Journal of Neuroscience Methods最新文献

{"title":"EEG-based fatigue state evaluation by combining complex network and frequency-spatial features","authors":"Kefa Wang,&nbsp;Xiaoqian Mao,&nbsp;Yuebin Song,&nbsp;Qiuyu Chen","doi":"10.1016/j.jneumeth.2025.110385","DOIUrl":"10.1016/j.jneumeth.2025.110385","url":null,"abstract":"<div><h3>Background</h3><div>The proportion of traffic accidents caused by fatigue driving is increasing year by year, which has aroused wide concerns for researchers. In order to rapidly and accurately detect drivers' fatigue, this paper proposed an electroencephalogram (EEG)-based fatigue state evaluation method by combining complex network and frequency-spatial features.</div></div><div><h3>New method</h3><div>First, this paper constructed a complex network model based on the relative wavelet entropy to characterize the correlation strength information between channels. Then, the differential entropy and symmetry quotient were respectively calculated to extract frequency and spatial features. Then, the brain heat map combined the complex network and frequency-spatial features with different dimensions together as the fusion features. Finally, a convolutional neural network-long short-term memory (CNN-LSTM) neural network was used to evaluate the three-class fatigue states of the EEG data in the Shanghai Jiao Tong University (SJTU) Emotion EEG Dataset (SEED)-VIG dataset, and it was validated on the dataset on the Mendeley Data website.</div></div><div><h3>Results</h3><div>The experimental results of SEED-VIG dataset show that the average classification accuracy of three-class fatigue states, namely, awake, tired and drowsy, reaches 96.57 %. The average classification accuracy on the dataset on the Mendeley Data website reaches 99.23 %.</div></div><div><h3>Comparison with existing methods</h3><div>This method has a best evaluation performance compared with the state-of-the-art methods for the three-class fatigue states recognition.</div></div><div><h3>Conclusions</h3><div>The experiment results validated the feasibility of the fatigue state evaluation method based on the correlations between channels and the frequency-spatial features, which is of great significance for developing a driver fatigue detection system.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110385"},"PeriodicalIF":2.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255909","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":"Latency correction in sparse neuronal spike trains with overlapping global events","authors":"Arturo Mariani ,&nbsp;Federico Senocrate ,&nbsp;Jason Mikiel-Hunter ,&nbsp;David McAlpine ,&nbsp;Barbara Beiderbeck ,&nbsp;Michael Pecka ,&nbsp;Kevin Lin ,&nbsp;Thomas Kreuz","doi":"10.1016/j.jneumeth.2025.110378","DOIUrl":"10.1016/j.jneumeth.2025.110378","url":null,"abstract":"<div><h3>Background:</h3><div>In Kreuz et al., J Neurosci Methods 381, 109703 (2022) two methods were proposed that perform latency correction, i.e., optimize the spike time alignment of sparse neuronal spike trains with well-defined global spiking events. The first one based on direct shifts is fast but uses only partial latency information, while the other one makes use of the full information but relies on the computationally costly simulated annealing. Both methods reach their limits and can become unreliable when successive global events are not sufficiently separated or even overlap.</div></div><div><h3>New Method:</h3><div>Here we propose an iterative scheme that combines the advantages of the two original methods by using in each step as much of the latency information as possible and by employing a very fast extrapolation direct shift method instead of the much slower simulated annealing.</div></div><div><h3>Results:</h3><div>We illustrate the effectiveness and the improved performance, measured in terms of the relative shift error, of the new iterative scheme not only on simulated data with known ground truths but also on single-unit recordings from two medial superior olive neurons of a gerbil.</div></div><div><h3>Comparison with Existing Method(s):</h3><div>The iterative scheme outperforms the existing approaches on both the simulated and the experimental data. Due to its low computational demands, and in contrast to simulated annealing, it can also be applied to very large datasets.</div></div><div><h3>Conclusions:</h3><div>The new method generalizes and improves on the original method both in terms of accuracy and speed. Importantly, it is the only method that allows to disentangle global events with overlap.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110378"},"PeriodicalIF":2.