Journal of Neuroscience Methods最新文献

{"title":"Robust cortical thickness estimation in the presence of partial volumes using adaptive diffusion equation","authors":"Anand A. Joshi ,&nbsp;Ronald Salloum ,&nbsp;Chitresh Bhushan ,&nbsp;Jessica L. Wisnowski ,&nbsp;Soyoung Choi ,&nbsp;David W. Shattuck ,&nbsp;Richard M. Leahy","doi":"10.1016/j.jneumeth.2025.110552","DOIUrl":"10.1016/j.jneumeth.2025.110552","url":null,"abstract":"<div><h3>Background:</h3><div>Automated estimation of cortical thickness in brain MRI is a critical step when investigating neuroanatomical population differences and changes associated with normal development and aging, as well as in neurodegenerative diseases such as Alzheimer’s and Parkinson’s. The limited spatial resolution of the scanner leads to partial volume effects, where each voxel in the scanned image may represent a mixture of more than one type of tissue. Due to the highly convoluted structure of the cortex, this can have a significant impact on the accuracy of thickness estimates, particularly if a hard intensity threshold is used to delineate cortical boundaries.</div></div><div><h3>New methods:</h3><div>In this paper, we describe a novel method based on an adaptive diffusion equation (ADE) that explicitly accounts for the presence of partial tissue volumes to estimate cortical thickness more accurately. The diffusivity term uses gray matter fractions to incorporate partial tissue volumes into the thickness calculation.</div></div><div><h3>Results:</h3><div>We show that the proposed method is robust to the effects of finite voxel resolution and blurring. The method was validated through simulations, comparisons with histological measurements reported in the literature, and single- and multi-scanner test–retest studies.</div></div><div><h3>Comparison with existing methods</h3><div>: The proposed method was compared with methods based on the Laplace equation, a linked distance metric, and the FreeSurfer software package.</div></div><div><h3>Conclusion:</h3><div>We introduced a novel method (ADE) for estimating cortical thickness that is robust to variations in image resolution and scanner field strength. ADE yields accurate, histologically consistent thickness estimates and demonstrates superior consistency in multi-scanner test–retest studies.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110552"},"PeriodicalIF":2.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925048","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 heat flow approach to functional infrared thermography","authors":"Michael Iorga ,&nbsp;Nils Schneider ,&nbsp;Jaden Cho ,&nbsp;Matthew C. Tate ,&nbsp;Todd B. Parrish","doi":"10.1016/j.jneumeth.2025.110560","DOIUrl":"10.1016/j.jneumeth.2025.110560","url":null,"abstract":"<div><h3>Background</h3><div>Functional infrared thermography is a noncontact approach for intraoperative functional mapping which leverages neurovascular coupling-driven heating of activated cortical areas. Conventional analysis of thermography data relies on demonstrating changes in absolute temperature, which can be an inconsistent marker of brain activity.</div></div><div><h3>New Method</h3><div>This work compares analyzing thermography data through the time derivative of temperature (heat flow) instead of absolute temperature (local heating). Functional maps were created for each patient using both the local heating and local heat flow approaches by calculating a group thermal response function and then correlating this signal to parcellated ROIs on the cortical surface.</div></div><div><h3>Results</h3><div>The validity of each map was assessed by comparison with direct electrical stimulation, the clinical gold-standard. Maps created using heat flow were marginally improved for hand motor mapping (ROC-AUC 0.96 vs 0.93), but significantly improved for face motor mapping (ROC-AUC 0.89 vs 0.68). Both approaches were comparatively inconsistent in identifying hand sensory areas (ROC-AUC 0.69 vs 0.68).</div></div><div><h3>Comparison with existing methods</h3><div>Functional maps created with the heat flow approach have better overall correspondence to direct electrical stimulation results. In addition, the temperature-based approach is susceptible to activation artefacts outside of positive stimulation sites, which was markedly decreased in the heat flow approach.</div></div><div><h3>Conclusions</h3><div>Our results demonstrate the importance of applying the temporal derivative when analyzing thermography experiments with long-block designs. Identifying reliable indicators of brain activity is essential for establishing infrared thermography as a brain mapping technique.