Sleep functional connectivity, hyperexcitability, and cognition in Alzheimer's disease.

INTRODUCTION: Sleep disturbances are common in Alzheimer's disease (AD) and may reflect pathologic changes in brain networks. To date, no studies have examined changes in sleep functional connectivity (FC) in AD or their relationship with network hyperexcitability and cognition. METHODS: We assessed electroencephalogram (EEG) sleep FC in 33 healthy controls, 36 individuals with AD without epilepsy, and 14 individuals with AD and epilepsy. RESULTS: AD participants showed increased gamma connectivity in stage 2 sleep (N2), which was associated with longitudinal cognitive decline. Network hyperexcitability in AD was associated with a distinct sleep connectivity signature, characterized by decreased N2 delta connectivity and reversal of several connectivity changes associated with AD. Machine learning algorithms using sleep connectivity features accurately distinguished diagnostic groups and identified "fast cognitive decliners" among study participants who had AD. DISCUSSION: Our findings reveal changes in sleep functional networks associated with cognitive decline in AD and may have implications for disease monitoring and therapeutic development. HIGHLIGHTS: Brain functional connectivity (FC) in Alzheimer's disease is altered during sleep. Sleep FC measures correlate with cognitive decline in AD. Network hyperexcitability in AD has a distinct sleep connectivity signature.

An electroencephalogram microdisplay to visualize neuronal activity on the brain surface.

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.

Aberrant fast spiking interneuronal activity precedes seizure transitions in humans.

There is active debate regarding how GABAergic function changes during seizure initiation and propagation, and whether interneuronal activity drives or impedes the pathophysiology. Here, we track cell-type specific firing during spontaneous human seizures to identify neocortical mechanisms of inhibitory failure. Fast-spiking interneuron activity was maximal over 1 second before equivalent excitatory increases, and showed transitions to out-of-phase firing prior to local tissue becoming incorporated into the seizure-driving territory. Using computational modeling, we linked this observation to transient saturation block as a precursor to seizure invasion, as supported by multiple lines of evidence in the patient data. We propose that transient blocking of inhibitory firing due to selective fast-spiking interneuron saturation-resulting from intense excitatory synaptic drive-is a novel mechanism that contributes to inhibitory failure, allowing seizure propagation.

Flexible, scalable, high channel count stereo-electrode for recording in the human brain.

Over the past decade, stereotactically placed electrodes have become the gold standard for deep brain recording and stimulation for a wide variety of neurological and psychiatric diseases. Current electrodes, however, are limited in their spatial resolution and ability to record from small populations of neurons, let alone individual neurons. Here, we report on an innovative, customizable, monolithically integrated human-grade flexible depth electrode capable of recording from up to 128 channels and able to record at a depth of 10 cm in brain tissue. This thin, stylet-guided depth electrode is capable of recording local field potentials and single unit neuronal activity (action potentials), validated across species. This device represents an advance in manufacturing and design approaches which extends the capabilities of a mainstay technology in clinical neurology.

Modular Phoneme Processing in Human Superior Temporal Gyrus.

Modular organization is fundamental to cortical processing, but its presence is human association cortex is unknown. We characterized phoneme processing with 128-1024 channel micro-arrays at 50-200µm pitch on superior temporal gyrus of 7 patients. High gamma responses were highly correlated within ~1.7mm diameter modules, sharply delineated from adjacent modules with distinct time-courses and phoneme-selectivity. We suggest that receptive language cortex may be organized in discrete processing modules.

Linking brain structure, cognition, and sleep: insights from clinical data.

STUDY OBJECTIVES: To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition. METHODS: We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links. RESULTS: Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40). CONCLUSIONS: Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.

Responsive neurostimulation as a treatment for super-refractory focal status epilepticus: a systematic review and case series.

