Journal of Neuroscience Methods最新文献

{"title":"An orthotopic vestibular schwannoma mouse model to study tumor-host interactions and mechanism of sensorineural hearing loss","authors":"Bailey H. Duhon ,&nbsp;Melanie Fisher ,&nbsp;Han TN. Nguyen ,&nbsp;Matthew T. Rocco ,&nbsp;Eric C. Bielefeld ,&nbsp;Yin Ren","doi":"10.1016/j.jneumeth.2026.110709","DOIUrl":"10.1016/j.jneumeth.2026.110709","url":null,"abstract":"<div><h3>Background</h3><div>Sensorineural hearing loss (SNHL) is the most common symptom of vestibular schwannoma (VS), arising from multifactorial tumor-host interactions including mechanical cochleovestibular nerve compression and ototoxic tumor secretion, yet underlying mechanisms remain incompletely defined. This study establishes an anatomically precise mouse model and investigates the role of blood-labyrinth barrier (BLB) disruption in VS-associated SNHL.</div></div><div><h3>New method</h3><div>Adapting neuro-otologic surgical techniques, a petrosectomy with lateral semicircular canal fenestration was used to implant mouse <em>Nf2</em>^<em>-/-</em> Schwann cells and patient-derived primary VS cells into the cochleovestibular nerve within the internal auditory canal (IAC). Tumor growth was assessed by MRI and bioluminescence, while auditory and vestibular functions were evaluated by auditory brainstem response and behavioral assays. Immunofluorescence of inflammatory, matrix-remodeling, and tight junction markers were performed in the tumor, brainstem and cochlea.</div></div><div><h3>Results</h3><div>VS allografts progressed from the IAC to the cerebellopontine angle, exhibiting mixed Antoni A/B architecture. Auditory and vestibular function was preserved postoperatively and progressively declined with tumor growth. Macrophage/microglia activation was observed in the tumor, brainstem and cochleovestibular nerve. Matrix metalloprotease-9 (MMP-9) and high mobility group box 1 (HMGB1) overexpression in the tumor and ipsilateral cochlea was associated with evidence of BLB disruption, characterized by tight junction downregulation and significant vascular disorganization in the stria vascularis.</div></div><div><h3>Comparison with existing methods</h3><div>Existing animal models either require months to develop or fail to recapitulate native VS progression and hearing decline.</div></div><div><h3>Conclusion</h3><div>This novel mouse model recapitulates native VS progression within the IAC and offers a powerful platform to investigate mechanisms underlying VS-associated SNHL.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"430 ","pages":"Article 110709"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential confounds of identification methods in Parkinson's disease models: neuroinflammatory aggravation by toe-clipping versus sensorimotor disruption by ear-tagging.","authors":"Xin Jiang, Yaoxin Wei, Rui Wang","doi":"10.1016/j.jneumeth.2026.110790","DOIUrl":"https://doi.org/10.1016/j.jneumeth.2026.110790","url":null,"abstract":"<p><strong>Background: </strong>Toe-clipping and ear-tagging are standard rodent identification methods. Their potential to confound outcomes in Parkinson's disease (PD) research remains poorly characterized.</p><p><strong>New method: </strong>We evaluated the methodological impacts of these procedures in a C57BL/6 male mouse PD model using behavioral assays and neuropathological analyses.</p><p><strong>Results: </strong>Toe-clipping triggered sustained neuroinflammation, with 5-toe clipped mice showing elevated Interleukin (IL)-1β compared to ear-tagged (mean difference = 0.3647, 95% CI: 0.1203-0.6090, P = 0.0025) and 2-toe clipped mice (mean difference = 0.2333, 95% CI: 0.00036-0.4663, P = 0.0496) in non-PD conditions. In PD conditions, 5-toe clipped mice exhibited elevated IL-1β compared to non-PD 5-toe clipped mice (mean difference = 0.3967, 95% CI: 0.1123-0.6810, P = 0.0016). Toe-clipping exacerbated motor deficits, with significant grip strength impairments in 5-toe versus control mice (mean difference = 1.513, 95% CI: 0.01114-3.016, P = 0.0479) and in PD-5-toe versus PD-control mice (mean difference = 2.542, 95% CI: 1.132-3.951, P = 0.0003). In contrast, ear-tagging selectively impaired pole test performance, with ear-tagged mice showing prolonged head-turning times versus controls (mean difference = 1.232, 95% CI: 0.3723-2.091, P = 0.0035) and 2-toe mice (mean difference = 1.438, 95% CI: 0.5789-2.298, P = 0.0008), effects maintained after PD modeling (PD-ear-tagged vs PD-control: mean difference = 1.367, 95% CI: 0.6123-2.121, P = 0.0003). Swimming speed did not differ between groups (P = 0.9891).