Electrical brain stimulation and continuous behavioral state tracking in ambulatory humans

Objective. Electrical deep brain stimulation (DBS) is an established treatment for patients with drug-resistant epilepsy. Sleep disorders are common in people with epilepsy, and DBS may actually further disturb normal sleep patterns and sleep quality. Novel implantable devices capable of DBS and streaming of continuous intracranial electroencephalography (iEEG) signals enable detailed assessments of therapy efficacy and tracking of sleep related comorbidities. Here, we investigate the feasibility of automated sleep classification using continuous iEEG data recorded from Papez's circuit in four patients with drug resistant mesial temporal lobe epilepsy using an investigational implantable sensing and stimulation device with electrodes implanted in bilateral hippocampus (HPC) and anterior nucleus of thalamus (ANT). Approach. The iEEG recorded from HPC is used to classify sleep during concurrent DBS targeting ANT. Simultaneous polysomnography (PSG) and sensing from HPC were used to train, validate and test an automated classifier for a range of ANT DBS frequencies: no stimulation, 2 Hz, 7 Hz, and high frequency (>100 Hz). Main results. We show that it is possible to build a patient specific automated sleep staging classifier using power in band features extracted from one HPC iEEG sensing channel. The patient specific classifiers performed well under all thalamic DBS frequencies with an average F1-score 0.894, and provided viable classification into awake and major sleep categories, rapid eye movement (REM) and non-REM. We retrospectively analyzed classification performance with gold-standard PSG annotations, and then prospectively deployed the classifier on chronic continuous iEEG data spanning multiple months to characterize sleep patterns in ambulatory patients living in their home environment. Significance. The ability to continuously track behavioral state and fully characterize sleep should prove useful for optimizing DBS for epilepsy and associated sleep, cognitive and mood comorbidities

Thalamic deep brain stimulation modulates cycles of seizure risk in epilepsy

Chronic brain recordings suggest that seizure risk is not uniform, but rather varies systematically relative to daily (circadian) and multiday (multidien) cycles. Here, one human and seven dogs with naturally occurring epilepsy had continuous intracranial EEG (median 298 days) using novel implantable sensing and stimulation devices. Two pet dogs and the human subject received concurrent thalamic deep brain stimulation (DBS) over multiple months. All subjects had circadian and multiday cycles in the rate of interictal epileptiform spikes (IES). There was seizure phase locking to circadian and multiday IES cycles in five and seven out of eight subjects, respectively. Thalamic DBS modified circadian (all 3 subjects) and multiday (analysis limited to the human participant) IES cycles. DBS modified seizure clustering and circadian phase locking in the human subject. Multiscale cycles in brain excitability and seizure risk are features of human and canine epilepsy and are modifiable by thalamic DBS

Mesenchymal stromal cells from human perinatal tissues: From biology to cell therapy

Cell-based regenerative medicine is of growing interest in biomedical research. The role of stem cells in this context is under intense scrutiny and may help to define principles of organ regeneration and develop innovative therapeutics for organ failure. Utilizing stem and progenitor cells for organ replacement has been conducted for many years when performing hematopoietic stem cell transplantation. Since the first successful transplantation of umbilical cord blood to treat hematological malignancies, non-hematopoietic stem and progenitor cell populations have recently been identified within umbilical cord blood and other perinatal and fetal tissues. A cell population entitled mesenchymal stromal cells (MSCs) emerged as one of the most intensely studied as it subsumes a variety of capacities: MSCs can differentiate into various subtypes of the mesodermal lineage, they secrete a large array of trophic factors suitable of recruiting endogenous repair processes and they are immunomodulatory

Nuclei-specific thalamic connectivity predicts seizure frequency in drug-resistant medial temporal lobe epilepsy

