Neural Circuits Research Articles

Neurobiology and Treatment of Posttraumatic Stress Disorder.

The recent worldwide surge of warfare and hostilities exposes increasingly large numbers of individuals to traumatic events, placing them at risk of developing posttraumatic stress disorder (PTSD) and challenging both clinicians and service delivery systems. This overview summarizes and updates the core knowledge of the genetic, molecular, and neural circuit features of the neurobiology of PTSD and advances in evidence-based psychotherapy, pharmacotherapy, neuromodulation, and digital treatments. While the complexity of the neurobiology and the biological and clinical heterogeneity of PTSD have challenged clinicians and researchers, there is an emerging consensus concerning the underlying mechanisms and approaches to diagnosis, treatment, and prevention of PTSD. This update addresses PTSD diagnosis, prevalence, course, risk factors, neurobiological mechanisms, current standard of care, and innovations in next-generation treatment and prevention strategies. It provides a comprehensive summary and concludes with areas of research for integrating advances in the neurobiology of the disorder with novel treatment and prevention targets.

Prediction of vulnerability severity using vulnerability description with natural language processing and deep learning

One of the most critical aspects of a software piece is its vulnerabilities. Regardless of the years of experience, type of project, or the size of the team, it is impossible to avoid introducing vulnerabilities while developing or maintaining software. This aspect becomes crucial when the software is deployed in production or released to the final users. At that point finding vulnerabilities becomes a race between the developers and malicious intruders, whoever finds it first can either exploit it or fix it. Acknowledging this situation and using the tools and standards that we have available in the field, such as common vulnerability exposures and common vulnerability scoring systems, and based on modern researches, in this study, we propose to have an approach different from the common practices of manual classification, using a 2-layer convolutional neuronal network (CNN) to automatize the classification of vulnerabilities, speeding up this process and enabling developers to have a faster response towards vulnerabilities, producing safer software. The experimental results obtained in this study suggest that pre-trained word embeddings contributed to an increase in accuracy of approximately 2% and the overall accuracy become 0.816%.

Population bursts in a modular neural network as a mechanism for synchronized activity in KNDy neurons.

The pulsatile activity of gonadotropin-releasing hormone neurons (GnRH neurons) is a key factor in the regulation of reproductive hormones. This pulsatility is orchestrated by a network of neurons that release the neurotransmitters kisspeptin, neurokinin B, and dynorphin (KNDy neurons), and produce episodic bursts of activity driving the GnRH neurons. We show in this computational study that the features of coordinated KNDy neuron activity can be explained by a neural network in which connectivity among neurons is modular. That is, a network structure consisting of clusters of highly-connected neurons with sparse coupling among the clusters. This modular structure, with distinct parameters for intracluster and intercluster coupling, also yields predictions for the differential effects on synchronization of changes in the coupling strength within clusters versus between clusters.

A Detailed Re-Examination of the Period Gene Rescue Experiments Shows That Four to Six Cryptochrome-Positive Posterior Dorsal Clock Neurons (DN1p) of Drosophila melanogaster Can Control Morning and Evening Activity.

