Journal of Neuroscience Methods最新文献

{"title":"Development and testing of an MR-compatible tactile stimulator system: Application for individuals with a brain injury","authors":"Nahid Kalantaryardebily ,&nbsp;Anna C. Feldbush ,&nbsp;Rebecca Faubion-Trejo ,&nbsp;Jonathan Lisinski ,&nbsp;Neha A. Reddy ,&nbsp;Molly G. Bright ,&nbsp;Stephen M. LaConte ,&nbsp;Netta Gurari","doi":"10.1016/j.jneumeth.2025.110583","DOIUrl":"10.1016/j.jneumeth.2025.110583","url":null,"abstract":"<div><h3>Background:</h3><div>Accurate tactile perception is essential for daily function. Abnormally perceiving tactile stimuli is associated with poorer movement recovery in individuals post brain injury. The mechanisms causing abnormal tactile perception post brain injury remain incompletely understood, partially due to insufficient examination methods. Here, we present a custom tactile stimulator system that enables examination of how abnormal tactile perception arises post brain injury.</div></div><div><h3>New Method:</h3><div>The novel tactile stimulator pneumatically inflates and deflates a membrane to stimulate the skin via a small circular contact area (diameter: <span><math><mo>∼</mo></math></span>4–5 mm). The tactile stimulator is compact (14 mm length<span><math><mo>×</mo></math></span>6.5 mm height), compatible with magnetic resonance imaging (MRI), and precise in automatically applying low intensity forces (1.1–2.5<!--> <!-->N) in the MRI.</div></div><div><h3>Results:</h3><div>Feedback on a Likert 5-point scale from 14 young adults who are neurotypical during an MRI study with the tactile stimulator identified comfort in feeling the applied force stimuli as <em>most comfortable</em> (score: 5) and <em>second most comfortable</em> (score: 4) for 11 and 3 participants, respectively. The force stimuli activated the contralateral primary somatosensory cortex and bilateral secondary somatosensory cortices.</div></div><div><h3>Comparison with Existing Methods:</h3><div>Unlike existing tools, our system combines a compact size, precise control of a range of forces, and a relatively fixed contact area.</div></div><div><h3>Conclusions:</h3><div>The novel tactile stimulator system can enable high-precision studies that lead to a better understanding of the brain processes governing tactile perceptual dysfunction in patient populations, including those living with a brain injury.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110583"},"PeriodicalIF":2.3,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106200","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":"EC-FST: A novel pipeline for automatically analyzing mouse forced swim test","authors":"Yang Xia ,&nbsp;Xuechun Meng ,&nbsp;Yuxing Ning ,&nbsp;Hongqi Li ,&nbsp;Yue Wu ,&nbsp;Jian Zhang ,&nbsp;Ling Liu ,&nbsp;Zhaohuan Huang ,&nbsp;Ji Liu","doi":"10.1016/j.jneumeth.2025.110585","DOIUrl":"10.1016/j.jneumeth.2025.110585","url":null,"abstract":"<div><h3>Background</h3><div>The mouse forced swim test (FST) is widely used to evaluate the efficacy of potential anti-depressant drugs. Traditional methods for analyzing forced swim test results rely on manually setting the threshold for immobility, which is time-consuming and barely reproducible.</div></div><div><h3>New method</h3><div>In the present study, we introduced a novel pipeline (EC-FST) by extracting the feature of mouse status instead of calculating immobility time. First, we utilized event camera, a powerful AI tool for dynamic object-tracking framework, to capture the mobile events from mouse forced swim test. By quantifying event numbers and their temporal distribution, we were able to determine mouse’s mobile state across time-line.</div></div><div><h3>Results</h3><div>The EC-FST results showed perfect correlation with manual scoring, suggesting that the proposed method is reliable for analyzing forced swim test. We further tested the power of the EC-FST for detecting depressive-like behavior in mouse depression models，including lipopolysaccharide (LPS) injection and chronic restraint stress (CRS). Depressive-model mice exhibited significantly fewer motion events and lower event frequency than controls, aligning with manual scoring.