Cingulate dynamics track depression recovery with deep brain stimulation.

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD)1. However, achieving stable recovery is unpredictable2, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting3. We currently lack objective brain-based biomarkers to guide clinical decisions by distinguishing natural transient mood fluctuations from situations requiring intervention. To address this gap, we used a new device enabling electrophysiology recording to deliver SCC DBS to ten TRD participants (ClinicalTrials.gov identifier NCT01984710). At the study endpoint of 24 weeks, 90% of participants demonstrated robust clinical response, and 70% achieved remission. Using SCC local field potentials available from six participants, we deployed an explainable artificial intelligence approach to identify SCC local field potential changes indicating the patient's current clinical state. This biomarker is distinct from transient stimulation effects, sensitive to therapeutic adjustments and accurate at capturing individual recovery states. Variable recovery trajectories are predicted by the degree of preoperative damage to the structural integrity and functional connectivity within the targeted white matter treatment network, and are matched by objective facial expression changes detected using data-driven video analysis. Our results demonstrate the utility of objective biomarkers in the management of personalized SCC DBS and provide new insight into the relationship between multifaceted (functional, anatomical and behavioural) features of TRD pathology, motivating further research into causes of variability in depression treatment.

Outcome measures in pediatric chronic inflammatory demyelinating polyradiculoneuropathy.

INTRODUCTION/AIMS: Objective outcome measures in children undergoing treatment for chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) are lacking. The aim of the study was to record serial grip strength and motor nerve conduction studies to assess interval change. METHODS: This was a retrospective review of 16 children (8 females and 8 males; median age, 9.7 years; interquartile range, 6-13 years) with CIDP followed at a tertiary children's hospital from 2013 to 2021. Subjects were treated with intravenous immunoglobulin (IVIG). Right and left grip strength measurements were obtained at each clinic visit using a handheld dynamometer. Annual right median motor nerve conduction study data were recorded during the study period. RESULTS: Mean duration of follow-up was 2.9 years. Grip strength (right: 0.19 kg/month, p < 0.001; left 0.23 kg/month, p < 0.001) and median F-wave latencies (-0.23/month, p = 0.015) showed significant improvement over time. Akaike information criterion showed time + IVIG frequency <21 days as best fit for grip strength and distal compound muscle action potential amplitude. DISCUSSION: Our study results indicate serial grip strength measurements are a feasible and objective way to assess motor strength improvement in children with CIDP receiving immunotherapy.

DeepLabCut increases markerless tracking efficiency in X-ray video analysis of rodent locomotion.

Despite the prevalence of rat models to study human disease and injury, existing methods for quantifying behavior through skeletal movements are problematic owing to skin movement inaccuracies associated with optical video analysis, or require invasive implanted markers or time-consuming manual rotoscoping for X-ray video approaches. We examined the use of a machine learning tool, DeepLabCut, to perform automated, markerless tracking in bi-planar X-ray videos of locomoting rats. Models were trained on 590 pairs of video frames to identify 19 unique skeletal landmarks of the pelvic limb. Accuracy, precision and time savings were assessed. Machine-identified landmarks deviated from manually labeled counterparts by 2.4±0.2 mm (n=1710 landmarks). DeepLabCut decreased analysis time by over three orders of magnitude (1627×) compared with manual labeling. Distribution of these models may enable the processing of a large volume of accurate X-ray kinematics locomotion data in a fraction of the time without requiring surgically implanted markers.

Solution Chemistry to Control Boron-Containing Monolayers on Silicon: Reactions of Boric Acid and 4-Fluorophenylboronic Acid with H- and Cl-terminated Si(100).

The reactions of boric acid and 4-fluorophenylboronic acid with H- and Cl-terminated Si(100) surfaces in solution were investigated. X-ray photoelectron spectroscopy (XPS) studies reveal that both molecules react preferentially with Cl-Si(100) and not with H-Si(100) at identical conditions. On Cl-Si(100), the reactions introduce boron onto the surface, forming a Si-O-B structure. The quantification of boron surface coverage demonstrates that the 4-fluorophenylboronic acid leads to ∼2.8 times higher boron coverage compared to that of boric acid on Cl-Si(100). Consistent with these observations, density functional theory studies show that the reaction of boric acid and 4-fluorophenylboronic acid is more favorable with the Cl- versus H-terminated surface and that on Cl-Si(100) the reaction with 4-fluorophenylboronic acid is ∼55.3 kJ/mol more thermodynamically favorable than the reaction with boric acid. The computational studies were also used to demonstrate the propensity of the overall approach to form high-coverage monolayers on these surfaces, with implications for selective-area boron-based monolayer doping.