Animal circadian clocks play a crucial role in regulating behavioral adaptations to daily environmental changes. The fruit fly Drosophila melanogaster exhibits 2 prominent peaks of activity in the morning and evening, known as morning (M) and evening (E) peaks. These peaks are controlled by 2 distinct circadian oscillators located in separate groups of clock neurons in the brain. To investigate the clock neurons responsible for the M and E peaks, a cell-specific gene expression system, the GAL4-UAS system, has been commonly employed. In this study, we re-examined the two-oscillator model for the M and E peaks of Drosophila by utilizing more than 50 Gal4 lines in conjunction with the UAS-period16 line, which enables the restoration of the clock function in specific cells in the period (per) null mutant background. Previous studies have indicated that the group of small ventrolateral neurons (s-LNv) is responsible for controlling the M peak, while the other group, consisting of the 5th ventrolateral neuron (5th LNv) and the three cryptochrome (CRY)-positive dorsolateral neurons (LNd), is responsible for the E peak. Furthermore, the group of posterior dorsal neurons 1 (DN1p) is thought to also contain M and E oscillators. In this study, we found that Gal4 lines directed at the same clock neuron groups can lead to different results, underscoring the fact that activity patterns are influenced by many factors. Nevertheless, we were able to confirm previous findings that the entire network of circadian clock neurons controls M and E peaks, with the lateral neurons playing a dominant role. In addition, we demonstrate that 4 to 6 CRY-positive DN1p cells are sufficient to generate M and E peaks in light-dark cycles and complex free-running rhythms in constant darkness. Ultimately, our detailed screening could serve as a catalog to choose the best Gal4 lines that can be used to rescue per in specific clock neurons.

Multitask learning of a biophysically-detailed neuron model.

The human brain operates at multiple levels, from molecules to circuits, and understanding these complex processes requires integrated research efforts. Simulating biophysically-detailed neuron models is a computationally expensive but effective method for studying local neural circuits. Recent innovations have shown that artificial neural networks (ANNs) can accurately predict the behavior of these detailed models in terms of spikes, electrical potentials, and optical readouts. While these methods have the potential to accelerate large network simulations by several orders of magnitude compared to conventional differential equation based modelling, they currently only predict voltage outputs for the soma or a select few neuron compartments. Our novel approach, based on enhanced state-of-the-art architectures for multitask learning (MTL), allows for the simultaneous prediction of membrane potentials in each compartment of a neuron model, at a speed of up to two orders of magnitude faster than classical simulation methods. By predicting all membrane potentials together, our approach not only allows for comparison of model output with a wider range of experimental recordings (patch-electrode, voltage-sensitive dye imaging), it also provides the first stepping stone towards predicting local field potentials (LFPs), electroencephalogram (EEG) signals, and magnetoencephalography (MEG) signals from ANN-based simulations. While LFP and EEG are an important downstream application, the main focus of this paper lies in predicting dendritic voltages within each compartment to capture the entire electrophysiology of a biophysically-detailed neuron model. It further presents a challenging benchmark for MTL architectures due to the large amount of data involved, the presence of correlations between neighbouring compartments, and the non-Gaussian distribution of membrane potentials.

Motor cortical inactivation impairs corrective submovements in mice performing a hold-still center-out reach task.

Holding still and aiming reaches to spatial targets may depend on distinct neural circuits. Using automated homecage training and a sensitive joystick, we trained freely-moving mice to contact a joystick, hold their forelimb still, and then reach to rewarded target locations. Mice learned the task by initiating forelimb sequences with clearly resolved submillimeter-scale micromovements followed by millimeter-scale reaches to learned spatial targets. Hundreds of thousands of trajectories were decomposed into millions of kinematic submovements, while photoinhibition was used to test roles of motor cortical areas. Inactivation of both caudal and rostral forelimb areas preserved the ability to produce aimed reaches, but reduced reach speed. Inactivation specifically of contralateral caudal forelimb area (CFA) additionally impaired the ability to aim corrective submovements to remembered locations following target undershoots. Our findings show that motor cortical inactivations reduce the gain of forelimb movements but that inactivation specifically of contralateral CFA impairs corrective movements important for reaching a target location.

In vivo optogenetics using a Utah Optrode Array with enhanced light output and spatial selectivity.

