Local Field Research Articles

Effects of ketamine on frontoparietal interactions in a rule-based antisaccade task in macaque monkeys.

Cognitive control is engaged by working memory processes and high-demand situations like antisaccade, where one must suppress a prepotent response. While it is known to be supported by the frontoparietal control network, how intra- and inter-areal dynamics contribute to cognitive control processes remain unclear. N-Methyl-D-aspartate glutamate receptors (NMDARs) play a key role in prefrontal dynamics that support cognitive control, and its antagonists, such as ketamine, are known to alter task-related prefrontal activities and impair cognitive performance. However, the role of NMDAR in cognitive control-related frontoparietal dynamics remain underexplored. Here, we simultaneously recorded local field potentials and single unit activities from lateral prefrontal (lPFC) and posterior parietal cortices (PPC) in two male macaque monkeys during a rule-based antisaccade task, with both Rule-Visible (RV) and Rule-Memorized (RM) conditions. In addition to altering the E/I balance in both areas, ketamine had a negative impact on rule-coding in true oscillatory activities. It also reduced frontoparietal coherence in a frequency- and rule-dependent manner. Granger prediction analysis revealed that ketamine induced an overall reduction in bidirectional connectivity. Among antisaccade trials, a greater reduction in lPFC-PPC connectivity during the delay period preceded a greater delay in saccadic onset under the RM condition, and a greater deficit in performance under the RV condition. Lastly, ketamine compromised rule coding in lPFC neurons in both RV and RM conditions, and in PPC neurons only in the RV condition. Our findings demonstrate the utility of acute NMDA receptor antagonist in understanding the mechanisms through which frontoparietal dynamics support cognitive control processes.Significance statement A low dose of ketamine is known to induce a transient cognitive control deficit in healthy humans and animals, but it remains unclear whether this deficit is related to a frontoparietal dysconnection. In macaque monkeys performing a rule-based pro- and anti-saccade task, we found that ketamine impaired information coding in frontoparietal neuron, local oscillations and inter-areal synchrony in a rule- and frequency-dependent manner. Notably, under the antisaccade rule, the amount of impairment in task performance could be predicted by the loss in fronto-parietal connectivity in the period just before the monkeys responded. The observations support the utility of NMDA receptor antagonists like ketamine as a tool to understand the role of frontoparietal dynamics in cognitive control.

PDeT: A Progressive Deformable Transformer for Photovoltaic Panel Defect Segmentation

Defects in photovoltaic (PV) panels can significantly reduce the power generation efficiency of the system and may cause localized overheating due to uneven current distribution. Therefore, adopting precise pixel-level defect detection, i.e., defect segmentation, technology is essential to ensuring stable operation. However, for effective defect segmentation, the feature extractor must adaptively determine the appropriate scale or receptive field for accurate defect localization, while the decoder must seamlessly fuse coarse-level semantics with fine-grained features to enhance high-level representations. In this paper, we propose a Progressive Deformable Transformer (PDeT) for defect segmentation in PV cells. This approach effectively learns spatial sampling offsets and refines features progressively through coarse-level semantic attention. Specifically, the network adaptively captures spatial offset positions and computes self-attention, expanding the model’s receptive field and enabling feature extraction across objects of various shapes. Furthermore, we introduce a semantic aggregation module to refine semantic information, converting the fused feature map into a scale space and balancing contextual information. Extensive experiments demonstrate the effectiveness of our method, achieving an mIoU of 88.41% on our solar cell dataset, outperforming other methods. Additionally, to validate the PDeT’s applicability across different domains, we trained and tested it on the MVTec-AD dataset. The experimental results demonstrate that the PDeT exhibits excellent recognition performance in various other scenarios as well.