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110560"},"PeriodicalIF":2.3,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144889734","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":"Investigation into the influence of stimulation area and coil orientation on the results of navigated transcranial magnetic stimulation (nTMS) mapping of lower limb intracortical excitability","authors":"Ralf Becker ,&nbsp;Sabrina Lorenz ,&nbsp;Jan Coburger ,&nbsp;Christian Rainer Wirtz ,&nbsp;Andrej Pala ,&nbsp;Thomas Kammer ,&nbsp;Gregor Durner","doi":"10.1016/j.jneumeth.2025.110559","DOIUrl":"10.1016/j.jneumeth.2025.110559","url":null,"abstract":"<div><h3>Background</h3><div>Transcranial magnetic stimulation (TMS) is widely used to assess corticomotor excitability. Coil orientation and stimulation location are crucial for eliciting motor-evoked potentials (MEPs) and determining resting motor thresholds (RMT). Since the cortical foot area is challenging to examine, identifying the optimal coil angle and location is essential.</div></div><div><h3>Method</h3><div>Eleven healthy volunteers underwent navigated TMS mapping using a predefined protocol. Stimulation was applied at six locations around the tibialis anterior (TA) motor hotspot, with coil direction varied in 45° increments. Mapping was performed using the Nexstim NBS 5.0 system, and statistical analysis was conducted in RStudio 2024.</div></div><div><h3>Results</h3><div>TA cortical representation mapping was successful in all participants. The mean hotspot was located in the precentral gyrus, 6–13 mm lateral to the midline. The highest MEP amplitude was observed at a stimulation angle of 90°, perpendicular to the falx cerebri.</div></div><div><h3>Comparison with Existing Methods</h3><div>Unlike previous studies with limited coil orientations or without MRI-guided neuronavigation, our approach systematically evaluated multiple directions and locations. The findings align with prior research regarding optimal stimulation sites and angles.</div></div><div><h3>Conclusion</h3><div>We refined the anatomical stimulation area and preferred angle for lower-extremity TMS. These findings may improve clinical applications, especially when considering individual and pathological differences.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110559"},"PeriodicalIF":2.3,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886253","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":"Unveiling epigenetic-driven synaptic remodeling by parallel analysis of nuclei and synapses using NucleuSynapse-Tag","authors":"Yunuen Moreno-López,&nbsp;Citlali A. Suárez-Rangel,&nbsp;José A. Bonilla,&nbsp;G. Aleph Prieto","doi":"10.1016/j.jneumeth.2025.110550","DOIUrl":"10.1016/j.jneumeth.2025.110550","url":null,"abstract":"<div><h3>Background</h3><div>Neuronal functions rely on coordinated molecular mechanisms across cell compartments, with communication between the nucleus and synapses. However, a multiplex and quantitative analysis of nuclear and synaptic content in parallel remains a significant technical challenge.</div></div><div><h3>New method</h3><div>Neurons were tagged with EGFP by stereotaxic injection of AAV-EGFP viral particles into the dorsal dentate gyrus (DG) of mice. This was followed by dorsal hippocampal dissection, homogenization, and differential centrifugation to obtain the nuclear (P1) and synaptosomal crude fractions (P2); both P1 and P2 were obtained from the same hippocampal homogenate. After filtration, fractions were immunolabeled and analyzed by flow cytometry.</div></div><div><h3>Results</h3><div>In EGFP⁺ events, NeuN and PROX1 identified nuclei from DG neurons, while synaptosomes were identified by size, FM4–64, and VGluT1. Bright-field, confocal, and electron microscopy confirmed the identity and integrity of EGFP⁺ nuclei and EGFP⁺ synaptosomes isolated from DG neurons tagged with EGFP. Through parallel analyses of synaptosomes and nuclei tagged with EGFP using AAV-EGFP-shRNA-SUV39H1 particles, <em>NucleuSynapse-Tag</em> provided the first direct evidence supporting the idea that epigenetic mechanisms modulate BDNF protein levels at the synapse.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike current methods that focus either on nuclei or on synapses, the <em>NucleuSynapse-Tag</em> protocol offers a quantitative approach for studying synaptic and nuclear molecular markers in parallel from a single brain sample, by tracking genetically fluorescent-tagged specific populations of neurons.</div></div><div><h3>Conclusions</h3><div>Combined with tools like AAV, Cre mice, and tracers, our approach enables a comprehensive analysis of molecular remodeling in two interdependent subcellular compartments that control neuronal function and plasticity.