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143080359","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":"Integrating neuroscience and artificial intelligence: EEG analysis using ensemble learning for diagnosis Alzheimer’s disease and frontotemporal dementia","authors":"Amir Hossein Hachamnia ,&nbsp;Ali Mehri ,&nbsp;Maryam Jamaati","doi":"10.1016/j.jneumeth.2025.110377","DOIUrl":"10.1016/j.jneumeth.2025.110377","url":null,"abstract":"<div><h3>Background:</h3><div>Alzheimer’s disease (AD) and frontotemporal dementia (FTD) are both progressive neurological disorders that affect the elderly. Distinguishing between individuals suffering from these two diseases in the early stages can be quite challenging, and due to their different treatments, it has become an important problem. Machine learning (ML) algorithms can be helpful in this matter due to their high ability to manage large data and deliver high-quality diagnostic results.</div></div><div><h3>New method:</h3><div>In this research, we integrate multiple ML algorithms into 10 ensemble learning techniques, utilizing 7 distinct features: 3 from the time domain and 4 from the frequency domain.</div></div><div><h3>Results:</h3><div>They are used to achieve a higher diagnostic accuracy level in binary and multiclass classification of samples from electroencephalography (EEG) signals of elderly patients with AD, FTD, and healthy age-matching controls (CN), during the eye resting state.</div></div><div><h3>Comparison with existing methods:</h3><div>The best results in carrying out binary AD/CN, FTD/CN, and AD/FTD classifications with significant accuracy<span><math><mo>&gt;</mo></math></span>95% have been obtained with the help of the light gradient boosting machine (LGBM) method applying the wavelet transform feature.</div></div><div><h3>Conclusion:</h3><div>This combination (LGBM&amp;wavelet) also displays the best performance in the AD/FTD/CN multiclass classification process with accuracy<span><math><mo>&gt;</mo></math></span>93%.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110377"},"PeriodicalIF":2.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143080357","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":"Developing a predictive value for predicting stroke recovery based on transcranial doppler ultrasound parameters","authors":"Liu Yang,&nbsp;Xinyi Cai,&nbsp;Yanhong Yan,&nbsp;Pinjing Hui","doi":"10.1016/j.jneumeth.2025.110383","DOIUrl":"10.1016/j.jneumeth.2025.110383","url":null,"abstract":"<div><h3>Background</h3><div>One of the leading causes of disability and death is acute ischemic stroke (AIS) brought on by middle cerebral artery (MCA) obstruction. For the best patient care, it is essential to accurately anticipate the functional prognosis in the early stages of stroke. The ability of conventional clinical evaluations and imaging methods to deliver precise and timely prognostic information is frequently limited.</div></div><div><h3>New method</h3><div>In this work, a predictive value for predicting functional outcome in patients with acute ischemic stroke caused by MCA blockage was developed utilizing transcranial Doppler (TCD) ultrasonography characteristics. Within 24 h after intravenous thrombolysis (IVT), TCD measures such as pulsatility index (PI), mean flow velocity (Vm), end-diastolic velocity (EDV), and peak systolic velocity (PSV) were assessed. Independent determinants of functional outcome, as determined by the modified Rankin Scale (mRS), were found using logistic regression analysis. These important factors were used to create a prediction model.</div></div><div><h3>Comparison with existing methods</h3><div>Favorable functional outcomes were substantially correlated with a number of TCD characteristics, such as the ratio of pulsatility index to mean flow velocity (rPI) and peak systolic velocity to end-diastolic velocity (rPSV). At three months after a stroke, a logistic regression model that included these measures together with additional clinical indicators showed excellent accuracy in predicting functional prognosis.</div></div><div><h3>Conclusion</h3><div>In individuals who have experienced an acute ischemic stroke as a result of MCA blockage, TCD ultrasonography parameters—in particular, rPSV and rPI—are useful prognostic indicators for forecasting functional prognosis. Early risk classification and individualized treatment plans can benefit from the creation of a quantitative model based on these criteria. Validating and improving this model in bigger and more varied patient groups should be the goal of future research.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110383"},"PeriodicalIF":2.