Neural Function Research Articles

Astrocyte Calcium Signaling.

Astrocytes are predominant glial cells that tile the central nervous system and participate in well-established functional and morphological interactions with neurons, blood vessels, and other glia. These ubiquitous cells display rich intracellular Ca2+ signaling, which has now been studied for over 30 years. In this review, we provide a summary and perspective of recent progress concerning the study of astrocyte intracellular Ca2+ signaling as well as discussion of its potential functions. Progress has occurred in the areas of imaging, silencing, activating, and analyzing astrocyte Ca2+ signals. These insights have collectively permitted exploration of the relationships of astrocyte Ca2+ signals to neural circuit function and behavior in a variety of species. We summarize these aspects along with a framework for mechanistically interpreting behavioral studies to identify directly causal effects. We finish by providing a perspective on new avenues of research concerning astrocyte Ca2+ signaling.

Effects of Cycloastragenol on Alzheimer's Disease in Rats by Reducing Oxidative Stress, Inflammation, and Apoptosis.

As individuals age, they may develop Alzheimer's disease (AD), which is characterized by difficulties in speech, memory loss, and other issues related to neural function. Cycloastragenol is an active ingredient of Astragalus trojanus and has been used to treat inflammation, aging, heart disease, and cancer. This study aimed to explore the potential therapeutic benefits of cycloastragenol in rats with experimentally induced AD. Moreover, the underlying molecular mechanisms were also evaluated by measuring Nrf2 and HO-1, which are involved in oxidative stress, NFκB and TNF-α, which are involved in inflammation, and BCL2, BAX, and caspase-3, which are involved in apoptosis. Sprague-Dawley rats were given 70 mg/kg of aluminum chloride intraperitoneally daily for six weeks to induce AD. Following AD induction, the rats were given 25 mg/kg of cycloastragenol daily by oral gavage for three weeks. Hippocampal sections were stained with hematoxylin/ eosin and with anti-caspase-3 antibodies. The Nrf2, HO-1, NFκB, TNF-α, BCL2, BAX, and caspase-3 gene expressions and protein levels in the samples were analyzed. Cycloastragenol significantly improved rats' behavioral test performance. It also strengthened the organization of the hippocampus. Cycloastragenol significantly improved behavioral performance and improved hippocampal structure in rats. It caused a marked decrease in the expression of NFκB, TNF-α, BAX, and caspase-3, which was associated with an increase in the expression of BCL2, Nrf2, and HO-1. Cycloastragenol improved the structure of the hippocampus in rats with AD. It enhanced the outcomes of behavioral tests, decreased the concentration of AChE in the brain, and exerted antioxidant and anti-inflammatory effects. Antiapoptotic effects were also noted, leading to significant improvements in cognitive function, memory, and behavior in treated rats.

Sustained attention operates via dissociable neural mechanisms across different eccentric locations.

In primates, foveal and peripheral vision have distinct neural architectures and functions. However, it has been debated if selective attention operates via the same or different neural mechanisms across eccentricities. We tested these alternative accounts by examining the effects of selective attention on the steady-state visually evoked potential (SSVEP) and the fronto-parietal signal measured via EEG from human subjects performing a sustained visuospatial attention task. With a negligible level of eye movements, both SSVEP and SND exhibited the heterogeneous patterns of attentional modulations across eccentricities. Specifically, the attentional modulations of these signals peaked at the parafoveal locations and such modulations wore off as visual stimuli appeared closer to the fovea or further away towards the periphery. However, with a relatively higher level of eye movements, the heterogeneous patterns of attentional modulations of these neural signals were less robust. These data demonstrate that the top-down influence of covert visuospatial attention on early sensory processing in human cortex depends on eccentricity and the level of saccadic responses. Taken together, the results suggest that sustained visuospatial attention operates differently across different eccentric locations, providing new understanding of how attention augments sensory representations regardless of where the attended stimulus appears.

Soft Bioelectronics Using Nanomaterials and Nanostructures for Neuroengineering.