High Q transparency, strong third harmonic generation, and giant nonlinear chirality driven by toroidal dipole-quasi-BIC

Electromagnetically induced transparency (EIT), nonlinearity, and optical chirality hold significant applications in many areas such as optical switches, slow-light devices, chiral harmonic conversion, and optical storage. In this work, we theoretically propose an asymmetric all-dielectric metasurface supporting toroidal dipole-quasi-bound states in the continuum (TD-q-BICs). High quality (Q) EIT, strong third harmonic generation (THG), and giant nonlinear chirality are achieved via the extremely enhanced electric field energy localized in the Si plate by the TD-q-BIC. A huge transition from high Q EIT with transmission of ∼0.99 to strong chirality with circular dichroism (CD) of ∼0.9 is realized by tuning the angle and polarization state of incident light. Strong THG with efficiency of 4.5 × 10−3 under linear polarization light is due to the highly localized electric field supported by the TD-q-BIC and perfect nonlinear CD chirality with theoretically value of ∼1 originates from the large discrepancy in electric field distributions under different circularly polarized light. Our work provides an innovative paradigm to construct TD-q-BICs-governed EIT analogs, THG, and nonlinear chirality for the development of multifunction nanophotonic meta-devices.

A finite element based approach for nonlocal stress analysis for multi-phase materials and composites

AbstractThis study proposes a numerical method for calculating the stress fields in nano-scale multi-phase/composite materials, where the classical continuum theory is inadequate due to the small-scale effects, including intermolecular spaces. The method focuses on weakly nonlocal and inhomogeneous materials and involves post-processing the local stresses obtained using a conventional finite element approach, applying the classical continuum theory to calculate the nonlocal stresses. The capabilities of this method are demonstrated through some numerical examples, namely, a two-dimensional case with a circular inclusion and some commonly used scenarios to model nanocomposites. Representative volume elements of various nanocomposites, including epoxy-based materials reinforced with fumed silica, silica (Nanopox F700), and rubber (Albipox 1000) are subjected to uniaxial tensile deformation combined with periodic boundary conditions. The local and nonlocal stress fields are computed through numerical simulations and after post-processing are compared with each other. The results acquired through the nonlocal theory exhibit a softening effect, resulting in reduced stress concentration and less of a discontinuous behaviour. This research contributes to the literature by proposing an efficient and standardised numerical method for analysing the small-scale stress distribution in small-scale multi-phase materials, providing a method for more accurate design in the nano-scale regime. This proposed method is also easy to implement in standard finite element software that employs classical continuum theory.

Learning-dependent gating of hippocampal inputs by frontal interneurons

The hippocampus is a brain region that is essential for the initial encoding of episodic memories. However, the consolidation of these memories is thought to occur in the neocortex, under guidance of the hippocampus, over the course of days and weeks. Communication between the hippocampus and the neocortex during hippocampal sharp wave-ripple oscillations is believed to be critical for this memory consolidation process. Yet, the synaptic and circuit basis of this communication between brain areas is largely unclear. To address this problem, we perform in vivo whole-cell patch-clamp recordings in the frontal neocortex and local field potential recordings in CA1 of head-fixed mice exposed to a virtual-reality environment. In mice trained in a goal-directed spatial task, we observe a depolarization in frontal principal neurons during hippocampal ripple oscillations. Both this ripple-associated depolarization and goal-directed task performance can be disrupted by chemogenetic inactivation of somatostatin-positive (SOM+) interneurons. In untrained mice, a ripple-associated depolarization is not observed, but it emerges when frontal parvalbumin-positive (PV+) interneurons are inactivated. These results support a model where SOM+ interneurons inhibit PV+ interneurons during hippocampal activity, thereby acting as a disinhibitory gate for hippocampal inputs to neocortical principal neurons during learning.

