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Yu, K.

Publications and source records attributed to Yu, K..

At least 55 records · Page 3Linked to original sources

Stress-activated neuronal ensemble in the supramammillary nucleus stores anxiety but not memory

Anxiety is a prevalent negative emotional state induced by stress; however, the neural mechanism underlying anxiety is still largely unknown. We used acute and chronic stress to induce anxiety and test anxiety-like behavior; immunostaining, multichannel extracellular electrophysiological recording and Ca2+ imaging to evaluate neuronal activity; and virus-based neuronal tracing to label circuits and manipulate circuitry activity. Here, we identified a hypothalamic region, the supramammillary nucleus (SuM), plays important role in anxiety-like behavior. We then characterized a small ensemble of stress-activated neurons (SANs) that are recruited by stress. These SANs respond specifically to stress, and their activation robustly increases anxiety-like behavior in male mice. We also found that ventral subiculum (vSub)-SuM projection but not dorsal subiculum (dSub)-SuM projections encode anxiety-like behavior and that inhibition of these vSub-SuM projections has an antianxiety effect. These results indicate that the reactivation of stress-activated supramammillary cells and relevant neural circuits are important neural processes underlying anxiety-like behavior.

neuroscience↗

Regenerative failure of sympathetic axons contributes to deficits in functional recovery after nerve injury

Renewed scientific interest in sympathetic modulation of muscle and neuromuscular junctions has spurred a flurry of new discoveries with major implications for motor diseases. However, the role sympathetic axons play in the persistent dysfunction that occurs after nerve injuries remains to be explored. Peripheral nerve injuries are common and lead to motor, sensory, and autonomic deficits that result in lifelong disabilities. Given the importance of sympathetic signaling in muscle metabolic health and maintaining bodily homeostasis, it is imperative to understand the regenerative capacity of sympathetic axons after injury. Therefore, we tested sympathetic axon regeneration and functional reinnervation of skin and muscle, both acute and long-term, using a battery of anatomical, pharmacological, chemogenetic, cell culture, analytical chemistry, and electrophysiological techniques. We employed several established growth-enhancing interventions, including electrical stimulation and conditioning lesion, as well as an innovative tool called bioluminescent optogenetics. Our results indicate that sympathetic regeneration is not enhanced by any of these treatments and may even be detrimental to sympathetic regeneration. Despite the complete return of motor reinnervation after sciatic nerve injury, gastrocnemius muscle atrophy and deficits in muscle cellular energy charge, as measured by relative ATP, ADP, and AMP concentrations, persisted long after injury, even with electrical stimulation. We suggest that these long-term deficits in muscle energy charge and atrophy are related to the deficiency in sympathetic axon regeneration. New studies are needed to better understand the mechanisms underlying sympathetic regeneration to develop therapeutics that can enhance the regeneration of all axon types.

neuroscience↗

Neuronal activation in the axolotl brain promotes spinal cord regeneration

The axolotl retains a remarkable capacity for regenerative repair and is one of the few vertebrate species capable of regenerating its brain and spinal cord after injury. To date, studies investigating axolotl spinal cord regeneration have placed particular emphasis on understanding how cells immediately adjacent to the injury site respond to damage to promote regenerative repair. How neurons outside of this immediate injury site respond to an injury remains unknown. Here, we identify a population of dpErk+/etv1+ glutamatergic neurons in the axolotl telencephalon that are activated in response to tail amputation. Importantly, the activation of these neurons facilitates successful tail regeneration by promoting axon extension into the newly regenerated tissue. We demonstrate that these dpErk+ neurons extend axons into the hypothalamus, which has a well-established role in hormone production. Furthermore, these neurons upregulate the neuropeptide neurotensin in response to injury, which in turn stimulates the production of multiple hormones in the hypothalamus to promote regenerative repair. Together, these findings identify a unique population of neurons in the axolotl brain whose activation is necessary for successful spinal cord regeneration, and sheds light on how neurons outside of the immediate injury site respond to a spinal cord injury.

developmental biology↗

Spotiphy enables single-cell spatial whole transcriptomics across the entire section

Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole tissue sections1, but the approach remains dogged by the challenge of achieving single-cell resolution without sacrificing whole genome coverage2,3. Here we present Spotiphy (Spot imager with pseudo single-cell resolution histology), a novel computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. In evaluations with Alzheimers disease (AD) and normal mouse brains, Spotiphy delivers the most precise cellular compositions. For the first time, Spotiphy reveals novel astrocyte regional specification in mouse brains. It distinguishes sub-populations of DAM (Disease-Associated Microglia) located in different AD mouse brain regions. Spotiphy also identifies multiple spatial domains as well as changes in the patterns of tumor-tumor microenvironment interactions using human breast ST data. Spotiphy enables visualization of cell localization and gene expression in tissue sections, offering key insights into the function of complex biological systems.

systems biology↗

Selective Enhancement of the Interneuron Network and Gamma-Band Power via GluN2C/GluN2D NMDA Receptor Potentiation

N-methyl-D-aspartate receptors (NMDARs) comprise a family of ligand-gated ionotropic glutamate receptors that mediate a slow, calcium-permeable component to excitatory neurotransmission. The GluN2D subunit is enriched in GABAergic inhibitory interneurons in cortical tissue. Diminished levels of GABAergic inhibition contribute to multiple neuropsychiatric conditions, suggesting that enhancing inhibition may have therapeutic utility, thus making GluN2D modulation an attractive drug target. Here, we describe the actions of a GluN2C/GluN2D-selective positive allosteric modulator (PAM), (+)-EU1180-453, which has improved drug-like properties such as increased aqueous solubility compared to the first-in-class GluN2C/GluN2D-selective prototypical PAM (+)-CIQ. (+)-EU1180-453 doubles the NMDAR response at lower concentrations (< 10 {micro}M) compared to (+)-CIQ, and produces a greater degree of maximal potentiation at 30 {micro}M. Using in vitro electrophysiological recordings, we show that (+)-EU1180-453 potentiates triheteromeric NMDARs containing at least one GluN2C or GluN2D subunit, and is active at both exon5-lacking and exon5-containing GluN1 splice variants. (+)-EU1180-453 increases glutamate efficacy for GluN2C/GluN2D-containing NMDARs by both prolonging the deactivation time and potentiating the peak response amplitude. We show that (+)-EU1180-453 selectively increases synaptic NMDAR-mediated charge transfer onto P11-15 CA1 stratum radiatum hippocampal interneurons, but is without effect on CA1 pyramidal cells. This increased charge transfer enhances inhibitory output from GABAergic interneurons onto CA1 pyramidal cells in a GluN2D-dependent manner. (+)-EU1180-453 also shifts excitatory-to-inhibitory coupling towards increased inhibition and produces enhanced gamma band power from carbachol-induced field potential oscillations in hippocampal slices. Thus, (+)-EU1180-453 can enhance overall circuit inhibition, which could prove therapeutically useful for the treatment of anxiety, depression, schizophrenia, and other neuropsychiatric disorders. Significance StatementInterneuron dysfunction and diminished GABAergic inhibition in neocortical and hippocampal circuits remains a prominent molecular hypothesis for neuropsychiatric diseases including anxiety, depression, and schizophrenia. Pharmacological agents that boost GABA receptor function have shown utility in various forms of depression and treating symptoms of schizophrenia. Cortical GABAergic interneurons, unlike their excitatory pyramidal cell counterparts, are enriched for the GluN2D subunit of the NMDA receptor. Thus, GluN2D subunit-selective modulation could be a useful therapeutic tool to enhance local inhibition, improving the prognosis for neuropsychiatric diseases for which interneuron dysfunction is prominent and causal to circuit aberration.

neuroscience↗

Generalized cell phenotyping for spatial proteomics with language-informed vision models

We present DeepCell Types, a novel approach to cell phenotyping for spatial proteomics that addresses the challenge of generalization across diverse datasets with varying marker panels collected across different platforms. Our approach utilizes a transformer with channel-wise attention to create a language-informed vision model; this models semantic understanding of the underlying marker panel enables it to learn from and adapt to heterogeneous datasets. Leveraging a curated, diverse dataset named Expanded TissueNet with cell type labels spanning the literature and the NIH Human BioMolecular Atlas Program (HuBMAP) consortium, our model demonstrates robust performance across various cell types, tissues, and imaging modalities. Comprehensive benchmarking shows that our method outperforms existing approaches on cell-type prediction and, from the same model, predicts marker positivity competitively with a dedicated specialist; it further matches manual expert gating and adapts to new data with modest fine-tuning, well past what baselines reach when trained from scratch. This work equips the spatial proteomics community with a single, continuously improvable phenotyping model that generalizes to new marker panels and can be fine-tuned efficiently when needed. We release both DeepCell Types and Expanded TissueNet as open-source resources.