</p><p><strong>Comparison with existing methods: </strong>This study demonstrates that routine identification methods significantly influence PD research outcomes. The induced confounds-chronic neuroinflammation from toe-clipping and sensorimotor disruption from ear-tagging-can mimic or mask PD pathology, threatening data validity.</p><p><strong>Conclusion: </strong>Identification methods must be documented as critical methodological variables. Adoption of non-invasive alternatives is imperative for rigor and reproducibility in neurodegenerative research.</p>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110790"},"PeriodicalIF":2.3,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147856436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel method to sort and enrich sensory neurons.","authors":"Zerina Kurtović, Sven David Arvidsson, Juan Antonio Vazquez Mora, Sijing Ye, Alex Bersellini Farinotti, Nils Simon, Emerson Krock, Lisbet Haglund, Michael Hagemann-Jensen, Harald Lund, Camilla I Svensson","doi":"10.1016/j.jneumeth.2026.110789","DOIUrl":"https://doi.org/10.1016/j.jneumeth.2026.110789","url":null,"abstract":"<p><p>Peripheral sensory neurons, residing in the dorsal root ganglia (DRG), relay sensory information from the periphery to the central nervous system. Although single-cell transcriptomic studies have identified over 20 distinct sensory neuron subtypes, functional analysis and assessment of subtype-specific pathological changes remain difficult. Effective isolation and enrichment of sensory neurons are challenging yet essential for functional studies. Therefore, we used single-cell transcriptomic data from DRG to identify a panel of neuronal surface markers, including Nrxn2 and Pirt. Using these markers, we developed a fluorescence-activated cell sorting (FACS) panel for neuronal enrichment and analysis that does not rely on transgenic mouse strains and can be broadly applied. The panel was validated by microscopy and single-cell RNA (scRNA) sequencing, which also revealed broad representation of neuronal subtypes. Expression of these markers in human DRG underscores the translational value of this isolation method for sensory and pain studies. Overall, this study provides a valuable tool for isolating DRG neurons, advancing research on sensory neuron function and pain biology, and facilitating neuroimmune studies.</p>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110789"},"PeriodicalIF":2.3,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147839068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Taurine and MAO B binding sites in the brain of monkeys determine differing responses to MPTP administration.","authors":"Christian Pifl, Alexandra Wolf, Carmen Cavada, Javier Blesa, José A Obeso","doi":"10.1016/j.jneumeth.2026.110788","DOIUrl":"https://doi.org/10.1016/j.jneumeth.2026.110788","url":null,"abstract":"<p><strong>Background: </strong>The inter-individual variability of subhuman primates in vulnerability to MPTP is unresolved.</p><p><strong>New method: </strong>Therefore, we analysed caudate, putamen, primary motor cortex and prefrontal cortex in groups of monkeys with four distinct stages of MPTP-induced neurodegeneration: (1) staying asymptomatic, (2) recovered from mild parkinsonism, with stable (3) moderate or (4) severe parkinsonism. We determined taurine and the amino acid aspartate by high-pressure gradient system with fluorometric detection, the glial biomarker glial fibrillary acidic protein (GFAP) with quantitative Westernblotting with total protein normalization and MAO B tissue levels with [³H]-L-deprenyl binding and performed correlative analyses.</p><p><strong>Results: </strong>Taurine was higher in asymptomatic and recovered than in control and parkinsonian monkeys, in particular in cortex. [³H]-L-deprenyl binding was higher in putamen and in primary motor cortex of severely parkinsonian monkeys than in asymptomatic and recovered animals. Similarly to [³H]-L-deprenyl, GFAP was increased in putamen of severely parkinsonian monkeys, and a significant correlation of [³H]-L-deprenyl binding with GFAP single values within the four MPTP groups was found.</p><p><strong>Comparison with existing methods: </strong>Instead of comparing different routes of MPTP administration, brain constituents primarily unrelated to the neurodegenerative process were compared in groups of monkeys responding differently to the neurotoxin.</p><p><strong>Conclusions: </strong>Correlative analyses of the higher taurine levels in asymptomatic and recovered and the higher MAO B levels in severely parkinsonian monkeys in the putamen with, as well as in the cortex without neurodegeneration suggest, that monkeys with less potentially neuroprotective taurine and more MPTP-bioactivating MAO B react more likely with neurodegeneration to MPTP administration.