobiological principles have the potential to lead to long-term functional improvements. The Brain-Computer Interface (BCI) controlled Functional Electrical Stimulation (FES) system is one such strategy. It is based on Hebbian principles and has shown promise in early feasibility studies. The current study describes the BCI-FES clinical trial, which examines the safety and efficacy of this system, compared to conventional physical therapy (PT), to improve gait velocity for those with chronic gait impairment post-stroke. The trial also aims to find other secondary factors that may impact or accompany these improvements and establish the potential of Hebbian-based rehabilitation therapies. METHODS: This Phase II clinical trial is a two-arm, randomized, controlled, longitudinal study with 66 stroke participants in the chronic (> 6 months) stage of gait impairment. The participants undergo either BCI-FES paired with PT or dose-matched PT sessions (three times weekly for four weeks). The primary outcome is gait velocity (10-meter walk test), and secondary outcomes include gait endurance, range of motion, strength, sensation, quality of life, and neurophysiological biomarkers. These measures are acquired longitudinally. DISCUSSION: BCI-FES holds promise for gait velocity improvements in stroke patients. This clinical trial will evaluate the safety and efficacy of BCI-FES therapy when compared to dose-matched conventional therapy. The success of this trial will inform the potential utility of a Phase III efficacy trial. TRIAL REGISTRATION: The trial was registered as BCI-FES Therapy for Stroke Rehabilitation on February 19, 2020, at clinicaltrials.gov with the identifier NCT04279067.

OBJECTIVE: Relapse of epileptic spasms after initial treatment of infantile epileptic spasms syndrome (IESS) is common. However, past studies of small cohorts have inconsistently linked relapse risk to etiology, treatment modality, and EEG features upon response. Using a large single-center IESS cohort, we set out to quantify the risk of epileptic spasms relapse and identify specific risk factors. METHODS: We identified all children with epileptic spasms at our center using a clinical EEG database. Using the electronic medical record, we confirmed IESS syndrome classification and ascertained treatment, response, time to relapse, etiology, EEG features, and other demographic factors. Relapse-free survival analysis was carried out using Cox proportional hazards regression. RESULTS: Among 599 children with IESS, 197 specifically responded to hormonal therapy and/or vigabatrin (as opposed to surgery or other second-line treatments). In this study, 41 (21%) subjects exhibited relapse of epileptic spasms within 12 months of response. Longer duration of IESS prior to response (>3 months) was strongly associated with shorter latency to relapse (hazard ratio = 3.11; 95% CI 1.59-6.10; p = 0.001). Relapse was not associated with etiology, developmental status, or any post-treatment EEG feature. SIGNIFICANCE: This study suggests that long duration of IESS before response is the single largest clinical predictor of relapse risk, and therefore underscores the importance of prompt and successful initial treatment. Further study is needed to evaluate candidate biomarkers of epileptic spasms relapse and identify treatments to mitigate this risk. PLAIN LANGUAGE SUMMARY: Relapse of infantile spasms is common after initially successful treatment. With study of a large group of children with infantile spasms, we determined that relapse is linked to long duration of infantile spasms. In contrast, relapse was not associated with the cause of infantile spasms, developmental measures, or EEG features at the time of initial response. Further study is needed to identify tools to predict impending relapse of infantile spasms.

Principal component analysis (PCA) has been widely employed for dimensionality reduction prior to multivariate pattern classification (decoding) in EEG research. The goal of the present study was to provide an evaluation of the effectiveness of PCA on decoding accuracy (using support vector machines) across a broad range of experimental paradigms. We evaluated several different PCA variations, including group-based and subject-based component decomposition and the application of Varimax rotation or no rotation. We also varied the numbers of PCs that were retained for the decoding analysis. We evaluated the resulting decoding accuracy for seven common event-related potential components (N170, mismatch negativity, N2pc, P3b, N400, lateralized readiness potential, and error-related negativity). We also examined more challenging decoding tasks, including decoding of face identity, facial expression, stimulus location, and stimulus orientation. The datasets also varied in the number and density of electrode sites. Our findings indicated that none of the PCA approaches consistently improved decoding performance related to no PCA, and the application of PCA frequently reduced decoding performance. Researchers should therefore be cautious about using PCA prior to decoding EEG data from similar experimental paradigms, populations, and recording setups.

Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

Functional mapping during brain surgery is applied to define brain areas that control critical functions and cannot be removed. Currently, these procedures rely on verbal interactions between the neurosurgeon and electrophysiologist, which can be time-consuming. In addition, the electrode grids that are used to measure brain activity and to identify the boundaries of pathological versus functional brain regions have low resolution and limited conformity to the brain surface. Here, we present the development of an intracranial electroencephalogram (iEEG)-microdisplay that consists of freestanding arrays of 2048 GaN light-emitting diodes laminated on the back of micro-electrocorticography electrode grids. With a series of proof-of-concept experiments in rats and pigs, we demonstrate that these iEEG-microdisplays allowed us to perform real-time iEEG recordings and display cortical activities by spatially corresponding light patterns on the surface of the brain in the surgical field. Furthermore, iEEG-microdisplays allowed us to identify and display cortical landmarks and pathological activities from rat and pig models. Using a dual-color iEEG-microdisplay, we demonstrated coregistration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The iEEG-microdisplay holds promise to facilitate monitoring of pathological brain activity in clinical settings.

Observers can discriminate between correct versus incorrect perceptual decisions with feelings of confidence. The centro-parietal positivity build-up rate (CPP slope) has been suggested as a likely neural signature of accumulated evidence, which may guide both perceptual performance and confidence. However, CPP slope also covaries with reaction time, which also covaries with confidence in previous studies, and performance and confidence typically covary; thus, CPP slope may index signatures of perceptual performance rather than confidence per se. Moreover, perceptual metacognition-including neural correlates-has largely been studied in vision, with few exceptions. Thus, we lack understanding of domain-general neural signatures of perceptual metacognition outside vision. Here we designed a novel auditory pitch identification task and collected behavior with simultaneous 32-channel EEG in healthy adults. Participants saw two tone labels which varied in tonal distance on each trial (e.g., C vs D, C vs F), then heard a single auditory tone; they identified which label was correct and rated confidence. We found that pitch identification confidence varied with tonal distance, but performance, metacognitive sensitivity (trial-by-trial covariation of confidence with accuracy), and reaction time did not. Interestingly, however, while CPP slope covaried with performance and reaction time, it did not significantly covary with confidence. We interpret these results to mean that CPP slope is likely a signature of first-order perceptual processing and not confidence-specific signals or computations in auditory tasks. Our novel pitch identification task offers a valuable method to examine the neural correlates of auditory and domain-general perceptual confidence.

A large body of research has linked childhood family socioeconomic status (SES) to neurodevelopment in childhood and adolescence. However, it remains unclear to what extent childhood family SES relates to brain functioning in adulthood. To address this gap, the present study investigated the associations between retrospective accounts of objective and subjective childhood family SES and two well-established electrophysiological indices of brain functioning in adulthood-the MMN and P3b event-related potentials (ERP) components, as neural correlates of automatic change detection and cognitive control respectively. Higher objective childhood family SES, as proxied by parent educational attainment in childhood, was associated with larger (more positive) P3b amplitudes in adulthood. In contrast, there was no association between childhood parent educational attainment and the magnitude of MMN. Adult reports of subjective family SES during childhood were not related to the magnitude of MMN or P3b. These findings suggest that the links between childhood parent educational attainment and brain functioning may extend into adulthood, especially for brain functions supporting cognitive control. These results also imply that, when using retrospective accounts of childhood family SES, objective and subjective reports likely proxy different childhood experiences that have distinct links with specific neurodevelopmental outcomes, and that some of these links may not persist into adulthood. Our findings lay the groundwork for future investigations on how and why childhood family SES relates to brain functioning in adulthood.