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074816","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":"Intra-rater reliability and validity of neuro-mobinavigation: A mobile app and laser-guided system of motor HotSpot localization","authors":"Hussein Youssef ,&nbsp;Ali Emre Öge ,&nbsp;Koen Cuypers ,&nbsp;Atay Vural","doi":"10.1016/j.jneumeth.2025.110374","DOIUrl":"10.1016/j.jneumeth.2025.110374","url":null,"abstract":"<div><h3>Background</h3><div>Optimal transcranial magnetic stimulation (TMS) efficacy depends on precise coil placement and orientation, as even minor deviations can significantly change the excitation evoked when stimulating the primary motor cortex (M1). To compare the intra-rater reliability of a novel method for consistent TMS coil orientation over a predetermined hotspot in M1, and to benchmark its accuracy against non-navigated method.</div></div><div><h3>New method</h3><div>A three-step method was employed. First, a laser-guided-system stabilized head position. Second, a mobile-app monitored coil tilt and orientation. Finally, coil position was marked on participant's head cap for visual reference for both methods. Twenty-nine healthy-participants underwent six TMS blocks of 20 pulses each. Six experimental blocks, alternating between non-navigated-TMS and Neuro-Mobinavigated-TMS, to investigate the parameters of motor evoked potential (MEP). The experimental blocks were quasi-randomized with a five-minute interval.</div></div><div><h3>Results and comparison with existing method(s)</h3><div>The novel method demonstrated excellent intra-rater reliability (ICC = 0.95, 95 % CI: 0.90–0.97) compared to moderate intra-rater reliability of the non-navigated TMS (ICC = 0.73, 95 % CI: 0.57–0.85) for MEP peak amplitude. Repeated measures ANOVA for novel-method showed consistent peak amplitude across three blocks (p = 0.078), non-navigated TMS exhibited significant variations (p &lt; 0.0001). Wilcoxon signed rank test revealed significantly higher mean peak amplitudes for the novel method (1.02 ± 0.74) compared to non-navigated TMS (0.78 ± 0.61) (p &lt; 0.001), small effect size (r = 0.35).</div></div><div><h3>Conclusions</h3><div>Neuro-Mobinavigation is superior to non-navigated method and provides a reliable and cost-effective alternative for MEP studies where gold standard neuronavigation is not available.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110374"},"PeriodicalIF":2.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074767","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":"Does intra-epidermal electrical stimulation activate mechano- and thermo-nociceptors? A discrimination approach","authors":"S.U. Júlio ,&nbsp;M. Schneuwly ,&nbsp;P.S. Scheuren ,&nbsp;M. Hubli ,&nbsp;M. Schubert","doi":"10.1016/j.jneumeth.2025.110382","DOIUrl":"10.1016/j.jneumeth.2025.110382","url":null,"abstract":"<div><h3>Background</h3><div>Objective laboratory tests are needed to diagnose lesions within the nociceptive system accurately. One approach is assessing pain-related evoked potentials (PREPs) in response to intra-epidermal electrical stimulation (IES). In this context, peripheral characterization of the specificity of nociceptor activation with IES is needed.</div></div><div><h3>New Method</h3><div>As IES directly depolarizes free nerve endings, it might allow a more comprehensive nociceptor activation than classical contact heat stimulation. Hence, this study aimed to investigate whether mechano-nociceptors are activated by IES. To test this hypothesis, a heat pain model was used to assess whether IES would show comparable pain hypersensitivity in the experimentally-induced area of secondary mechanical hyperalgesia (SMH), as known for pinprick but not for contact heat stimuli. Pain ratings and PREPs were recorded in response to 15 contact heat and pinprick stimuli as well as IES applied to the volar forearm before (PRE) and after (POST) a heat pain model inducing an area of SMH (EXP) or a control model (CTRL).</div></div><div><h3>Results and Comparison with Existing Methods</h3><div>All 24 participants (25.5 ± 4.7 y, 10 f/14 m) presented with SMH in POST-EXP condition. Pain ratings were significantly increased in EXP versus CTRL for IES (p = 0.016) and pinprick (p = 0.006) but not for contact heat (p = 0.683). PREP NP-amplitude between EXP and CTRL was only increased in response to pinprick (p = 0.027), but not to IES (p = 0.547) and contact heat stimuli (p = 0.070).</div></div><div><h3>Conclusions</h3><div>Psychophysical assessments suggest mechano-nociceptor activation by IES, while PREPs do not support this assumption, indicating the predominant activation of thermo-nociceptors by IES.