</p>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110788"},"PeriodicalIF":2.3,"publicationDate":"2026-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147839076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"'RMT-Finder': an automated procedure to determine the Resting Motor Threshold for Transcranial Magnetic Stimulation.","authors":"Laurine F Boidequin, Marcos Moreno-Verdú, Baptiste M Waltzing, Julien J Lambert, Elise E Van Caenegem, Charlène Truong, Robert M Hardwick","doi":"10.1016/j.jneumeth.2026.110787","DOIUrl":"https://doi.org/10.1016/j.jneumeth.2026.110787","url":null,"abstract":"<p><strong>Background: </strong>Transcranial Magnetic Stimulation (TMS) studies identify the Resting Motor Threshold (RMT) to calibrate stimulation intensity. However, this procedure is time-consuming and subject to variability. We developed an automated procedure to improve the efficiency and standardization of RMT determination.</p><p><strong>New method: </strong>We developed an algorithm that measures MEP amplitudes and automatically adjusts stimulation intensity to determine the RMT. Experiment 1 compared this automated method with the manual procedure in terms of reliability and equivalence. Experiment 2 developed a \"Fast\" automated process, assessing it against both the manual and initial automated procedures.</p><p><strong>Results: </strong>Across both experiments the automated approach demonstrated excellent test-retest reliability and strong agreement with the manual method (Intraclass Correlation Coefficients ≥0.95), giving estimates of RMT statistically equivalent to those of manual measurements within ±3% MSO, with the majority of comparisons within ±2% MSO. Experiment 2 optimized the procedure, allowing empirical determination of the RMT in an average of <3minutes with only 33-34 pulses.</p><p><strong>Comparison with existing methods: </strong>'RMT-Finder' provides a reliable and time-efficient alternative to manual approaches. This procedure can improve standardization and reproducibility in TMS studies.</p><p><strong>Conclusions: </strong>Automating RMT assessment allows rapid and highly reproducible assessment of this standard TMS measurement, making it viable for inclusion in routine clinical applications that require standardized procedures.</p>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110787"},"PeriodicalIF":2.3,"publicationDate":"2026-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147839147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing brain–computer interface performance through source-level attention mechanism: An EEG motor imagery study","authors":"Jia-He Lim,&nbsp;Po-Chih Kuo","doi":"10.1016/j.jneumeth.2025.110666","DOIUrl":"10.1016/j.jneumeth.2025.110666","url":null,"abstract":"<div><h3>Background:</h3><div>Brain–computer interfaces (BCIs) enable direct communication between humans and machines by translating brain signals into control commands. Electroencephalography (EEG) is a commonly used modality in BCI systems due to its non-invasiveness and high temporal resolution. However, EEG-based BCIs often suffer from low signal-to-noise ratios and limited spatial resolution, primarily due to the small number of recording electrodes. Although source estimation techniques can improve spatial specificity, they typically require subject-specific information such as individual brain anatomy or electrode positions, which may not always be available. This study aims to address these challenges by proposing a framework that enhances task-relevant EEG signals using an attention-guided source estimation approach based on coarse predefined brain regions.</div></div><div><h3>New method:</h3><div>We developed an attention-guided neural network that estimates source-level activity most relevant to the BCI task, without requiring subject-specific structural data. The model uses predefined regions of interest to guide attention mechanisms toward informative spatial features.</div></div><div><h3>Results:</h3><div>The framework was validated using publicly available motor imagery EEG datasets, achieving strong performance. Comparison with existing methods: Comparative analyses were conducted against baseline models using traditional EEG signals and standard feature extraction methods. This study presents an effective approach for improving EEG-based BCI performance by integrating an attention-guided source estimation network into the decoding pipeline. The method does not rely on subject-specific anatomical information, making it broadly applicable.</div></div><div><h3>Conclusion:</h3><div>By emphasizing task-relevant source activity, the framework enhances signal quality and classification accuracy, thereby advancing the potential of BCIs for precise and practical applications.