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110550"},"PeriodicalIF":2.3,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886252","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":"Human spinal cord microglia/macrophages culture: Accutase digestion and non-enzymatic purification","authors":"Yuanyuan Wang ,&nbsp;He Jiang ,&nbsp;Junyan Yan ,&nbsp;Shijie Li ,&nbsp;Zihao Xin ,&nbsp;Jiaxiong He ,&nbsp;Sihan Wang ,&nbsp;Caixia Fan ,&nbsp;Lulu Zhang","doi":"10.1016/j.jneumeth.2025.110558","DOIUrl":"10.1016/j.jneumeth.2025.110558","url":null,"abstract":"<div><h3>Background</h3><div>Spinal cord injury (SCI) and neurological diseases pose major medical challenges, with microglia/macrophages critical for neuroinflammation and repair. Traditional in vitro models using animal or human brain microglia/macrophages suffer from species/regional differences, limiting translation. The lack of efficient isolation methods for human spinal cord microglia/macrophages (hSCM) has hindered SCI mechanistic research and drug screening.</div></div><div><h3>New method</h3><div>This study optimized an hSCM isolation/culture protocol with two key innovations:</div><div><strong>Accutase digestion:</strong> Mechanical mincing+ 37 °C Accutase for 15 min replaces traditional mechanical dissociation, enhancing single-cell yield (&gt;95 % viability) while preserving surface antigens (e.g., Iba-1, CD45).</div><div><strong>Two-step non-enzymatic purification:</strong> Using adhesion force differences between microglia/macrophages and astrocytes, \"moderate expansion+hand-shaking\" removes non-adherent cells, avoiding enzymatic damage and maintaining&gt; 90 % viability.</div></div><div><h3>Results</h3><div><strong>Cell characteristics:</strong> Isolated hSCM showed typical resting-state morphology (rod-shaped/branched processes) and expressed microglia/macrophages markers (Iba-1⁺/DAPI⁺ &gt;95 %, CD45 94.18 %, CD11b 80.9 %) via immunofluorescence and flow cytometry.</div><div><strong>Purity and viability:</strong> Purity &gt; 90 %, viability &gt; 92 % post-purification. Cells retained proliferative capacity (doubling time 48–72 h) and phenotypic stability (Iba-1⁺ &gt;90 % over 3 passages).</div></div><div><h3>Comparison with existing methods</h3><div><strong>Higher efficiency:</strong> Single-cell yield (95 %) exceeds traditional mechanical dissociation (∼60–70 %).</div><div><strong>Superior purity:</strong> Non-enzymatic purification achieves &gt; 95 % purity, outperforming classical mouse brain microglia/macrophages methods (85–90 %).</div><div><strong>Gentler dissociation:</strong> Accutase preserves antigen integrity versus harsh trypsin-based protocols.</div></div><div><h3>Conclusions</h3><div>The system establishes a standardized, high-purity hSCM model, filling critical gaps in human-specific SCI research. It facilitates studies on microglia/macrophage immunoregulatory mechanisms, drug screening, and cross-species translation. Future applications may integrate induced iPSC technology for personalized disease modeling to advance precision medicine in SCI.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110558"},"PeriodicalIF":2.3,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144858354","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":"Evaluation of the deep learning-based detection of dopaminergic neurons in primary culture: A practical alternative to manual counting","authors":"Yasuhiko Izumi ,&nbsp;Saori Ikawa ,&nbsp;Kouya Yamaki ,&nbsp;Toshiaki Kume ,&nbsp;Yutaka Koyama","doi":"10.1016/j.jneumeth.2025.110557","DOIUrl":"10.1016/j.jneumeth.2025.110557","url":null,"abstract":"<div><h3>Background</h3><div>Manual counting remains the gold standard for assessing neurotoxicity in cultured neurons. However, it is labor-intensive and susceptible to subjective variability, limiting its scalability and reproducibility in high-throughput studies.</div></div><div><h3>New method</h3><div>To address these limitations, we evaluated two artificial intelligence–based object detection methods for identifying tyrosine hydroxylase-positive dopaminergic neurons in immunostained primary cultures. Specifically, we compared a traditional cascade classifier with a deep learning-based model employing the YOLOv3 algorithm.</div></div><div><h3>Results</h3><div>The cascade classifier performed reasonably well in detecting healthy dopaminergic neurons but showed a high rate of false positives under neurotoxic conditions involving neuronal degeneration. In contrast, the deep learning-based model maintained high precision under both healthy and neurotoxic conditions. The deep learning model detected the neuroprotective effect of a test compound, consistent with expert manual counting. In terms of processing time, the deep learning model was more than seven times faster than manual counting.</div></div><div><h3>Comparison with existing methods</h3><div>While expert manual counting is commonly accepted in biological image analysis, it lacks objectivity and is not suitable for large-scale analyses. The cascade classifier provides limited utility under neurotoxic conditions. The deep learning-based model outperformed the cascade-based approach in terms of precision, especially under neurotoxic conditions.