Background and objectives: We assessed correlations between the resting state functional connectivity (RSFC) of different thalamic nuclei and seizure frequency in patients with drug-resistant medial temporal lobe epilepsy (mTLE). Methods: Seventeen patients with mTLE and 17 sex-/age-/handedness-matched controls participated. A seed-based correlation method for the resting-state FMRI data was implemented to get RSFC maps of 70 thalamic nuclei seed masks. Group statistics for individual RSFC for subjects and seed masks were performed to obtain within-group characteristics and between-group differences with age covariates. A linear regression was applied to test whether seizure frequency correlated with thalamic nuclear RSFC with the whole brain in mTLE patients. Results: RSFC of thalamic nuclei showed spatially distinguishable connectivity patterns that reflected principal inputs and outputs that were derived from priori anatomical knowledge. We found group differences between normal control and mTLE groups in RSFC for nuclei seeds located in various subdivisions of thalamus. The RSFCs in some of those nuclei were strongly correlated with seizure frequency. Conclusions: Mediodorsal thalamic nuclei may play important roles in seizure activity or in the regulation of neuronal activity in the limbic system. The RSFC of motor- and sensory-relay nuclei may help elucidate sensory-motor deficits associated with chronic seizure activity. RSFC of the pulvinar nuclei of the thalamus could also be a key reflection of symptom-related functional deficits in mTLE

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

Automated sleep classification with chronic neural implants in freely behaving canines

Objective. Long-term intracranial electroencephalography (iEEG) in freely behaving animals provides valuable electrophysiological information and when correlated with animal behavior is useful for investigating brain function. Approach. Here we develop and validate an automated iEEG-based sleep–wake classifier for canines using expert sleep labels derived from simultaneous video, accelerometry, scalp electroencephalography (EEG) and iEEG monitoring. The video, scalp EEG, and accelerometry recordings were manually scored by a board-certified sleep expert into sleep–wake state categories: awake, rapid-eye-movement (REM) sleep, and three non-REM sleep categories (NREM1, 2, 3). The expert labels were used to train, validate, and test a fully automated iEEG sleep–wake classifier in freely behaving canines. Main results. The iEEG-based classifier achieved an overall classification accuracy of 0.878 ± 0.055 and a Cohen's Kappa score of 0.786 ± 0.090. Subsequently, we used the automated iEEG-based classifier to investigate sleep over multiple weeks in freely behaving canines. The results show that the dogs spend a significant amount of the day sleeping, but the characteristics of daytime nap sleep differ from night-time sleep in three key characteristics: during the day, there are fewer NREM sleep cycles (10.81 ± 2.34 cycles per day vs. 22.39 ± 3.88 cycles per night; p < 0.001), shorter NREM cycle durations (13.83 ± 8.50 min per day vs. 15.09 ± 8.55 min per night; p < 0.001), and dogs spend a greater proportion of sleep time in NREM sleep and less time in REM sleep compared to night-time sleep (NREM 0.88 ± 0.09, REM 0.12 ± 0.09 per day vs. NREM 0.80 ± 0.08, REM 0.20 ± 0.08 per night; p < 0.001). Significance. These results support the feasibility and accuracy of automated iEEG sleep–wake classifiers for canine behavior investigations

Three Levels of Ethical Influences on Selling Behavior and Performance: Synergies and Tensions

In general, the business ethics literature has treated the conceptual domains and outcomes of macro-level (industrial), meso-level (organizational), and micro-level (individual) ethical influence separately. However, this singular treatment ignores the synergies and tensions that can arise across these different types of ethical influence. Using sales as a research context, the current study argues that all three ethical frames of references are important in shaping employee behavior and performance and, as such, should be examined simultaneously. The findings show that industrial ethical climate and salesperson moral equity are positively associated with salesperson customer orientation. In addition, industrial and organizational ethical norms have a stronger joint effect on customer orientation than either ethical climate alone. More specifically, a more ethical organizational climate enhances the positive effects of the industrial ethical climate on customer orientation. Furthermore, whereas salesperson moral equity is significantly associated with salesperson customer orientation, strong moral equity beliefs in situations requiring adaptive selling result in weaker sales outcomes. This study concludes with a set of theoretical and actionable implications, as well as a discussion of future research avenues