BackgroundSleep disturbances are a prevalent and complex comorbidity in neurodevelopmental disorders (NDDs). Dup15q syndrome (duplications of 15q11.2-13.1) is a genetic disorder highly penetrant for NDDs such as autism and intellectual disability and it is frequently accompanied by significant disruptions in sleep patterns. The 15q critical region harbors genes crucial for brain development, notably UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We previously described an electrophysiological biomarker of the syndrome, marked by heightened beta oscillations (12-30 Hz) in individuals with Dup15q syndrome, akin to electroencephalogram (EEG) alterations induced by allosteric modulation of GABAARs. Those with Dup15q syndrome exhibited increased beta oscillations during the awake resting state and during sleep, and they showed profoundly abnormal NREM sleep. This study aims to assess the translational validity of these EEG signatures and to delve into their neurobiological underpinnings by quantifying sleep physiology in chromosome-engineered mice with maternal (matDp/ + mice) or paternal (patDp/ + mice) inheritance of the full 15q11.2-13.1-equivalent duplication, and mice with duplication of just the UBE3A gene (Ube3a overexpression mice; Ube3a OE mice) and comparing the sleep metrics with their respective wildtype (WT) littermate controls.MethodsWe collected 48-h EEG/EMG recordings from 35 (23 male, 12 female) 12-24-week-old matDp/ + , patDp/ + , Ube3a OE mice, and their WT littermate controls. We quantified baseline sleep, sleep fragmentation, spectral power dynamics during sleep states, and recovery following sleep deprivation. Within each group, distinctions between Dup15q mutant mice and WT littermate controls were evaluated using analysis of variance (ANOVA) and student's t-test. The impact of genotype and time was discerned through repeated measures ANOVA, and significance was established at p

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

A prominent theoretical framework spanning philosophy, psychology, and neuroscience holds that selective attention penetrates early stages of perceptual processing to alter the subjective visual experience of behaviorally relevant stimuli. For example, searching for a red apple at the grocery store might make the relevant color appear brighter and more saturated compared with seeing the exact same red apple while searching for a yellow banana. In contrast, recent proposals argue that data supporting attention-related changes in appearance reflect decision- and motor-level response biases without concurrent changes in perceptual experience. Here, we tested these accounts by evaluating attentional modulations of EEG responses recorded from male and female human subjects while they compared the perceived contrast of attended and unattended visual stimuli rendered at different levels of physical contrast. We found that attention enhanced the amplitude of the P1 component, an early evoked potential measured over visual cortex. A linking model based on signal detection theory suggests that response gain modulations of the P1 component track attention-induced changes in perceived contrast as measured with behavior. In contrast, attentional cues induced changes in the baseline amplitude of posterior alpha band oscillations (∼9-12 Hz), an effect that best accounts for cue-induced response biases, particularly when no stimuli are presented or when competing stimuli are similar and decisional uncertainty is high. The observation of dissociable neural markers that are linked to changes in subjective appearance and response bias supports a more unified theoretical account and demonstrates an approach to isolate subjective aspects of selective information processing.SIGNIFICANCE STATEMENT Does attention alter visual appearance, or does it simply induce response bias? In the present study, we examined these competing accounts using EEG and linking models based on signal detection theory. We found that response gain modulations of the visually evoked P1 component best accounted for attention-induced changes in visual appearance. In contrast, cue-induced baseline shifts in alpha band activity better explained response biases. Together, these results suggest that attention concurrently impacts visual appearance and response bias, and that these processes can be experimentally isolated.

Study objectivesAdolescence is characterized by significant brain development, accompanied by changes in sleep timing and architecture. It also is a period of profound psychosocial changes, including the initiation of alcohol use; however, it is unknown how alcohol use affects sleep architecture in the context of adolescent development. We tracked developmental changes in polysomnographic (PSG) and electroencephalographic (EEG) sleep measures and their relationship with emergent alcohol use in adolescents considering confounding effects (e.g. cannabis use).MethodsAdolescents (n = 94, 43% female, age: 12-21 years) in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study had annual laboratory PSG recordings across 4-years. Participants were no/low drinkers at baseline.ResultsLinear mixed effect models showed developmental changes in sleep macrostructure and EEG, including a decrease in slow wave sleep and slow wave (delta) EEG activity with advancing age. Emergent moderate/heavy alcohol use across three follow-up years was associated with a decline in percentage rapid eye movement (REM) sleep over time, a longer sleep onset latency (SOL) and shorter total sleep time (TST) in older adolescents, and lower non-REM delta and theta power in males.ConclusionsThese longitudinal data show substantial developmental changes in sleep architecture. Emergent alcohol use during this period was associated with altered sleep continuity, architecture, and EEG measures, with some effects dependent on age and sex. These effects, in part, could be attributed to the effects of alcohol on underlying brain maturation processes involved in sleep-wake regulation.

Language comprehension must require some degree of attentional focus, but how do periods of inattention and/or split attention impact how language is processed? Here EEG was recorded while participants listened to full-length stories, and were periodically asked about whether they were fully attentive, were completely inattentive, or felt that they were in a split attention state. The ERP response to the words immediately preceding these attention questions was examined as a function of participant response, which allowed for the comparison of word processing in each of these attentional states. When participants were on-task, typical N400 effects of lexical frequency (smaller N400 for common compared to less common words), word position (smaller N400 for words appearing late in a sentence compared to words appearing with less preceding context), and surprisal (smaller N400 for relatively expected words compared to relatively unexpected words) were observed. When participants were in a fully inattentive state, the word-level effect of frequency was intact, but the context-dependent effects of word position and surprisal were significantly reduced. Interestingly, the pattern of results when participants were in a split attention state closely matched that of the fully inattentive state. Overall, the results demonstrate how attentional state influences sensitivity to language context during comprehension, and show that the consequences of inattention and split attention on word processing in context are quite similar, at least on the indices measured here.

Prior research has found that iconicity facilitates sign production in picture-naming paradigms and has effects on ERP components. These findings may be explained by two separate hypotheses: (1) a task-specific hypothesis that suggests these effects occur because visual features of the iconic sign form can map onto the visual features of the pictures, and (2) a semantic feature hypothesis that suggests that the retrieval of iconic signs results in greater semantic activation due to the robust representation of sensory-motor semantic features compared to non-iconic signs. To test these two hypotheses, iconic and non-iconic American Sign Language (ASL) signs were elicited from deaf native/early signers using a picture-naming task and an English-to-ASL translation task, while electrophysiological recordings were made. Behavioral facilitation (faster response times) and reduced negativities were observed for iconic signs (both prior to and within the N400 time window), but only in the picture-naming task. No ERP or behavioral differences were found between iconic and non-iconic signs in the translation task. This pattern of results supports the task-specific hypothesis and provides evidence that iconicity only facilitates sign production when the eliciting stimulus and the form of the sign can visually overlap (a picture-sign alignment effect).

