Journal of Neuroscience Methods最新文献

{"title":"Isolation of ependymal cilia from mouse brain","authors":"Akihiro Mizuno ,&nbsp;Kazuhito Takeuchi ,&nbsp;Yuichi Nagata ,&nbsp;Hideyuki Harada ,&nbsp;Taiki Yamamoto ,&nbsp;Takayuki Ishikawa ,&nbsp;Sachi Maeda ,&nbsp;Fumiharu Ohka ,&nbsp;Hironori Ueno ,&nbsp;Ryuta Saito","doi":"10.1016/j.jneumeth.2024.110198","DOIUrl":"10.1016/j.jneumeth.2024.110198","url":null,"abstract":"<div><h3>Background</h3><p>Ependymal cilia play a major role in the circulation of cerebrospinal fluid. Although isolation of cilia is an essential technique for investigating ciliary structure, to the best of our knowledge, no report on the isolation and structural analysis of ependymal cilia from mouse brain is available.</p></div><div><h3>New method</h3><p>We developed a novel method for isolating ependymal cilia from mouse brain ventricles. We isolated ependymal cilia by partially opening the lateral ventricles and gently applying shear stress, followed by pipetting and ultracentrifugation.</p></div><div><h3>Results</h3><p>Using this new method, we were able to observe cilia separately. The results demonstrated that our method successfully isolated intact ependymal cilia with preserved morphology and ultrastructure. In this procedure, the ventricular ependymal cell layer was partially detached.</p></div><div><h3>Comparison with existing methods</h3><p>Compared to existing methods for isolating cilia from other tissues, our method is meticulously tailored for extracting ependymal cilia from the mouse brain. Designed with a keen understanding of the fragility of the ventricular ependyma, our method prioritizes minimizing tissue damage during the isolation procedure.</p></div><div><h3>Conclusions</h3><p>We isolated ependymal cilia from mouse brain by applying shear stress selectively to the ventricles. Our method can be used to conduct more detailed studies on the structure of ependymal cilia.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0165027024001432/pdfft?md5=bc1b231530f4bfdb12f32fbe9de7337a&pid=1-s2.0-S0165027024001432-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141327593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Localizing hidden Interictal Epileptiform Discharges with simultaneous intracerebral and scalp high-density EEG recordings","authors":"Flavia Maria Zauli ,&nbsp;Maria Del Vecchio ,&nbsp;Andrea Pigorini ,&nbsp;Simone Russo ,&nbsp;Marcello Massimini ,&nbsp;Ivana Sartori ,&nbsp;Francesco Cardinale ,&nbsp;Piergiorgio d’Orio ,&nbsp;Ezequiel Mikulan","doi":"10.1016/j.jneumeth.2024.110193","DOIUrl":"10.1016/j.jneumeth.2024.110193","url":null,"abstract":"<div><h3>Background</h3><p>Scalp EEG is one of the main tools in the clinical evaluation of epilepsy. In some cases intracranial Interictal Epileptiform Discharges (IEDs) are not visible from the scalp. Recent studies have shown the feasibility of revealing them in the EEG if their timings are extracted from simultaneous intracranial recordings, but their potential for the localization of the epileptogenic zone is not yet well defined.</p></div><div><h3>New method</h3><p>We recorded simultaneous high-density EEG (HD-EEG) and stereo-electroencephalography (SEEG) during interictal periods in 8 patients affected by drug-resistant focal epilepsy. We identified IEDs in the SEEG and systematically analyzed the time-locked signals on the EEG by means of evoked potentials, topographical analysis and Electrical Source Imaging (ESI). The dataset has been standardized and is being publicly shared.</p></div><div><h3>Results</h3><p>Our results showed that IEDs that were not clearly visible at single-trials could be uncovered by averaging, in line with previous reports. They also showed that their topographical voltage distributions matched the position of the SEEG electrode where IEDs had been identified, and that ESI techniques can reconstruct it with an accuracy of ∼2 cm. Finally, the present dataset provides a reference to test the accuracy of different methods and parameters.</p></div><div><h3>Comparison with existing methods</h3><p>Our study is the first to systematically compare ESI methods on simultaneously recorded IEDs, and to share a public resource with <em>in-vivo</em> data for their evaluation.</p></div><div><h3>Conclusions</h3><p>Simultaneous HD-EEG and SEEG recordings can unveil hidden IEDs whose origins can be reconstructed using topographical and ESI analyses, but results depend on the selected methods and parameters.