Optogenetics allows the manipulation of neural circuits in vivo with high spatial and temporal precision. However, combining this precision with control over a significant portion of the brain is technologically challenging (especially in larger animal models). Here, we have developed, optimised, and tested in vivo, the Utah Optrode Array (UOA), an electrically addressable array of optical needles and interstitial sites illuminated by 181 µLEDs and used to optogenetically stimulate the brain. The device is specifically designed for non-human primate studies. Thinning the combined µLED and needle backplane of the device from 300 µm to 230 µm improved the efficiency of light delivery to tissue by 80%, allowing lower µLED drive currents, which improved power management and thermal performance. The spatial selectivity of each site was also improved by integrating an optical interposer to reduce stray light emission. These improvements were achieved using an innovative fabrication method to create an anodically bonded glass/silicon substrate with through-silicon vias etched, forming an optical interposer. Optical modelling was used to demonstrate that the tip structure of the device had a major influence on the illumination pattern. The thermal performance was evaluated through a combination of modelling and experiment, in order to ensure that cortical tissue temperatures did not rise by more than 1°C. The device was tested in vivo in the visual cortex of macaque expressing ChR2-tdTomato in cortical neurons. It was shown that the UOA produced the strongest optogenetic response in the region surrounding the needle tips, and that the extent of the optogenetic response matched the predicted illumination profile based on optical modelling - demonstrating the improved spatial selectivity resulting from the optical interposer approach. Furthermore, different needle illumination sites generated different patterns of low-frequency potential (LFP) activity.

Multiple Sex- and Circuit-Specific Mechanisms Underlie Exercise-Induced Stress Resistance.

Prior physical activity reduces the risk of future stress-related mental health disorders including depression, anxiety, and post-traumatic stress disorder. Rodents allowed to engage in voluntary wheel running are similarly protected from behavioral consequences of stress. The present review summarizes current knowledge on mechanisms underlying exercise-induced stress resistance. A conceptual framework involving the development (during exercise) and expression (during stress) of stress resistance from exercise is proposed. During the development of stress resistance, adaptations involving multiple exercise signals and molecular mediators occur within neural circuits orchestrating various components of the stress response, which then respond differently to stress during the expression of stress resistance. Recent data indicate that the development and expression of stress resistance from exercise involve multiple independent mechanisms that depend on sex, stressor severity, and behavioral outcome. Recent insight into the role of the prefrontal cortex in exercise-induced stress resistance illustrates these multiple mechanisms. This knowledge has important implications for the design of future experiments aimed at identifying the mechanisms underlying exercise-induced stress resistance.

Recall tempo of Hebbian sequences depends on the interplay of Hebbian kernel with tutor signal timing

Understanding how neural circuits generate sequential activity is a longstanding challenge. While foundational theoretical models have shown how sequences can be stored as memories in neural networks with Hebbian plasticity rules, these models considered only a narrow range of Hebbian rules. Here, we introduce a model for arbitrary Hebbian plasticity rules, capturing the diversity of spike-timing-dependent synaptic plasticity seen in experiments, and show how the choice of these rules and of neural activity patterns influences sequence memory formation and retrieval. In particular, we derive a general theory that predicts the tempo of sequence replay. This theory lays a foundation for explaining how cortical tutor signals might give rise to motor actions that eventually become "automatic." Our theory also captures the impact of changing the tempo of the tutor signal. Beyond shedding light on biological circuits, this theory has relevance in artificial intelligence by laying a foundation for frameworks whereby slow and computationally expensive deliberation can be stored as memories and eventually replaced by inexpensive recall.

Impaired olfactory performance and anxiety-like behavior in a rat model of multiple sclerosis are associated with enhanced adenosine signaling in the olfactory bulb via A1R, A2BR, and A3R

