An orexigenic subnetwork within the human hippocampus.

Only recently have more specific circuit-probing techniques become available to inform previous reports implicating the rodent hippocampus in orexigenic appetitive processing1-4. This function has been reported to be mediated at least in part by lateral hypothalamic inputs, including those involving orexigenic lateral hypothalamic neuropeptides, such as melanin-concentrating hormone5,6. This circuit, however, remains elusive in humans. Here we combine tractography, intracranial electrophysiology, cortico-subcortical evoked potentials, and brain-clearing 3D histology to identify an orexigenic circuit involving the lateral hypothalamus and converging in a hippocampal subregion. We found that low-frequency power is modulated by sweet-fat food cues, and this modulation was specific to the dorsolateral hippocampus. Structural and functional analyses of this circuit in a human cohort exhibiting dysregulated eating behaviour revealed connectivity that was inversely related to body mass index. Collectively, this multimodal approach describes an orexigenic subnetwork within the human hippocampus implicated in obesity and related eating disorders.

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity.

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

Electrical Stimulation of Temporal and Limbic Circuitry Produces Distinct Responses in Human Ventral Temporal Cortex.

The human ventral temporal cortex (VTC) is highly connected to integrate visual perceptual inputs with feedback from cognitive and emotional networks. In this study, we used electrical brain stimulation to understand how different inputs from multiple brain regions drive unique electrophysiological responses in the VTC. We recorded intracranial EEG data in 5 patients (3 female) implanted with intracranial electrodes for epilepsy surgery evaluation. Pairs of electrodes were stimulated with single-pulse electrical stimulation, and corticocortical evoked potential responses were measured at electrodes in the collateral sulcus and lateral occipitotemporal sulcus of the VTC. Using a novel unsupervised machine learning method, we uncovered 2-4 distinct response shapes, termed basis profile curves (BPCs), at each measurement electrode in the 11-500 ms after stimulation interval. Corticocortical evoked potentials of unique shape and high amplitude were elicited following stimulation of several regions and classified into a set of four consensus BPCs across subjects. One of the consensus BPCs was primarily elicited by stimulation of the hippocampus; another by stimulation of the amygdala; a third by stimulation of lateral cortical sites, such as the middle temporal gyrus; and the final one by stimulation of multiple distributed sites. Stimulation also produced sustained high-frequency power decreases and low-frequency power increases that spanned multiple BPC categories. Characterizing distinct shapes in stimulation responses provides a novel description of connectivity to the VTC and reveals significant differences in input from cortical and limbic structures.SIGNIFICANCE STATEMENT Disentangling the numerous input influences on highly connected areas in the brain is a critical step toward understanding how brain networks work together to coordinate human behavior. Single-pulse electrical stimulation is an effective tool to accomplish this goal because the shapes and amplitudes of signals recorded from electrodes are informative of the synaptic physiology of the stimulation-driven inputs. We focused on targets in the ventral temporal cortex, an area strongly implicated in visual object perception. By using a data-driven clustering algorithm, we identified anatomic regions with distinct input connectivity profiles to the ventral temporal cortex. Examining high-frequency power changes revealed possible modulation of excitability at the recording site induced by electrical stimulation of connected regions.

Signatures of Electrical Stimulation Driven Network Interactions in the Human Limbic System.

Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In eight patients (four male, four female) with drug-resistant epilepsy, we stimulated the limbic system with single-pulse electrical stimulation. Reliable corticocortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the "limbic Hippocampus-Anterior nucleus of the thalamus-Posterior cingulate, HAP-wave." This limbic HAP-wave was visually distinct and separately decoded from the CCEP waveform in ACC after amygdala stimulation. Diffusion MRI data show that the measured end points in the PCC overlap with the end points of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic HAP-wave may travel through fornix, mammillary bodies, and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic HAP-wave but with an earlier latency. Limbic subsystems have unique stimulation-evoked signatures that may be used in the future to help network pathology diagnosis.SIGNIFICANCE STATEMENT The limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimer's disease, and characterizing its typical circuit responses may provide diagnostic insight. Stimulation-evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation-evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the "limbic HAP-wave." The limbic HAP-wave follows anatomic white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.

Impedance Rhythms in Human Limbic System.