bioinformatics↗

A PI3Kδ-Foxo1-FasL signaling amplification loop rewires CD4+ T helper cell signaling, differentiation and epigenetic remodeling

While inputs regulating CD4+ T helper cell (Th) differentiation are well-defined, the integration of downstream signaling with transcriptional and epigenetic programs that define Th-lineage identity remain unresolved. PI3K signaling is a critical regulator of T cell function; activating mutations affecting PI3K{delta} result in an immunodeficiency with multiple T cell defects. Using mice expressing activated-PI3K{delta}, we found aberrant expression of proinflammatory Th1-signature genes under Th2-inducing conditions, both in vivo and in vitro. This dysregulation was driven by a robust PI3K{delta}-IL-2-Foxo1 signaling loop, fueling Foxo1-inactivation, loss of Th2-lineage restriction, altered chromatin accessibility and global impairment of CTCF-DNA interactions. Surprisingly, ablation of Fasl, a Foxo1-repressed gene, restored normal Th2 differentiation, TCR signaling and CTCF expression. BioID revealed Fas interactions with TCR- signaling components, which were supported by Fas-mediated potentiation of TCR signaling. Our results highlight Fas-FasL signaling as a critical intermediate in phenotypes driven by activated-PI3K{delta}, thereby linking two key pathways of immune dysregulation.

immunology↗

Human-mouse proteomics reveals the shared pathways in Alzheimer's disease and delayed protein turnover in the amyloidome

Murine models of Alzheimers disease (AD) are crucial for elucidating disease mechanisms but have limitations in fully representing AD molecular complexities. We comprehensively profiled age-dependent brain proteome and phosphoproteome (n > 10,000 for both) across multiple mouse models of amyloidosis. We identified shared pathways by integrating with human metadata, and prioritized novel components by multi-omics analysis. Collectively, two commonly used models (5xFAD and APP-KI) replicate 30% of the human protein alterations; additional genetic incorporation of tau and splicing pathologies increases this similarity to 42%. We dissected the proteome-transcriptome inconsistency in AD and 5xFAD mouse brains, revealing that inconsistent proteins are enriched within amyloid plaque microenvironment (amyloidome). Determining the 5xFAD proteome turnover demonstrates that amyloid formation delays the degradation of amyloidome components, including A{beta}-binding proteins and autophagy/lysosomal proteins. Our proteomic strategy defines shared AD pathways, identify potential new targets, and underscores that protein turnover contributes to proteome-transcriptome discrepancies during AD progression.

biochemistry↗

Generalizability of Normative Models of Brain Morphometry Across Distinct Ethnoracial Groups

Normative modeling of brain morphometric data can inform about the clinical significance of deviations from typical patterns in brain structure. Their usefulness, however, is dependent on their applicability to diverse ethnoracial groups. With this in mind, we developed age- and sex-specific normative models for cortical thickness, surface area, and subcortical volumes using brain scans from 37,407 healthy individuals from a diverse international sample. Here we demonstrate the validity of these models in diverse and distinct populations. Specifically, we tested these pre-trained models on independent samples of healthy individuals that either self-identified as Black, South Asian, East Asian Chinese, East Asian Japanese, or we categorized as African, Admixed American, East Asian, and European based on their genetic ancestry. Regardless of ethnoracial definition, the performance of the pretrained models in these samples was exceptionally high; the relative mean absolute error for each regional brain morphometry measure was less than 10% across all the distinct ethnoracial groups. These findings affirm the broad applicability of our models, ensuring that brain morphometry assessments using these models are accurate and reliable for individuals regardless of background. This broad applicability has significant implications for advancing personalized medicine and improving health outcomes in diverse populations.

bioinformatics↗

Mutant p53 regulates cancer cell invasion in complex three-dimensional environments through mevalonate pathway-dependent Rho/ROCK signaling.