Enhancing drug-target interaction predictions in context of neurodegenerative diseases using bidirectional long short-term memory in male Swiss albino mice pharmaco-EEG analysis

Background and ObjectiveEmerging diseases like Parkinson or Alzheimer's, which are not curable, endanger human mental health and are challenging to research. Drug target interactions (DTI) are pivotal in the screening of candidate drugs and focus on a small pool of drug targets. Electroencephalogram shows the responses to psychotropic medicines in the brain bioelectric activity. Synaptic activity can be analyzed by using Local Field Potential recordings obtained from micro-electrodes implanted in the brain. The aim is to evaluate the effects of drug on brain bioelectric activity and increase the drug classification accuracy. The ultimate goal is to advance our understanding of how drugs affect synaptic activity and open the door to more focused treatment for neurodegenerative diseases. MethodsIn this study, Pharmaco-EEG recordings are processed using Advanced neural network models, particularly Convolutional Neural Networks, to assess the effects of medications. The five different medicines used in this study are Ephedrine, Fluoxetine, Kratom, Morphine, and Saline. The signals observed are local field potential signals. To overcome some limits of DTI prediction, we propose Bidirectional Long Short-Term Memory (LSTM) for the categorization of intracranial EEG (i-EEG) data, departing from standard approaches. Similar EEG patterns are presumably caused by drugs that work by homologous pharmacological pathways, producing similar psychotropic effects. To improve accuracy and reduce training loss, our study introduces a bidirectional LSTM model for classification along with Bayesian optimization ResultsHigh recall, precision, and F1-Scores, particularly a 95% F1-Score for morphine, ephedrine, fluoxetine, and saline, suggest good performance in predicting these drug classes. Kratom produces a somewhat lower recall of 94%, but a high F1-Score of 97% and perfect precision of 1.00. The weighted average F1-Score, macro average, and overall accuracy are all consistently high (around 97%), indicating that the model works well throughout the spectrum of drugs. ConclusionsImproved model performance was demonstrated by using a diversified dataset with five drug categories and bidirectional LSTM boosted with Bayesian optimization for hyperparameter tuning. From earlier limited-category models, it represents a substantial advancement.

Effects of puerarin on gait disturbance in a 6-hydroxydopamine mouse model of Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder caused by dopamine (DA) neuronal dysfunction. Although DA agonists and N-methyl-D-aspartate receptor (NMDAR) antagonists are used to treat PD, chronic use causes severe side effects. Puerarin (PUE) is a natural bioactive compound that affects the DA system; however, its effect on PD-associated motor functions is unknown. Therefore, we investigated whether PUE treatment in a 6-hydroxydopamine (6-OHDA) PD mouse model affects motor dysfunction. Adult male ICR mice received unilateral 6-OHDA microinfusion into the right medial forebrain bundle. After a 2-week recovery period, PUE (20 or 50mg/kg) or the vehicle (saline, VEH) was administered intraperitoneally once daily for 21 days. Motor dysfunction was assessed using the locomotion, gait cycle, and rotation tests. Local field potentials (LFPs) were measured in the substantia nigra compacta (SNc), striatum (STR), subthalamic nucleus (STN), and primary motor cortex. 6-OHDA-lesioned PD mice showed increased gait cycle disturbance and unidirectional rotation. PUE treatment ameliorated the gait cycle disturbance, but not unidirectional rotation of PD mice. These effects differed with DA agonist treatment (which improved PD symptoms) and NMDAR antagonist treatment (which aggravated PD symptoms). Moreover, locomotion was increased only in NMDAR antagonist treatment. PUE treatment induced no changes in the attenuated LFP of the beta wave in the STR and STN, and SNc-STN delta-wave coherence was shown in PD animals. This study suggests that PUE is a beneficial co-therapeutic agent for alleviating gait cycle disturbance in PD symptoms.

Quantitative magnetooptical analysis using indicator films for the detection of magnetic field distributions, temperature, and electrical currents

The accurate characterization of local magnetic fields and temperature is vital for the design of electronic systems. To meet this imperative, we present a novel non-contact approach for simultaneous quantitative magnetic field imaging and temperature sensing using magnetooptics and a bismuth-doped yttrium iron garnet film with out-of-plane anisotropy. For the direct signal quantification, a Stokes polarization camera is employed in a conventional magnetooptical microscope. The magnetization in the garnet is modulated with an external magnetic field to continuously image the Faraday rotation at four distinct points along the saturating magnetization loop. The method enables sensing of the magnetooptical signal in saturation, the magnetooptical susceptibility, the temperature, and self-calibrated driftfree imaging of the out-of-plane magnetic field component. A spatial resolution of magnetic field in the micrometer range with millisecond exposure time is demonstrated. The method is verified by analyzing the stray magnetic field distribution of electrical current in a wire simultaneously to the Joule heating induced by the applied current.