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110382"},"PeriodicalIF":2.7,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074855","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":"Ramp protocol for non-linear cerebrovascular reactivity with transcranial doppler ultrasound","authors":"Genevieve Hayes,&nbsp;Sierra Sparks,&nbsp;Joana Pinto,&nbsp;Daniel P. Bulte","doi":"10.1016/j.jneumeth.2025.110381","DOIUrl":"10.1016/j.jneumeth.2025.110381","url":null,"abstract":"<div><h3>Background</h3><div>Cerebrovascular reactivity (CVR) reflects the ability of cerebral blood vessels to adjust their diameter in response to vasoactive stimuli, which is crucial for maintaining brain health. Traditional CVR assessments commonly use a two-point measurement, assuming a linear relationship between cerebral blood flow (CBF) and arterial CO₂. However, this approach fails to capture non-linear characteristics, particularly the plateaus at extreme CO₂ levels.</div></div><div><h3>New method</h3><div>This study introduces a cost-effective, ramp-based end-tidal CO₂ (PETCO₂) protocol to assess non-linear aspects of CVR. Using transcranial Doppler ultrasound, we monitored blood velocity responses to progressive increases in arterial CO₂ levels in eleven healthy adults, covering a spectrum from hypocapnia to hypercapnia.</div></div><div><h3>Results</h3><div>All eleven participants successfully completed the protocol, with an average PETCO₂ range of 26 ± 4 mmHg and blood velocity changes from −29 % to + 50 % relative to baseline. Non-linear CVR characteristics were observed in all subjects. Sigmoid models provided significantly better fits to the CVR data than linear models, while Bayesian approaches followed expected physiological ranges more accurately than least squares regression methods.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike traditional CVR methods, this ramp protocol captures the full, non-linear CVR profile. The sigmoid modeling approach offers a more accurate representation of cerebrovascular dynamics, particularly at CO₂ extremes.</div></div><div><h3>Conclusions</h3><div>The PETCO₂ ramp protocol with non-linear CVR modeling shows promise as an accessible and reliable tool for assessing CBF dynamics. With high completion rates, straightforward implementation, and low equipment cost, this approach holds significant potential for clinical applications in cerebrovascular health evaluation.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110381"},"PeriodicalIF":2.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143065635","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":"Predictive models of clinical outcome of endovascular treatment for anterior circulation stroke using machine learning","authors":"Bogey Clement ,&nbsp;Rouchaud Aymeric ,&nbsp;Gentric Jean-Christophe ,&nbsp;Beaufreton Edouard ,&nbsp;Timsit Serge ,&nbsp;Clarencon Frederic ,&nbsp;Caroff Jildaz ,&nbsp;Bourcier Romain ,&nbsp;Zhu François ,&nbsp;Dargazanli Cyril ,&nbsp;Hak Jean-François ,&nbsp;Boulouis Gregoire ,&nbsp;Ifergan Heloise ,&nbsp;Pop Raoul ,&nbsp;Forestier Geraud ,&nbsp;Lapergue Bertrand ,&nbsp;Ognard Julien ,&nbsp;Etis Investigators","doi":"10.1016/j.jneumeth.2025.110376","DOIUrl":"10.1016/j.jneumeth.2025.110376","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Mechanical Thrombectomy (MT) has recently become the standard of care for anterior circulation stroke with large vessel occlusion, but predictive factors of successful MT are still not clearly defined. To tailor treatment individually for each patient, the aim of this study was to evaluate the performances of Machine Learning to predict clinical outcome (mRS) at 3 months after MT.</div></div><div><h3>Material and methods</h3><div>From the ETIS French prospective multicenter registry, data from patients who underwent MT for anterior circulation stroke with large vessel occlusion between January 2018 and December 2020 were extracted. Three machine learning models (Support Vector Machine, Random Forest and XGBoost) have been trained with clinical, biological and brain imaging data available in emergency conditions from the cohort of patients treated from 2018 to 2019. Models’ performances to predict good outcome (3-months mRS &lt;3) were evaluated on patients treated in 2020. Performances were evaluated with AUC, accuracy, sensitivity and specificity, then ROC curves AUC were compared with the best performing model.</div></div><div><h3>Results</h3><div>4297 patients were included, 1737 (40 %) with good outcome and 2560 (60 %) with bad outcome were used to train models and 599 patients treated in 2020 were used to evaluate their performances. The best model was obtained with <em>XGBoost: A</em>UC = 0.77, accuracy = 69.3 % but no statistically significant difference existed between models.