Certain mutations can confer neomorphic gain of function (GOF) activities to the p53 protein that affect cancer progression. Yet the concept of mutant p53 GOF has been challenged. Here, using various strategies to alter the status of mutant versions of p53 in different cell lines, we demonstrate that mutant p53 stimulates cancer cell invasion in three-dimensional environments. Mechanistically, mutant p53 enhances RhoA/ROCK-dependent cell contractility and cell-mediated extracellular matrix (ECM) re-organization via increasing mevalonate pathway-dependent RhoA localization to the membrane. In line with this, RhoA-dependent pro-invasive activity is also mediated by IDI-1, a mevalonate pathway product. Further, the invasion-enhancing effect of mutant p53 is dictated by the biomechanical properties of the surrounding ECM, thereby adding a cell-independent layer of regulation to mutant p53 GOF activity that is mediated by dynamic reciprocal cell-ECM interactions. Together our findings link mutant p53 metabolic GOF activity with an invasive cellular phenotype in physiologically relevant and context-dependent settings. SignificanceThis study addresses the contribution of mutant p53 to the process of cancer cell dissemination in physiologically relevant three-dimensional environments - a key characteristic of metastatic disease. Several mutant p53 proteins display pro-oncogenic activity with respect to cancer cell invasion in 3D environments via mevalonate pathway-dependent Rho/ROCK signaling axis.

cancer biology↗

The FIP 1.0 Data Set: Highly Resolved Annotated Image Time Series of 4,000 Wheat Plots Grown in Six Years

BackgroundUnderstanding genotype-environment interactions of plants is crucial for crop improvement, yet limited by the scarcity of quality phenotyping data. This data note presents the Field Phenotyping Platform 1.0 data set, a comprehensive resource for winter wheat research that combines imaging, trait, environmental, and genetic data. FindingsWe provide time series data for more than 4,000 wheat plots, including aligned high-resolution image sequences totaling more than 153,000 aligned images across six years. Measurement data for eight key wheat traits is included, namely canopy cover values, plant heights, wheat head counts, senescence ratings, heading date, final plant height, grain yield, and protein content. Genetic marker information and environmental data complement the time series. Data quality is demonstrated through heritability analyses and genomic prediction models, achieving accuracies aligned with previous research. ConclusionsThis extensive data set offers opportunities for advancing crop modeling and phenotyping techniques, enabling researchers to develop novel approaches for understanding genotype-environment interactions, analyzing growth dynamics, and predicting crop performance. By making this resource publicly available, we aim to accelerate research in climate-adaptive agriculture and foster collaboration between plant science and machine learning communities.

plant biology↗

Weed Instance Segmentation from UAV ortho-mosaic Images based on Deep Learning

Weeds significantly impact agricultural production, and traditional weed control methods often harm soil health and the environment. This study aims to develop deep learning-based segmentation models in identifying weeds in potato fields captured by Unmanned Aerial Vehicle (UAV) orthophotos and to explore the effects of weeds on potato yield. UAVs were used to collect RGB data from potato fields, flying at an altitude of 10m, with Real-ESRGAN Super-Resolution (SR) enhancing image resolution. We applied the Segment Anything Model (SAM) to do semi-automatic annotation, followed by training the YOLOv8 and MASK-RCNN models for segmentation. Also we used ANOVA and linear regression to analyze the effects of weeds and nitrogen fertilizer on yield. Results showed that the detection accuracy mAP50 scores for YOLOv8 and Mask R-CNN were 0.902 and 0.920, respectively, with the Real-ESRGAN-enhanced model achieving 0.909. When multiple weed types were present, accuracy decreased to 0.86. The linear regression model, incorporating plant and weed coverage areas, explained 41.2% of yield variation (R2 = 0.412, p-value = 0.01). Both YOLOv8 and Mask R-CNN achieved high accuracy, with YOLOv8 converging faster. Real-ESRGAN reconstruction slightly improved accuracy. Different nitrogen fertilizer treatments had no significant effect on yield, while weed control treatments significantly impacted yield, showing the importance of precise weed mapping.. This study provides insights into weed segmentation and contributes to environmentally friendly precision weed control. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/607729v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@40492org.highwire.dtl.DTLVardef@1c847b8org.highwire.dtl.DTLVardef@1dcb53corg.highwire.dtl.DTLVardef@fe96e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

Transcranial focused ultrasound modulates visual thalamus in a nonhuman primate model