OBJECTIVE: Super-refractory status epilepticus (SRSE) has high rates of morbidity and mortality. Few published studies have investigated neurostimulation treatment options in the setting of SRSE. This systematic literature review and series of 10 cases investigated the safety and efficacy of implanting and activating the responsive neurostimulation (RNS) system acutely during SRSE and discusses the rationale for lead placement and selection of stimulation parameters. METHODS: Through a literature search (of databases and American Epilepsy Society abstracts that were last searched on March 1, 2023) and direct contact with the manufacturer of the RNS system, 10 total cases were identified that utilized RNS acutely during SE (9 SRSE cases and 1 case of refractory SE [RSE]). Nine centers obtained IRB approval for retrospective chart review and completed data collection forms. A tenth case had published data from a case report that were referenced in this study. Data from the collection forms and the published case report were compiled in Excel. RESULTS: All 10 cases presented with focal SE: 9 with SRSE and 1 with RSE. Etiology varied from known lesion (focal cortical dysplasia in 7 cases and recurrent meningioma in 1) to unknown (2 cases, with 1 presenting with new-onset refractory focal SE [NORSE]). Seven of 10 cases exited SRSE after RNS placement and activation, with a time frame ranging from 1 to 27 days. Two patients died of complications due to ongoing SRSE. Another patient's SE never resolved but was subclinical. One of 10 cases had a device-related significant adverse event (trace hemorrhage), which did not require intervention. There was 1 reported recurrence of SE after discharge among the cases in which SRSE resolved up to the defined endpoint. CONCLUSIONS: This case series offers preliminary evidence that RNS is a safe and potentially effective treatment option for SRSE in patients with 1-2 well-defined seizure-onset zone(s) who meet the eligibility criteria for RNS. The unique features of RNS offer multiple benefits in the SRSE setting, including real-time electrocorticography to supplement scalp EEG for monitoring SRSE progress and response to treatment, as well as numerous stimulation options. Further research is indicated to investigate the optimal stimulation settings in this unique clinical scenario.

Neural manifolds carry reactivation of phonetic representations during semantic processing.

Traditional models of speech perception posit that neural activity encodes speech through a hierarchy of cognitive processes, from low-level representations of acoustic and phonetic features to high-level semantic encoding. Yet it remains unknown how neural representations are transformed across levels of the speech hierarchy. Here, we analyzed unique microelectrode array recordings of neuronal spiking activity from the human left anterior superior temporal gyrus, a brain region at the interface between phonetic and semantic speech processing, during a semantic categorization task and natural speech perception. We identified distinct neural manifolds for semantic and phonetic features, with a functional separation of the corresponding low-dimensional trajectories. Moreover, phonetic and semantic representations were encoded concurrently and reflected in power increases in the beta and low-gamma local field potentials, suggesting top-down predictive and bottom-up cumulative processes. Our results are the first to demonstrate mechanisms for hierarchical speech transformations that are specific to neuronal population dynamics.

Intraoperative application and early experience with novel high-resolution, high-channel-count thin-film electrodes for human microelectrocorticography.

OBJECTIVE: The study objective was to evaluate intraoperative experience with newly developed high-spatial-resolution microelectrode grids composed of poly(3,4-ethylenedioxythiophene) with polystyrene sulfonate (PEDOT:PSS), and those composed of platinum nanorods (PtNRs). METHODS: A cohort of patients who underwent craniotomy for pathological tissue resection and who had high-spatial-resolution microelectrode grids placed intraoperatively were evaluated. Patient demographic and baseline clinical variables as well as relevant microelectrode grid characteristic data were collected. The primary and secondary outcome measures of interest were successful microelectrode grid utilization with usable resting-state or task-related data, and grid-related adverse intraoperative events and/or grid dysfunction. RESULTS: Included in the analysis were 89 cases of patients who underwent a craniotomy for resection of neoplasms (n = 58) or epileptogenic tissue (n = 31). These cases accounted for 94 grids: 58 PEDOT:PSS and 36 PtNR grids. Of these 94 grids, 86 were functional and used successfully to obtain cortical recordings from 82 patients. The mean cortical grid recording duration was 15.3 ± 1.15 minutes. Most recordings in patients were obtained during experimental tasks (n = 52, 58.4%), involving language and sensorimotor testing paradigms, or were obtained passively during resting state (n = 32, 36.0%). There were no intraoperative adverse events related to grid placement. However, there were instances of PtNR grid dysfunction (n = 8) related to damage incurred by suboptimal preoperative sterilization (n = 7) and improper handling (n = 1); intraoperative recordings were not performed. Vaporized peroxide sterilization was the most optimal sterilization method for PtNR grids, providing a significantly greater number of usable channels poststerilization than did steam-based sterilization techniques (median 905.0 [IQR 650.8-935.5] vs 356.0 [IQR 18.0-597.8], p = 0.0031). CONCLUSIONS: High-spatial-resolution microelectrode grids can be readily incorporated into appropriately selected craniotomy cases for clinical and research purposes. Grids are reliable when preoperative handling and sterilization considerations are accounted for. Future investigations should compare the diagnostic utility of these high-resolution grids to commercially available counterparts and assess whether diagnostic discrepancies relate to clinical outcomes.

Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans.

How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.

Network-motif delay differential analysis of brain activity during seizures.

Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.

Benefits of sharing neurophysiology data from the BRAIN Initiative Research Opportunities in Humans Consortium.