</div></div><div><h3>Conclusions</h3><div>Deep learning-based analysis offers a practical and reproducible alternative to manual cell counting in dopaminergic neurons. It is particularly useful in studies involving neurotoxicity or neuroprotection and has the potential to support scalable and reliable quantification in preclinical research.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110557"},"PeriodicalIF":2.3,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860546","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":"Crush nerve injury model in the rat sciatic nerve: A comprehensive review and validation of various methods","authors":"Daiki Kitano ,&nbsp;Dzana Katana ,&nbsp;Alexander R. Madanat ,&nbsp;Anna E. Bazell ,&nbsp;Jade M. Smith ,&nbsp;Kacey G. Marra","doi":"10.1016/j.jneumeth.2025.110556","DOIUrl":"10.1016/j.jneumeth.2025.110556","url":null,"abstract":"<div><h3>Introduction</h3><div>The rat sciatic nerve crush injury model is commonly employed to evaluate the efficacy of treatments aimed at promoting nerve regeneration. This review examines various crush techniques and the types of nerve injuries they are designed to produce.</div></div><div><h3>Methods</h3><div>A literature review was conducted using PubMed, Embase, Web of Science, and SCOPUS for studies published between 2010 and 2024. Studies were included if they involved surgical crush injuries on the rat sciatic nerve, performed at least one sensory functional evaluation, and compared outcomes with naive or sham controls. Crush techniques and the resulting nerve injuries were analyzed based on postoperative sensory evaluations.</div></div><div><h3>Results</h3><div>Of the 48 studies reviewed, 21 met the inclusion criteria. The crush techniques used included clamp (11 studies), forceps (5), clip (4), and others (1), all of which resulted in sensory impairments. Ten studies reported transient impairments with recovery to control levels, while 11 reported no recovery during the observation period (permanent). The transient group had significantly longer observation periods compared to the permanent group (57.7 vs. 17.4 days, p = 0.0009). ROC analysis determined 25 days as the optimal cutoff to distinguish transient from permanent injuries, with 90.0 % sensitivity and 81.8 % specificity.</div></div><div><h3>Discussion</h3><div>Regardless of the technique used, the induced nerve injury aligns with axonotmesis, characterized by spontaneous recovery over time. To accurately evaluate functional recovery, a minimum postoperative observation period of 4 weeks is recommended. This model is best suited for assessing rapid-acting agents, as spontaneous recovery may obscure the effects of slower-acting treatments.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110556"},"PeriodicalIF":2.3,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144873613","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":"EEG-based cerebral pattern analysis for neurological disorder detection via hybrid machine and deep learning approaches","authors":"Kusum Tara ,&nbsp;Ruimin Wang ,&nbsp;Yoshitaka Matsuda ,&nbsp;Satoru Goto ,&nbsp;Takako Mitsudo ,&nbsp;Takao Yamasaki ,&nbsp;Takenao Sugi","doi":"10.1016/j.jneumeth.2025.110551","DOIUrl":"10.1016/j.jneumeth.2025.110551","url":null,"abstract":"<div><h3>Background</h3><div>Monitoring neurological disorders is crucial for the early detection of neurodegeneration and abnormal neural activity of the human brain.</div></div><div><h3>New methods</h3><div>This study combines a feature-based random forest (RF) machine learning model with an image-based convolutional neural network (CNN) deep-learning approach, forming a hybrid random forest-convolutional neural network (RF-CNN) model to detect neurological disorders such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and epilepsy (Ep) using electroencephalography (EEG) signals. EEG data from 19 channels were segmented into delta, theta, alpha, and beta frequency bands, generating power-based features, spectral topographic maps, and continuous wavelet transform (CWT) based scalograms, as inputs for cerebral pattern analysis.</div></div><div><h3>Results</h3><div>The experimental results demonstrated detection accuracy of 88 % and F1-score of 84.85 % with RF, accuracy of 97.58 % and F1-score of 95.16 % using scalograms, accuracy of 98.39 % and F1-score of 97.64 % using spectral maps, and an outstanding 99.19 % accuracy and 98.32 % F1-score with hybrid RF-CNN model.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike previous models that relied solely on feature-based machine learning or image-based deep learning, this approach enhances disorder detection with greater accuracy by integrating both features and images. Features like power asymmetry increase with cognitive decline, indicating hemispheric imbalance, while a declining cognition index reflects interhemispheric communication loss. Additionally, images including spectral topographic maps and CWT-based scalograms provide a comprehensive view of spatial power distribution and time-frequency characteristics.