The present study shows that animals with experimental autoimmune encephalomyelitis (EAE) exhibit olfactory dysfunction and impaired general cognitive abilities, as well as anxiety-like behavior. Olfactory dysfunction occurs on average at 2 dpi, well before the onset of the first motor signs of EAE (8–10 dpi). After the initial olfactory dysfunction, the EAE animals show a fluctuation in olfactory performance that resembles the relapsing–remitting course of human MS. The study also shows severe neuroinflammation in the olfactory bulb (OB), with numerous infiltrated CD4+ T cells and peripheral macrophages in the superficial OB layers, marked microgliosis, and massive induction of TNF-α, IL-1β, and IL-6. Reduced tyrosine hydroxylase activity in the glomerular layer, pronounced granule cell atrophy, and reduced numbers of type B neuroblasts in the rostral migratory stream also indicate altered plasticity of the neuronal network in the OB. Considering the exceptionally high purinome expression in the OB, the possible involvement of purinergic signaling was also investigated. The study shows that macrophages infiltrating the OB overexpress A3R, while highly reactive microglia overexpress the adenosine-producing enzyme eN/CD73 as well as A2BR, A3R, and P2X4R. Given the simultaneous induction of complement component C3, the results suggest that the microglial cells develop a functional phenotype of phagocytizing microglia. The study also demonstrates transcriptional and translational upregulation of A1R in mitral and tufted cells, which likely influence resting network activity in OB and likely contribute to olfactory dysfunction in EAE. Overall, our study shows that olfactory dysfunction and altered social and cognitive behavior in EAE are associated with increased adenosine signaling via A1R, A2BR, and A3R.

Real-Time Analysis of Neuronal Cell Cultures for CNS Drug Discovery

The ability to screen for agents that can promote the development and/or maintenance of neuronal networks creates opportunities for the discovery of novel agents for the treatment of central nervous system (CNS) disorders. Over the past 10 years, advances in robotics, artificial intelligence, and machine learning have paved the way for the improved implementation of live-cell imaging systems for drug discovery. These instruments have revolutionized our ability to quickly and accurately acquire large standardized datasets when studying complex cellular phenomena in real-time. This is particularly useful in the field of neuroscience because real-time analysis can allow efficient monitoring of the development, maturation, and conservation of neuronal networks by measuring neurite length. Unfortunately, due to the relative infancy of this type of analysis, standard practices for data acquisition and processing are lacking, and there is no standardized format for reporting the vast quantities of data generated by live-cell imaging systems. This paper reviews the current state of live-cell imaging instruments, with a focus on the most commonly used equipment (IncuCyte systems). We provide an in-depth analysis of the experimental conditions reported in publications utilizing these systems, particularly with regard to studying neurite outgrowth. This analysis sheds light on trends and patterns that will enhance the use of live-cell imaging instruments in CNS drug discovery.

Host circuit engagement of human cortical organoids transplanted in rodents.

Human neural organoids represent promising models for studying neural function; however, organoids grown in vitro lack certain microenvironments and sensory inputs that are thought to be essential for maturation. The transplantation of patient-derived neural organoids into animal hosts helps overcome some of these limitations and offers an approach for neural organoid maturation and circuit integration. Here, we describe a method for transplanting human stem cell-derived cortical organoids (hCOs) into the somatosensory cortex of newborn rats. The differentiation of human induced pluripotent stem cells into hCOs occurs over 30-60 days, and the transplantation procedure itself requires ~0.5-1 hours per animal. The use of neonatal hosts provides a developmentally appropriate stage for circuit integration and allows the generation and experimental manipulation of a unit of human neural tissue within the cortex of a living animal host. After transplantation, animals can be maintained for hundreds of days, and transplanted hCO growth can be monitored by using brain magnetic resonance imaging. We describe the assessment of human neural circuit function in vivo by monitoring genetically encoded calcium responses and extracellular activity. To demonstrate human neuron-host functional integration, we also describe a procedure for engaging host neural circuits and for modulating animal behavior by using an optogenetic behavioral training paradigm. The transplanted human neurons can then undergo ex vivo characterization across modalities including dendritic morphology reconstruction, single-nucleus transcriptomics, optogenetic manipulation and electrophysiology. This approach may enable the discovery of cellular phenotypes from patient-derived cells and uncover mechanisms that contribute to human brain evolution from previously inaccessible developmental stages.