Sharing human brain data can yield scientific benefits, but because of various disincentives, only a fraction of these data is currently shared. We profile three successful data-sharing experiences from the NIH BRAIN Initiative Research Opportunities in Humans (ROH) Consortium and demonstrate benefits to data producers and to users.

DREDge: robust motion correction for high-density extracellular recordings across species.

High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.

Altered Sleep Microarchitecture and Cognitive Impairment in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: To investigate the spatiotemporal characteristics of sleep waveforms in temporal lobe epilepsy (TLE) and examine their association with cognition. METHODS: In this retrospective, cross-sectional study, we examined overnight EEG data from adult patients with TLE and nonepilepsy comparisons (NECs) admitted to the epilepsy monitoring unit at Mass General Brigham hospitals. Automated algorithms were used to characterize sleep macroarchitecture (sleep stages) and microarchitecture (spindles, slow oscillations [SOs]) on scalp EEG and to detect hippocampal interictal epileptiform discharges (hIEDs) from foramen ovale electrodes simultaneously recorded in a subset of patients with TLE. We examined the association of sleep features and hIEDs with memory and executive function from clinical neuropsychological evaluations. RESULTS: A total of 81 adult patients with TLE and 28 NEC adult patients were included with similar mean ages. There were no significant differences in sleep macroarchitecture between groups, including relative time spent in each sleep stage, sleep efficiency, and sleep fragmentation. By contrast, the spatiotemporal characteristics of sleep microarchitecture were altered in TLE compared with NEC and were associated with cognitive impairments. Specifically, we observed a ∼30% reduction in spindle density in patients with TLE compared with NEC, which was significantly associated with worse memory performance. Spindle-SO coupling strength was also reduced in TLE and, in contrast to spindles, was associated with diminished executive function. We found no significant association between sleep macroarchitectural and microarchitectural parameters and hIEDs. DISCUSSION: There is a fundamental alteration of sleep microarchitecture in TLE, characterized by a reduction in spindle density and spindle-SO coupling, and these changes may contribute to neurocognitive comorbidity in this disorder.

An examination of sleep spindle metrics in the Sleep Heart Health Study: superiority of automated spindle detection over total sigma power in assessing age-related spindle decline.

BACKGROUND: Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design. METHODS: We estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial. RESULTS: In a simulated clinical trial, sigma power required a sample size of 115 to achieve 95% power to identify age-related changes in sigma coherence, while automated spindle detection required a sample size of only 60. CONCLUSIONS: Measurements of spindle activity utilizing automated spindle detection outperformed conventional sigma power analysis by a wide margin, suggesting that many studies would benefit from incorporation of automated spindle detection. These results further suggest that some previous studies which have failed to detect changes in sigma power or coherence may have failed simply because they were underpowered.

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices.

A magnetoelectric antenna (ME) can exhibit the dual capabilities of wireless energy harvesting and sensing at different frequencies. In this article, a behavioral circuit model for hybrid ME antennas is described to emulate the radio frequency (RF) energy harvesting and sensing operations during circuit simulations. The ME antenna of this work is interfaced with a CMOS energy harvester chip towards the goal of developing a wireless communication link for fully integrated implantable devices. One role of the integrated system is to receive pulse-modulated power from a nearby transmitter, and another role is to sense and transmit low-magnitude neural signals. The measurements reported in this paper are the first results that demonstrate simultaneous low-frequency wireless magnetic sensing and high-frequency wireless energy harvesting at two different frequencies with one dual-mode ME antenna. The proposed behavioral ME antenna model can be utilized during design optimizations of energy harvesting circuits. Measurements were performed to validate the wireless power transfer link with an ME antenna having a 2.57 GHz resonance frequency connected to an energy harvester chip designed in 65nm CMOS technology. Furthermore, this dual-mode ME antenna enables concurrent sensing using a carrier signal with a frequency that matches the second 63.63 MHz resonance mode. A wireless test platform has been developed for evaluation of ME antennas as a tool for neural implant design, and this prototype system was utilized to provide first experimental results with the transmission of magnetically modulated action potential waveforms.

Differential cortical network engagement during states of un/consciousness in humans.

