Journal of Neuroscience Methods最新文献

{"title":"Customizable artificial simulator for developing, planning, and training personnel on neurophysiology and surgical procedures in non-human primates","authors":"Lydia I. Smith ,&nbsp;Amy L. Orsborn","doi":"10.1016/j.jneumeth.2025.110587","DOIUrl":"10.1016/j.jneumeth.2025.110587","url":null,"abstract":"<div><h3>Background</h3><div>Neuroscience researchers often surgically implant hardware into model organisms to measure and manipulate neural activity. Designing and optimizing these procedures in non-human primates often requires sedated or euthanized animals. Artificial tissue technologies can reduce animal use in this process, but existing simulators do not include all relevant tissues and do not facilitate iterative design processes.</div></div><div><h3>New method</h3><div>We created a comprehensive, customizable, and modular surgical simulator for neuroscience research. Our simulator incorporates artificial skull, brain, and soft tissues (skin and muscle) into one 3-dimensional model with adaptable components.</div></div><div><h3>Results</h3><div>Incorporating 3-dimensional soft tissues enabled surgical and implant design improvements, which may contribute to improving implant longevity, research outcomes, and animal wellbeing. Our modular design allowed researchers to rapidly prototype designs and exchange parts to reflect implant or anatomical changes across a study. Incorporating all relevant tissues also enabled surgical practice and improved communication with veterinarians. Our approach is low-cost (a few hundred dollars) and uses readily available tools like 3D printing. We also provide models of different non-human primate species to increase access to our approach.</div></div><div><h3>Comparison with existing methods</h3><div>Our method improves upon past surgical simulators for neuroscience research by: adapting existing skin and muscle artificial tissue technologies to more accurately represent cranial 3-dimensional geometry, incorporating models of all tissues relevant for implant design, and introducing modular designs that increase flexibility/customization.</div></div><div><h3>Conclusions</h3><div>We found that this surgery simulator was an inexpensive tool that was useful for planning and practicing surgical procedures, as well as prototyping new neuroscience experiment hardware.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110587"},"PeriodicalIF":2.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225548","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":"Corrigendum to \"Reconstructing time-domain data from discontinuous Percept™ PC and RC output using external data acquisition and linear filtering\" [J. Neurosci. Methods 424 (2025) 110566].","authors":"Jinxin Chen, Mandy M Koop, Kenneth B Baker, Jay L Alberts, James Y Liao","doi":"10.1016/j.jneumeth.2025.110596","DOIUrl":"https://doi.org/10.1016/j.jneumeth.2025.110596","url":null,"abstract":"","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110596"},"PeriodicalIF":2.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212936","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":"On the issue of low-frequency EEG generators and methods of their spatial localization","authors":"A.V. Vartanov ,&nbsp;E.L. Masherov","doi":"10.1016/j.jneumeth.2025.110592","DOIUrl":"10.1016/j.jneumeth.2025.110592","url":null,"abstract":"<div><h3>Background</h3><div>The article reviews the theoretical foundations of low-frequency EEG generation and the problems of existing methods and algorithms for localizing low-frequency EEG</div></div><div><h3>New method</h3><div>A new method based on spatial filtering for signal recovery from a specific, pre-set point in space (area of interest) is presented. The algorithm uses the dynamics and correlation of signals in EEG leads with the addition of artificially generated data. The method assumes a volume charge (unipole) as a source and a function of linear potential decay from values inverse to the distance from a given point to scalp electrodes.</div></div><div><h3>Results</h3><div>It is shown that the dipole model based on the summation of postsynaptic potentials cannot adequately describe the low-frequency component of the EEG; arguments are given in favor of the unipolar model based on the summation of trace potentials.</div></div><div><h3>Comparison with existing method</h3><div>Based on deep brain stimulation data, the new method was verified and its effectiveness was compared with some existing algorithms (sLORETA, dSPM, etc., included in the Brainstorm package).</div></div><div><h3>Conclusions</h3><div>As a result, it is shown that the new \"Virtually implanted electrode\" method makes it possible to accurately determine the localization of unipolar current sources. At the same time, it is shown that other methods based on the dipole model gave false solutions. In this regard, it is necessary to revise the results of localization of the low-frequency component of the EEG previously obtained using these tools, especially when evaluating functional relationships based on these data.