Reaction of Hydrazine with Solution- and Vacuum-Prepared Selectively Terminated Si(100) Surfaces: Pathways to the Formation of Direct Si-N Bonds.

The reactivity of liquid hydrazine (N2H4) with respect to H-, Cl-, and Br-terminated Si(100) surfaces was investigated to uncover the principles of nitrogen incorporation into the interface. This process has important implications in a wide variety of applications, including semiconductor surface passivation and functionalization, nitride growth, and many others. The use of hydrazine as a precursor allows for reactions that exclude carbon and oxygen, the primary sources of contamination in processing. In this work, the reactivity of N2H4 with H- and Cl-terminated surfaces prepared by traditional solvent-based methods and with a Br-terminated Si(100) prepared in ultrahigh vacuum was compared. The reactions were studied with X-ray photoelectron spectroscopy, atomic force microscopy, and scanning tunneling microscopy, and the observations were supported by computational investigations. The H-terminated surface led to the highest level of nitrogen incorporation; however, the process proceeds with increasing surface roughness, suggesting possible etching or replacement reactions. In the case of Cl-terminated (predominantly dichloride) and Br-terminated (monobromide) surfaces, the amount of nitrogen incorporation on both surfaces after the reaction with hydrazine was very similar despite the differences in preparation, initial structure, and chemical composition. Density functional theory was used to propose the possible surface structures and to analyze surface reactivity.

Reaction of BCl3 with H- and Cl-terminated Si(1 0 0) as a pathway for selective, monolayer doping through wet chemistry.

The reaction of boron trichloride with the H and Cl-terminated Si(100) surfaces was investigated to understand the interaction of this molecule with the surface for designing wet-chemistry based silicon surface doping processes using a carbon- and oxygen-free precursor. The process was followed with X-ray photoelectron spectroscopy (XPS). Within the reaction conditions investigated, the reaction is highly effective on Cl-Si(100) for temperatures below 70°C, at which point both surfaces react with BCl3. The XPS investigation followed the formation of a B 1s peak at 193.5 eV corresponding to (B-O)x species. Even the briefest exposure to ambient conditions lead to hydroxylation of surface borochloride species. However, the Si 2p signature at 102 eV allowed for a confirmation of the formation of a direct Si-B bond. Density functional theory was utilized to supplement the analysis and identify possible major surface species resulting from these reactions. This work provides a new pathway to obtain a functionalized silicon surface with a direct Si-B bond that can potentially be exploited as a means of selective, ultra-shallow, and supersaturated doping.

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI).

The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.

Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period.

Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.

Differential fiber-specific block of nerve conduction in mammalian peripheral nerves using kilohertz electrical stimulation.

Kilohertz electrical stimulation (KES) has been shown to induce repeatable and reversible nerve conduction block in animal models. In this study, we characterized the ability of KES stimuli to selectively block specific components of stimulated nerve activity using in vivo preparations of the rat sciatic and vagus nerves. KES stimuli in the frequency range of 5-70 kHz and amplitudes of 0.1-3.0 mA were applied. Compound action potentials were evoked using either electrical or sensory stimulation, and block of components was assessed through direct nerve recordings and muscle force measurements. Distinct observable components of the compound action potential had unique conduction block thresholds as a function of frequency of KES. The fast component, which includes motor activity, had a monotonically increasing block threshold as a function of the KES frequency. The slow component, which includes sensory activity, showed a nonmonotonic block threshold relationship with increasing KES frequency. The distinct trends with frequency of the two components enabled selective block of one component with an appropriate choice of frequency and amplitude. These trends in threshold of the two components were similar when studying electrical stimulation and responses of the sciatic nerve, electrical stimulation and responses of the vagus nerve, and sensorimotor stimulation and responses of the sciatic nerve. This differential blocking effect of KES on specific fibers can extend the applications of KES conduction block to selective block and stimulation of neural signals for neuromodulation as well as selective control of neural circuits underlying sensorimotor function.

Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks.

In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics.

Charged Impurity Scattering and Electron-Electron Interactions in Large-Area Hydrogen Intercalated Bilayer Graphene.