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110666"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145998391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale spatiotemporal neural network with multi-attention mechanism using brain partitioning for motor imagery recognition","authors":"Moeed Sehnan ,&nbsp;Haoyu Li ,&nbsp;Xiaoyang Li ,&nbsp;Celso Grebogi ,&nbsp;Zhongke Gao ,&nbsp;Weidong Dang","doi":"10.1016/j.jneumeth.2026.110704","DOIUrl":"10.1016/j.jneumeth.2026.110704","url":null,"abstract":"<div><h3>Background:</h3><div>Motor imagery (MI)-based electroencephalogram (EEG) brain-computer interfaces (BCIs) facilitate communication for motor-impaired patients by leveraging artificial intelligence to accurately interpret brain signals. However, EEG signal classification remains challenging due to low signal-to-noise ratio (SNR) and individual variability in brain activity.</div></div><div><h3>New method:</h3><div>We propose a novel parallel multi-depth spatial–temporal neural network aimed at enhancing the integration of spatial and temporal features from multichannel EEG signals by leveraging brain functional topography. To improve cortical representations associated with motor imagery, the model incorporates two parallel branches. One branch focuses on inter-channel differences corresponding to contralateral electrode pairs, emphasizing hemispheric disparities, while the other targets the frontal and parietal brain regions. These region-specific enhanced signal representations are then fed into the multi-depth spatial–temporal network for feature extraction and subsequent motor imagery classification. The architecture of the feature extraction network integrates four specialized blocks, ensuring the comprehensive capture of discriminative features that are particularly sensitive to task-relevant frequencies for each MI class. A multi-loss design further optimizes feature integration across networks.</div></div><div><h3>Results:</h3><div>Cross-validation results on the BCI Competition IV 2a dataset and High Gamma dataset achieve accuracies of 82.14% and 95.61%, respectively, with kappa values of 0.76 and 0.93, surpassing state-of-the-art methods.</div></div><div><h3>Conclusion:</h3><div>These experimental results highlight the significance of parallel spatial–temporal networks based on brain partitioning for MI classification in rehabilitation engineering and real-world BCI applications.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110704"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146125325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple epileptiform waves detection algorithm based on improved VMD and multidimensional feature fusion","authors":"Qiwei Cai ,&nbsp;Dinghan Hu ,&nbsp;Feng Gao ,&nbsp;Xiaohui Lou ,&nbsp;Jiuwen Cao","doi":"10.1016/j.jneumeth.2026.110703","DOIUrl":"10.1016/j.jneumeth.2026.110703","url":null,"abstract":"<div><h3>Background:</h3><div>Spikes, ripples, and ripples on spikes (RonS) during non-rapid eye movement (NREM) sleep are all important biomarkers associated with epileptic seizures, and accurate detection of these epileptiform waves is vital for epilepsy analysis.</div></div><div><h3>New Method:</h3><div>An improved variational mode decomposition (VMD) decomposes frequency bands to isolate target epileptiform waves. Multidimensional handcrafted features are extracted from low and high frequency bands to characterize these waves, with recursive feature elimination (RFE) selecting key ones. Meanwhile, a dual-stream 1-dimension convolutional neural network (1D CNN) with an adaptive scale factor extracts deep features from VMD-decomposed bands, which are then fused with the handcrafted features.</div></div><div><h3>Results:</h3><div>Experimental results show that the proposed algorithm achieves an average precision of 91%, a recall of 90.36%, and an F1-score of 90.62% on the scalp electroencephalogram (EEG) data of 16 children with benign childhood epilepsy with centrotemporal spikes (BECTS) from the Children’s Hospital of Zhejiang University School of Medicine (CHZU).</div></div><div><h3>Comparison with existing methods:</h3><div>Previous studies have often focused on only one type of epileptiform discharge. This narrow focus limits the translation of these biomarkers into clinical practice and their comprehensive application. In the present study, three types of epileptiform discharges are focused on simultaneously.</div></div><div><h3>Conclusion:</h3><div>Our method achieves the optimal overall detection performance in the detection of multiple epileptiform waves. It can be concluded that the proposed technique is capable of serving as an effective tool for evaluating multiple epileptiform waves.