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110592"},"PeriodicalIF":2.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206678","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":"High - quality decoding of RGB images from the neuronal signals of the pigeon optic tectum","authors":"Zhen Dong,&nbsp;Yingjie Xiang,&nbsp;Songwei Wang","doi":"10.1016/j.jneumeth.2025.110595","DOIUrl":"10.1016/j.jneumeth.2025.110595","url":null,"abstract":"<div><h3>Background</h3><div>Decoding neural activity to reverse-engineer sensory inputs advances understanding of neural encoding and boosts brain-computer interface and visual prosthesis tech. A major challenge is high-quality RGB image reconstruction from natural scenes, which this study tackles using pigeon optic tectum neurons.</div></div><div><h3>New method</h3><div>We built a neural response dataset via microelectrode arrays capturing tectal neurons' ON-OFF responses to RGB images. A modular decoding algorithm, integrating a convolutional encoding network, linear decoder, and image enhancement network, enabled inverse RGB image reconstruction from neural signals.</div></div><div><h3>Results</h3><div>Experimental results confirmed high-quality RGB image reconstruction by the proposed algorithm. For all test set reconstructions, average metrics were: correlation coefficient (R) of 0.853, structural similarity index (SSIM) of 0.618, peak signal-to-noise ratio (PSNR) of 19.94 dB, and feature similarity index (FSIMc) of 0.801. These results confirm accurate recapitulation of both color and contour details of the original images.</div></div><div><h3>Comparison with existing methods</h3><div>In terms of key quantitative metrics, the proposed algorithm achieves a significant improvement over traditional linear reconstruction methods, with the correlation coefficient (R) increased by 12.65 %, the structural similarity index (SSIM) increased by 38.92 %, the peak signal-to-noise ratio (PSNR) increased by 12.65 %, and the feature similarity index (FSIMc) increased by 9.28 %.</div></div><div><h3>Conclusions</h3><div>This research provides a novel technical pathway for high-quality visual neural decoding, with robust experimental metrics validating its effectiveness. It also offers experimental evidence to support investigations into the information processing mechanisms of the avian visual pathway.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110595"},"PeriodicalIF":2.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206660","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":"TEDNet: Cascaded CNN-transformer with dual attentions for taste EEG decoding","authors":"Xueli Wang,&nbsp;Guoce Lv","doi":"10.1016/j.jneumeth.2025.110594","DOIUrl":"10.1016/j.jneumeth.2025.110594","url":null,"abstract":"<div><h3>Background</h3><div>Traditional taste evaluation methods suffer from subjective biases and limited sensor capabilities, while existing Electroencephalogram (EEG) approaches struggle to decode complex neural patterns evoked by sour, sweet, bitter, and salty stimuli due to noise sensitivity and inadequate multi-scale feature integration.</div></div><div><h3>New method</h3><div>To address this, we propose Taste EEG Decoding Network (TEDNet), a novel deep learning architecture integrating: 1) a Temporal Spatial Convolution Module (TSCM) capturing electrode-wise dependencies, 2) a Temporal Spatial Attention Module (TSAM) adaptively reweighting critical features, and 3) a Local Global Fusion Module (LGFM) combines the local features of taste EEG with the global ones.</div></div><div><h3>Results</h3><div>Evaluated on a well-controlled dataset containing 2400 EEG samples from 30 subjects, the accuracy of TEDNet is 98.92 %, the F1-score is 98.75 %, and the Kappa coefficient is 98.49 %.</div></div><div><h3>Comparison with existing methods</h3><div>While maintaining computational efficiency, TEDNet has surpassed the existing advanced convolution and self-attention methods.</div></div><div><h3>Conclusions</h3><div>This framework establishes a robust solution for objective taste perception decoding, advancing sensory evaluation in food science.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110594"},"PeriodicalIF":2.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145191970","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":"Optogenetic control of peripheral nerves: A novel approach to modulation of detrusor contractility in vivo","authors":"Akihiro Maeda ,&nbsp;Fumiaki Yoshida ,&nbsp;Maki Kawasaki ,&nbsp;Shohei Tobu ,&nbsp;Hiroaki Kakinoki ,&nbsp;Hiroki Yasuda ,&nbsp;Mitsuru Noguchi","doi":"10.1016/j.jneumeth.2025.110591","DOIUrl":"10.1016/j.jneumeth.2025.110591","url":null,"abstract":"<div><h3>Background</h3><div>The increasing prevalence of lower urinary tract symptoms (LUTS), particularly voiding dysfunction, has become a significant concern in aging societies. Conventional treatments, including pharmacotherapy and sacral neuromodulation, offer limited efficacy or involve invasive procedures. There is a pressing need for novel, precise, and minimally invasive neuromodulation techniques to restore bladder contractility without compromising continence.