</div></div><div><h3>Conclusion</h3><div>The hybrid RF-CNN approach enhances more reliable analysis of altered non-linear brain dynamics and transitional phases, making it a valuable tool for detecting neurological disorders.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110551"},"PeriodicalIF":2.3,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852375","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 ANN-based classification of spike-wave activity in 24-hour EEG recordings in rats using spectrograms: Spike-Wave Discharge Artificial Neural Network (SWAN)","authors":"Ivan Lazarenko,&nbsp;Evgenia Sitnikova","doi":"10.1016/j.jneumeth.2025.110555","DOIUrl":"10.1016/j.jneumeth.2025.110555","url":null,"abstract":"<div><h3>Background</h3><div>Electroencephalographic (EEG) detection of spike-wave discharges (SWDs) is essential for diagnosing absence epilepsy. Automated tools for long-term wearable EEG are needed, but current methods relying on basic signal variability metrics inadequately capture SWD complexity.</div></div><div><h3>New method</h3><div>We developed the Spike-Wave discharge Artificial Neural Network (SWAN), a shallow ANN classifier analyzing STFT spectrograms. SWAN addresses two critical dimensions of absence epilepsy: 1) spontaneous SWDs in WAG/Rij rats, and 2) drug-induced SWD transformations mediated by alpha2-adrenoreceptor agonists (xylazine, dexmedetomidine).</div></div><div><h3>Results</h3><div>Trained on baseline EEG from 3 rats and tested on baseline/pharmacological recordings from 4 rats, SWAN achieved high precision (0.96) and sensitivity (0.79) across both conditions. It incorporates a novel \"certainty\" metric quantifying detection confidence.</div></div><div><h3>Comparison with existing methods</h3><div>SWAN surpasses amplitude-based variability measures (e.g., standard deviation) by directly evaluating complex spatiotemporal SWD patterns in spectrograms, enabling more reliable detection. Its shallow architecture facilitates mathematical interrogation of SWD features.</div></div><div><h3>Conclusions</h3><div>SWAN accurately identifies both spontaneous and pharmacologically transformed SWDs in a validated rat model. High precision minimizes over-diagnosis in prolonged recordings, while automation supports unattended monitoring via wearable devices. Future work requires expanded datasets to optimize sensitivity under pharmacological challenge. SWAN provides a robust tool for epilepsy research and therapeutic assessment.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110555"},"PeriodicalIF":2.3,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842874","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":"CLARITY in Alzheimer’s Research: Merging Tissue Transparency with Next-Gen Neurotechnologies","authors":"Anchal Trisal ,&nbsp;Abhishek Kumar Singh","doi":"10.1016/j.jneumeth.2025.110554","DOIUrl":"10.1016/j.jneumeth.2025.110554","url":null,"abstract":"<div><div>CLARITY is a technique that makes tissues optically transparent, enabling the clear visualization of complex cellular and subcellular structures with relative ease. Traditionally, this technique has been used to visualize the pathologies of certain diseases. In the case of Alzheimer’s disease (AD), the CLARITY technique of clearing lipids from tissues has enabled precise visualization of amyloid-beta (Aβ) and tau pathologies with a temporal analysis of the extent of protein aggregation associated with disease progression. This information has been invaluable for determining the progression of AD. Moreover, the structural characteristics of Aβ plaques and neurofibrillary tangles provide details about aggregation patterns. Here, we highlight critical insights into the potential applications of the CLARITY technique in conjunction with other modalities. We elucidated microscopy techniques, namely confocal microscopy and light-sheet microscopy, which are often used to detect fluorescently labeled compounds within cells, aiding in the qualitative and quantitative estimation of target proteins. Additionally, we discuss the application of super-resolution expansion microscopy (SREM) to increase the resolution of tissue images without compromising molecular specificity. We also expounded on the application of CLARITY-based imaging in improving optogenetics and organoid development. Furthermore, we highlight the potential of CLARITY in assisting the formulation and validation of machine learning algorithms and conducting hypothesis testing.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"423 ","pages":"Article 110554"},"PeriodicalIF":2.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859282","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}