Unveiling non-monochromatic modes and nonlinearity in Piet Hein quantum semiconductor waveguides

We investigate the propagation characteristics of transverse electric (TE) and transverse magnetic (TM) modes in a semiconductor quantum plasma-filled coaxial waveguide with a Piet Hein cross-section. The unique geometry of the Piet Hein cross-section offers intriguing possibilities for tailoring modal properties and exploiting novel nonlinear phenomena. Using analytical and numerical methods, we unveil the non-monochromatic behaviour of TE and TM modes, characterized by distinct peaks and troughs in their field components. The Ez\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_{z}$$\\end{document} component of the TM mode exhibits a suppressed field within the central core and higher concentration in the cladding region, potentially minimizing energy loss within the waveguide. The Eρ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_{\\rho }$$\\end{document} component exhibits pronounced oscillations near the waveguide boundaries, suggesting constructive and destructive interference patterns. The Eξ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_{\\xi }$$\\end{document} component displays a non-monotonic behaviour with multiple pits and bumps, highlighting the interplay between the TE mode, the Piet Hein geometry, and the semiconductor quantum plasma properties. The Bρ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_{\\rho }$$\\end{document} component of the TM mode exhibits a non-monochromatic behaviour with multiple maxima and minima, attributed to the complex interactions between propagating waves with different phase shifts. The Bξ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_{\\xi }$$\\end{document} component exhibits a non-uniform distribution with distinct pits and bumps, with a resurgence towards the waveguide edges potentially due to higher-order mode contributions and local field enhancement effects. Our findings pave the way for the development of novel photonic devices with enhanced functionalities based on Piet Hein semiconductor quantum plasma waveguides.

Performance enhancement of magnetoactive elastomer soft robots through a coupled magnetoelastic topology optimization scheme

Abstract We have found that considering local magnetic fields, large deformations, and magnetoelastic coupling simultaneously significantly affect the resulting shape in magnetoelastic topology optimization in a uniaxial actuator case. In contrast to the work presented here, other works incorporate magnetoelastic formulations that include simplifying assumptions on the local field, and subsequent effects on the magnetization response of the material, or the absence of large deformation mechanics, or both. These assumptions were shown to produce solutions that differ substantively from cases where local fields and large deformations are addressed concurrently. Magnetoelastic topology optimization schemes are needed to optimize magnetoactive elastomer (MAE) devices. MAE devices are magnetic particle-filled polymer matrices designed for specific actuations and controlled remotely by an external magnetic field. They garner considerable research interest as an emerging technology for actuators in soft robots or in applications requiring untethered actuation. The material properties of MAEs are dependent on the volume fraction of particles in the elastomer matrix, where a high-volume fraction increases relative permeability (for soft magnetic particles) but also increases elastic modulus. For optimal actuation, a tradeoff between low stiffness and high magnetic response must be made by adjusting volume fraction and controlling material placement. Using a topology optimization scheme that considers both the magnetic and mechanical properties of the material, the shape and material composition of the device can be tuned to best achieve the desired actuation displacement. In this work, a density-based magnetoelastic multimaterial topology optimization scheme for soft magnetic material is developed in COMSOL Multiphysics. The optimization scheme uses multiphysics coupling that considers local magnetic fields and large deformations at each iteration through a Maxwell stress tensor formulation. A simulated example is then considered to demonstrate the effectiveness and necessity of a coupled optimization. The effect of considering large deformations during optimization is also investigated. It was found that a coupled topology optimization scheme with large deformations produced shapes with modes of actuation not captured by schemes with simplifying assumptions, leading to better performance at lower material cost. Considering large deformations in the coupled scheme offered significantly better performance, with an increase of 81.3% in a side-by-side performance simulation when compared to uncoupled cases.