The impedance is a fundamental electrical property of brain tissue, playing a crucial role in shaping the characteristics of local field potentials, the extent of ephaptic coupling, and the volume of tissue activated by externally applied electrical brain stimulation. We tracked brain impedance, sleep-wake behavioral state, and epileptiform activity in five people with epilepsy living in their natural environment using an investigational device. The study identified impedance oscillations that span hours to weeks in the amygdala, hippocampus, and anterior nucleus thalamus. The impedance in these limbic brain regions exhibit multiscale cycles with ultradian (∼1.5-1.7 h), circadian (∼21.6-26.4 h), and infradian (∼20-33 d) periods. The ultradian and circadian period cycles are driven by sleep-wake state transitions between wakefulness, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Limbic brain tissue impedance reaches a minimum value in NREM sleep, intermediate values in REM sleep, and rises through the day during wakefulness, reaching a maximum in the early evening before sleep onset. Infradian (∼20-33 d) impedance cycles were not associated with a distinct behavioral correlate. Brain tissue impedance is known to strongly depend on the extracellular space (ECS) volume, and the findings reported here are consistent with sleep-wake-dependent ECS volume changes recently observed in the rodent cortex related to the brain glymphatic system. We hypothesize that human limbic brain ECS changes during sleep-wake state transitions underlie the observed multiscale impedance cycles. Impedance is a simple electrophysiological biomarker that could prove useful for tracking ECS dynamics in human health, disease, and therapy.SIGNIFICANCE STATEMENT The electrical impedance in limbic brain structures (amygdala, hippocampus, anterior nucleus thalamus) is shown to exhibit oscillations over multiple timescales. We observe that impedance oscillations with ultradian and circadian periodicities are associated with transitions between wakefulness, NREM, and REM sleep states. There are also impedance oscillations spanning multiple weeks that do not have a clear behavioral correlate and whose origin remains unclear. These multiscale impedance oscillations will have an impact on extracellular ionic currents that give rise to local field potentials, ephaptic coupling, and the tissue activated by electrical brain stimulation. The approach for measuring tissue impedance using perturbational electrical currents is an established engineering technique that may be useful for tracking ECS volume.

Flexible multi-step hypothesis testing of human ECoG data using cluster-based permutation tests with GLMEs.

BACKGROUND: Time series analysis is critical for understanding brain signals and their relationship to behavior and cognition. Cluster-based permutation tests (CBPT) are commonly used to analyze a variety of electrophysiological signals including EEG, MEG, ECoG, and sEEG data without a priori assumptions about specific temporal effects. However, two major limitations of CBPT include the inability to directly analyze experiments with multiple fixed effects and the inability to account for random effects (e.g. variability across subjects). Here, we propose a flexible multi-step hypothesis testing strategy using CBPT with Linear Mixed Effects Models (LMEs) and Generalized Linear Mixed Effects Models (GLMEs) that can be applied to a wide range of experimental designs and data types. METHODS: We first evaluate the statistical robustness of LMEs and GLMEs using simulated data distributions. Second, we apply a multi-step hypothesis testing strategy to analyze ERPs and broadband power signals extracted from human ECoG recordings collected during a simple image viewing experiment with image category and novelty as fixed effects. Third, we assess the statistical power differences between analyzing signals with CBPT using LMEs compared to CBPT using separate t-tests run on each fixed effect through simulations that emulate broadband power signals. Finally, we apply CBPT using GLMEs to high-gamma burst data to demonstrate the extension of the proposed method to the analysis of nonlinear data. RESULTS: First, we found that LMEs and GLMEs are robust statistical models. In simple simulations LMEs produced highly congruent results with other appropriately applied linear statistical models, but LMEs outperformed many linear statistical models in the analysis of "suboptimal" data and maintained power better than analyzing individual fixed effects with separate t-tests. GLMEs also performed similarly to other nonlinear statistical models. Second, in real world human ECoG data, LMEs performed at least as well as separate t-tests when applied to predefined time windows or when used in conjunction with CBPT. Additionally, fixed effects time courses extracted with CBPT using LMEs from group-level models of pseudo-populations replicated latency effects found in individual category-selective channels. Third, analysis of simulated broadband power signals demonstrated that CBPT using LMEs was superior to CBPT using separate t-tests in identifying time windows with significant fixed effects especially for small effect sizes. Lastly, the analysis of high-gamma burst data using CBPT with GLMEs produced results consistent with CBPT using LMEs applied to broadband power data. CONCLUSIONS: We propose a general approach for statistical analysis of electrophysiological data using CBPT in conjunction with LMEs and GLMEs. We demonstrate that this method is robust for experiments with multiple fixed effects and applicable to the analysis of linear and nonlinear data. Our methodology maximizes the statistical power available in a dataset across multiple experimental variables while accounting for hierarchical random effects and controlling FWER across fixed effects. This approach substantially improves power leading to better reproducibility. Additionally, CBPT using LMEs and GLMEs can be used to analyze individual channels or pseudo-population data for the comparison of functional or anatomical groups of data.