ObjectiveTo describe the clinical signs, electroencephalographic (EEG) findings, treatment, and outcome in a dog after successful resuscitation from out-of-hospital cardiopulmonary arrest (OHCA) induced by pentobarbital intoxication.Case summaryA 10-year-old, male intact Jack Russell Terrier was referred for management of refractory status epilepticus and presented dead on arrival. After 7 minutes of cardiopulmonary resuscitation, return of spontaneous circulation was achieved, but the dog remained comatose, apneic, and lacked brainstem reflexes on neurological examination 6 hours following resuscitation. Magnetic resonance imaging showed polioencephalomalacia consistent with prolonged epileptiform activity, and EEG was initially concerning for electrocerebral inactivity. Following supportive care that included short-term mechanical ventilation, the dog made a full recovery and was discharged from the hospital alive 7 days postresuscitation. It was later revealed that the dog had been administered an unknown amount of pentobarbital during transportation, which likely contributed to the OHCA, clinical, and EEG findings.New information providedThis is the first report to describe the full recovery and hospital discharge of a dog suffering OHCA and the first description of EEG findings in a clinical veterinary patient following cardiopulmonary arrest and successful resuscitation. Factors likely contributing to successful patient outcome and potential benefits and limitations of EEG in monitoring postcardiac arrest patients are discussed.

BackgroundMajor depressive disorder (MDD) and chronic pain are highly comorbid, and pain symptoms are associated with a poorer response to antidepressant medication treatment. It is unclear whether comorbid pain also is associated with a poorer response to treatment with repetitive transcranial magnetic stimulation (rTMS).Methods162 MDD subjects received 30 sessions of 10 Hz rTMS treatment administered to the left dorsolateral prefrontal cortex (DLPFC) with depression and pain symptoms measured before and after treatment. For a subset of 96 patients, a resting-state electroencephalogram (EEG) was recorded at baseline. Clinical outcome was compared between subjects with and without comorbid pain, and the relationships among outcome, pain severity, individual peak alpha frequency (PAF), and PAF phase-coherence in the EEG were examined.Results64.8% of all subjects reported pain, and both depressive and pain symptoms were significantly reduced after rTMS treatment, irrespective of age or gender. Patients with severe pain were 27% less likely to respond to MDD treatment than pain-free individuals. PAF was positively associated with pain severity. PAF phase-coherence in the somatosensory and default mode networks was significantly lower for MDD subjects with pain who failed to respond to MDD treatment.ConclusionsPain symptoms improved after rTMS to left DLPFC in MDD irrespective of age or gender, although the presence of chronic pain symptoms reduced the likelihood of treatment response. Individual PAF and baseline phase-coherence in the sensorimotor and midline regions may represent predictors of rTMS treatment outcome in comorbid pain and MDD.

ObjectiveThe combination of d-methylphenidate and guanfacine (an α-2A adrenergic agonist) may be an effective alternative to either agent as monotherapy in children with attention-deficit/hyperactivity disorder (ADHD). This study investigated the neural mechanisms underlying medication effects using cortical source analysis of electroencephalography (EEG) data.MethodA total of 172 children with ADHD (aged 7-14; 118 boys) completed an 8-week randomized, double-blind, comparative study with 3 treatment arms: d-methylphenidate, guanfacine, or their combination. EEG modulations of brain oscillations at baseline and end point were measured during a spatial working memory task from cortical sources localized within the anterior cingulate (midfrontal) and primary visual cortex (midoccipital), based on previously reported ADHD and control differences. Linear mixed models examined treatment effects on EEG and performance measures.ResultsCombined treatment decreased midoccipital EEG power across most frequency bands and task phases. Several midoccipital EEG measures also showed significantly greater changes with combined treatment than with monotherapies. D-methylphenidate significantly increased midoccipital theta during retrieval, while guanfacine produced only trend-level reductions in midoccipital alpha during maintenance and retrieval. Task accuracy improved with combined treatment, was unchanged with d-methylphenidate, and worsened with guanfacine. Treatment-related changes in midoccipital power correlated with improvement in ADHD severity.ConclusionThese findings show that combined treatment ameliorates midoccipital neural activity associated with treatment-related behavioral improvements and previously implicated in visuo-attentional deficits in ADHD. Both monotherapies had limited effects on EEG measures, with guanfacine further showing detrimental effects on performance. The identified midoccipital EEG profile may aid future treatment monitoring for children with ADHD.Clinical trial registration informationSingle Versus Combination Medication Treatment for Children With Attention Deficit Hyperactivity Disorder (Project1); https://clinicaltrials.gov/; NCT00429273.Diversity & inclusion statementWe worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure sex and gender balance in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. We actively worked to promote sex and gender balance in our author group.

Pediatric anxiety disorders are characterized by potentiated threat responses and maladaptive emotion regulation (ER). The Late Positive Potential (LPP) is a neural index of heightened attention to emotional stimuli. Anxious individuals typically exhibit a larger LPP to unpleasant stimuli, but the LPP may also be blunted to unpleasant and pleasant stimuli for those with co-morbid depression. While a larger LPP is thought to reflect greater emotional reactivity, it is unknown to what extent variation in the LPP to laboratory stimuli corresponds to daily emotional functioning. We assessed the LPP in the laboratory in response to unpleasant, pleasant, and neutral images in combination with ecological momentary assessment of emotional reactivity and regulation in daily life among youth (9-14 years old; 55 % female) with anxiety disorders (ANX, N = 130) and no psychiatric diagnoses (ND, N = 47). We tested whether LPP amplitudes to unpleasant and pleasant stimuli (vs. neutral) are greater in ANX (vs. ND) youth and whether LPP amplitudes inversely correlate with co-morbid depression symptoms. We also examined associations between the LPP and daily life emotional functioning among ANX and ND youth. We found no group-by-valence effects on LPP amplitudes. Within ANX youth, higher depression symptoms were associated with smaller LPP amplitudes to unpleasant, but not pleasant, stimuli relative to neutral stimuli. Larger LPP amplitudes to emotional (relative to neutral) stimuli were correlated with use of specific ER strategies among ANX and ND youth but not emotional reactivity. While the LPP may reflect initial emotional reactivity to laboratory stimuli, it is associated with ER behaviors, and not emotional reactivity, in daily life.

In humans, sleep spindles are 10- to 16-Hz oscillations lasting approximately 0.5-2 s. Spindles, along with cortical slow oscillations, may facilitate memory consolidation by enabling synaptic plasticity. Early recordings of spindles at the scalp found anterior channels had overall slower frequency than central-posterior channels. This robust, topographical finding led to dichotomizing spindles as "slow" versus "fast," modeled as two distinct spindle generators in frontal versus posterior cortex. Using a large dataset of intracranial stereoelectroencephalographic (sEEG) recordings from 20 patients (13 female, 7 male) and 365 bipolar recordings, we show that the difference in spindle frequency between frontal and parietal channels is comparable to the variability in spindle frequency within the course of individual spindles, across different spindles recorded by a given site, and across sites within a given region. Thus, fast and slow spindles only capture average differences that obscure a much larger underlying overlap in frequency. Furthermore, differences in mean frequency are only one of several ways that spindles differ. For example, compared with parietal, frontal spindles are smaller, tend to occur after parietal when both are engaged, and show a larger decrease in frequency within-spindles. However, frontal and parietal spindles are similar in being longer, less variable, and more widespread than occipital, temporal, and Rolandic spindles. These characteristics are accentuated in spindles which are highly phase-locked to posterior hippocampal spindles. We propose that rather than a strict parietal-fast/frontal-slow dichotomy, spindles differ continuously and quasi-independently in multiple dimensions, with variability due about equally to within-spindle, within-region, and between-region factors.SIGNIFICANCE STATEMENT Sleep spindles are 10- to 16-Hz neural oscillations generated by cortico-thalamic circuits that promote memory consolidation. Spindles are often dichotomized into slow-anterior and fast-posterior categories for cognitive and clinical studies. Here, we show that the anterior-posterior difference in spindle frequency is comparable to that observed between different cycles of individual spindles, between spindles from a given site, or from different sites within a region. Further, we show that spindles vary on other dimensions such as duration, amplitude, spread, primacy and consistency, and that these multiple dimensions vary continuously and largely independently across cortical regions. These findings suggest that multiple continuous variables rather than a strict frequency dichotomy may be more useful biomarkers for memory consolidation or psychiatric disorders.