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike traditional threshold-based approaches, EC-FST provides an automated, unbiased, and reproducible analysis of FST behavior, eliminating the subjectivity of manual scoring.</div></div><div><h3>Conclusion</h3><div>Leveraging AI-driven event cameras, we established a robust pipeline for analyzing mouse behavior in the FST, offering greater efficiency and reproducibility for depression research.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110585"},"PeriodicalIF":2.3,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102927","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":"Wireless high-density electroencephalography in the perioperative setting","authors":"Nathan Runstadler ,&nbsp;Selena Martinez ,&nbsp;UnCheol Lee ,&nbsp;Duan Li ,&nbsp;Kourosh Maboudi ,&nbsp;George A. Mashour ,&nbsp;Phillip E. Vlisides","doi":"10.1016/j.jneumeth.2025.110584","DOIUrl":"10.1016/j.jneumeth.2025.110584","url":null,"abstract":"<div><h3>Background</h3><div>Electroencephalographic (EEG) systems used in the operating room are constrained to frontal channels, providing limited neuroanatomical insights into altered perioperative brain states. Our objective is to present pragmatic strategies for placing whole-scalp, high-density EEG systems perioperatively that enable more comprehensive analysis.</div></div><div><h3>New method</h3><div>We present the successful implementation of wireless high-density (72-channel) EEG in the perioperative setting for the ongoing Caffeine, Postoperative Delirium, and Change in Outcomes after Surgery (CAPACHINOS-2) clinical trial (NCT05574400). Placement time was calculated, impedance and data quality were assessed, and data acquisition and analysis pipelines were established. Lastly, proof-of-principle analyses using source localization were conducted.</div></div><div><h3>Results</h3><div>High-density wireless EEG data have been successfully acquired for n = 45 participants, with median (interquartile range) placement time of 34 (25 – 52) minutes. Data acquisition was supported by an established workflow, and a subsequent data processing pipeline was used to evaluate channel quality, remove artifacts, and generate proof-of-principle high-density analyses.</div></div><div><h3>Comparison with existing methods</h3><div>Compared to a low-density system used for a similar, previous clinical trial (n = 54 participants), preoperative median impedance values (kΩ) were lower with the high-density system (13 [11–16] vs. 39 [28–47] kΩ; p &lt; 0.001). Additionally, proof-of-principle analysis demonstrates a more complex connectivity matrix and broader distribution of cortical alpha rhythms after induction of general anesthesia with the high-density system, highlighting an expanded capacity for neurophysiologic analysis.</div></div><div><h3>Conclusions</h3><div>Wireless high-density EEG serves as a feasible, promising tool to advance understanding of altered perioperative brain states by providing high spatiotemporal resolution of cortical oscillations.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110584"},"PeriodicalIF":2.3,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102947","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":"MSAttNet: Multi-scale attention convolutional neural network for motor imagery classification","authors":"Ruiyu Zhao ,&nbsp;Ian Daly ,&nbsp;Yixin Chen ,&nbsp;Weijie Wu ,&nbsp;Lifei Liu ,&nbsp;Xingyu Wang ,&nbsp;Andrzej Cichocki ,&nbsp;Jing Jin","doi":"10.1016/j.jneumeth.2025.110578","DOIUrl":"10.1016/j.jneumeth.2025.110578","url":null,"abstract":"<div><h3>Background:</h3><div>Convolutional neural networks (CNNs) are widely employed in motor imagery (MI) classification. However, due to cumbersome data collection experiments, and limited, noisy, and non-stationary EEG signals, small MI datasets present considerable challenges to the design of these decoding algorithms.