Piezoelectric Heterojunctions as Bacteria-Killing Bone-Regenerative Implants.

Heterojunctions are widely used in energy conversion, environmental remediation, and photodetection, but have not been fully explored in regenerative medicine. In particular, piezoelectric heterojunctions have never been examined in tissue regeneration. Here the development of piezoelectric heterojunctions is shown to promote bone regeneration while eradicating pathogenic bacteria through light-cellular force-electric coupling. Specifically, an array of heterojunctions (TiO2/Bi2WO6), made of piezoelectric nanocrystals (Bi2WO6) decorating TiO2 nanowires, is fabricated as a biocompatible implant. Upon exposure to near-infrared light, the piezoelectric heterojunctions generate reactive oxygen species and heat to kill bacteria through photodynamic and photothermal therapy, respectively. Meanwhile, the mechanical forces of the stem cells grown on the implant trigger the heterojunctions to produce electric fields that further promote osteogenesis to achieve osteointegration. The heterojunctions effectively suppress postoperative recurrent infections while promoting osseointegration through the local electric fields induced by cells. Therefore, the piezoelectric heterojunctions represent a promising antibacterial tissue-regenerative implant.

Immersed boundary method for dynamic simulation of polarizable colloids of arbitrary shape in explicit ion electrolytes.

We develop a computational method for modeling electrostatic interactions of arbitrarily shaped, polarizable objects on colloidal length scales, including colloids/nanoparticles, polymers, and surfactants, dispersed in explicit ion electrolytes and nonionic solvents. Our method computes the nonuniform polarization charge distribution induced in a colloidal particle by both externally applied electric fields and local electric fields arising from other charged objects in the dispersion. This leads to expressions for electrostatic energies, forces, and torques that enable efficient molecular dynamics and Brownian dynamics simulations of colloidal dispersions in electrolytes, which can be harnessed to accurately predict structural and transport properties. We describe an implementation in which colloidal particles are modeled as rigid composites of small spherical beads that tessellate the surface of the particle. The electrostatics calculations are accelerated using a spectrally accurate particle-mesh-Ewald technique implemented on a graphics processing unit and regularized such that the electrostatic calculations are well-defined even for overlapping bodies. We illustrate the effectiveness of this approach with a comprehensive set of calculations: the induced dipole moments and forces for individual, paired, and lattice configurations of spherical colloids in an electric field; the induced dipole moment and torque for anisotropic particles subjected to an electric field; the equilibrium ion distribution in the double layer surrounding charged colloids; the dynamics of charged colloids; and the behavior of ions in the double layer of a polarizable colloid under the influence of an electric field.

Analysis of nerve excitability in the dentate gyrus of the hippocampus in cerebral ischaemia-reperfusion mice

Ischemic stroke often leads to cognitive dysfunction, which delays the recovery process of patients. However, its pathogenesis is not yet clear. In this study, the cerebral ischemia-reperfusion model was built as the experimental object, and the hippocampal dentate gyrus (DG) was the target brain area. TTC staining was used to evaluate the degree of cerebral infarction, and nerve cell membrane potentials and local field potentials (LFPs) signals were collected to explore the mechanism of cognitive impairment in ischemia-reperfusion mice. The results showed that the infarcted area on the right side of the brain of the mice in the model group was white. The resting membrane potential, the number of action potential discharges, the post-hyperpolarization potential and the maximum ascending slope of the hippocampal DG nerve cells in the model mice were significantly lower than those in the control group ( P < 0.01); the peak time, half-wave width, threshold and maximum descending slope of the action potential were significantly higher than those in the control group ( P < 0.01). The time-frequency energy values of LFPs signals in the θ and γ bands of mice in the ischemia and reperfusion groups were significantly reduced ( P < 0.01), and the time-frequency energy values in the reperfusion group were increased compared with the ischemia group ( P < 0.01). The signal complexity of LFPs in the ischemia and reperfusion group was significantly reduced ( P < 0.05), and the signal complexity in the reperfusion group was increased compared with the ischemia group ( P < 0.05). In summary, cerebral ischemia-reperfusion reduced the excitability of nerve cells in the DG area of the mouse hippocampus; cerebral ischemia reduced the discharge activity and signal complexity of nerve cells, and the electrophysiological indicators recovered after reperfusion, but it failed to reach the healthy state during the experiment period.