Canonical Response Parameterization: Quantifying the structure of responses to single-pulse intracranial electrical brain stimulation.

Single-pulse electrical stimulation in the nervous system, often called cortico-cortical evoked potential (CCEP) measurement, is an important technique to understand how brain regions interact with one another. Voltages are measured from implanted electrodes in one brain area while stimulating another with brief current impulses separated by several seconds. Historically, researchers have tried to understand the significance of evoked voltage polyphasic deflections by visual inspection, but no general-purpose tool has emerged to understand their shapes or describe them mathematically. We describe and illustrate a new technique to parameterize brain stimulation data, where voltage response traces are projected into one another using a semi-normalized dot product. The length of timepoints from stimulation included in the dot product is varied to obtain a temporal profile of structural significance, and the peak of the profile uniquely identifies the duration of the response. Using linear kernel PCA, a canonical response shape is obtained over this duration, and then single-trial traces are parameterized as a projection of this canonical shape with a residual term. Such parameterization allows for dissimilar trace shapes from different brain areas to be directly compared by quantifying cross-projection magnitudes, response duration, canonical shape projection amplitudes, signal-to-noise ratios, explained variance, and statistical significance. Artifactual trials are automatically identified by outliers in sub-distributions of cross-projection magnitude, and rejected. This technique, which we call "Canonical Response Parameterization" (CRP) dramatically simplifies the study of CCEP shapes, and may also be applied in a wide range of other settings involving event-triggered data.

Preliminary Experience with a Four-Lead Implantable Pulse Generator for Deep Brain Stimulation.

BACKGROUND: Implantable pulse generators (IPGs) store energy and deliver electrical impulses for deep brain stimulation (DBS) to treat neurological and psychiatric disorders. IPGs have evolved over time to meet the demands of expanding clinical indications and more nuanced therapeutic approaches. OBJECTIVES: The aim of this study was to examine the workflow of the first 4-lead IPG for DBS in patients with complex disease. METHOD: The engineering capabilities, clinical use cases, and surgical technique are described in a cohort of 12 patients with epilepsy, essential tremor, Parkinson's disease, mixed tremor, and Tourette's syndrome with comorbid obsessive-compulsive disorder between July 2021 and July 2022. RESULTS: This system is a rechargeable 32-channel, 4-port system with independent current control that can be connected to 8 contact linear or directionally segmented leads. The system is ideal for patients with mixed disease or those with multiple severe symptoms amenable to >2 lead implantations. A multidisciplinary team including neurologists, radiologists, and neurosurgeons is necessary to safely plan the procedure. There were no serious intraoperative or postoperative adverse events. One patient required revision surgery for bowstringing. CONCLUSIONS: This new 4-lead IPG represents an important new tool for DBS surgery with the ability to expand lead implantation paradigms for patients with complex disease.

Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.

Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography was conducted in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFPs) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamic states, which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.SIGNIFICANCE STATEMENT This study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity-an auditory prediction error response-is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of nonoscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.

Advances in human intracranial electroencephalography research, guidelines and good practices.

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Decision-making in stereotactic epilepsy surgery.

Surgery can cure or significantly improve both the frequency and the intensity of seizures in patients with medication-refractory epilepsy. The set of diagnostic and therapeutic interventions involved in the path from initial consultation to definitive surgery is complex and includes a multidisciplinary team of neurologists, neurosurgeons, neuroradiologists, and neuropsychologists, supported by a very large epilepsy-dedicated clinical architecture. In recent years, new practices and technologies have emerged that dramatically expand the scope of interventions performed. Stereoelectroencephalography has become widely adopted for seizure localization; stereotactic laser ablation has enabled more focal, less invasive, and less destructive interventions; and new brain stimulation devices have unlocked treatment of eloquent foci and multifocal onset etiologies. This article articulates and illustrates the full framework for how epilepsy patients are considered for surgical intervention, with particular attention given to stereotactic approaches.