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110703"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146093141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroimaging of reality: A new approach for investigating neural bases of decision-making with real-world objects","authors":"Damien Gabriel ,&nbsp;Guillaume Bertrand ,&nbsp;Magali Nicolier ,&nbsp;Julie Giustiniani","doi":"10.1016/j.jneumeth.2026.110692","DOIUrl":"10.1016/j.jneumeth.2026.110692","url":null,"abstract":"<div><h3>Background</h3><div>Neuroimaging studies often use computerized tasks, but reliance on virtual stimuli limits ecological validity. Incorporating real object interaction under controlled recording conditions may enhance the study of decision-making processes.</div></div><div><h3>New method</h3><div>We developed Lab-Life, a device enabling manipulation of real objects while ensuring precise monitoring and compatibility with electrophysiological recordings. Forty-four right-handed healthy volunteers performed two decision-making tasks: the Iowa Gambling Task (IGT, real vs. virtual cards) and the Game of Dice Task (GDT, real vs. virtual dice). Twenty-two participants (11 per task) used Lab-Life (hybrid condition), while additional virtual task groups were included to illustrate typical behavioral and EEG signatures. Object identity and values were tracked with infrared cameras, and EEG was recorded to analyze event-related potentials (ERPs) to outcomes.</div></div><div><h3>Results</h3><div>Behavioral analyses showed perfect concordance between expected and detected object values in hybrid condition, validating Lab-Life’s automated object recognition. EEG analyses revealed comparable numbers of valid trials and similar ERP patterns between hybrid and virtual task conditions, indicating that the device does not introduce movement artifacts. Participants consistently reported higher enjoyment when manipulating real compared to virtual objects.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike conventional paradigms relying solely on virtual stimuli, Lab-Life integrates real objects without compromising behavioral or electrophysiological data quality. The device allows precise temporal synchronization between object manipulation and EEG recordings while preserving experimental control.</div></div><div><h3>Conclusions</h3><div>Lab-Life is a validated methodological tool for combining behavioral and electrophysiological measures with real object manipulation. It offers a flexible and adaptable platform for decision-making, memory, or perceptual tasks, thereby bridging the gap between laboratory experiments and real-life conditions. Larger studies are warranted to further explore its impact on cognitive performance.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110692"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research progress in vivo, in vitro, and in silico models of intracranial atherosclerotic stenosis","authors":"Fanqiang Meng ,&nbsp;Hanlu Xiang ,&nbsp;Mengjie Huo ,&nbsp;Jiaqi Wu ,&nbsp;Wentao Yao ,&nbsp;Hebo Wang","doi":"10.1016/j.jneumeth.2026.110685","DOIUrl":"10.1016/j.jneumeth.2026.110685","url":null,"abstract":"<div><div>Intracranial atherosclerotic stenosis (ICAS) is a major global cause of stroke with high recurrence risk. However, research on its pathophysiology is limited by difficulties in obtaining histopathological samples and the absence of adequate experimental models. The rising incidence of ICAS imposes a significant burden on families and healthcare systems, highlighting the urgent need for affordable, robust, and reliable animal models to study its prevention and treatment. To better understand the disease, researchers frequently employ animal models to replicate the progression of ICAS in humans. In recent years, many researchers have provided a variety of solutions for modeling methods and intervention protocols in animal models of ICAS, which has greatly improved the success rate of atherosclerosis models. Nevertheless, variations in intervention factors, material selection, and treatment methods have resulted in no consensus on the optimal animal model for ICAS. This review evaluates the strengths and limitations of existing in vivo、in vitro model and computational models of ICAS and the atherosclerotic process, aiming to inform better future models and drive novel stroke-reducing treatment strategies.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110685"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145998558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}