ConspectusThe identification of neural networks for large areas and the regulation of neuronal activity at the single-neuron scale have garnered considerable attention in neuroscience. In addition, detecting biochemical molecules and electrically, optically, and chemically controlling neural functions are key research issues. However, conventional rigid and bulky bioelectronics face challenges for neural applications, including mechanical mismatch, unsatisfactory signal-to-noise ratio, and poor integration of multifunctional components, thereby degrading the sensing and modulation performance, long-term stability and biocompatibility, and diagnosis and therapy efficacy. Implantable bioelectronics have been developed to be mechanically compatible with the brain environment by adopting advanced geometric designs and utilizing intrinsically stretchable materials, but such advances have not been able to address all of the aforementioned challenges.Recently, the exploration of nanomaterial synthesis and nanoscale fabrication strategies has facilitated the design of unconventional soft bioelectronics with mechanical properties similar to those of neural tissues and submicrometer-scale resolution comparable to typical neuron sizes. The introduction of nanotechnology has provided bioelectronics with improved spatial resolution, selectivity, single neuron targeting, and even multifunctionality. As a result, this state-of-the-art nanotechnology has been integrated with bioelectronics in two main types, i.e., bioelectronics integrated with synthesized nanomaterials and bioelectronics with nanoscale structures. The functional nanomaterials can be synthesized and assembled to compose bioelectronics, allowing easy customization of their functionality to meet specific requirements. The unique nanoscale structures implemented with the bioelectronics could maximize the performance in terms of sensing and stimulation. Such soft nanobioelectronics have demonstrated their applicability for neuronal recording and modulation over a long period at the intracellular level and incorporation of multiple functions, such as electrical, optical, and chemical sensing and stimulation functions.In this Account, we will discuss the technical pathways in soft bioelectronics integrated with nanomaterials and implementing nanostructures for application to neuroengineering. We traced the historical development of bioelectronics from rigid and bulky structures to soft and deformable devices to conform to neuroengineering requirements. Recent approaches that introduced nanotechnology into neural devices enhanced the spatiotemporal resolution and endowed various device functions. These soft nanobioelectronic technologies are discussed in two categories: bioelectronics with synthesized nanomaterials and bioelectronics with nanoscale structures. We describe nanomaterial-integrated soft bioelectronics exhibiting various functionalities and modalities depending on the integrated nanomaterials. Meanwhile, soft bioelectronics with nanoscale structures are explained with their superior resolution and unique administration methods. We also exemplified the neural sensing and stimulation applications of soft nanobioelectronics across various modalities, showcasing their clinical applications in the treatment of neurological diseases, such as brain tumors, epilepsy, and Parkinson's disease. Finally, we discussed the challenges and direction of next-generation technologies.

Clinical Neurophysiological Methods Verify Improvement in the Motor Neural Transmission in Patients with Surgically Treated Idiopathic Scoliosis in Long-Term Follow-up

The evaluation of patients after the surgical correction of idiopathic scoliosis in a long-term follow-up with clinical neurophysiological methods has not been presented in detail. This study aimed to compare the results of neurophysiological studies in 45 girls with scoliosis of Lenke types 1–3 performed pre- (T0) and postoperatively, 1 week after surgery (T1) and 6 months after surgery (T2). The parameter values of the surface electromyography while attempting maximal contraction (mcsEMG) and the transcranial motor-evoked potentials (MEPs) recorded in the anterior tibial muscles, as well as the electroneurography (ENG) of the peripheral transmission in the peroneal nerve motor fibers, were compared. The results indicate that efferent neural conduction function both centrally and peripherally, and TA muscle function slightly improved immediately after the surgical correction of scoliosis, and further normalization appeared after six months in the long-term follow-up (at p = 0.03). The sEMG recordings indicate that half a year after surgical treatment in IS patients, the TA muscle motor unit recruitment function, as well as the muscle strength evaluated with Lovett’s scale, was comparable to the normal condition. The ENG recording results indicated a gradual reduction in the motor fiber injury symptoms, mainly of the axonal type, in the peroneal nerves. The surgeries also improved the lumbar ventral roots’ neural transmission to a normal functional status. The MEP amplitude parameter values recorded after the surgical scoliosis corrections in T1 indicated a slight improvement in the efferent transmission of neural impulses within the fibers of the spinal tracts; in the long-term T2 observation period, they reached values comparable to those recorded in healthy volunteers, bilaterally. Preoperatively (T0), the results of all the neurophysiological study parameters in the IS patients were asymmetrical at p = 0.036–0.05 and recorded as worse on the concave side, suggesting the lateralization of neurological motor deficits. One week postoperatively (T1), this asymmetry was recorded as gradually reduced, showing almost no difference between the right and left sides six months later (T2). The presented algorithm for the neurophysiological assessments performed in the pre-, intra-, and long-term postoperative periods using the mcsEMG, MEP, and ENG neurophysiological examinations, together with the clinical studies, may help in the comprehensive functional evaluation of the spinal cord tracts and ventral root neural conduction, which allows the detection of the subclinical neurological changes related to scoliosis itself and the consequences of the corrective surgery. Such an evaluation can also be significant in making final decisions regarding IS surgeries and their personalization after attempting conservative treatments with bracing and kinesiotherapy. Neurophysiological studies, as a sensitive biomarker, allowed us to predict and ascertain the final result of IS treatment in the long-term follow-up, which showed the health status of patients as being comparable to that of healthy volunteers.