The crucial role of the parietal cortex in working memory (WM) storage has been identified by fMRI studies. However, it remains unknown whether repeated parietal intermittent theta-burst stimulation (iTBS) can improve WM. In this within-subject randomized controlled study, under the guidance of fMRI-identified parietal activation in the left hemisphere, 22 healthy adults received real and sham iTBS sessions (five consecutive days, 600 pulses per day for each session) with an interval of 9 months between the two sessions. Electroencephalography signals of each subject before and after both iTBS sessions were collected during a change detection task. Changes in contralateral delay activity (CDA) and K-score were then calculated to reflect neural and behavioral WM improvement. Repeated-measures ANOVA suggested that real iTBS increased CDA more than the sham one (p = .011 for iTBS effect). Further analysis showed that this effect was more significant in the left hemisphere than in the right hemisphere (p = .029 for the hemisphere-by-iTBS interaction effect). Pearson correlation analyses showed significant correlations for two conditions between CDA changes in the left hemisphere and K score changes (ps

Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography-derived neural oscillations following stroke using a data-driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting-state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross-validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1-30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20-30 Hz) and alpha (8-12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal-parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R2  = 0-6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal-parietal regions overlooked by traditional hypothesis-driven prediction models.

ObjectiveThe aim was to compare the outcomes of subdural electrode (SDE) implantations versus stereotactic electroencephalography (SEEG), the 2 predominant methods of intracranial electroencephalography (iEEG) performed in difficult-to-localize drug-resistant focal epilepsy.MethodsThe Surgical Therapies Commission of the International League Against Epilepsy created an international registry of iEEG patients implanted between 2005 and 2019 with ≥1 year of follow-up. We used propensity score matching to control exposure selection bias and generate comparable cohorts. Study endpoints were: (1) likelihood of resection after iEEG; (2) seizure freedom at last follow-up; and (3) complications (composite of postoperative infection, symptomatic intracranial hemorrhage, or permanent neurological deficit).ResultsTen study sites from 7 countries and 3 continents contributed 2,012 patients, including 1,468 (73%) eligible for analysis (526 SDE and 942 SEEG), of whom 988 (67%) underwent subsequent resection. Propensity score matching improved covariate balance between exposure groups for all analyses. Propensity-matched patients who underwent SDE had higher odds of subsequent resective surgery (odds ratio [OR] = 1.4, 95% confidence interval [CI] 1.05, 1.84) and higher odds of complications (OR = 2.24, 95% CI 1.34, 3.74; unadjusted: 9.6% after SDE vs 3.3% after SEEG). Odds of seizure freedom in propensity-matched resected patients were 1.66 times higher (95% CI 1.21, 2.26) for SEEG compared with SDE (unadjusted: 55% seizure free after SEEG-guided resections vs 41% after SDE).InterpretationIn comparison to SEEG, SDE evaluations are more likely to lead to brain surgery in patients with drug-resistant epilepsy but have more surgical complications and lower probability of seizure freedom. This comparative-effectiveness study provides the highest feasible evidence level to guide decisions on iEEG. ANN NEUROL 2021;90:927-939.

We studied the role of temporal and spatial changes in high-frequency oscillation (HFO, 80-500 Hz) generation in epileptogenesis following traumatic brain injury (TBI). Experiments were conducted on adult male Sprague Dawley rats. For the TBI group, fluid percussion injury (FPI) on the left sensorimotor area was performed to induce posttraumatic epileptogenesis. For the sham control group, only the craniotomy was performed. After TBI, 8 bipolar micro-electrodes were implanted bilaterally in the prefrontal cortex, perilesional area and homotopic contralateral site, striatum, and hippocampus. Long-term video/local field potential (LFP) recordings were performed for up to 21 weeks to identify and characterize seizures and capture HFOs. The electrode tip locations and the volume of post TBI brain lesions were further estimated by ex-vivo MRI scans. HFOs were detected during slow-wave sleep and categorized as ripple (80-200 Hz) and fast ripple (FR, 250-500 Hz) events. HFO rates and the HFO peak frequencies were compared in the 8 recording locations and across 8-weeks following TBI. Data from 48 rats (8 sham controls and 40 TBI rats) were analyzed. Within the TBI group, 22 rats (55%) developed recurrent spontaneous seizures (E+ group), at an average of 62.2 (+17.1) days, while 18 rats (45%) did not (E- group). We observed that the HFOs in the E+ group had a higher mean peak frequency than the E- group and the sham group (P

BackgroundGenes with multiple co-active promoters appear common in brain, yet little is known about functional requirements for these potentially redundant genomic regulatory elements. SCN1A, which encodes the NaV1.1 sodium channel alpha subunit, is one such gene with two co-active promoters. Mutations in SCN1A are associated with epilepsy, including Dravet syndrome (DS). The majority of DS patients harbor coding mutations causing SCN1A haploinsufficiency; however, putative causal non-coding promoter mutations have been identified.MethodsTo determine the functional role of one of these potentially redundant Scn1a promoters, we focused on the non-coding Scn1a 1b regulatory region, previously described as a non-canonical alternative transcriptional start site. We generated a transgenic mouse line with deletion of the extended evolutionarily conserved 1b non-coding interval and characterized changes in gene and protein expression, and assessed seizure activity and alterations in behavior.ResultsMice harboring a deletion of the 1b non-coding interval exhibited surprisingly severe reductions of Scn1a and NaV1.1 expression throughout the brain. This was accompanied by electroencephalographic and thermal-evoked seizures, and behavioral deficits.ConclusionsThis work contributes to functional dissection of the regulatory wiring of a major epilepsy risk gene, SCN1A. We identified the 1b region as a critical disease-relevant regulatory element and provide evidence that non-canonical and seemingly redundant promoters can have essential function.