The thalamus plays a pivotal role as a neural hub, integrating and distributing visual information to cortical regions responsible for visual processing. Transcranial focused ultrasound (tFUS) has emerged as a promising non-invasive brain stimulation technology, enabling modulation of neural circuits with high spatial precision. This study investigates the tFUS neuromodulation at visual thalamus and characterizes the resultant effects on interconnected visual areas in a nonhuman primate model. Experiments were conducted on a rhesus macaque trained in a visual fixation task, combining tFUS stimulation with simultaneous scalp electroencephalography (EEG) and intracranial recordings from area V4, a region closely linked to the thalamus. Ultrasound was delivered through a 128-element random array ultrasound transducer operating at 700 kHz, with the focus steered onto the pulvinar of the thalamus based on neuroanatomical atlas and individual brain model. EEG source imaging revealed localized tFUS-induced activities in the thalamus, midbrain, and visual cortical regions. Critically, tFUS stimulation of the pulvinar can elicit robust neural responses in V4 without visual input, manifested as significant modulations in local field potentials, elevated alpha and gamma power, corroborating the functional thalamocortical connectivity. Furthermore, the tFUS neuromodulatory effects on visually-evoked V4 activities were region-specific within the thalamus and dependent on ultrasound pulse repetition frequency. This work provides direct electrophysiological evidence demonstrating the capability of tFUS in modulating the visual thalamus and its functional impact on interconnected cortical regions in a large mammalian model, paving the way for potential investigations for tFUS treating visual, sensory, and cognitive impairments.

neuroscience↗

Glioblastoma Neurovascular Progenitor Orchestrates Tumor Cell Type Diversity

Glioblastoma (GBM) exhibits developmental programs and marked cellular heterogeneity, yet how these features are organized into connected lineage hierarchies remains unclear. Here we identify a rare tumor-intrinsic population, termed the neurovascular progenitor (NVP), that occupies an intermediate position between the major GBM organizational axes. NVP cells co-express neural progenitor and perivascular transcriptional features, are consistently detected across independent patient cohorts, retain canonical GBM copy-number alterations, and localize in situ in both vessel-associated and parenchymal niches. Using direct-from-patient lineage tracing in a human organoid tumor transplantation system, we show that individual NVP cells clonally generate both neural-like and mesenchymal/vascular-like malignant progeny, providing a concrete lineage link between states that are commonly considered mutually exclusive. Despite comprising [~]1% of tumor cells, NVP-derived lineages account for a majority of observed tumor cell types and disproportionately contribute to cycling compartments. Orthogonally, ablation of NVP-associated programs in an in vivo GBM model remodels tumor composition, elicits compensatory progenitor states, and significantly prolongs survival. Together, these findings position NVP as a fate-restricted yet highly influential lineage intermediate that serves as a functional bridge and organizational nexus within GBM hierarchies, linking population-level lineage architecture to the behavior of a specific progenitor cell type.

cancer biology↗

NanoLAS 2.0: A Comprehensive Update on a Nanobody-Focused Platform with Advanced Visualization and Docking Simulation Features

SummaryNanobodies, a unique subclass of antibodies initially discovered in camelids, characterized by the absence of light chains and consisting solely of a heavy chain variable region. This distinctive structure endows nanobodies with inherent advantages in the realms of disease treatment and biopharmaceutical applications. Presently, research and applications concerning nanobodies are experiencing rapid growth. However, existing databases suffer from non-uniform data sources and a lack of data standardization. To address these issues, we developed the NanoLAS database in 2023. Despite the progress in data integration made by NanoLAS, there was room for improvement in search functionality, three-dimensional structural display, and other areas. Building upon this foundation, we introduce the comprehensively updated NanoLAS 2.0. This version offers updates to data sources, precise 3D structural presentation, and molecular docking simulation capabilities, refines the multi-condition search mechanism, and incorporates a brand-new sequence viewer as well as epitope prediction functionality. Additionally, to cater to the needs of researchers, we have designed a user-friendly and intuitive interface. In summary, we anticipate that NanoLAS 2.0 will serve as a powerful and easy-to-use research tool, facilitating researchers in their exploration of nanobodies and propelling advancements in the field of nanobody research and application. AvailabilityNanoLAS 2.0 is available at https://www.nanolas2.online Contactbingdinghuang@sztu.edu.cn and wangxin@sztu.edu.cn