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317558","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":"Introducing the portable AttentionTrip: An engaging tool for measuring the networks of attention","authors":"Raymond M. Klein ,&nbsp;Colin R. McCormick ,&nbsp;Rafael de Souza Almeida ,&nbsp;Zeina Lawen ,&nbsp;Swasti Arora","doi":"10.1016/j.jneumeth.2024.110194","DOIUrl":"10.1016/j.jneumeth.2024.110194","url":null,"abstract":"<div><h3>Background</h3><p>Measurement of the efficacy of the networks of attention is a frequent component of research in cognitive and clinical neuroscience. Developed in 2002, the Attention Network Test (ANT), has become the most widely used tool for this purpose.</p></div><div><h3>New method</h3><p>In 2017 a more engaging, game-like tool based on the ANT, called the AttentionTrip was described. The network scores from five studies which used AttentionTrip are shown to be robust.</p></div><div><h3>Newer method</h3><p>That version of AttentionTrip required a steering wheel and desk-top computer. Here we describe a new, portable version of the AttentionTrip that is administered using a hand-held tablet (iPad)</p></div><div><h3>Results</h3><p>Three samples of participants (total = 44) completed the portable version of AttentionTrip. The network scores generated using the portable AttentionTrip were also robust. Effect sizes compare favourably with those generated by the ANT and the desktop version.</p></div><div><h3>Conclusions</h3><p>The findings support the use of the portable AttentionTrip as an alternative to the ANT when user engagement is important, such as when participants are prone to boredom, and when repeated administrations are required.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141310915","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":"Impact of intelligent convolutional neural network -based algorithms on head computed tomography evaluation and comprehensive rehabilitation acupuncture therapy for patients with cerebral infarction","authors":"Jianlin Chen ,&nbsp;Jinfeng Zhang ,&nbsp;Jingjing Xiang ,&nbsp;Jie Yu ,&nbsp;Fanghui Qiu","doi":"10.1016/j.jneumeth.2024.110185","DOIUrl":"10.1016/j.jneumeth.2024.110185","url":null,"abstract":"<div><p>This work was to evaluate the impacts of comprehensive rehabilitation acupuncture therapy on the recovery of neurological function in cerebral infarction (CI) patients and to utilize convolutional neural network (CNN) intelligent algorithms to optimize head computed tomography (CT) images and improve lesion localization accuracy. 98 CI patients were divided into a control group (Ctrl group) and an experimental group (Exp group), with 48 patients in each group. The patients in the Ctrl group received CT evaluation combined with comprehensive rehabilitation acupuncture therapy. While, those in the Exp group received CT evaluation with the use of CNN algorithms for optimization, along with comprehensive rehabilitation acupuncture therapy. Acupuncture therapy included selecting acupoints on the patient’s head, selecting two horizontal needling needles from top to bottom at the acupoints on the front side of the lesion, and then horizontal needling along the top midline. The differences in treatment outcomes were compared between the two groups based on Fugl-Meyer upper limb assessment (FMA) scores, Barthel Index (BI) scores, National Institutes of Health Stroke Scale (NIHSS4) scores, Modified Edinburgh-Scandinavian Stroke Scale (MESSS) scores, and hemodynamics. Simultaneously, the CT images were optimized using CNN intelligent algorithms to improve image quality and lesion localization accuracy. The results showed that the CI CT images processed by the CNN-based intelligent algorithm showed significant improvements in clarity and contrast compared to conventional CT images. The CNN-based intelligent algorithm demonstrated higher sensitivity (97.5 %, 93.8 %), higher PSNR (30.14 dB, 24.72 dB), and lower missed detection rate (0.52 %, 1.88 %) in detecting CI lesions. The total effective rate in the Exp group was 95.83 %, which was significantly higher than the 85.42 % in the Ctrl group (<em>P</em> &lt; 0.05). The Exp group showed significantly higher levels in FMA and BI scores (<em>P</em> &lt; 0.05). After treatment, the NIHSS4 and MESSS scores in the Exp group were lower than those in the Ctrl group (<em>P</em> &lt; 0.05). Additionally, post-treatment, the plasma concentrations and whole-blood viscosity (low shear and high shear) in the Exp group were lower than those in the Ctrl group, and the plasma concentration and whole-blood viscosity (high shear) were also lower than those in the Ctrl group (<em>P</em> &lt; 0.05). In conclusion, comprehensive rehabilitation acupuncture therapy had a positive impact on the recovery of neurological function in CI patients. By applying CNN-based intelligent algorithms to optimize head CT images, lesion localization accuracy can be improved, thereby guiding rehabilitation treatment more effectively.