BackgroundIndividuals with Fragile X syndrome (FXS) and autism spectrum disorder (ASD) exhibit an array of symptoms, including sociability deficits, increased anxiety, hyperactivity, and sensory hyperexcitability. It is unclear how endocannabinoid (eCB) modulation can be targeted to alleviate neurophysiological abnormalities in FXS as behavioral research reveals benefits to inhibiting cannabinoid (CB) receptor activation and increasing endocannabinoid ligand levels. Here, we hypothesize that enhancement of 2-arachidonoyl-sn-glycerol (2-AG) in Fragile X mental retardation 1 gene knock-out (Fmr1 KO) mice may reduce cortical hyperexcitability and behavioral abnormalities observed in FXS.MethodsTo test whether an increase in 2-AG levels normalized cortical responses in a mouse model of FXS, animals were subjected to electroencephalography (EEG) recording and behavioral assessment following treatment with JZL-184, an irreversible inhibitor of monoacylglycerol lipase (MAGL). Assessment of 2-AG was performed using lipidomic analysis in conjunction with various doses and time points post-administration of JZL-184. Baseline electrocortical activity and evoked responses to sound stimuli were measured using a 30-channel multielectrode array (MEA) in adult male mice before, 4 h, and 1 day post-intraperitoneal injection of JZL-184 or vehicle. Behavior assessment was done using the open field and elevated plus maze 4 h post-treatment.ResultsLipidomic analysis showed that 8 mg/kg JZL-184 significantly increased the levels of 2-AG in the auditory cortex of both Fmr1 KO and WT mice 4 h post-treatment compared to vehicle controls. EEG recordings revealed a reduction in the abnormally enhanced baseline gamma-band power in Fmr1 KO mice and significantly improved evoked synchronization to auditory stimuli in the gamma-band range post-JZL-184 treatment. JZL-184 treatment also ameliorated anxiety-like and hyperactivity phenotypes in Fmr1 KO mice.ConclusionsOverall, these results indicate that increasing 2-AG levels may serve as a potential therapeutic approach to normalize cortical responses and improve behavioral outcomes in FXS and possibly other ASDs.

Organophosphate (OP) nerve agents and pesticides are a class of neurotoxic compounds that can cause status epilepticus (SE), and death following acute high-dose exposures. While the standard of care for acute OP intoxication (atropine, oxime, and high-dose benzodiazepine) can prevent mortality, survivors of OP poisoning often experience long-term brain damage and cognitive deficits. Preclinical studies of acute OP intoxication have primarily used rat models to identify candidate medical countermeasures. However, the mouse offers the advantage of readily available knockout strains for mechanistic studies of acute and chronic consequences of OP-induced SE. Therefore, the main objective of this study was to determine whether a mouse model of acute diisopropylfluorophosphate (DFP) intoxication would produce acute and chronic neurotoxicity similar to that observed in rat models and humans following acute OP intoxication. Adult male C57BL/6J mice injected with DFP (9.5 mg/kg, s.c.) followed 1 min later with atropine sulfate (0.1 mg/kg, i.m.) and 2-pralidoxime (25 mg/kg, i.m.) developed behavioral and electrographic signs of SE within minutes that continued for at least 4 h. Acetylcholinesterase inhibition persisted for at least 3 d in the blood and 14 d in the brain of DFP mice relative to vehicle (VEH) controls. Immunohistochemical analyses revealed significant neurodegeneration and neuroinflammation in multiple brain regions at 1, 7, and 28 d post-exposure in the brains of DFP mice relative to VEH controls. Deficits in locomotor and home-cage behavior were observed in DFP mice at 28 d post-exposure. These findings demonstrate that this mouse model replicates many of the outcomes observed in rats and humans acutely intoxicated with OPs, suggesting the feasibility of using this model for mechanistic studies and therapeutic screening.

Background. Gait impairments are common in Parkinson's disease (PD) and increase falls risk. Visual cues can improve gait in PD, particularly freezing of gait (FOG), but mechanisms involved in visual cue response are unknown. This study aimed to examine brain activity in response to visual cues in people with PD who do (PD+FOG) and do not report FOG (PD-FOG) and explore relationships between attention, brain activity and gait. Methods. Mobile EEG measured brain activity during gait in 20 healthy older adults and 43 PD participants (n=22 PD+FOG, n=21 PD-FOG). Participants walked for 2-minutes with and without visual cues (transverse lines to step over). We report power spectral density (PSD) in Delta (1-4 Hz), Theta (4-7 Hz), Alpha (8-12 Hz), Beta (14-24 Hz) and Gamma (30-50 Hz) bands within clusters of similarly brain localized independent component sources. Results. PSDs within the parietal and occipital lobes were altered when walking with visual cues in PD, particularly in PD+FOG. Between group, differences suggested that parietal sources in PD, particularly with PD+FOG, had larger activity compared to healthy older adults when walking. Within group, visual cues altered brain activity in PD, particularly in PD+FOG, within visual processing brain regions. In PD participants, brain activity differences with cues correlated with gait improvements, and in PD+FOG those with worse attention required more visual attentional processing (reduced alpha PSD) in the occipital lobe. Conclusions. Visual cues improve gait and influence brain activity during walking in PD, particularly in PD+FOG. Findings may allow development of more effective therapeutics.

Effective listening comprehension not only requires processing local linguistic input, but also necessitates incorporating contextual cues available in the global communicative environment. Local sentence processing can be facilitated by pre-activation of likely upcoming input, or predictive processing. Recent evidence suggests that young adults can flexibly adapt local predictive processes based on cues provided by the global communicative environment, such as the reliability of specific speakers. Whether older comprehenders can also flexibly adapt to global contextual cues is currently unknown. Moreover, it is unclear whether the underlying mechanisms supporting local predictive processing differ from those supporting adaptation to global contextual cues. Critically, it is unclear whether these mechanisms change as a function of typical aging. We examined the flexibility of prediction in young and older adults by presenting sentences from speakers whose utterances were typically more or less predictable (i.e., reliable speakers who produced expected words 80% of the time, versus unreliable speakers who produced expected words 20% of the time). For young listeners, global speaker reliability cues modulated neural effects of local predictability on the N400. In contrast, older adults, on average, did not show global modulation of local processing. Importantly, however, cognitive control (i.e., Stroop interference effects) mediated age-related reductions in sensitivity to the reliability of the speaker. Both young and older adults with high cognitive control showed greater N400 effects of predictability during sentences produced by a reliable speaker, suggesting that cognitive control is required to regulate the strength of top-down predictions based on global contextual information. Critically, cognitive control predicted sensitivity to global speaker-specific information but not local predictability cues, suggesting that predictive processing in local sentence contexts may be supported by separable neural mechanisms from adaptation of prediction as a function of global context. These results have important implications for interpreting age-related change in predictive processing, and for drawing more generalized conclusions regarding domain-general versus language-specific accounts of prediction.

ObjectiveTo determine whether screening continuous EEG monitoring (cEEG) is associated with greater odds of treatment success for neonatal seizures.MethodsWe included term neonates with acute symptomatic seizures enrolled in the Neonatal Seizure Registry (NSR), a prospective, multicenter cohort of neonates with seizures. We compared 2 cEEG approaches: (1) screening cEEG, initiated for indications of encephalopathy or paralysis without suspected clinical seizures; and (2) confirmatory cEEG, initiated for the indication of clinical events suspicious for seizures, either alone or in addition to other indications. The primary outcome was successful response to initial seizure treatment, defined as seizures resolved without recurrence within 30 minutes after initial loading dose of antiseizure medicine. Multivariable logistic regression analyses assessed the association between cEEG approach and successful seizure treatment.ResultsAmong 514 neonates included, 161 (31%) had screening cEEG and 353 (69%) had confirmatory cEEG. Neonates with screening cEEG had a higher proportion of successful initial seizure treatment than neonates with confirmatory cEEG (39% vs 18%; p < 0.0001). After adjusting for covariates, there remained a greater odds ratio (OR) for successful initial seizure treatment in the screening vs confirmatory cEEG groups (adjusted OR 2.44, 95% confidence interval 1.45-4.11, p = 0.0008).ConclusionsThese findings provide evidence from a large, contemporary cohort of neonates that a screening cEEG approach may improve odds of successful treatment of acute seizures.Classification of evidenceThis study provides Class III evidence that for neonates a screening cEEG approach, compared to a confirmatory EEG approach, increases the probability of successful treatment of acute seizures.