Basis profile curve identification to understand electrical stimulation effects in human brain networks.

Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique "basis profile curves" (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.

Invasive neuromodulation for epilepsy: Comparison of multiple approaches from a single center.

BACKGROUND: Drug-resistant epilepsy (DRE) patients not amenable to epilepsy surgery can benefit from neurostimulation. Few data compare different neuromodulation strategies. OBJECTIVE: Compare five invasive neuromodulation strategies for the treatment of DRE: anterior thalamic nuclei deep brain stimulation (ANT-DBS), centromedian thalamic nuclei DBS (CM-DBS), responsive neurostimulation (RNS), chronic subthreshold stimulation (CSS), and vagus nerve stimulation (VNS). METHODS: Single center retrospective review and phone survey for patients implanted with invasive neuromodulation for 2004-2021. RESULTS: N = 159 (ANT-DBS = 38, CM-DBS = 19, RNS = 30, CSS = 32, VNS = 40). Total median seizure reduction (MSR) was 61 % for the entire cohort (IQR 5-90) and in descending order: CSS (85 %), CM-DBS (63 %), ANT-DBS (52 %), RNS (50 %), and VNS (50 %); p = 0.07. The responder rate was 60 % after a median follow-up time of 26 months. Seizure severity, life satisfaction, and quality of sleep were improved. Cortical stimulation (RNS and CSS) was associated with improved seizure reduction compared to subcortical stimulation (ANT-DBS, CM-DBS, and VNS) (67 % vs. 52 %). Effectiveness was similar for focal epilepsy vs. generalized epilepsy, closed-loop vs. open-loop stimulation, pediatric vs. adult cases, and high frequency (>100 Hz) vs. low frequency (<100 Hz) stimulation settings. Delivered charge per hour varied widely across approaches but was not correlated with improved seizure reduction. CONCLUSIONS: Multiple invasive neuromodulation approaches are available to treat DRE, but little evidence compares the approaches. This study used a uniform approach for single-center results and represents an effort to compare neuromodulation approaches.

Safety and efficacy of responsive neurostimulation in the pediatric population: Evidence from institutional review and patient-level meta-analysis.

BACKGROUND: Responsive neurostimulation (RNS) is a novel technology for drug-resistant epilepsy rising from bilateral hemispheres or eloquent cortex. Although recently approved for adults, its safety and efficacy for pediatric patients is under investigation. METHODS: A comprehensive literature search (Pubmed/Medline, Scopus, Cochrane) was conducted for studies on RNS for pediatric epilepsy (<18 y/o) and supplemented by our institutional series (4 cases). Reduction in seizure frequency at last follow-up compared to preoperative baseline comprised the primary endpoint. RESULTS: A total of 8 studies (49 patients) were analyzed. Median age at implant was 15 years (interquartile range [IQR] 12-17) and 63% were males. A lesional MRI was noted in 64% (14/22). Prior invasive EEG recording was performed in the majority of patients (90%) and the most common modality was stereoelectroencephalography (57%). The most common implant location (total of 94 RNS leads) was the frontal lobe (27%), followed by mesial temporal structures (23%) and thalamus (17%). At a median follow-up of 22 months, median seizure frequency reduction was 75% (IQR: 50-88%) and 80% were responders (>50% seizure reduction). Responses ranged from 50% for temporal lobe epilepsy to 81-93% for frontal, parietal, and multilobar epilepsy. Four infections were observed (8%) and there were no hematomas or postoperative neurological deficits. CONCLUSION: Current evidence, albeit limited by potential publication bias, supports the promising safety and efficacy profile of RNS for medically refractory pediatric epilepsy. Randomized controlled trial data are needed to further establish the role of this intervention in preoperative discussions with patients and their families.

Low occurrence of long-term subsequent fusion in pediatric patients following decompressive surgery for Chiari malformation: an institutional review.