Physiological Biomarkers of Upper Motor Neuron Dysfunction in ALS

Upper motor neuron (UMN) dysfunction is an important feature of amyotrophic lateral sclerosis (ALS) for the diagnosis and understanding of pathogenesis. The identification of UMN signs forms the basis of ALS diagnosis, although may be difficult to discern, especially in the setting of severe muscle weakness. Transcranial magnetic stimulation (TMS) techniques have yielded objective physiological biomarkers of UMN dysfunction in ALS, enabling the interrogation of cortical and subcortical neuronal networks with diagnostic, pathophysiological, and prognostic implications. Transcranial magnetic stimulation techniques have provided pertinent pathogenic insights and yielded novel diagnostic and prognostic biomarkers. Cortical hyperexcitability, as heralded by a reduction in short interval intracortical inhibition (SICI) and an increase in short interval intracortical facilitation (SICF), has been associated with lower motor neuron degeneration, patterns of disease evolution, as well as the development of specific ALS clinical features including the split hand phenomenon. Reduction in SICI has also emerged as a potential diagnostic aid in ALS. More recently, physiological distinct inhibitory and facilitatory cortical interneuronal circuits have been identified, which have been shown to contribute to ALS pathogenesis. The triple stimulation technique (TST) was shown to enhance the diagnostic utility of conventional TMS measures in detecting UMN dysfunction. Resting-state EEG is a novel neurophysiological technique developed for directly interrogating cortical neuronal networks in ALS, that have yielded potentially useful physiological biomarkers of UMN dysfunction. The present review discusses physiological biomarkers of UMN dysfunction in ALS, encompassing conventional and novel TMS techniques developed to interrogate the functional integrity of the corticomotoneuronal system, focusing on pathogenic, diagnostic, and prognostic utility.

Investigating the Effects of Transcranial Alternating Current Stimulation on Cortical Oscillations and Network Dynamics

Transcranial electrical brain stimulation techniques like transcranial direct current (tDCS) and transcranial alternating current (tACS) have emerged as potential tools for treating neurological diseases by modulating cortical excitability. These techniques deliver small electric currents to the brain non-invasively through electrodes on the scalp. tDCS uses constant direct current which weakly alters the membrane voltage of cortical neurons, while tACS utilizes alternating current to target and enhance cortical oscillations, though the underlying mechanisms are not fully understood more specifically. To elucidate how tACS perturbs endogenous network dynamics, we simulated spiking neuron network models. We identified distinct roles of the depolarizing and hyperpolarizing phases in driving network activity towards and away from the strong nonlinearity provided by pyramidal neurons. Exploring resonance effects, we found matching tACS frequency to the network’s endogenous resonance frequency creates greater entrainment. Based on this, we developed an algorithm to determine the network’s endogenous frequency, phase, and amplitude, then deliver optimized tACS to entrain network oscillations. Together, these computational results provide mechanistic insight into the effects of tACS on network dynamics and could inform future closed-loop tACS systems that dynamically tune stimulation parameters to ongoing brain activity.

Deficit of satellite oligodendrocytes of neurons in the rostral part of the head of the caudate nucleus in schizophrenia.

Increasing evidence implicates compromised myelin integrity and oligodendrocyte abnormalities in the dysfunction of neuronal networks in schizophrenia. We previously reported a deficiency of myelinating oligodendrocytes (OL), oligodendrocyte progenitors (OP) and satellite oligodendrocytes of neurons (Sat-OL) in the prefrontal cortex and the inferior parietal cortex - cortical hubs of the frontoparietal cognitive network and default mode network (DMN) altered in schizophrenia. Deficiency of OL and OP was also detected in the head of the caudate nucleus (HCN), which accumulates cortical projections from the associative cortex and is the central node of these networks. However, the number of Sat-Ol per neuron in schizophrenia has not been studied in the HCN. In the current study we estimated the number of Sat-Ol per neuron in the rostral part of the HCN in schizophrenia (n = 18) compared to healthy controls (n = 18) in the same section collection that was previously used to study the number Ol and OP. We found a significant decrease of the number of Sat-Ol per neuron (- 50%, p < 0.001) in schizophrenia as compared to normal controls. Considering that the rostral part of the HCN is an individual network-specific projection zone of the DMN, the deficit of Sat-Ol found in schizophrenia may be related to the dysfunctional DMN-HCN connections, which has been repeatedly described in schizophrenia. The dramatic decrease of the number of Sat-Ol per neuron may be partially related to a pronounced excess of dopamine concentration in the rostral part of the HCN in schizophrenia.