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141293489","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":"Cognitive driven gait freezing phase detection and classification for neuro-rehabilitated patients using machine learning algorithms","authors":"Aditya Khamparia ,&nbsp;Deepak Gupta ,&nbsp;Mashael Maashi ,&nbsp;Hanan Abdullah Mengash","doi":"10.1016/j.jneumeth.2024.110183","DOIUrl":"10.1016/j.jneumeth.2024.110183","url":null,"abstract":"<div><h3>Background</h3><p>The significance of diagnosing illnesses associated with brain cognitive and gait freezing phase patterns has led to a recent surge in interest in the study of gait for mental disorders. A more precise and effective way to characterize and classify many common gait problems, such as foot and brain pulse disorders, can improve prognosis evaluation and treatment options for Parkinson patients. Nonetheless, the primary clinical technique for assessing gait abnormalities at the moment is visual inspection, which depends on the subjectivity of the observer and can be inaccurate.</p></div><div><h3>Research question</h3><p>This study investigates whether it is possible to differentiate between gait brain disorder and the typical walking pattern using machine learning driven supervised learning techniques and data obtained from inertial measurement unit sensors for brain, hip and leg rehabilitation.</p></div><div><h3>Method</h3><p>The proposed method makes use of the Daphnet freezing of Gait Data Set, consisted of 237 instances with 9 attributes. The method utilizes machine learning and feature reduction approaches in leg and hip gait recognition.</p></div><div><h3>Results</h3><p>From the obtained results, it is concluded that among all classifiers RF achieved highest accuracy as 98.9 % and Perceptron achieved lowest i.e. 70.4 % accuracy. While utilizing LDA as feature reduction approach, KNN, RF and NB also achieved promising accuracy and F1-score in comparison with SVM and LR classifiers.</p></div><div><h3>Significance</h3><p>In order to distinguish between the different gait disorders associated with brain tissues freezing/non-freezing and normal walking gait patterns, it is shown that the integration of different machine learning algorithms offers a viable and prospective solution. This research implies the need for an impartial approach to support clinical judgment.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141228940","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":"Adoption of deep learning-based magnetic resonance image information diagnosis in brain function network analysis of Parkinson’s disease patients with end-of-dose wearing-off","authors":"Jingwen Yuan,&nbsp;Yan He","doi":"10.1016/j.jneumeth.2024.110184","DOIUrl":"10.1016/j.jneumeth.2024.110184","url":null,"abstract":"<div><h3>Objective</h3><p>this study was to analyze the brain functional network of end-of-dose wearing-off (EODWO) in patients with Parkinson’s disease (PD) using a convolutional neural network (CNN)-based functional magnetic resonance imaging (fMRI) data classification model.</p></div><div><h3>Methods</h3><p>one hundred PD patients were recruited and assigned to control (Ctrl) group (39 cases without EODWO) and experimental (Exp) group (61 cases with EODWO). The data classification model based on a CNN was employed to assist the analysis of the changes in brain functional network structure in the two groups. The CNN-based fMRI data classification model was primarily based on a CNN architecture, with improvements made to the initialization of convolutional kernel parameters. Firstly, a structure based on restricted Boltzmann machine (RBM) was constructed, followed by the initialization of convolutional kernel parameters. Subsequently, the model underwent training. Utilizing the data analysis module within the GRETNA toolbox, extracted feature sets were analyzed, including local measures such as betweenness centrality (BC) and degree centrality (DC), as well as global measures such as global efficiency (Eg) and local efficiency (Eloc).</p></div><div><h3>Results</h3><p>as sparsity increased, there was a gradual upward trend observed in Eg; however, the values of Eg in both brain functional networks remained relatively stable within the range of 0.2–0.5. The Eg value of the Ctrl group’s whole-brain functional network was 0.17 ± 0.02, while that of the Exp group’s whole-brain functional network was 0.17 ± 0.03, with no significant difference between them (<em>P</em>&gt;0.05). The functional DC value of the superior frontal gyrus in the Exp group (8.71 ± 2.56) was significantly lower than that of the Ctrl group (13.32 ± 3.22), whereas the functional DC value of the anterior cingulate gyrus in the Exp group (19.33 ± 4.78) was significantly higher than that of the Ctrl group (15.21 ± 4.02) (<em>P</em>&lt;0.05). There was no significant correlation observed between the functional DC value and levodopa or dopamine agonist therapy (DDT) in the Exp group, whereas the Ctrl group exhibited a significant positive correlation.