bioinformatics↗

Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcome

Intra-tumor heterogeneity is characterized by a diverse population of tumor clones and subclones which are important drivers of tumor evolution and therapeutic response. However, accurate subclonal reconstruction at scale remains challenging. We developed a machine learning tool, CliPP, and surveyed 9,972 tumors from 32 cancer types. We found that high subclonal mutation load (sML), the fraction of subclonal single nucleotide variants (SNVs) to all SNVs in the coding region, was prognostic of survival (progression free survival or overall survival) in 18 cancer types. In 14 cancers with low to moderate tumor mutation burden (TMB), high sML was associated with better prognosis. In immunotherapy trials for 42 metastatic prostate cancer (mCRPC), high sML was predictive of favorable response to ipilimumab and associated with increased CD8+ T-cell infiltration and decreased macrophage population. A validation using 613 whole-genomes of esophageal adenocarcinoma confirms the favorable effect of high sML and the observed tumor-associated macrophage. Our study identifies sML as a key feature of cancer, suggesting a biphasic relationship between evolutionary dynamics and differential immune environments. Finally, sML may serve as an orthogonal approach to identify likely responders of immune checkpoint blockade in low to moderate TMB tumors.

genomics↗

Alzheimer Disease Knowledge Graph Enhances Knowledge Discovery and Disease Prediction

BackgroundAlzheimers disease (AD), a progressive neurodegenerative disorder, continues to increase in prevalence without any effective treatments to date. In this context, knowledge graphs (KGs) have emerged as a pivotal tool in biomedical research, offering new perspectives on drug repurposing and biomarker discovery by analyzing intricate network structures. Our study seeks to build an AD-specific knowledge graph, highlighting interactions among AD, genes, variants, chemicals, drugs, and other diseases. The goal is to shed light on existing treatments, potential targets, and diagnostic methods for AD, thereby aiding in drug repurposing and the identification of biomarkers. ResultsWe annotated 800 PubMed abstracts and leveraged GPT-4 for text augmentation to enrich our training data for named entity recognition (NER) and relation classification. A comprehensive data mining model, integrating NER and relationship classification, was trained on the annotated corpus. This model was subsequently applied to extract relation triplets from unannotated abstracts. To enhance entity linking, we utilized a suite of reference biomedical databases and refine the linking accuracy through abbreviation resolution. As a result, we successfully identified 3,199,276 entity mentions and 633,733 triplets, elucidating connections between 5,000 unique entities. These connections were pivotal in constructing a comprehensive Alzheimers Disease Knowledge Graph (ADKG). We also integrated the ADKG constructed after entity linking with other biomedical databases. The ADKG served as a training ground for Knowledge Graph Embedding models with the high-ranking predicted triplets supported by evidence, underscoring the utility of ADKG in generating testable scientific hypotheses. Further application of ADKG in predictive modeling using the UK Biobank data revealed models based on ADKG outperforming others, as evidenced by higher values in the areas under the receiver operating characteristic (ROC) curves. ConclusionThe ADKG is a valuable resource for generating hypotheses and enhancing predictive models, highlighting its potential to advance ADs disease research and treatment strategies.

bioinformatics↗

Transcranial focused ultrasound activates feedforward and feedback cortico-thalamo-cortical pathways by selectively activating excitatory neurons

Transcranial focused ultrasound stimulation (tFUS) has been proven capable of altering focal neuronal activities and neural circuits non-invasively in both animals and humans. The abilities of tFUS for cell-type selection within the targeted area like somatosensory cortex have been shown to be parameter related. However, how neuronal subpopulations across neural pathways are affected, for example how tFUS affected neuronal connections between brain areas remains unclear. In this study, multi-site intracranial recordings were used to quantify the neuronal responses to tFUS stimulation at somatosensory cortex (S1), motor cortex (M1) and posterior medial thalamic nucleus (POm) of cortico-thalamo-cortical (CTC) pathway. We found that when targeting at S1 or POm, only regular spiking units (RSUs, putative excitatory neurons) responded to specific tFUS parameters (duty cycle: 6%-60% and pulse repetition frequency: 1500 and 3000 Hz ) during sonication. RSUs from the directly connected area (POm or S1) showed a synchronized response, which changed the directional correlation between RSUs from POm and S1. The tFUS induced excitation of RSUs activated the feedforward and feedback loops between cortex and thalamus, eliciting delayed neuronal responses of RSUs and delayed activities of fast spiking units (FSUs) by affecting local network. Our findings indicated that tFUS can modulate the CTC pathway through both feedforward and feedback loops, which could influence larger cortical areas including motor cortex.

neuroscience↗