</div></div><div><h3>New method:</h3><div>To capture more feature information from inadequately sized data, we propose a new method, a multi-scale attention convolutional neural network (MSAttNet). Our method includes three main components–a multi-band segmentation module, an attention spatial convolution module, and a multi-scale temporal convolution module. First, the multi-band segmentation module adopts a filter bank with overlapping frequency bands to enhance features in the frequency domain. Then, the attention spatial convolution module is used to adaptively adjust different convolutional kernel parameters according to the input through the attention mechanism to capture the features of different datasets. The outputs of the attention spatial convolution module are grouped to perform multi-scale temporal convolution. Finally, the output of the multi-scale temporal convolution module uses the bilinear pooling layer to extract temporal features and perform noise elimination. The extracted features are then classified.</div></div><div><h3>Results:</h3><div>We use four datasets, including <em>BCI Competition IV Dataset IIa</em>, <em>BCI Competition IV Dataset IIb</em>, the <em>OpenBMI</em> dataset and the <em>ECUST-MI</em> dataset, to test our proposed method. MSAttNet achieves accuracies of 78.20%, 84.52%, 75.94% and 78.60% in cross-session experiments, respectively.</div></div><div><h3>Comparison with existing methods</h3><div>: Compared with state-of-the-art algorithms, MSAttNet enhances the decoding performance of MI tasks.</div></div><div><h3>Conclusion:</h3><div>MSAttNet effectively addresses the challenges of MI-EEG datasets, improving decoding performance by robust feature extraction.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110578"},"PeriodicalIF":2.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060868","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":"REVS: A new open-source platform for high-resolution analysis of rodent wheel running behavior","authors":"James L. Bonanno ,&nbsp;Ciara F. O’Brien ,&nbsp;William B.J. Cafferty","doi":"10.1016/j.jneumeth.2025.110581","DOIUrl":"10.1016/j.jneumeth.2025.110581","url":null,"abstract":"<div><h3>Background</h3><div>Rodent wheel running is widely used in neuroscience and preclinical research to assess locomotor function, recovery post-trauma or disease, circadian rhythms, and exercise physiology. However, most existing wheel-running systems offer limited metrics, lack flexibility in hardware, or require costly proprietary software, reducing their usefulness for detailed behavioral phenotyping—especially in models of injury or rehabilitation.</div></div><div><h3>New method</h3><div>We developed REVS (Revolution Evaluation and Visualization Software), a low-cost, open-source hardware and software platform for analyzing and visualizing rodent wheel running behavior. REVS captures wheel revolutions using Hall effect sensors and computes 13 day-level behavioral metrics along with detailed bout-level data. Users can interactively explore high-resolution temporal features and export data in Open Data Commons (ODC)-compatible formats. REVS supports customizable wheel types, facilitating use in animals with motor and/or sensory impairments.</div></div><div><h3>Results</h3><div>We validated REVS using a mouse model of partial spinal cord injury, where fine motor control is compromised. REVS detected impairments in 10 of 13 behavioral metrics post-injury, with varied recovery trajectories across measures. Principal component analysis revealed that recovery was closely linked to bout quality and intensity, rather than timing.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike commercial and open-source systems, REVS offers more detailed metrics, customizable wheel compatibility, seamless blending with common vivarium hardware, integrated data visualizations, and ODC-compatible data export. It also supports flexible analysis across individuals and groups.</div></div><div><h3>Conclusions</h3><div>REVS provides a powerful, scalable tool for granular behavioral phenotyping in rodent studies, enhancing reproducibility and revealing insights into subtle locomotor changes associated with injury, recovery, and intervention.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110581"},"PeriodicalIF":2.