Human tripartite cortical network model for temporal assessment of alpha-synuclein aggregation and propagation in Parkinson’s Disease

Previous studies have shown that aggregated alpha-synuclein (α-s) protein, a key pathological marker of Parkinson’s disease (PD), can propagate between cells, thus participating in disease progression. This prion-like propagation has been widely studied using in vivo and in vitro models, including rodent and human cell cultures. In this study, our focus was on temporal assessment of functional changes during α-s aggregation and propagation in human induced pluripotent stem cell (hiPSC)-derived neuronal cultures and in engineered networks. Here, we report an engineered circular tripartite human neuronal network model in a microfluidic chip integrated with microelectrode arrays (MEAs) as a platform to study functional markers during α-s aggregation and propagation. We observed progressive aggregation of α-s in conventional neuronal cultures and in the exposed (proximal) compartments of circular tripartite networks following exposure to preformed α-s fibrils (PFF). Furthermore, aggregated forms propagated to distal compartments of the circular tripartite networks through axonal transport. We observed impacts of α-s aggregation on both the structure and function of neuronal cells, such as in presynaptic proteins, mitochondrial motility, calcium oscillations and neuronal activity. The model enabled an assessment of the early, middle, and late phases of α-s aggregation and its propagation during a 13-day follow-up period. While our temporal analysis suggested a complex interplay of structural and functional changes during the in vitro propagation of α-s aggregates, further investigation is required to elucidate the underlying mechanisms. Taken together, this study demonstrates the technical potential of our introduced model for conducting in-depth analyses for revealing such mechanisms.

Characterization of idiopathic chronic diarrhea and associated intestinal inflammation and preliminary observations of effects of vagal nerve stimulation in a non-human primate.

Diarrhea is commonly associated with irritable bowel syndrome, inflammatory bowel disease, microscopic colitis, and other gastrointestinal dysfunctions. Spontaneously occurring idiopathic chronic diarrhea is frequent in rhesus macaques, but has not been used as a model for the investigation of diarrhea or its treatment. We characterized this condition and present preliminary data demonstrating that left vagal nerve stimulation provides relief. Stool consistency scores were followed for up to 12 years. Inflammation was assessed by plasma C-reactive protein, [18F]fluorodeoxyglucose (FDG) uptake, measured by positron emission tomography (PET), multiplex T cell localization, endoscopy and histology. The vagus was stimulated for 9 weeks in conscious macaques, using fully implanted electrodes, under wireless control. Macaques exhibited recurrent periods of diarrhea for up to 12 years, and signs of inflammation: elevated plasma C-reactive protein, increased bowel FDG uptake and increased mucosal T helper1 T-cells. The colon and distal ileum were endoscopically normal, and histology revealed mild colonic inflammation. Application of vagal nerve stimulation to conscious macaques (10 Hz, 30 s every 3 h; 24 h a day for 9 weeks) significantly reduced severity of diarrhea and also reduced inflammation, as measured by FDG uptake and C-reactive protein. These macaques exhibit spontaneously occurring diarrhea with intestinal inflammation that can be reduced by VNS. The data demonstrate the utility of this naturally occurring primate model to study the physiology and treatments for chronic diarrhea and the neural control circuits influencing diarrhea and inflammation that are not accessible in human subjects.