OBJECTIVE: Chiari I malformation is treated with suboccipital craniectomy with cervical laminectomy, a procedure which has been associated with the possibility of pre-existing or iatrogenic occipitocervical instability. The long-term risk of subsequent spinal deformity and need for occipito cervical fusion after standard Chiari decompression in pediatric patients has not yet been characterized. METHODS: We queried our institutional electronic database for patients aged 18 and under, with at least 5 years of follow-up, that underwent surgical decompression for Chiari I malformation. Occurrence of subsequent occipitocervical fusion at follow-up comprised the primary endpoint. Cases with myelomeningocele, Chiari II, or fusion at time of decompression were excluded. RESULTS: A total of 30 patients (median age 5.5 years, 60% males) were analyzed. Age distribution was as follows: n = 3 for 0-1 years, n = 11 for 1-5 years, n = 4 for 5-10 years, and n = 12 for 10-18 years. Median tonsillar descent below the foramen magnum was 12.5 mm (interquartile range [IQR]: 10.8-19.5 mm). Syringomyelia was observed in 43%, retroflexion of the dens in 55%, basilar invagination in 6.7%, and medullary kinking in 27%. The median clivo-axial angle was 142° (132-150°). The majority of patients underwent C1 laminectomy (n = 24, 80%), followed by C1-C2 laminectomy (n = 4, 13%), while one patient had C1-upper C2 and C1-C3 laminectomy each, respectively. At a median follow-up of 6.3 years, there was only one patient (3.3% of overall cohort) that underwent subsequent occipitocervical fusion. The patient (4-year-old male) initially had a suboccipital craniectomy with C1 laminectomy and duraplasty and presented with recurrence of posterior headaches and neck pain 4 months after original surgery. We proceeded with occiput-C2 fusion with subsequent resolution of his symptoms. CONCLUSION: Current analysis shows that in the absence of clinical or imaging features suggestive of craniocervical instability, Chiari I decompressive surgery is associated with very low long-term risk of requiring occipitocervical fusion. This observance can be used to guide surgical treatment decisions, especially in young children with Chiari I malformations.

Within-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms.

Variations in reaction time are a ubiquitous characteristic of human behavior. Extensively documented, they have been successfully modeled using parameters of the subject or the task, but the neural basis of behavioral reaction time that varies within the same subject and the same task has been minimally studied. In this paper, we investigate behavioral reaction time variance using 28 datasets of direct cortical recordings in humans who engaged in four different types of simple sensory-motor reaction time tasks. Using a previously described technique that can identify the onset of population-level cortical activity and a novel functional connectivity algorithm described herein, we show that the cumulative latency difference of population-level neural activity across the task-related cortical network can explain up to 41% of the trial-by-trial variance in reaction time. Furthermore, we show that reaction time variance may primarily be due to the latencies in specific brain regions and demonstrate that behavioral latency variance is accumulated across the whole task-related cortical network. Our results suggest that population-level neural activity monotonically increases prior to movement execution, and that trial-by-trial changes in that increase are, in part, accounted for by inhibitory activity indexed by low-frequency oscillations. This pre-movement neural activity explains 19% of the measured variance in neural latencies in our data. Thus, our study provides a mechanistic explanation for a sizable fraction of behavioral reaction time when the subject's task is the same from trial to trial.

Anticipatory human subthalamic area beta-band power responses to dissociable tastes correlate with weight gain.

The availability of enticing sweet, fatty tastes is prevalent in the modern diet and contribute to overeating and obesity. In animal models, the subthalamic area plays a role in mediating appetitive and consummatory feeding behaviors, however, its role in human feeding is unknown. We used intraoperative, subthalamic field potential recordings while participants (n = 5) engaged in a task designed to provoke responses of taste anticipation and receipt. Decreased subthalamic beta-band (15-30 Hz) power responses were observed for both sweet-fat and neutral tastes. Anticipatory responses to taste-neutral cues started with an immediate decrease in beta-band power from baseline followed by an early beta-band rebound above baseline. On the contrary, anticipatory responses to sweet-fat were characterized by a greater and sustained decrease in beta-band power. These activity patterns were topographically specific to the subthalamic nucleus and substantia nigra. Further, a neural network trained on this beta-band power signal accurately predicted (AUC ≥ 74%) single trials corresponding to either taste. Finally, the magnitude of the beta-band rebound for a neutral taste was associated with increased body mass index after starting deep brain stimulation therapy. We provide preliminary evidence of discriminatory taste encoding within the subthalamic area associated with control mechanisms that mediate appetitive and consummatory behaviors.