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145064877","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":"X-ray diffraction reveals alterations in mouse somatosensory cortex following sensory deprivation","authors":"Sasha Murokh ,&nbsp;Ezekiel Willerson ,&nbsp;Alexander Lazarev ,&nbsp;Pavel Lazarev ,&nbsp;Lev Mourokh ,&nbsp;Joshua C. Brumberg","doi":"10.1016/j.jneumeth.2025.110582","DOIUrl":"10.1016/j.jneumeth.2025.110582","url":null,"abstract":"<div><h3>Background</h3><div>Sensory experience impacts brain development. In the mouse somatosensory cortex, sensory deprivation via whisker trimming induces reductions in the perineuronal net, the size of neuronal cell bodies, the size and orientation of dendritic arbors, the density of dendritic spines, and the level of myelination, among other effects.</div></div><div><h3>New methods</h3><div>Using a custom-developed laboratory diffractometer, we measured the X-ray diffraction patterns of mouse brain tissue to establish a novel method for examining nanoscale brain structures. Two groups of mice were examined: a control group and one that underwent 30 days of whisker-trimming from birth <img> an established method of sensory deprivation that affects the mouse barrel cortex (whisker sensory processing region of the primary somatosensory cortex). Mice were perfused, and primary somatosensory cortices were isolated for immunocytochemistry and X-ray diffraction imaging.</div></div><div><h3>Results</h3><div>X-ray images were characterized using a specially developed machine-learning approach, and the clusters that correspond to the two groups are well separated in principal components space. We obtained the perfect values for sensitivity and specificity, as well as for the receiver operator curve classifier.</div></div><div><h3>Comparison with existing methods</h3><div>New machine-learning approaches allow for the first time x-ray diffraction to identify cortex that has undergone sensory deprivation without the use of stains.</div></div><div><h3>Conclusions</h3><div>We hypothesize that our results are related to the alteration of different nanoscale structural components in the brains of sensory deprived mice. The effects of these nanoscale structural formations can be reflective of changes in the micro- and macro-scale structures and assemblies with the neocortex.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110582"},"PeriodicalIF":2.3,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145054244","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":"Lost in a large EEG multiverse? Comparing sampling approaches for representative pipeline selection","authors":"Cassie Ann Short ,&nbsp;Andrea Hildebrandt ,&nbsp;Robin Bosse ,&nbsp;Stefan Debener ,&nbsp;Metin Özyağcılar ,&nbsp;Katharina Paul ,&nbsp;Jan Wacker ,&nbsp;Daniel Kristanto","doi":"10.1016/j.jneumeth.2025.110564","DOIUrl":"10.1016/j.jneumeth.2025.110564","url":null,"abstract":"<div><h3>Background</h3><div>The multiplicity of defensible pipelines for processing and analysing data has been implicated as a core contributor to low replicability, creating uncertainty about the robustness of results to defensible variations. This is exacerbated where many defensible pipelines exist, such as in processing electroencephalography (EEG) signals. In multiverse analyses, equally defensible pipelines are computed and the robustness across pipelines is reported. Computing all pipelines is often infeasible, and researchers rely on sampling approaches, assuming representativeness of the full multiverse. However, different sampling methods may yield different robustness estimates, introducing what we term <em>multiverse sampling uncertainty</em>.</div></div><div><h3>New method</h3><div>We developed an open-source tool to compare pipeline samples on their representativeness of the full multiverse. We computed a 528-pipeline use case multiverse on EEG recordings during an emotion classification task to predict extraversion scores from the Late Positive Potential. We applied three sampling methods (random, stratified, active learning) to sample 26 pipelines (5 %) and evaluated the representativeness of model fit distributions.</div></div><div><h3>Results</h3><div>Our results highlight variability in the representativeness of model fit distributions across samples, with active learning and stratified sampling most closely representing the full multiverse. Replicability of results is reported using cross-validation, and reproducibility is explored across pipeline sample sizes.