ObjectiveThe goal of the present study was to determine whether spike and wave discharges (SWDs) and SWDs with superimposed fast ripples (SWDFRs) could be biomarkers of posttraumatic epileptogenesis.MethodsFluid percussion injury was conducted on 13-14-week old male Sprague Dawley rats. Immediately after traumatic brain injury (TBI), they were implanted with microelectrodes in the neocortex, hippocampus, and striatum bilaterally. Age-matched sham rats with the same electrode implantation montage acted as controls. Wideband brain electrical activity was recorded intermittently from Day 1 of TBI, and continued from 2 to 21 weeks after TBI. SWD and SWDFR analysis was performed during the first 2 weeks to investigate whether the occurrence of this pattern predicted development of epilepsy. The remaining 3-21 weeks were used for identifying which rats became epileptic (E+ group) and which did not (E- group).ResultsThe E+ group (n = 9) showed a significant increase in SWD rate in prefrontal cortex during Weeks 1 and 2 after TBI. The E- group showed a significant increase in SWD rate only in the second week. One hundred percent of rats in the E+ group displayed SWDFRs beginning from the first week after TBI. The SWDFR pattern was observed in all recorded brain areas: prefrontal and perilesional cortices, hippocampus, and striatum. None of rats in the E- group showed coexistence of fast ripples with SWDs.SignificanceOccurrence of SWDFRs after TBI, but not an increase in the rate of SWDs, could be a noninvasive electroencephalographic biomarker of posttraumatic epileptogenesis.

ObjectiveThe current study applies a precision medicine approach to trigeminal nerve simulation (TNS), a Food and Drug Administration-approved neuromodulation treatment for attention-deficit/hyperactivity disorder (ADHD), by testing secondary outcomes of cognitive and electroencephalographic [EEG] predictors of treatment response among subjects from the original randomized controlled trial.MethodChildren aged 8 to 12 years with ADHD, were randomized to 4 weeks of active or sham TNS treatment, after which the sham group crossed over into 4 weeks of open-label treatment. TNS treatment responders (RESP) had an ADHD Rating Scale (ADHD-RS) Total score reduction of ≥25%, whereas nonresponders (NR) had

ObjectiveAngelman syndrome (AS) is a severe neurodevelopmental disorder caused by loss of function of the maternally inherited UBE3A gene in neurons. Promising disease-modifying treatments to reinstate UBE3A expression are under development and an early measure of treatment response is critical to their deployment in clinical trials. Increased delta power in EEG recordings, reflecting abnormal neuronal synchrony, occurs in AS across species and correlates with genotype. Whether delta power provides a reliable biomarker for clinical symptoms remains unknown.MethodsWe analyzed combined EEG recordings and developmental assessments in a large cohort of individuals with AS (N = 82 subjects, 133 combined EEG and cognitive assessments, 1.08-28.16 years; 32F) and evaluated delta power as a biomarker for cognitive function, as measured by the Bayley Cognitive Score. We examined the robustness of this biomarker to varying states of consciousness, recording techniques and analysis procedures.ResultsDelta power predicted the Bayley Scale cognitive score (P  4) and predicted performance in expressive (P = 0.0209) and receptive communication (P

Meditation practice is believed to foster states of mindful awareness and mental quiescence in everyday life. If so, then the cultivation of these qualities with training ought to leave its imprint on the activity of intrinsic functional brain networks. In an intensive longitudinal study, we investigated associations between meditation practitioners' experiences of felt mindful awareness and changes in the spontaneous electrophysiological dynamics of functional brain networks. Experienced meditators were randomly assigned to complete 3 months of full-time training in focused-attention meditation (during an initial intervention) or to serve as waiting-list controls and receive training second (during a later intervention). We collected broadband electroencephalogram (EEG) during rest at the beginning, middle, and end of the two training periods. Using a data-driven approach, we segmented the EEG into a time series of transient microstate intervals based on clustering of topographic voltage patterns. Participants also provided daily reports of felt mindful awareness and mental quiescence, and reported daily on four experiential qualities of their meditation practice during training. We found that meditation training led to increases in mindful qualities of awareness, which corroborate contemplative accounts of deepening mental calm and attentional focus. We also observed reductions in the strength and duration of EEG microstates across both interventions. Importantly, changes in the dynamic sequencing of microstates were associated with daily increases in felt attentiveness and serenity during training. Our results connect shifts in subjective qualities of meditative experience with the large-scale dynamics of whole brain functional EEG networks at rest.

Recent evidence suggests that language processing is well-adapted to noise in the input (e.g., spelling or speech errors, misreading or mishearing) and that comprehenders readily correct the input via rational inference over possible intended sentences given probable noise corruptions. In the current study, we probed the processing of noisy linguistic input, asking whether well-studied ERP components may serve as useful indices of this inferential process. In particular, we examined sentences where semantic violations could be attributed to noise-for example, in "The storyteller could turn any incident into an amusing antidote", where the implausible word "antidote" is orthographically and phonologically close to the intended "anecdote". We found that the processing of such sentences-where the probability that the message was corrupted by noise exceeds the probability that it was produced intentionally and perceived accurately-was associated with a reduced (less negative) N400 effect and an increased P600 effect, compared to semantic violations which are unlikely to be attributed to noise ("The storyteller could turn any incident into an amusing hearse"). Further, the magnitudes of these ERP effects were correlated with the probability that the comprehender retrieved a plausible alternative. This work thus adds to the growing body of literature that suggests that many aspects of language processing are optimized for dealing with noise in the input, and opens the door to electrophysiologic investigations of the computations that support the processing of imperfect input.

Loneliness and wisdom have opposing impacts on health and well-being, yet their neuro-cognitive bases have never been simultaneously investigated. In this study of 147 healthy human subjects sampled across the adult lifespan, we simultaneously studied the cognitive and neural correlates of loneliness and wisdom in the context of an emotion bias task. Aligned with the social threat framework of loneliness, we found that loneliness was associated with reduced speed of processing when angry emotional stimuli were presented to bias cognition. In contrast, we found that wisdom was associated with greater speed of processing when happy emotions biased cognition. Source models of electroencephalographic data showed that loneliness was specifically associated with enhanced angry stimulus-driven theta activity in the left transverse temporal region of interest, which is located in the area of the temporoparietal junction (TPJ), while wisdom was specifically related to increased TPJ theta activity during happy stimulus processing. Additionally, enhanced attentiveness to threatening stimuli for lonelier individuals was observed as greater beta activity in left superior parietal cortex, while wisdom significantly related to enhanced happy stimulus-evoked alpha activity in the left insula. Our results demonstrate emotion-context driven modulations in cognitive neural circuits by loneliness versus wisdom.