Intercalation is a promising technique to modify the structural and electronic properties of 2D materials on the wafer scale for future electronic device applications. Yet, few reports to date demonstrate 2D intercalation as a viable technique on this scale. Spurred by recent demonstrations of mm-scale sensors, we use hydrogen intercalated quasi-freestanding bilayer graphene (hQBG) grown on 6H-SiC(0001), to understand the electronic properties of a large-area (16 mm2) device. To do this, we first analyze Shubnikov-de Haas (SdH) oscillations and weak localization, permitting determination of the Fermi level, cyclotron effective mass, and quantum scattering time. Our transport results indicate that at low temperature, scattering in hQBG is dominated by charged impurities and electron-electron interactions. Using low- temperature scanning tunneling microscopy and spectroscopy (STS), we investigate the source of the charged impurities on the nm-scale via observation of Friedel oscillations. Comparison to theory suggests that the Friedel oscillations we observe are caused by hydrogen vacancies underneath the hQBG. Furthermore, STS measurements demonstrate that hydrogen vacancies in the hQBG have an extremely localized effect on the local density of states, such that the Fermi level of the hQBG is only affected directly above the location of the defect. Hence, we find that the calculated Fermi level from SdH oscillations on the millimeter scale agrees with the value measured locally on the nanometer scale with STS measurements.

Electrical polarization of titanium surfaces for the enhancement of osteoblast differentiation.

Electrical stimulation has been used clinically to promote bone regeneration in cases of fractures with delayed union or nonunion, with several in vitro and in vivo reports suggesting its beneficial effects on bone formation. However, the use of electrical stimulation of titanium (Ti) implants to enhance osseointegration is less understood, in part because of the few in vitro models that attempt to represent the in vivo environment. In this article, the design of a new in vitro system that allows direct electrical stimulation of osteoblasts through their Ti substrates without the flow of exogenous currents through the media is presented, and the effect of applied electrical polarization on osteoblast differentiation and local factor production was evaluated. A custom-made polycarbonate tissue culture plate was designed to allow electrical connections directly underneath Ti disks placed inside the wells, which were supplied with electrical polarization ranging from 100 to 500 mV to stimulate MG63 osteoblasts. Our results show that electrical polarization applied directly through Ti substrates on which the cells are growing in the absence of applied electrical currents may increase osteoblast differentiation and local factor production in a voltage-dependent manner.

Contentious problems in bioscience and biotechnology: a pilot study of an approach to ethics education.

This manuscript describes a pilot study in ethics education employing a problem-based learning approach to the study of novel, complex, ethically fraught, unavoidably public, and unavoidably divisive policy problems, called "fractious problems," in bioscience and biotechnology. Diverse graduate and professional students from four US institutions and disciplines spanning science, engineering, humanities, social science, law, and medicine analyzed fractious problems employing "navigational skills" tailored to the distinctive features of these problems. The students presented their results to policymakers, stakeholders, experts, and members of the public. This approach may provide a model for educating future bioscientists and bioengineers so that they can meaningfully contribute to the social understanding and resolution of challenging policy problems generated by their work.

Mitigating Mismatch Compression in Differential Local Field Potentials.

Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.

Strain-tunable Berry curvature in quasi-two-dimensional chromium telluride.

Magnetic transition metal chalcogenides form an emerging platform for exploring spin-orbit driven Berry phase phenomena owing to the nontrivial interplay between topology and magnetism. Here we show that the anomalous Hall effect in pristine Cr2Te3 thin films manifests a unique temperature-dependent sign reversal at nonzero magnetization, resulting from the momentum-space Berry curvature as established by first-principles simulations. The sign change is strain tunable, enabled by the sharp and well-defined substrate/film interface in the quasi-two-dimensional Cr2Te3 epitaxial films, revealed by scanning transmission electron microscopy and depth-sensitive polarized neutron reflectometry. This Berry phase effect further introduces hump-shaped Hall peaks in pristine Cr2Te3 near the coercive field during the magnetization switching process, owing to the presence of strain-modulated magnetic layers/domains. The versatile interface tunability of Berry curvature in Cr2Te3 thin films offers new opportunities for topological electronics.

Dynamic Oscillations Evoked by Subcallosal Cingulate Deep Brain Stimulation.

Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCCwm) alleviates symptoms of depression, but its mechanistic effects on brain dynamics remain unclear. In this study we used novel intracranial recordings (LFP) in n = 6 depressed patients stimulated with DBS around the SCCwm target, observing a novel dynamic oscillation (DOs). We confirm that DOs in the LFP are of neural origin and consistently evoked within certain patients. We then characterize the frequency and dynamics of DOs, observing significant variability in DO behavior across patients. Under the hypothesis that LFP-DOs reflect network engagement, we characterize the white matter tracts associated with LFP-DO observations and report a preliminary observation of DO-like activity measured in a single patient's electroencephalography (dEEG). These results support further study of DOs as an objective signal for mechanistic study and connectomics guided DBS.