Developmental neurotoxicity of PFOA exposure on hiPSC-derived cortical neurons

PFOA is a legacy Per- and Polyfluorinated Substances (PFAS), a group of chemicals widely used in various industrial applications and consumer products. Although there has been a voluntary phase out of PFOA since 2005, it is still widely detected in various water supplies. A growing body of evidence suggests an association between PFOA exposure, particularly during developmental stages, with increased risks of neurodegenerative diseases (NDs). The neurotoxic mechanism of developmental PFOA exposure, however, remains poorly understood. Utilizing human induced-pluripotent stem cell (hiPSC)-derived cortical neurons, we investigated the effect of PFOA exposure prior to differentiation and assessed changes in neuronal characteristics, transcriptome, and neurodegeneration markers mimicking a Developmental Origin of Health and Disease (DoHAD) paradigm. Exposure to PFOA before neuron differentiation resulted in persistent alterations in nuclear morphology, neuronal network, and calcium activity. RNA sequencing analysis further revealed transcriptomic changes aligning with Alzheimer’s Disease (AD) after PFOA exposure. These observations were further corroborated by alterations in tau phosphorylation markers, the presence of fibrillar tau, an increase in liquid droplets, and a decrease in RNA translational efficiency characterized using a battery of biochemical assays. Taken together, our results revealed persistent deficits of key neuronal characteristics induced by pre-differentiation PFOA exposure, suggesting impairments in several AD-related pathways that can together contribute to the elevation of AD risk after pre-differentiation PFOA exposure.

Sensory-motor circuit is a therapeutic target for dystonia musculorum mice, a model of hereditary sensory and autonomic neuropathy 6.

Mutations in Dystonin (DST), which encodes cytoskeletal linker proteins, cause hereditary sensory and autonomic neuropathy 6 (HSAN-VI) in humans and the dystonia musculorum (dt) phenotype in mice; however, the neuronal circuit underlying the HSAN-VI and dt phenotype is unresolved. dt mice exhibit dystonic movements accompanied by the simultaneous contraction of agonist and antagonist muscles and postnatal lethality. Here, we identified the sensory-motor circuit as a major causative neural circuit using a gene trap system that enables neural circuit-selective inactivation and restoration of Dst by Cre-mediated recombination. Sensory neuron-selective Dst deletion led to motor impairment, degeneration of proprioceptive sensory neurons, and disruption of the sensory-motor circuit. Restoration of Dst expression in sensory neurons using Cre driver mice or a single postnatal injection of Cre-expressing adeno-associated virus ameliorated sensory degeneration and improved abnormal movements. These findings demonstrate that the sensory-motor circuit is involved in the movement disorders in dt mice and that the sensory circuit is a therapeutic target for HSAN-VI.

The interactions between energy homeostasis and neurovascular plasticity.

Food intake and energy expenditure are sensed and processed by multiple brain centres to uphold energy homeostasis. Evidence from the past decade points to the brain vasculature as a new critical player in regulating energy balance that functions in close association with the local neuronal networks. Nutritional imbalances alter many properties of the neurovascular system (such as neurovascular coupling and blood-brain barrier permeability), thus suggesting a bidirectional link between the nutritional milieu and neurovascular health. Increasing numbers of people are consuming a Western diet (comprising ultra-processed food with high-fat and high-sugar content) and have a sedentary lifestyle, with these factors contributing to the current obesity epidemic. Emerging pharmacological interventions (for example, glucagon-like peptide 1 receptor agonists) successfully trigger weight loss. However, whether these approaches can reverse the detrimental effects of long-term exposure to the Western diet (such as neurovascular uncoupling, neuroinflammation and blood-brain barrier disruption) and maintain stable body weight in the long-term needs to be clarified in addition to possible adverse effects. Lifestyle interventions revert the nutritional trigger for obesity and positively affect our overall health, including the cardiovascular system. This Perspective examines how lifestyle interventions affect the neurovascular system and neuronal networks.