</p></div><div><h3>Conclusion</h3><p>analysis conducted via a CNN-based fMRI data classification model revealed a correlation between the occurrence of EODWO in PD patients and functional impairments in the left precuneus. Additionally, the occurrence of EODWO may potentially diminish the plasticity of the central prefrontal dopamine.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141262065","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":"Introducing HiBoP: a Unity‐based visualization software for large iEEG datasets","authors":"Maria Del Vecchio ,&nbsp;Benjamin Bontemps ,&nbsp;Florian Lance ,&nbsp;Adrien Gannerie ,&nbsp;Florian Sipp ,&nbsp;Davide Albertini ,&nbsp;Chiara Maria Cassani ,&nbsp;Benoit Chatard ,&nbsp;Maryne Dupin ,&nbsp;Jean-Philippe Lachaux","doi":"10.1016/j.jneumeth.2024.110179","DOIUrl":"10.1016/j.jneumeth.2024.110179","url":null,"abstract":"<div><h3>Background</h3><p>Intracranial EEG data offer a unique spatio-temporal precision to investigate human brain functions. Large datasets have become recently accessible thanks to new iEEG data-sharing practices and tighter collaboration with clinicians. Yet, the complexity of such datasets poses new challenges, especially regarding the visualization and anatomical display of iEEG.</p></div><div><h3>New method</h3><p>We introduce HiBoP, a multi-modal visualization software specifically designed for large groups of patients and multiple experiments. Its main features include the dynamic display of iEEG responses induced by tasks/stimulations, the definition of Regions and electrodes Of Interest, and the shift between group-level and individual-level 3D anatomo-functional data.</p></div><div><h3>Results</h3><p>We provide a use-case with data from 36 patients to reveal the global cortical dynamics following tactile stimulation. We used HiBoP to visualize high-gamma responses [50–150 Hz], and define three major response components in primary somatosensory and premotor cortices and parietal operculum.</p></div><div><h3>Comparison with existing methods(s)</h3><p>Several iEEG softwares are now publicly available with outstanding analysis features. Yet, most were developed in languages (Python/Matlab) chosen to facilitate the inclusion of new analysis by users, rather than the quality of the visualization. HiBoP represents a visualization tool developed with videogame standards (Unity/C#), and performs detailed anatomical analysis rapidly, across multiple conditions, patients, and modalities with an easy export toward third-party softwares.</p></div><div><h3>Conclusion</h3><p>HiBoP provides a user-friendly environment that greatly facilitates the exploration of large iEEG datasets, and helps users decipher subtle structure/function relationships.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141186249","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":"Standardizing a method for functional assessment of neural networks in brain organoids","authors":"MK Oliva ,&nbsp;J. Bourke ,&nbsp;D. Kornienko ,&nbsp;C. Mattei ,&nbsp;M. Mao ,&nbsp;A. Kuanyshbek ,&nbsp;D. Ovchinnikov ,&nbsp;A. Bryson ,&nbsp;TJ Karle ,&nbsp;S. Maljevic ,&nbsp;S. Petrou","doi":"10.1016/j.jneumeth.2024.110178","DOIUrl":"10.1016/j.jneumeth.2024.110178","url":null,"abstract":"<div><p>During the last decade brain organoids have emerged as an attractive model system, allowing stem cells to be differentiated into complex 3D models, recapitulating many aspects of human brain development. Whilst many studies have analysed anatomical and cytoarchitectural characteristics of organoids, their functional characterisation has been limited, and highly variable between studies. Standardised, consistent methods for recording functional activity are critical to providing a functional understanding of neuronal networks at the synaptic and network level that can yield useful information about functional network phenotypes in disease and healthy states. In this study we outline a detailed methodology for calcium imaging and Multi-Electrode Array (MEA) recordings in brain organoids. To illustrate the utility of these functional interrogation techniques in uncovering induced differences in neural network activity we applied various stimulating media protocols. We demonstrate overlapping information from the two modalities, with comparable numbers of active cells in the four treatment groups and an increase in synchronous behaviour in BrainPhys treated groups. Further development of analysis pipelines to reveal network level changes in brain organoids will enrich our understanding of network formation and perturbation in these structures, and aid in the future development of drugs that target neurological disorders at the network level.