Impact of a multidisciplinary collaborative nutritional treatment model in patients who are critically ill with neurological disorders: A randomized controlled trial.

Malnutrition is a widespread problem in critically ill patients with neurological disorders. The purpose of this study is to investigate the effect of a multidisciplinary collaborative nutritional treatment mode based on a standardized unit for nutritional support on the outcome metrics in patients with neurological disorders who are critically ill. We enrolled 84 participants who were hospitalized in the intensive care unit (ICU) of Yancheng No. 1 People's Hospital for neurological disorders between June 2018 and December 2021. The participants were randomly assigned to the control group and the test group. The control group received traditional nutritional support, while the test group was treated with a multidisciplinary collaborative nutritional treatment mode based on a standardized unit for nutritional support. We collected the general information, feeding tolerance (FT), nutritional risk score, and laboratory indicators before intervention, after intervention for one week, and after intervention for 2 weeks, and other data of the participants. After the intervention, the test group scored significantly lower than the control group in the incidence of gastroparesis and diarrhea, as well as the NUTRIC score, with statistically significant differences (P< 0.001). The prealbumin levels in the test group increased progressively prior to intervention, after intervention for one week, and after intervention for two weeks. Compared to the control group, the test group had higher prealbumin levels prior to intervention, after intervention for one week, and after intervention for two weeks, with statistically significant differences (P< 0.001). We developed a multidisciplinary collaborative nutritional treatment model based on a standard unit for nutritional support. This model can improve neural function, FT, and pertinent outcome indicators and is generally applicable.

Characteristics and Neural Mechanisms of Sleep-Wake Disturbances After Traumatic Brain Injury.

Sleep-wake disturbances (SWDs) are one of the most common complaints following traumatic brain injury (TBI). The high prevalence and socioeconomic burden of SWDs post-TBI have only been recognized in the past decade. Common SWDs induced by TBI include excessive daytime sleepiness (EDS), hypersomnia, insomnia, obstructive sleep apnea (OSA), and circadian rhythm sleep disorders. Sleep disturbances can significantly compromise quality of life, strain interpersonal relationships, diminish work productivity, exacerbate other clinical conditions, and impede the rehabilitation process of TBI patients. Consequently, the prompt regulation and enhancement of sleep homeostasis in TBI patients is of paramount importance. Although studies have shown that abnormal neural network function, neuroendocrine changes, disturbance of sleep-wake regulators, and immune inflammatory responses related to brain structural damage induced by TBI are involved in the development of SWDs, the exact neuropathological mechanisms are still poorly understood. Therefore, we systematically review the current clinical and experimental studies on the characteristics and possible neural mechanisms of post-TBI SWDs. Elucidating the neural underpinnings of post-TBI SWDs holds the potential to diversify and enhance therapeutic approaches for these conditions. Such advancements could hasten the recuperation of TBI patients and ameliorate their overall quality of life. It is our aspiration that departments specializing in neurosurgery, rehabilitation, and neuropsychiatry will be able to recognize and address these conditions promptly, thereby facilitating the healing journey of affected individuals.

Implication of thermal signaling in neuronal differentiation revealed by manipulation and measurement of intracellular temperature

Neuronal differentiation—the development of neurons from neural stem cells—involves neurite outgrowth and is a key process during the development and regeneration of neural functions. In addition to various chemical signaling mechanisms, it has been suggested that thermal stimuli induce neuronal differentiation. However, the function of physiological subcellular thermogenesis during neuronal differentiation remains unknown. Here we create methods to manipulate and observe local intracellular temperature, and investigate the effects of noninvasive temperature changes on neuronal differentiation using neuron-like PC12 cells. Using quantitative heating with an infrared laser, we find an increase in local temperature (especially in the nucleus) facilitates neurite outgrowth. Intracellular thermometry reveals that neuronal differentiation is accompanied by intracellular thermogenesis associated with transcription and translation. Suppression of intracellular temperature increase during neuronal differentiation inhibits neurite outgrowth. Furthermore, spontaneous intracellular temperature elevation is involved in neurite outgrowth of primary mouse cortical neurons. These results offer a model for understanding neuronal differentiation induced by intracellular thermal signaling.