</div></div><div><h3>Conclusion</h3><div>Our study shows satisfying performances of machine learning to predict clinical outcome after MT using data easily available at initial diagnosis and before the decision to treat.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110376"},"PeriodicalIF":2.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143065583","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":"Identifying autism spectrum disorder based on machine learning for multi-site fMRI","authors":"Li Kang ,&nbsp;Mubin Chen ,&nbsp;Jianjun Huang ,&nbsp;Jinyang Xu","doi":"10.1016/j.jneumeth.2025.110379","DOIUrl":"10.1016/j.jneumeth.2025.110379","url":null,"abstract":"<div><h3>Background</h3><div>Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by repetitive stereotypical behavior and social impairment. Early diagnosis is essential for developing a treatment plan for autism. Although multi-site data can expand the dataset to facilitate the process of data analysis, data heterogeneity between sites and the large amount of data make data analysis difficult.</div></div><div><h3>Method</h3><div>To address these issues, this paper proposes a multi-site autism identification method based on machine learning technique. Firstly, the fMRI data from all sites are converted into a glass brain dataset and their features are extracted with LeNet5. Then, the extracted glass brain features are used to construct a partial correlation matrix at subject-level and the multi-site dataset are constructed by feature selection, which is finally classified using MLP. In order to alleviate the heterogeneity of the data and improve the accuracy of data classification, a new dataset partitioning method, Split-Merge-Split (SMS), is proposed in this paper to reduce the variability between the features extracted by the model in the training and test sets.</div></div><div><h3>Results</h3><div>Extensive quantitative and qualitative evaluations demonstrate the proposed method enhanced the recognition accuracy on both single-site and multi-site dataset, which shows the effectiveness of this method. Specifically, in single-site classification, our method achieved its highest accuracy at the OHSU site, reaching an accuracy of 93 %. In multi-site classification, our method attained an accuracy of 83.5 %.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110379"},"PeriodicalIF":2.7,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059206","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 behavioral screening method for predicting PTSD-like phenotypes: Novel application to female rats","authors":"Giulia Chiacchierini ,&nbsp;Giulia Federica Mancini ,&nbsp;Benedetta Di Cesare ,&nbsp;Luca Romanelli ,&nbsp;Maria Morena ,&nbsp;Patrizia Campolongo","doi":"10.1016/j.jneumeth.2025.110380","DOIUrl":"10.1016/j.jneumeth.2025.110380","url":null,"abstract":"<div><h3>Background</h3><div>Only a small percentage of trauma-exposed subjects develop PTSD, with females being twice as likely. Most rodent models focus on males and fail to account for inter-individual variability in females.</div></div><div><h3>New method</h3><div>We tested a behavioral PTSD model in female rats to distinguish between susceptible and resilient individuals. In Experiment 1, female rats underwent footshocks paired with social isolation, a PTSD risk factor. They were re-exposed to the conditioned context to test memory retention, and assessed in the Elevated Plus Maze (EPM) and Social Interaction (SI) tests for anxiety and social behavior.</div></div><div><h3>Results</h3><div>Footshock-exposed rats showed fear memory retention up to 16 days, indicated by elevated freezing behavior during re-exposure. They also exhibited reduced exploration in the EPM and less SI time compared to controls. In Experiment 2, we classified rats into normal responders, susceptible, and resilient groups based on locomotor activity after trauma, correlating with memory retention and anxiety.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike existing models focused on males and lacking predictive variables before trauma, our method identifies PTSD-like susceptibility and resilience in female rats by using exploratory behavior as a predictor before trauma exposure.</div></div><div><h3>Conclusions</h3><div>Exploratory activity in a novel environment after trauma and before extinction is a reliable predictor of PTSD-like phenotypes and differentiates between susceptible and resilient female rats.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"416 ","pages":"Article 110380"},"PeriodicalIF":2.7,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059199","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}