Sleep spindles are intermittent bursts of 11-15 Hz EEG waves that occur during non-rapid eye movement sleep. Spindles are believed to help maintain sleep and to play a role in sleep-dependent memory consolidation. Here we applied an automated sleep spindle detection program to our large longitudinal sleep EEG dataset (98 human subjects, 6-18 years old, >2000 uninterrupted nights) to evaluate maturational trends in spindle wave frequency, density, amplitude, and duration. This large dataset enabled us to apply nonlinear as well as linear age models, thereby extending the findings of prior cross-sectional studies that used linear models. We found that spindle wave frequency increased with remarkable linearity across the age range. Central spindle density increased nonlinearly to a peak at age 15.1 years. Central spindle wave amplitude declined in a sigmoidal pattern with the age of fastest decline at 13.5 years. Spindle duration decreased linearly with age. Of the four measures, only spindle amplitude showed a sex difference in dynamics such that the age of most rapid decline in females preceded that in males by 1.4 years. This amplitude pattern, including the sex difference in timing, paralleled the maturational pattern for δ (1-4 Hz) wave power. We interpret these age-related changes in spindle characteristics as indicators of maturation of thalamocortical circuits and changes in sleep depth. These robust age-effects could facilitate the search for cognitive-behavioral correlates of spindle waveforms and might also help guide basic research on EEG mechanisms and postnatal brain maturation.SIGNIFICANCE STATEMENT The brain reorganization of adolescence produces massive changes in sleep EEG. These changes include the morphology and abundance of sleep spindles, an EEG marker of non-rapid eye movement sleep believed to reflect offline memory processes and/or protection of the sleep state. We analyzed >2000 nights of longitudinal sleep EEG from 98 subjects (age 6-18 years old) to investigate maturational changes in spindle amplitude, frequency, density, and duration. The large dataset enabled us to detect nonlinear as well as linear age changes. All measures showed robust age effects that we hypothesize reflect the maturation of thalamocortical circuits and decreasing sleep depth. These findings could guide further research into the cognitive-behavioral correlates of sleep spindles and their underlying brain mechanisms.

OBJECTIVES: To determine how continuous spike and wave during slow wave sleep (CSWS) is currently managed and to compare the effectiveness of current treatment strategies using a database from 11 pediatric epilepsy centers in the US. STUDY DESIGN: This retrospective study gathered information on baseline clinical characteristics, CSWS etiology, and treatment(s) in consecutive patients seen between 2014 and 2016 at 11 epilepsy referral centers. Treatments were categorized as benzodiazepines, steroids, other antiseizure medications (ASMs), or other therapies. Two measures of treatment response (clinical improvement as noted by the treating physician; and electroencephalography improvement) were compared across therapies, controlling for baseline variables. RESULTS: Eighty-one children underwent 153 treatment trials during the study period (68 trials of benzodiazepines, 25 of steroids, 45 of ASMs, 14 of other therapies). Children most frequently received benzodiazepines (62%) or ASMs (27%) as first line therapy. Treatment choice did not differ based on baseline clinical variables, nor did these variables correlate with outcome. After adjusting for baseline variables, children had a greater odds of clinical improvement with benzodiazepines (OR 3.32, 95%CI 1.57-7.04, P = .002) or steroids (OR 4.04, 95%CI 1.41-11.59, P = .01) than with ASMs and a greater odds of electroencephalography improvement after steroids (OR 3.36, 95% CI 1.09-10.33, P = .03) than after ASMs. CONCLUSIONS: Benzodiazepines and ASMs are the most frequent initial therapy prescribed for CSWS in the US. Our data suggests that ASMs are inferior to benzodiazepines and steroids and support earlier use of these therapies. Multicenter prospective studies that rigorously assess treatment protocols and outcomes are needed.

Mild, blast-induced traumatic brain injury (mbTBI) is a common combat brain injury characterized by typically normal neuroimaging findings, with unpredictable future cognitive recovery. Traditional methods of electroencephalography (EEG) analysis (e.g., spectral analysis) have not been successful in detecting the degree of cognitive and functional impairment in mbTBI. We therefore collected resting state EEG (5 minutes, 64 leads) from twelve patients with a history of mbTBI, along with repeat neuropsychological testing (D-KEFS Tower test) to compare two new methods for analyzing EEG (multifractal detrended fluctuation analysis (MF-DFA) and information transfer modeling (ITM)) with spectral analysis. For MF-DFA, we extracted relevant parameters from the resultant multifractal spectrum from all leads and compared with traditional power by frequency band for spectral analysis. For ITM, because the number of parameters from each lead far exceeded the number of subjects, we utilized a reduced set of 10 leads which were compared with spectral analysis. We utilized separate 30 second EEG segments for training and testing statistical models based upon regression tree analysis. ITM and MF-DFA models both generally had improved accuracy at correlating with relevant measures of cognitive performance as compared to spectral analytic models ITM and MF-DFA both merit additional research as analytic tools for EEG and cognition in TBI.

The understanding and treatment of psychiatric disorders, which are known to be neurobiologically and clinically heterogeneous, could benefit from the data-driven identification of disease subtypes. Here, we report the identification of two clinically relevant subtypes of post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) on the basis of robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the default mode network. We identified the disease subtypes by analysing, via unsupervised and supervised machine learning, the power-envelope-based connectivity of signals reconstructed from high-density resting-state electroencephalography in four datasets of patients with PTSD and MDD, and show that the subtypes are transferable across independent datasets recorded under different conditions. The subtype whose functional connectivity differed most from those of healthy controls was less responsive to psychotherapy treatment for PTSD and failed to respond to an antidepressant medication for MDD. By contrast, both subtypes responded equally well to two different forms of repetitive transcranial magnetic stimulation therapy for MDD. Our data-driven approach may constitute a generalizable solution for connectome-based diagnosis.

Discrepancies between actigraphic and self-reported sleep measures are common. Studies of people with insomnia, in whom both sleep disturbances and discrepancy are common, suggest disturbances and discrepancy reflect differences in the sleeping brain's activity measurable using spectral electroencephalogram (EEG). Disentangling effects of discrepancy and disturbance on sleep EEG could help target research on the consequences and treatments of different sleep phenotypes. We therefore categorized participants in a cohort study including 2,850 men (average age = 76 years, standard deviation = 5.5) into four groups using median splits on actigraphic and self-reported sleep efficiency (SE). We compared spectral power between these groups in 1-Hz bins up to 24 Hz. Compared with the concordant-high SE group: (a) the group with high actigraphic and low self-reported SE had higher spectral power from 11-15 Hz across the night; (b) both groups with low actigraphic SE had higher power across the 15-24 Hz range, predominantly in early cycles, and greater slow frequency power in later cycles. These findings suggest that perceived wakefulness undetected by actigraphy may result from or drive activity corresponding to spindles. We also found, consistent with hyperarousal models, that low SE detectable via actigraphy was related to higher frequency power in the beta range; actigraph-measured inefficiency was also associated with later slow oscillations, potentially representing attempts to dissipate homeostatic drive elevated from earlier hyperarousal. These distinct spectral EEG markers (of low SE measured with actigraphy vs. low perceived SE that is not captured by actigraphy) may have different causes or consequences.