</div></div><div><h3>Comparison with existing methods</h3><div>Large multiverse analyses in neuroimaging typically rely on sampling, but sampling approaches are not often systematically compared for their representation of the full multiverse.</div></div><div><h3>Conclusions</h3><div>The need for representative pipeline sampling to mitigate bias in large multiverse analyses is discussed.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110564"},"PeriodicalIF":2.3,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145040487","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":"Deep feature extraction and swarm-optimized enhanced extreme learning machine for motor imagery recognition in stroke patients","authors":"Vaishali R. Shirodkar ,&nbsp;Damodar Reddy Edla ,&nbsp;Annu Kumari ,&nbsp;Ramesh Dharavath","doi":"10.1016/j.jneumeth.2025.110565","DOIUrl":"10.1016/j.jneumeth.2025.110565","url":null,"abstract":"<div><h3>Background:</h3><div>Interpretation of motor imagery (MI) in brain–computer interface (BCI) applications is largely driven by the use of electroencephalography (EEG) signals. However, precise classification in stroke patients remains challenging due to variability, non-stationarity, and abnormal EEG patterns.</div></div><div><h3>New methods:</h3><div>To address these challenges, an integrated architecture is proposed, combining multi-domain feature extraction with evolutionary optimization for enhanced EEG-based MI classification. The approach begins with subject-specific frequency band selection based on event-related desynchronization (ERD), aimed at reducing non-stationarity and improving signal relevance. Spatial and temporal features are then extracted using a combination of the scale-invariant feature transform (SIFT) and a one-dimensional convolutional neural network (1D CNN), providing a comprehensive representation of EEG signal dynamics. These features are fused and classified using an enhanced extreme learning machine (EELM), with hidden layer weights optimized using differential evolution (DE), particle swarm optimization (PSO), and dynamic multi-swarm PSO (DMS-PSO).</div></div><div><h3>Results:</h3><div>Experimental validation on a dataset of 50 stroke patients demonstrated an average classification accuracy of 97% using DMS-PSO with 10-fold cross-validation. Additional evaluation on the BCI Competition IV 1a dataset yielded 95% and 91.56% on IV 2a, indicating strong generalization performance.</div></div><div><h3>Comparison with existing methods:</h3><div>Unlike conventional BCI approaches, this method combines adaptive filtering, spatial–temporal hybrid feature learning, and metaheuristic optimization, resulting in a lightweight model with improved classification accuracy and robustness.</div></div><div><h3>Conclusion:</h3><div>These findings demonstrate the effectiveness of evolutionary optimization in dealing with the constraints provided by high-dimensional, non-stationary EEG data, making it a promising strategy for real-time MI classification in BCI-based stroke applications.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110565"},"PeriodicalIF":2.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027314","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":"Assessing adult zebrafish despair-like behaviors in the small vertical cylinder immobility test (VCIT)","authors":"Jiyi Wang ,&nbsp;Vea Bley ,&nbsp;Jiayou Jiang ,&nbsp;Yunqian Zhang ,&nbsp;Yixing Qin ,&nbsp;Haoyu Feng ,&nbsp;Yucheng Liu ,&nbsp;Ruiyu Li ,&nbsp;Chaoming Wang ,&nbsp;Shulei He ,&nbsp;Gan Wang ,&nbsp;Kai He ,&nbsp;Huiling Cai ,&nbsp;Yuxiang Jia ,&nbsp;Chongguang Zhao ,&nbsp;Yingze Wang ,&nbsp;Jiahao Cui ,&nbsp;Longen Yang ,&nbsp;Adam Michael Stewart ,&nbsp;Murilo S. de Abreu ,&nbsp;Allan V. Kalueff","doi":"10.1016/j.jneumeth.2025.110569","DOIUrl":"10.1016/j.jneumeth.2025.110569","url":null,"abstract":"<div><h3>Background</h3><div>Affective disorders represent a major global health burden. Animal models are widely used for modeling brain disorders and neuroactive drug discovery. A novel powerful tool in translational neuroscience research, zebrafish (<em>Danio rerio</em>) provide multiple behavioral assays relevant to anxiety-like and depression-related conditions (including despair-like behavior, a common feature in depression).