Crosstalk Between Cell Death and Spinal Cord Injury: Neurology and Therapy.

Spinal cord injury (SCI) often leads to neurological dysfunction, and neuronal cell death is one of the main causes of neurological dysfunction. After SCI, in addition to necrosis, programmed cell death (PCD) occurs in nerve cells. At first, studies recognized only necrosis, apoptosis, and autophagy. In recent years, researchers have identified new forms of PCD, including pyroptosis, necroptosis, ferroptosis, and cuproptosis. Related studies have confirmed that all of these cell death modes are involved in various phases of SCI and affect the direction of the disease through different mechanisms and pathways. Furthermore, regulating neuronal cell death after SCI through various means has been proven to be beneficial for the recovery of neural function. In recent years, emerging therapies for SCI have also provided new potential methods to restore neural function. Thus, the relationship between SCI and cell death plays an important role in the occurrence and development of SCI. This review summarizes and generalizes the relevant research results on neuronal necrosis, apoptosis, autophagy, pyroptosis, necroptosis, ferroptosis, and cuproptosis after SCI to provide a new understanding of neuronal cell death after SCI and to aid in the treatment of SCI.

Contrasting neurofunctional correlates of face- and visuospatial-processing in children and adolescents with Williams syndrome: convergent results from four fMRI paradigms

Understanding neurogenetic mechanisms underlying neuropsychiatric disorders such as schizophrenia and autism is complicated by their inherent clinical and genetic heterogeneity. Williams syndrome (WS), a rare neurodevelopmental condition in which both the genetic alteration (hemideletion of ~ twenty-six 7q11.23 genes) and the cognitive/behavioral profile are well-defined, offers an invaluable opportunity to delineate gene-brain-behavior relationships. People with WS are characterized by increased social drive, including particular interest in faces, together with hallmark difficulty in visuospatial processing. Prior work, primarily in adults with WS, has searched for neural correlates of these characteristics, with reports of altered fusiform gyrus function while viewing socioemotional stimuli such as faces, along with hypoactivation of the intraparietal sulcus during visuospatial processing. Here, we investigated neural function in children and adolescents with WS by using four separate fMRI paradigms, two that probe each of these two cognitive/behavioral domains. During the two visuospatial tasks, but not during the two face processing tasks, we found bilateral intraparietal sulcus hypoactivation in WS. In contrast, during both face processing tasks, but not during the visuospatial tasks, we found fusiform hyperactivation. These data not only demonstrate that previous findings in adults with WS are also present in childhood and adolescence, but also provide a clear example that genetic mechanisms can bias neural circuit function, thereby affecting behavioral traits.

A neural network copula function approach for solving joint basic probability assignment in structural reliability analysis

AbstractApplying evidence theory to structural reliability analysis under epistemic uncertainty, it is necessary to consider the correlation of evidence variables. Among them, solving the joint basic probability assignment (BPA) of the evidence variables is a crucial link. In this study, a solution method of joint BPA based on neural network copula function is proposed. This method is to automatically construct copula function through neural network, which avoids the process of selecting the optimal copula function. Firstly, the neural network copula function is constructed based on the sample set of evidence variables. Then, the expression for solving the joint BPA using the neural network copula function is derived through vectors. Furthermore, the expression is used to map the marginal BPA of evidence variables to joint BPA, thus realizing the solution of joint BPA. Finally, the effectiveness of this method is verified by three examples. The results show that the neural network copula function describes the data distribution better than the optimal copula function selected by the traditional method. In addition, there is actually an error in solving the reliability intervals using the traditional optimal copula function method, whereas the results of this paper's neural network copula function method are more accurate and better for decision making.

Learning continuous shape priors from sparse data with neural implicit functions.