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141199768","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":"Investigating retinal explant models cultured in static and perfused systems to test the performance of exosomes secreted from retinal organoids","authors":"Tingting Yang ,&nbsp;Wenxuan Wang ,&nbsp;Linyao Xie ,&nbsp;Sihui Chen ,&nbsp;Xiuhong Ye ,&nbsp;Shuhao Shen ,&nbsp;Hang Chen ,&nbsp;Ling Qi ,&nbsp;Zekai Cui ,&nbsp;Wei Xiong ,&nbsp;Yonglong Guo ,&nbsp;Jiansu Chen","doi":"10.1016/j.jneumeth.2024.110181","DOIUrl":"10.1016/j.jneumeth.2024.110181","url":null,"abstract":"<div><h3>Background</h3><p><em>Ex vivo</em> cultures of retinal explants are appropriate models for translational research. However, one of the difficult problems of retinal explants <em>ex vivo</em> culture is that their nutrient supply needs cannot be constantly met.</p></div><div><h3>New method</h3><p>This study evaluated the effect of perfused culture on the survival of retinal explants, addressing the challenge of insufficient nutrition in static culture. Furthermore, exosomes secreted from retinal organoids (RO-Exos) were stained with PKH26 to track their uptake in retinal explants to mimic the efficacy of exosomal drugs <em>in vivo</em>.</p></div><div><h3>Results</h3><p>We found that the retinal explants cultured with perfusion exhibited significantly higher viability, increased NeuN⁺ cells, and reduced apoptosis compared to the static culture group at Days Ex Vivo (DEV) 4, 7, and 14. The perfusion-cultured retinal explants exhibited reduced mRNA markers for gliosis and microglial activation, along with lower expression of GFAP and Iba1, as revealed by immunostaining. Additionally, RNA-sequencing analysis showed that perfusion culture mainly upregulated genes associated with visual perception and photoreceptor cell maintenance while downregulating the immune system process and immune response. RO-Exos promoted the uptake of PKH26-labelled exosomes and the growth of retinal explants in perfusion culture.</p></div><div><h3>Comparison with existing methods</h3><p>Our perfusion culture system can provide a continuous supply of culture medium to achieve steady-state equilibrium in retinal explant culture. Compared to traditional static culture, it better preserves the vitality, provides better neuroprotection, and reduces glial activation.</p></div><div><h3>Conclusions</h3><p>This study provides a promising <em>ex vivo</em> model for further studies on degenerative retinal diseases and drug screening.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141186391","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 semi-automated pipeline for finite element modeling of electric field induced in nonhuman primates by transcranial magnetic stimulation","authors":"Neerav Goswami ,&nbsp;Michael Shen ,&nbsp;Luis J. Gomez ,&nbsp;Moritz Dannhauer ,&nbsp;Marc A. Sommer ,&nbsp;Angel V. Peterchev","doi":"10.1016/j.jneumeth.2024.110176","DOIUrl":"10.1016/j.jneumeth.2024.110176","url":null,"abstract":"<div><h3>Background</h3><p>Transcranial magnetic stimulation (TMS) is used to treat a range of brain disorders by inducing an electric field (E-field) in the brain. However, the precise neural effects of TMS are not well understood. Nonhuman primates (NHPs) are used to model the impact of TMS on neural activity, but a systematic method of quantifying the induced E-field in the cortex of NHPs has not been developed.</p></div><div><h3>New method</h3><p>The pipeline uses statistical parametric mapping (SPM) to automatically segment a structural MRI image of a rhesus macaque into five tissue compartments. Manual corrections are necessary around implants. The segmented tissues are tessellated into 3D meshes used in finite element method (FEM) software to compute the TMS induced E-field in the brain. The gray matter can be further segmented into cortical laminae using a volume preserving method for defining layers.</p></div><div><h3>Results</h3><p>Models of three NHPs were generated with TMS coils placed over the precentral gyrus. Two coil configurations, active and sham, were simulated and compared. The results demonstrated a large difference in E-fields at the target. Additionally, the simulations were calculated using two different E-field solvers and were found to not significantly differ.</p></div><div><h3>Comparison with existing methods</h3><p>Current methods segment NHP tissues manually or use automated methods for only the brain tissue. Existing methods also do not stratify the gray matter into layers.</p></div><div><h3>Conclusion</h3><p>The pipeline calculates the induced E-field in NHP models by TMS and can be used to plan implant surgeries and determine approximate E-field values around neuron recording sites.</p></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141131439","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}