</div></div><div><h3>New method</h3><div>Here, we introduce a novel behavioral paradigm for assessing zebrafish locomotion and despair-like phenotypes, the small 5-mL glass vertical cylinder immobility test (VCIT). Conceptually similar to rodent and other zebrafish ‘despair’-like models, the VCIT protocol is based on restricting fish locomotion vertically for 5 min in head-first position, to assess their locomotion and despair-like immobility.</div></div><div><h3>Results</h3><div>The test was sensitive to acute and chronic stressors that increased immobility duration (alarm pheromone, net chasing, chronic sleep deprivation and 12-week unpredictable stress), as well as to bidirectional modulation of zebrafish behavior by various acute and chronic neuroactive drugs. The VCIT immobility was reduced by psychostimulants nicotine and arecoline, as well as a conventional antidepressant fluoxetine. In contrast, the immobility in this test was increased by a pro-depressant dopamine-depleting drug reserpine, and remained unaltered by an anxiolytic agent ethanol or anxiogenic drugs caffeine and GBR-12909 (vanoxerine).</div></div><div><h3>Comparisons with existing method(s)</h3><div>The VCIT provides an easy-to-perform, minimally invasive, non-traumatic, and procedurally simpler and faster model of assessing zebrafish stress-evoked despair-like phenotypes.</div></div><div><h3>Conclusions</h3><div>The VCIT is sensitive to various stress-related manipulations and bidirectional pharmacological modulation, hence emphasizing the growing relevance and potential of zebrafish in advancing neuropsychiatric research and identifying innovative treatments for neuropsychiatric disorders.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110569"},"PeriodicalIF":2.3,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145029447","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 comparison of transduction efficiency of medial septal neurons by adeno-associated viruses with three promoters","authors":"Alena A. Koryagina ,&nbsp;Yulia V. Dobryakova ,&nbsp;Konstantin A. Gerasimov ,&nbsp;Ghofran Alhalabi ,&nbsp;Alexandr A. Moshchenko ,&nbsp;Vsevolod V. Belousov ,&nbsp;Alexey P. Bolshakov","doi":"10.1016/j.jneumeth.2025.110570","DOIUrl":"10.1016/j.jneumeth.2025.110570","url":null,"abstract":"<div><h3>Background</h3><div>Most researchers rely on popular promoters like the synthetic CAG promoter or human synapsin promoter to transduce various brain neurons. However, their effectiveness in transducing forebrain cholinergic neurons remains unclear.</div></div><div><h3>New method</h3><div>We compared efficacy of transduction of cholinergic neurons and parvalbumin-positive neurons in the medial septal area of rats and mice by adeno-associated viruses (AAVs) carrying the green fluorescent protein (GFP) marker gene under three distinct promoters—CAG, synapsin, and the mouse choline acetyltransferase (<em>CHAT</em>) promoter.</div></div><div><h3>Results</h3><div>In mice and rats, the CAG and synapsin promoters demonstrated extremely low efficacy for GFP expression in CHAT+ neurons but were effective for transducing PV+ neurons. The <em>CHAT</em> promoter yielded moderate GFP expression in cholinergic neurons in mice, with negligible expression in PV+ neurons, though it also led to off-target expression in other cell types. In rats, the <em>CHAT</em> promoter produced moderate GFP expression in both cholinergic and PV+ neurons; however, the majority of GFP-expressing cells were unrelated to these specific neuronal subtypes.</div><div>Comparison with existing methods: Contrary to expectations, human synapsin and CAG promoters provided negligible expression in cholinergic septal neurons in both rats and mice.</div></div><div><h3>Conclusions</h3><div>The mouse <em>CHAT</em> promoter is significantly more effective for cholinergic neuron expression in rats and mice compared to universal neuronal promoters like CAG and synapsin promoter.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110570"},"PeriodicalIF":2.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145015623","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}