</div></div><div><h3>New method</h3><div>We developed an in vivo optogenetic approach to modulate bladder detrusor activity by delivering an adeno-associated virus (AAV9-hSyn-SOUL) encoding a light-sensitive ion channel directly into the bladder wall of Sprague-Dawley rats. Four weeks post-injection, cystometry was conducted to evaluate bladder responses to blue light (473 nm) stimulation. Histological analysis confirmed transgene expression in peripheral nerves.</div></div><div><h3>Results</h3><div>Optical stimulation significantly increased intravesical pressure in all vector-injected rats, as confirmed by cystometric analysis. Urinary interval and voided volume showed no significant change following stimulation. Immunofluorescence staining revealed co-localization of SOUL expression with the peripheral nerve marker peripherin in the bladder wall.</div></div><div><h3>Comparison with existing methods</h3><div>Compared to electrical stimulation and pharmacologic agents, this optogenetic approach provided targeted and reversible control of bladder contractions without requiring transgenic animal models or systemic exposure. It offers a less invasive alternative to sacral neuromodulation with improved specificity.</div></div><div><h3>Conclusions</h3><div>This study demonstrates that optogenetic stimulation of the peripheral bladder nerves using AAV-mediated SOUL expression effectively enhances detrusor contractility while preserving voiding function. These findings support the feasibility of a light-controlled, minimally invasive neuromodulation strategy for the treatment of voiding dysfunction.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110591"},"PeriodicalIF":2.3,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145186186","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":"BrainTRACE (Brain Tumor Registration and Cortical Electrocorticography): A novel tool for localizing electrocorticography electrodes in patients with brain tumors","authors":"Sena Oten ,&nbsp;Sanjeev Herr ,&nbsp;Vardhaan Ambati ,&nbsp;Youssef Sibih ,&nbsp;Katie Lu ,&nbsp;Jasleen Kaur ,&nbsp;Shawn L. Hervey-Jumper ,&nbsp;David Brang","doi":"10.1016/j.jneumeth.2025.110588","DOIUrl":"10.1016/j.jneumeth.2025.110588","url":null,"abstract":"<div><h3>Background</h3><div>Intraoperative electrocorticography (ECoG) plays a critical role in clinical care and neuroscience research, enabling precise mapping of human cortex. However, localizing subdural electrodes in patients with brain tumors presents unique challenges due to altered neuroanatomy and the impracticality of acquiring extraoperative imaging.</div></div><div><h3>New method</h3><div>To address these gaps, we developed BrainTRACE, a novel MATLAB tool that combines MRI, cortical vascular reconstructions, and intraoperative photography for accurate subdural electrode grid placement. Preoperative MRI, cortical photography, and subdural electrode array data were recorded from patients with diffuse glioma and brain metastasis. BrainTRACE generated 3D cortical surfaces, integrated vascular reconstructions, and enabled precise placement of electrode grids. Each electrode was placed based on cortical anatomy and vascular landmarks informed by intraoperative photographs.</div></div><div><h3>Results</h3><div>Expert users achieved high consistency and accuracy, with an intraclass correlation coefficient (ICC) of 0.934 and a mean deviation of 4.3 mm from consensus placements. Novice users demonstrated lower reliability and greater variability, highlighting the non-trivial nature of intraoperative ECoG localization, which requires neuroanatomical expertise.</div></div><div><h3>Comparison with existing methods</h3><div>To our knowledge, BrainTRACE is the first freely available tool that enables photograph-guided ECoG localization using cortical surface reconstructions and vascular anatomy without relying on post-operative imaging.</div></div><div><h3>Conclusions</h3><div>BrainTRACE enables accurate localization of intraoperative ECoG electrodes in brain tumor patients. By integrating anatomical images, intraoperative photographs, and vascular mapping, the tool addresses challenges posed by tumor-induced artifacts. BrainTRACE provides a freely available practical tool for neurosurgical and neuroscience applications, including brain malignancy, epilepsy, and deep brain stimulation.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110588"},"PeriodicalIF":2.3,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155538","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":"Rapid and reliable image analysis pipeline for semi-automated quantification of CNS cell types in MATLAB","authors":"Adrian Castellanos-Molina ,&nbsp;Juliette Ferry ,&nbsp;Ana Boisvert ,&nbsp;Alexandre Chamberland ,&nbsp;Nicolas Vallières ,&nbsp;Steve Lacroix","doi":"10.1016/j.jneumeth.2025.110590","DOIUrl":"10.1016/j.jneumeth.2025.110590","url":null,"abstract":"<div><h3>Background</h3><div>Studying CNS cell responses is essential for understanding disease, injury, and developing effective therapies. While immunofluorescence and transgenic reporter models allow for specific labeling, automated quantification remains difficult due to tissue heterogeneity. Consequently, most analyses are conducted manually, introducing user bias and limiting reproducibility.