Statistical shape models are an essential tool for various tasks in medical image analysis, including shape generation, reconstruction and classification. Shape models are learned from a population of example shapes, which are typically obtained through segmentation of volumetric medical images. In clinical practice, highly anisotropic volumetric scans with large slice distances are prevalent, e.g., to reduce radiation exposure in CT or image acquisition time in MR imaging. For existing shape modeling approaches, the resolution of the emerging model is limited to the resolution of the training shapes. Therefore, any missing information between slices prohibits existing methods from learning a high-resolution shape prior. We propose a novel shape modeling approach that can be trained on sparse, binary segmentation masks with large slice distances. This is achieved through employing continuous shape representations based on neural implicit functions. After training, our model can reconstruct shapes from various sparse inputs at high target resolutions beyond the resolution of individual training examples. We successfully reconstruct high-resolution shapes from as few as three orthogonal slices. Furthermore, our shape model allows us to embed various sparse segmentation masks into a common, low-dimensional latent space - independent of the acquisition direction, resolution, spacing, and field of view. We show that the emerging latent representation discriminates between healthy and pathological shapes, even when provided with sparse segmentation masks. Lastly, we qualitatively demonstrate that the emerging latent space is smooth and captures characteristic modes of shape variation. We evaluate our shape model on two anatomical structures: the lumbar vertebra and the distal femur, both from publicly available datasets.

Nr4a1 regulates cell-specific transcriptional programs in inhibitory GABAergic interneurons.

The patterns of synaptic connectivity and physiological properties of diverse neuron types are shaped by distinct gene sets. Our study demonstrates that, in the mouse forebrain, the transcriptional profiles of inhibitory GABAergic interneurons are regulated by Nr4a1, an orphan nuclear receptor whose expression is transiently induced by sensory experiences and is required for normal learning. Nr4a1 exerts contrasting effects on the local axonal wiring of parvalbumin- and somatostatin-positive interneurons, which innervate different subcellular domains of their postsynaptic partners. The loss of Nr4a1 activity in these interneurons results in bidirectional, cell-type-specific transcriptional switches across multiple gene families, including those involved in surface adhesion and repulsion. Our findings reveal that combinatorial synaptic organizing codes are surprisingly flexible and highlight a mechanism by which inducible transcription factors can influence neural circuit structure and function.

IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning

We propose a novel framework for uncertainty quantification via information bottleneck (IB-UQ) for scientific machine learning tasks, including deep neural network (DNN) regression and neural operator learning (DeepONet). Specifically, we incorporate the bottleneck by a confidence-aware encoder, which encodes inputs into latent representations according to the confidence of the input data belonging to the region where training data is located, and utilize a Gaussian decoder to predict means and variances of outputs conditional on representation variables. Furthermore, we propose a data augmentation based information bottleneck objective which can enhance the quantification quality of the extrapolation uncertainty, and the encoder and decoder can be both trained by minimizing a tractable variational bound of the objective. In comparison to uncertainty quantification (UQ) methods for scientific learning tasks that rely on Bayesian neural networks with Hamiltonian Monte Carlo posterior estimators, the model we propose is computationally efficient, particularly when dealing with large-scale datasets. The effectiveness of the IB-UQ model has been demonstrated through several representative examples, such as regression for discontinuous functions, learning nonlinear operators for partial differential equations, and a large-scale climate map model. The experimental results indicate that the IB-UQ model can handle noisy data, generate robust predictions, and provide confident uncertainty evaluation for out-of-distribution data.

A positive affect intervention alters leukocyte DNA methylation in sexual minority men with HIV who use methamphetamine

ObjectiveThis epigenomics sub-study embedded within a randomized controlled trial examined whether an evidenced-based behavioral intervention model that decreased stimulant use altered leukocyte DNA methylation (DNAm). MethodsSexual minority men with HIV who use methamphetamine were randomized to a five-session positive affect intervention (n = 32) or an attention-control condition (n = 21), both delivered during three months of contingency management for stimulant abstinence. All participants exhibited sustained HIV virologic control – an HIV viral load less than 40 copies/mL at baseline and six months post-randomization. The Illumina EPIC BeadChip measured leukocyte methylation of cytosine-phosphate-guanosine (CpG) sites mapping onto five a priori candidate genes of interest (i.e., ADRB2, BDNF, FKBP5, NR3C1, OXTR). Functional DNAm pathways and soluble markers of immune dysfunction were secondary outcomes. ResultsCompared to the attention-control condition, the positive affect intervention significantly decreased methylation of CpG sites on genes that regulate β2 adrenergic and oxytocin receptors. There was an inconsistent pattern for the direction of the intervention effects on methylation of CpG sites on genes for glucocorticoid receptors and brain-derived neurotrophic factor. Pathway analyses adjusting for the false discovery rate (padj < 0.05) revealed significant intervention-related alterations in DNAm of Reactome pathways corresponding to neural function as well as dopamine, glutamate, and serotonin release. Positive affect intervention effects on DNAm were accompanied by significant reductions in the self-reported frequency of stimulant use. ConclusionsThere is an epigenetic signature of an evidence-based behavioral intervention model that reduced stimulant use, which will guide the identification of biomarkers for treatment responses.