Two types of independent bursting mechanisms in inspiratory neurons: an integrative model.

The network of coupled neurons in the pre-Bötzinger complex (pBC) of the medulla generates a bursting rhythm, which underlies the inspiratory phase of respiration. In some of these neurons, bursting persists even when synaptic coupling in the network is blocked and respiratory rhythmic discharge stops. Bursting in inspiratory neurons has been extensively studied, and two classes of bursting neurons have been identified, with bursting mechanism depends on either persistent sodium current or changes in intracellular Ca(2+), respectively. Motivated by experimental evidence from these intrinsically bursting neurons, we present a two-compartment mathematical model of an isolated pBC neuron with two independent bursting mechanisms. Bursting in the somatic compartment is modeled via inactivation of a persistent sodium current, whereas bursting in the dendritic compartment relies on Ca(2+) oscillations, which are determined by the neuromodulatory tone. The model explains a number of conflicting experimental results and is able to generate a robust bursting rhythm, over a large range of parameters, with a frequency adjusted by neuromodulators.

Effects of heterogeneity in synaptic conductance between weakly coupled identical neurons.

A significant degree of heterogeneity in synaptic conductance is present in neuron to neuron connections. We study the dynamics of weakly coupled pairs of neurons with heterogeneities in synaptic conductance using Wang-Buzsaki and Hodgkin-Huxley model neurons which have Types I and II excitability, respectively. This type of heterogeneity breaks a symmetry in the bifurcation diagrams of equilibrium phase difference versus the synaptic rate constant when compared to the identical case. For weakly coupled neurons coupled with identical values of synaptic conductance a phase locked solution exists for all values of the synaptic rate constant, α. In particular, in-phase and anti-phase solutions are guaranteed to exist for all α. Heterogeneity in synaptic conductance results in regions where no phase locked solution exists and the general loss of the ubiquitous in-phase and anti-phase solutions of the identically coupled case. We explain these results through examination of interaction functions using the weak coupling approximation and an in-depth analysis of the underlying multiple cusp bifurcation structure of the systems of coupled neurons.

Synaptic and intrinsic determinants of the phase resetting curve for weak coupling.

A phase resetting curve (PRC) keeps track of the extent to which a perturbation at a given phase advances or delays the next spike, and can be used to predict phase locking in networks of oscillators. The PRC can be estimated by convolving the waveform of the perturbation with the infinitesimal PRC (iPRC) under the assumption of weak coupling. The iPRC is often defined with respect to an infinitesimal current as z(i)(ϕ), where ϕ is phase, but can also be defined with respect to an infinitesimal conductance change as z(g)(ϕ). In this paper, we first show that the two approaches are equivalent. Coupling waveforms corresponding to synapses with different time courses sample z(g)(ϕ) in predictably different ways. We show that for oscillators with Type I excitability, an anomalous region in z(g)(ϕ) with opposite sign to that seen otherwise is often observed during an action potential. If the duration of the synaptic perturbation is such that it effectively samples this region, PRCs with both advances and delays can be observed despite Type I excitability. We also show that changing the duration of a perturbation so that it preferentially samples regions of stable or unstable slopes in z(g)(ϕ) can stabilize or destabilize synchrony in a network with the corresponding dynamics.

Conflicting effects of excitatory synaptic and electric coupling on the dynamics of square-wave bursters.

Using two-cell and 50-cell networks of square-wave bursters, we studied how excitatory coupling of individual neurons affects the bursting output of the network. Our results show that the effects of synaptic excitation vs. electrical coupling are distinct. Increasing excitatory synaptic coupling generally increases burst duration. Electrical coupling also increases burst duration for low to moderate values, but at sufficiently strong values promotes a switch to highly synchronous bursts where further increases in electrical or synaptic coupling have a minimal effect on burst duration. These effects are largely mediated by spike synchrony, which is determined by the stability of the in-phase spiking solution during the burst. Even when both coupling mechanisms are strong, one form (in-phase or anti-phase) of spike synchrony will determine the burst dynamics, resulting in a sharp boundary in the space of the coupling parameters. This boundary exists in both two cell and network simulations. We use these results to interpret the effects of gap-junction blockers on the neuronal circuitry that underlies respiration.