Anterior nucleus of the thalamus seizure detection in ambulatory humans.

There is a paucity of data to guide anterior nucleus of the thalamus (ANT) deep brain stimulation (DBS) with brain sensing. The clinical Medtronic Percept DBS device provides constrained brain sensing power within a frequency band (power-in-band [PIB]), recorded in 10-min averaged increments. Here, four patients with temporal lobe epilepsy were implanted with an investigational device providing full bandwidth chronic intracranial electroencephalogram (cEEG) from bilateral ANT and hippocampus (Hc). ANT PIB-based seizure detection was assessed. Detection parameters were cEEG PIB center frequency, bandwidth, and epoch duration. Performance was evaluated against epileptologist-confirmed Hc seizures, and assessed by area under the precision-recall curve (PR-AUC). Data included 99 days of cEEG, and 20, 278, 3, and 18 Hc seizures for Subjects 1-4. The best detector had 7-Hz center frequency, 5-Hz band width, and 10-s epoch duration (group PR-AUC = .90), with 75% sensitivity and .38 false alarms per day for Subject 1, and 100% and .0 for Subjects 3 and 4. Hc seizures in Subject 2 did not propagate to ANT. The relative change of ANT PIB was maximal ipsilateral to seizure onset for all detected seizures. Chronic ANT and Hc recordings provide direct guidance for ANT DBS with brain sensing.

Can we use intraoperative high-frequency oscillations to guide tumor-related epilepsy surgery?

OBJECTIVE: In people with low-grade intrinsic brain tumors, an epileptic focus is often located close to the lesion. High-frequency oscillations (HFOs) in electrocorticography (ECoG) might help to delineate this focus. We investigated the relationship between HFOs and low-grade brain tumors and their potential value for tumor-related epilepsy surgery. METHODS: We analyzed pre- and postresection intraoperative ECoG in 41 patients with refractory epilepsy and a low-grade lesion. Electrodes were designated as overlying the tumor, adjacent resected tissue (peritumoral), or outside the resection bed using magnetic resonance imaging (MRI) and intraoperative photographs. We then used a semiautomated approach to detect HFOs as either ripples (80-250 Hz) or fast ripples (250-500 Hz). RESULTS: The rate of fast ripples was higher in electrodes covering tumor and peritumoral tissue than outside the resection (p = .04). Mesiotemporal tumors showed more ripples (p = .002), but not more fast ripples (p = .07), than superficial tumors. Rates of fast ripples were higher in glioma and extraventricular neurocytoma than in ganglioglioma or dysembryoplastic neuroepithelial tumor (DNET). The rate of ripples and fast ripples in postresection ECoG was not higher in patients with residual tumor tissue on MRI than those without. The rate of ripples in postresection ECoG was higher in patients with good than bad seizure outcome (p = .03). Fast ripples outside the resection and in post-ECoG seem related to seizure recurrence. SIGNIFICANCE: Fast ripples in intraoperative ECoG can be used to help guide resection in tumor-related epilepsy surgery. Preresection fast ripples occur predominantly in epileptogenic tumor and peritumoral tissue. Fast ripple rates are higher in glioma and extraventricular neurocytoma than in ganglioglioma and DNET.

Closing the loop on impulsivity via nucleus accumbens delta-band activity in mice and man.

Reward hypersensitization is a common feature of neuropsychiatric disorders, manifesting as impulsivity for anticipated incentives. Temporally specific changes in activity within the nucleus accumbens (NAc), which occur during anticipatory periods preceding consummatory behavior, represent a critical opportunity for intervention. However, no available therapy is capable of automatically sensing and therapeutically responding to this vulnerable moment in time when anticipation-related neural signals may be present. To identify translatable biomarkers for an off-the-shelf responsive neurostimulation system, we record local field potentials from the NAc of mice and a human anticipating conventional rewards. We find increased power in 1- to 4-Hz oscillations predominate during reward anticipation, which can effectively trigger neurostimulation that reduces consummatory behavior in mice sensitized to highly palatable food. Similar oscillations are present in human NAc during reward anticipation, highlighting the translational potential of our findings in the development of a treatment for a major unmet need.