Thalamic Local Field Potentials and Closed-Loop Deep Brain Stimulation in Orthostatic Tremor.

Orthostatic tremor (OT) is a rare movement disorder characterized by a feeling of unsteadiness and a high-frequency tremor in the legs (13-18 Hz) relieved by sitting or walking. The aims were to study the brain electrophysiology captured chronically in a person with medication-refractory OT while standing and walking and in the semi-recumbent position using bilateral ventral intermedius nucleus deep brain stimulation (DBS) (Medtronic Percept PC) and to describe the clinical use of closed-loop DBS. A sensing survey was used to capture baseline local field potentials (LFPs) while standing. Livestreamed LFPs were synchronized with data collected from two accelerometers (legs) and gait analysis during OFF stimulation and continuous and closed-loop DBS. Strong oscillatory coupling between thalamic LFP and leg tremor with significant coherence at 14.65 Hz was found during weight-bearing. Single-threshold adaptive DBS (sensing at this frequency) was superior to continuous stimulation in reducing tremor and stimulation-related gait ataxia. This study provides new insights into both the pathophysiology and management of OT. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A parametrization of nonassociative cyclic algebras of prime degree

We determine and explicitly parametrize the isomorphism classes of nonassociative quaternion algebras over a field of characteristic different from two, as well as the isomorphism classes of nonassociative cyclic algebras of odd prime degree m when the base field contains a primitive mth root of unity. In the course of doing so, we prove that any two such algebras can be isomorphic only if the cyclic field extension and the chosen generator of the Galois group are the same. As an application, we give a parametrization of nonassociative cyclic algebras of prime degree over a local nonarchimedean field F, which is entirely explicit under mild hypotheses on the residual characteristic. In particular, this gives a rich understanding of the important class of nonassociative quaternion algebras up to isomorphism over nonarchimedean local fields.

Synergistic effects in Na0.5Bi0.5TiO3-based thin film through stress field regulation for excellent capacitive energy storage

Thin film dielectric capacitors have attracted significant attention under the current trend of integration and portability in electronic devices. In this work, Na0.5Bi0.5(Fe0.03Ti0.97)O3–SrTiO3 (NBFT–STO) thin films are synthesized via sol–gel method onto flexible Pt/Mica and rigid Pt/Ti/SiO2/Si substrates, respectively to obtain NBFT–STO dielectric capacitors under different local stress fields. Synergistic effects between dielectric polarization and breakdown strength (EBD), as well as dielectric polarization and polarization hysteresis are obtained, with the rigid one exhibiting higher EBD and the flexible one possessing high polarization linearity. Excellent capacitive energy storage performance with Wrec of 28.00 J/cm3 and η of 70.44 % are obtained at 20 kHz for the NBFT–STO thin film onto Pt/Mica. These findings provide a new route to modulate polarization behavior of NBT–based thin film through stress field regulation for capacitive energy storage.

Dislocation‐induced local symmetry reduction in single‐crystal KNbO3 observed by Raman spectroscopy

AbstractIn recent years, dislocation‐tuned functionalized ceramics have become one of the focal points of modern materials research due to their outstanding properties. These range from improved electrical conductivity and ferroelectric properties to dislocation‐enhanced toughening and superconductivity, caused by local strain fields. The aim of this work is to investigate the dislocation‐induced structural changes in single‐crystal KNbO3 by micro‐Raman spectroscopy. Dislocation‐rich regions with tailored densities have been generated using the Brinell indenter scratching method. The influence of the dislocations on the single‐crystal structure can be observed in the Raman spectra. The activation of additional Raman modes is observed, which does not occur in regions of low dislocation density. This observation is confirmed by DFT calculations of vibrational modes and is attributed to a reduction in the crystal symmetry due to increased defect densities in plastically deformed KNbO3. In addition, an increase in compressive stress at higher dislocation densities can be demonstrated by a blueshift in Raman mode positions.