GABA transporter mGat4 is involved in multiple neural functions in mice

γ-Aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the central nervous system. The termination of GABA transmission is through the action of GABA transporters (GATs). mGAT4 (encoded by Slc6a11) is another GAT besides GAT1 (encoded by Slc6a1) that functions in GABA reuptake in CNS. Research on the function of mGAT4 is still in its infancy. We developed an mGat4 knockout mouse model (mGat4−/− mice) and performed a series of behavioral analyses for the first time to study the effect of mGat4 on biological processes in CNS. Our results indicated that homozygous mGat4−/− mice had less depression, anxiety-like behavior and more social activities than their wild-type littermate controls. However, they had weight loss and showed motor incoordination and imbalance. Meanwhile, mGat4−/− mice showed increased pain threshold and hypoalgesia behavior in nociceptive stimulus and learning and memory impairments. The expression of multiple components of the GABAergic system including GAD67, GABAA and KCC2 was altered. There is little or no compensatory change in mGat1. In a word, mGat4 may play a key role in normal motor coordination, sensation, emotion, learning and memory and could be the potential target of neurological disorders.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice.

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within 'remapped' forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within ‘remapped’ forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

Multifunctional ultraflexible neural probe for wireless optogenetics and electrophysiology

Electrophysiology and optogenetics are pivotal in neuroscience for probing and modulating neural activities, playing a vital role in unraveling the complexities of brain functionality. Despite their importance, the efficacy of existing devices is hampered by insufficient functional integration, pronounced foreign body reactions, and physical constraints that impede natural animal behaviors. Here, we develop a multifunctional, ultraflexible neural probe designed for simultaneous electrophysiological monitoring and optical neural modulation, along with mechanical properties that are conducive to flexibility and compliance. By integrating a wireless neural signal acquisition and stimulation circuit, we achieved wireless recording of brain signals in mice and wireless optogenetic control over their locomotor behavior. The multifunctional ultraflexible probe presented in this study holds substantial promise for closed-loop brain-machine interfaces and deepening our understanding of neural circuit functions. This innovative approach addresses the aforementioned limitations by a comprehensive solution for in vivo neural interrogation and manipulation, marking a significant advancement in the tools available for neuroscience research.

C-Reactive Protein Does Not Predict Future Depression Onset in Adolescents: Preliminary Findings from a Longitudinal Study.

Introduction: Neuroinflammatory processes have been extensively implicated in the underlying neurobiology of numerous neuropsychiatric disorders. Elevated C-reactive protein (CRP), an indicator of nonspecific inflammation commonly utilized in clinical practice, has been associated with depression in adults. In adolescents, our group previously found CRP to be associated with altered neural reward function but not with mood and anxiety symptoms assessed cross-sectionally. We hypothesized that the distinct CRP findings in adolescent versus adult depression may be due to chronicity, with neuroinflammatory effects on psychiatric disorders gradually accumulating over time. Here, we conducted a longitudinal study to evaluate if CRP levels predicted future onset or progression of depression in adolescents. Methods: Participants were 53 adolescents (age = 14.74 ± 1.92 years, 35 female), 40 with psychiatric symptoms and 13 healthy controls. At baseline, participants completed semistructured diagnostic evaluations; dimensional assessments for anxiety, depression, anhedonia, and suicidality severity; and bloodwork to quantify CRP levels. Clinical assessments were repeated at longitudinal follow-up after ∼1.5 years. Spearman's correlation between CRP levels and follow-up symptom severity were controlled for body mass index, age, sex, and follow-up interval and considered significant at the two-tailed, Bonferroni-adjusted p < 0.05 level. Results: After correction for multiple comparisons, no relationships were identified between baseline CRP levels and follow-up symptom severity. Conclusion: CRP levels were not significantly associated with future psychiatric symptoms in adolescents in this preliminary analysis. This may suggest that CRP is not a useful biomarker for adolescent depression and anxiety. However, future longitudinal studies with larger sample sizes and incorporating additional indicators of neuroinflammation are needed.