What happens in the human brain when we are unconscious? Despite substantial work, we are still unsure which brain regions are involved and how they are impacted when consciousness is disrupted. Using intracranial recordings and direct electrical stimulation, we mapped global, network, and regional involvement during wake vs. arousable unconsciousness (sleep) vs. non-arousable unconsciousness (propofol-induced general anesthesia). Information integration and complex processing we`re reduced, while variability increased in any type of unconscious state. These changes were more pronounced during anesthesia than sleep and involved different cortical engagement. During sleep, changes were mostly uniformly distributed across the brain, whereas during anesthesia, the prefrontal cortex was the most disrupted, suggesting that the lack of arousability during anesthesia results not from just altered overall physiology but from a disconnection between the prefrontal and other brain areas. These findings provide direct evidence for different neural dynamics during loss of consciousness compared with loss of arousability.

Modified Neuropixels probes for recording human neurophysiology in the operating room.

Neuropixels are silicon-based electrophysiology-recording probes with high channel count and recording-site density. These probes offer a turnkey platform for measuring neural activity with single-cell resolution and at a scale that is beyond the capabilities of current clinically approved devices. Our team demonstrated the first-in-human use of these probes during resection surgery for epilepsy or tumors and deep brain stimulation electrode placement in patients with Parkinson's disease. Here, we provide a better understanding of the capabilities and challenges of using Neuropixels as a research tool to study human neurophysiology, with the hope that this information may inform future efforts toward regulatory approval of Neuropixels probes as research devices. In perioperative procedures, the major concerns are the initial sterility of the device, maintaining a sterile field during surgery, having multiple referencing and grounding schemes available to de-noise recordings (if necessary), protecting the silicon probe from accidental contact before insertion and obtaining high-quality action potential and local field potential recordings. The research team ensures that the device is fully operational while coordinating with the surgical team to remove sources of electrical noise that could otherwise substantially affect the signals recorded by the sensitive hardware. Prior preparation using the equipment and training in human clinical research and working in operating rooms maximize effective communication within and between the teams, ensuring high recording quality and minimizing the time added to the surgery. The perioperative procedure requires ~4 h, and the entire protocol requires multiple weeks.

Automated detection of immune effector cell-associated neurotoxicity syndrome via quantitative EEG.

OBJECTIVE: To develop an automated, physiologic metric of immune effector cell-associated neurotoxicity syndrome among patients undergoing chimeric antigen receptor-T cell therapy. METHODS: We conducted a retrospective observational cohort study from 2016 to 2020 at two tertiary care centers among patients receiving chimeric antigen receptor-T cell therapy with a CD19 or B-cell maturation antigen ligand. We determined the daily neurotoxicity grade for each patient during EEG monitoring via chart review and extracted clinical variables and outcomes from the electronic health records. Using quantitative EEG features, we developed a machine learning model to detect the presence and severity of neurotoxicity, known as the EEG immune effector cell-associated neurotoxicity syndrome score. RESULTS: The EEG immune effector cell-associated neurotoxicity syndrome score significantly correlated with the grade of neurotoxicity with a median Spearman's R2 of 0.69 (95% CI of 0.59-0.77). The mean area under receiving operator curve was greater than 0.85 for each binary discrimination level. The score also showed significant correlations with maximum ferritin (R2 0.24, p = 0.008), minimum platelets (R2 -0.29, p = 0.001), and dexamethasone usage (R2 0.42, p < 0.0001). The score significantly correlated with duration of neurotoxicity (R2 0.31, p < 0.0001). INTERPRETATION: The EEG immune effector cell-associated neurotoxicity syndrome score possesses high criterion, construct, and predictive validity, which substantiates its use as a physiologic method to detect the presence and severity of neurotoxicity among patients undergoing chimeric antigen receptor T-cell therapy.

Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes.

Implantation of electrodes in the brain has been used as a clinical tool for decades to stimulate and record brain activity. As this method increasingly becomes the standard of care for several disorders and diseases, there is a growing need to quickly and accurately localize the electrodes once they are placed within the brain. We share here a protocol pipeline for localizing electrodes implanted in the brain, which we have applied to more than 260 patients, that is accessible to multiple skill levels and modular in execution. This pipeline uses multiple software packages to prioritize flexibility by permitting multiple different parallel outputs while minimizing the number of steps for each output. These outputs include co-registered imaging, electrode coordinates, 2D and 3D visualizations of the implants, automatic surface and volumetric localizations of the brain regions per electrode, and anonymization and data sharing tools. We demonstrate here some of the pipeline's visualizations and automatic localization algorithms which we have applied to determine appropriate stimulation targets, to conduct seizure dynamics analysis, and to localize neural activity from cognitive tasks in previous studies. Further, the output facilitates the extraction of information such as the probability of grey matter intersection or the nearest anatomic structure per electrode contact across all data sets that go through the pipeline. We expect that this pipeline will be a useful framework for researchers and clinicians alike to localize implanted electrodes in the human brain.