Integration of single-photon miniature fluorescence microscopy and electrophysiological recording methods for &lt;i&gt;in vivo&lt;/i&gt; studying hippocampal neuronal activity

The miniature single-photon fluorescent microscope (miniscope) enables the visualization of calcium activity in vivo in freely moving laboratory animals, providing the capability to track cellular activity during the investigation of memory formation, learning, sleep, and social interactions. However, the use of calcium sensors for in vivo imaging is limited by their relatively slow (millisecond-scale) kinetics, which complicates the recording of high-frequency spike activity. The integration of methods from single-photon miniature fluorescent microscopy with electrophysiological recording, which possesses microsecond resolution, represents a potential solution to this issue. Such a combination of techniques allows for the simultaneous recording of optical and electrophysiological activity in a single animal in vivo. In this study, a flexible polyimide microelectrode was developed and integrated with the gradient lens of the miniscope. The in vivo tests conducted in this research confirmed that the microelectrode combined with the gradient lens facilitates simultaneous single-photon calcium imaging and local field potential recording in the hippocampus of an adult mouse.

Latent dynamics of primary sensory cortical population activity structured by fluctuations in the local field potential.

As emerging technologies enable measurement of precise details of the activity within microcircuits at ever-increasing scales, there is a growing need to identify the salient features and patterns within the neural populations that represent physiologically and behaviorally relevant aspects of the network. Accumulating evidence from recordings of large neural populations suggests that neural population activity frequently exhibits relatively low-dimensional structure, with a small number of variables explaining a substantial fraction of the structure of the activity. While such structure has been observed across the brain, it is not known how reduced-dimension representations of neural population activity relate to classical metrics of "brain state," typically described in terms of fluctuations in the local field potential (LFP), single-cell activity, and behavioral metrics. Hidden state models were fit to spontaneous spiking activity of populations of neurons, recorded in the whisker area of primary somatosensory cortex of awake mice. Classic measures of cortical state in S1, including the LFP and whisking activity, were compared to the dynamics of states inferred from spiking activity. A hidden Markov model fit the population spiking data well with a relatively small number of states, and putative inhibitory neurons played an outsize role in determining the latent state dynamics. Spiking states inferred from the model were more informative of the cortical state than a direct readout of the spiking activity of single neurons or of the population. Further, the spiking states predicted both the trial-by-trial variability in sensory responses and one aspect of behavior, whisking activity. Our results show how classical measurements of brain state relate to neural population spiking dynamics at the scale of the microcircuit and provide an approach for quantitative mapping of brain state dynamics across brain areas.

Arginine vasopressin induces analgesic effects and inhibits pyramidal cells in the anterior cingulate cortex in spared nerve injured mice.

Neuropathic pain (NP) is a severe disease caused by a primary disease or lesion affecting the somatosensory nervous system. It`s reported that NP is related to the increased activity of glutamatergic pyramidal cells and changed neural oscillations in the anterior cingulate cortex (ACC). Arginine vasopressin (AVP), a neurohypophyseal hormone, has been shown to cause pain-alleviating effects when applied to peripheral system. However, the extent to which, and the mechanisms by which, AVP induces analgesic effects in the central nervous system remain unclear. In the present study, we observed that intranasal delivery of AVP inhibited mechanical pain, thermal pain and spontaneous pain sensitivity in mice with spared nerve injury. Meanwhile, AVP application exclusively reduced the FOS expression in the pyramidal cells but not interneurons in the ACC. In vivo electrophysiological recording of the ACC further showed that AVP application not only inhibited the theta oscillation in local field potential analysis, but also reduced the firing rate of spikes of pyramidal cells in the ACC in neuropathic pain mice. In summary, AVP induce analgesic effects by inhibiting neural theta oscillations and the spiking of pyramidal cells of the ACC in mice with neuropathic pain, which should provide new potential noninvasive methods for clinical treatment of chronic pain.