Neurostimulation provides a new dimension in the treatment of neurologic disorders. For patients with drug-resistant epilepsy, the Responsive Neurostimulation (RNS) System (NeuroPace, Inc.) provides treatment of seizures with a closed-loop device that continuously records brain activity and provides stimulation designed to reduce seizure frequency over time. The presence of a chronic implanted device that can provide an electrographic record of neural activity provides great opportunities for treatment of seizure disorders and neuroscience research. However, our experience with this device indicates that a number of ethical and clinical challenges arise, and these issues may be applicable to neurotechnology developed for other disease states in the future. We present clinical scenarios based on cases from our center that present clinical or ethical dilemmas. The dilemmas revolve around 4 core themes: (1) electroclinical correlation and dissociation; (2) patient concerns about device capabilities; (3) clinician opportunities and burdens; and (4) data ownership and access. Developing a framework for understanding these issues will be critical as closed-loop neuromodulation is applied to a growing range of neuropsychiatric disorders.

Objective/backgroundDisrupted sleep can be a cause and a consequence of affective experiences. However, daily longitudinal studies show sleep assessed via sleep diaries is more consistently associated with positive and negative affect than sleep assessed via actigraphy. The objective of the study was to test whether sleep parameters derived from ambulatory electroencephalography (EEG) in a naturalistic setting were associated with day-to-day changes in affect.Participants/methodEighty adults (mean age = 32.65 years, 63% female) completed 7 days of affect and sleep assessments. We examined bidirectional associations between morning positive affect and negative affect with sleep assessed via diary, actigraphy, and ambulatory EEG.ResultsMornings with lower positive affect than average were associated with higher diary- and actigraphy-determined sleep efficiency that night. Mornings with higher negative affect than average were associated with longer actigraphy-determined total sleep time that night. Nights with longer diary-determined total sleep time, greater sleep efficiency, and shorter sleep onset latency than average were associated with higher next-morning positive affect, and nights with lower diary-determined wake-after-sleep-onset were associated with lower next-morning negative affect. EEG-determined sleep and affect results were generally null in both directions: only higher morning negative affect was associated with longer rapid eye movement (REM) sleep that night.ConclusionsSelf-reported sleep and affect may occur in a bidirectional fashion for some sleep parameters. EEG-determined sleep and affect associations were inconsistent but may still be important to assess in future studies to holistically capture sleep. Single-channel EEG represents a novel, ecologically valid tool that may provide information beyond diaries and actigraphy.

ObjectiveProlonged fever-induced seizures (febrile status epilepticus [FSE]) during early childhood increase the risk for later epilepsy, but the underlying mechanisms are incompletely understood. Experimental FSE (eFSE) in rats successfully models human FSE, recapitulating the resulting epileptogenesis in a subset of affected individuals. However, the powerful viral and genetic tools that may enhance mechanistic insights into epileptogenesis and associated comorbidities, are better-developed for mice. Therefore, we aimed to determine if eFSE could be generated in mice and if it provoked enduring changes in hippocampal-network excitability and the development of spontaneous seizures.MethodsWe employed C57BL/6J male mice, the strain used most commonly in transgenic manipulations, and examined if early life eFSE could be sustained and if it led to hyperexcitability of hippocampal networks and to epilepsy. Outcome measures included vulnerability to the subsequent administration of the limbic convulsant kainic acid (KA) and the development of spontaneous seizures. In the first mouse cohort, adult naive and eFSE-experiencing mice were exposed to KA. A second cohort of control and eFSE-experiencing young adult mice was implanted with bilateral hippocampal electrodes and recorded using continuous video-electroencephalography (EEG) for 2 to 3 months to examine for spontaneous seizures (epileptogenesis).ResultsInduction of eFSE was feasible and eFSE increased the susceptibility of adult C57BL/6J mice to KA, thereby reducing latency to seizure onset and increasing seizure severity. Of 24 chronically recorded eFSE mice, 4 (16.5%) developed hippocampal epilepsy with a latent period of ~3 months, significantly different from the expectation by chance (P = .04). The limbic epilepsy that followed eFSE was progressive.SignificanceeFSE promotes pro-epileptogenic network changes in a majority of C57BL/6J male mice and frank "temporal lobe-like" epilepsy in one sixth of the cohort. Mouse eFSE may thus provide a useful tool for investigating molecular, cellular, and circuit changes during the development of temporal lobe epilepsy and its comorbidities.

Covert spatial attention has a variety of effects on the responses of individual neurons. However, relatively little is known about the net effect of these changes on sensory population codes, even though perception ultimately depends on population activity. Here, we measured the EEG in human observers (male and female), and isolated stimulus-evoked activity that was phase-locked to the onset of attended and ignored visual stimuli. Using an encoding model, we reconstructed spatially selective population tuning functions from the pattern of stimulus-evoked activity across the scalp. Our EEG-based approach allowed us to measure very early visually evoked responses occurring ∼100 ms after stimulus onset. In Experiment 1, we found that covert attention increased the amplitude of spatially tuned population responses at this early stage of sensory processing. In Experiment 2, we parametrically varied stimulus contrast to test how this effect scaled with stimulus contrast. We found that the effect of attention on the amplitude of spatially tuned responses increased with stimulus contrast, and was well described by an increase in response gain (i.e., a multiplicative scaling of the population response). Together, our results show that attention increases the gain of spatial population codes during the first wave of visual processing.SIGNIFICANCE STATEMENT We know relatively little about how attention improves population codes, even though perception is thought to critically depend on population activity. In this study, we used an encoding-model approach to test how attention modulates the spatial tuning of stimulus-evoked population responses measured with EEG. We found that attention multiplicatively scales the amplitude of spatially tuned population responses. Furthermore, this effect was present within 100 ms of stimulus onset. Thus, our results show that attention improves spatial population codes by increasing their gain at this early stage of processing.

BACKGROUND: People with epilepsy are burdened with the apparent unpredictability of seizures. In the past decade, converging evidence from studies using chronic EEG (cEEG) revealed that epileptic brain activity shows robust cycles, operating over hours (circadian) and days (multidien). We hypothesised that these cycles can be leveraged to estimate future seizure probability, and we tested the feasibility of forecasting seizures days in advance. METHODS: We did a feasibility study in distinct development and validation cohorts, involving retrospective analysis of cEEG data recorded with an implanted device in adults (age ≥18 years) with drug-resistant focal epilepsy followed at 35 centres across the USA between Jan 19, 2004, and May 18, 2018. Patients were required to have had 20 or more electrographic seizures (development cohort) or self-reported seizures (validation cohort). In all patients, the device recorded interictal epileptiform activity (IEA; ≥6 months of continuous hourly data), the fluctuations in which helped estimate varying seizure risk. Point process statistical models trained on initial portions of each patients cEEG data (both cohorts) generated forecasts of seizure probability that were tested on subsequent unseen seizure data and evaluated against surrogate time-series. The primary outcome was the percentage of patients with forecasts showing improvement over chance (IoC). FINDINGS: We screened 72 and 256 patients, and included 18 and 157 patients in the development and validation cohorts, respectively. Models incorporating information about multidien IEA cycles alone generated daily seizure forecasts for the next calendar day with IoC in 15 (83%) patients in the development cohort and 103 (66%) patients in the validation cohort. The forecasting horizon could be extended up to 3 days while maintaining IoC in two (11%) of 18 patients and 61 (39%) of 157 patients. Forecasts with a shorter horizon of 1 h, possible only for electrographic seizures in the development cohort, showed IoC in all 18 (100%) patients. INTERPRETATION: This study shows that seizure probability can be forecasted days in advance by leveraging multidien IEA cycles recorded with an implanted device. This study will serve as a basis for prospective clinical trials to establish how people with epilepsy might benefit from seizure forecasting over long horizons. FUNDING: None. VIDEO ABSTRACT.