</div></div><div><h3>New method</h3><div>We developed a MATLAB-based semi-automated workflow for quantifying immunofluorescence-stained CNS cells, focusing on nuclear signal detection. The pipeline uses DAPI masking and the <em>imfindcircles</em> function to detect round nuclei, requiring minimal user input.</div></div><div><h3>Results</h3><div>The pipeline enabled robust quantification of CNS-resident cells. Automated analyses of brain and spinal cord tissue sections closely resembled manual quantification, with minimal error. In a mouse model of contusion spinal cord injury, it revealed a rostro-caudal decline in myelinating oligodendrocytes from the lesion epicenter, confirming the method’s accuracy and sensitivity in detecting injury-induced cellular changes.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike many commonly used quantification-based software, this novel pipeline does not perform full image segmentation. Instead, it uses nuclear morphology to detect round shapes. Moreover, the pipeline has been specifically designed and optimized for the quantification of CNS cells, whose heterogeneity and cytoarchitecture pose specific challenges to existing methods that are more generalized.</div></div><div><h3>Conclusions</h3><div>This study presents an alternative to classical segmentation models by offering a reproducible quantification of CNS-resident cells using nuclear morphology. Its simplicity, minimal input requirements, reduced time for semi-automated quantification, and specificity for CNS tissues make it a valuable tool for studying cellular responses in both healthy and pathological contexts.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110590"},"PeriodicalIF":2.3,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182061","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 transient motion-onset visual evoked potentials via stochastic resonance: Unimodal and cross-modal noise effects","authors":"Huanqing Zhang ,&nbsp;Jun Xie ,&nbsp;Hongwei Yu ,&nbsp;Fangzhao Du ,&nbsp;Zhiwei Jin ,&nbsp;Yujie Chen","doi":"10.1016/j.jneumeth.2025.110589","DOIUrl":"10.1016/j.jneumeth.2025.110589","url":null,"abstract":"<div><h3>Background</h3><div>Motion-onset visual evoked potential (mVEP) are transient brain responses triggered by sudden motion stimuli and are widely used in brain-computer interface (BCI) systems. However, the inherently weak nature of mVEP signals poses a significant challenge to achieving reliable and accurate BCI performance. Enhancing the signal quality of mVEP responses is therefore critical for improving system robustness and usability.</div></div><div><h3>New method</h3><div>This study introduces a novel approach based on stochastic resonance (SR) theory, where appropriate levels of noise can enhance the performance of nonlinear systems such as the brain. By applying auditory and visual noise of varying intensities alongside mVEP stimuli, both unimodal SR and cross-modal SR effects were investigated. The method examines the effects of these noise conditions on brain activation and classification performance in mVEP-BCI.</div></div><div><h3>Results</h3><div>The results show that moderate levels of auditory or visual noise significantly enhance the P2 component amplitude of mVEP and improve classification accuracy in BCI tasks. In contrast, excessive noise leads to suppression of neural responses, forming an inverted U-shaped relationship between noise intensity and mVEP amplitude.</div></div><div><h3>Comparison with existing methods</h3><div>Conventional mVEP enhancement techniques typically rely on signal processing methods such as spatial filtering or feature extraction. In comparison, the proposed noise modulation strategy directly enhances neural responses, offering a biologically inspired and computationally simple alternative that complements existing approaches.</div></div><div><h3>Conclusions</h3><div>Both unimodal and cross-modal SR effectively enhance mVEP responses and BCI performance. This strategy provides new insights into SR mechanisms and supports the development of more robust mVEP-BCI systems.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110589"},"PeriodicalIF":2.3,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155537","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":"Unlocking non-invasive brain stimulations for Next-Gen Clinical Speciality: Opportunities, challenges and future.","authors":"Mohammad Shabaz, Robert E Hampson, Sara Baber Sial","doi":"10.1016/j.jneumeth.2025.110586","DOIUrl":"https://doi.org/10.1016/j.jneumeth.2025.110586","url":null,"abstract":"","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110586"},"PeriodicalIF":2.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145137900","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}