Journal of Neuroscience Methods最新文献

{"title":"Neuroimaging of reality: A new approach for investigating neural bases of decision-making with real-world objects","authors":"Damien Gabriel ,&nbsp;Guillaume Bertrand ,&nbsp;Magali Nicolier ,&nbsp;Julie Giustiniani","doi":"10.1016/j.jneumeth.2026.110692","DOIUrl":"10.1016/j.jneumeth.2026.110692","url":null,"abstract":"<div><h3>Background</h3><div>Neuroimaging studies often use computerized tasks, but reliance on virtual stimuli limits ecological validity. Incorporating real object interaction under controlled recording conditions may enhance the study of decision-making processes.</div></div><div><h3>New method</h3><div>We developed Lab-Life, a device enabling manipulation of real objects while ensuring precise monitoring and compatibility with electrophysiological recordings. Forty-four right-handed healthy volunteers performed two decision-making tasks: the Iowa Gambling Task (IGT, real vs. virtual cards) and the Game of Dice Task (GDT, real vs. virtual dice). Twenty-two participants (11 per task) used Lab-Life (hybrid condition), while additional virtual task groups were included to illustrate typical behavioral and EEG signatures. Object identity and values were tracked with infrared cameras, and EEG was recorded to analyze event-related potentials (ERPs) to outcomes.</div></div><div><h3>Results</h3><div>Behavioral analyses showed perfect concordance between expected and detected object values in hybrid condition, validating Lab-Life’s automated object recognition. EEG analyses revealed comparable numbers of valid trials and similar ERP patterns between hybrid and virtual task conditions, indicating that the device does not introduce movement artifacts. Participants consistently reported higher enjoyment when manipulating real compared to virtual objects.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike conventional paradigms relying solely on virtual stimuli, Lab-Life integrates real objects without compromising behavioral or electrophysiological data quality. The device allows precise temporal synchronization between object manipulation and EEG recordings while preserving experimental control.</div></div><div><h3>Conclusions</h3><div>Lab-Life is a validated methodological tool for combining behavioral and electrophysiological measures with real object manipulation. It offers a flexible and adaptable platform for decision-making, memory, or perceptual tasks, thereby bridging the gap between laboratory experiments and real-life conditions. Larger studies are warranted to further explore its impact on cognitive performance.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110692"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025589","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":"Micromap: A low-cost multi-channel electrophysiology acquisition system","authors":"João Pedro Carvalho-Moreira ,&nbsp;Luiz Felipe Nogueira Varandas ,&nbsp;Matheus Costa Passos ,&nbsp;Márcio Flávio Dutra Moraes","doi":"10.1016/j.jneumeth.2026.110691","DOIUrl":"10.1016/j.jneumeth.2026.110691","url":null,"abstract":"<div><h3>Objective</h3><div>To develop an accessible, low-cost, and open-source system for multi-channel electrophysiological recordings across multiple brain regions, facilitating the investigation of neural dynamics and information flow in long-range integration. Approach: We designed a digital signal acquisition system that integrates two programmable analog-to-digital converter chipsets -- Intan RHD and Texas Instruments ADS -- with an Arduino-based microcontroller. In addition, we introduce a custom-designed headstage and a methodology for spatially distributed electrode placement using a perforated printed circuit board, which interfaces directly with the system to enable local field potential recordings from multiple brain regions. The system successfully recorded biopotentials without significant sample loss and performed comparably to gold-standard systems, enabling recordings across 32 channels at a 2 kHz sampling frequency. We verified signal integrity and stability under both experimental and simulated conditions, confirming the platform’s suitability for electrophysiology. Main results: We present a comprehensive, low-cost bioengineering solution for distributed electrophysiological recordings, enabling detailed investigation of brain dynamics through synchronized neural activity across regions. Significance: This open-source platform enables neuroscience laboratories to investigate large-scale neural interactions with high temporal precision, expanding access to systems neuroscience tools essential for understanding interregional brain connectivity.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110691"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994270","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":"OpenIrisDPI: An open-source digital dual Purkinje image eye tracker for visual neuroscience","authors":"Ryan A. Ressmeyer ,&nbsp;Jorge Otero-Millan ,&nbsp;Gregory D. Horwitz ,&nbsp;Jacob L. Yates","doi":"10.1016/j.jneumeth.2026.110693","DOIUrl":"10.1016/j.jneumeth.2026.110693","url":null,"abstract":"<div><h3>Background</h3><div>Video-based eye trackers are widely used in vision science, psychology, clinical assessment, and neurophysiology. Many such systems track the pupil center and corneal reflection (P-CR) and compare their positions to estimate the direction of gaze. However, P-CR eye trackers are often too imprecise for applications with stringent eye tracking quality requirements.</div></div><div><h3>New method</h3><div>We present OpenIrisDPI, an open-source plugin for the OpenIris framework that implements dual Purkinje image (DPI) tracking. OpenIrisDPI supports simultaneous pupillography, a technique widely used in perceptual psychology and neuroscience, and it enables direct comparison between P-CR and DPI signals.</div></div><div><h3>Results</h3><div>Data collected from macaque monkeys using OpenIrisDPI show that the P-CR method overestimates the amount of fixational drift between saccades compared to DPI. The accuracy of the DPI signal was further validated using high-density extracellular recording of neurons in the lateral geniculate nucleus. Compensating for the effects of fixational eye movements using DPI signals produced sharper estimates of neuronal receptive fields than using simultaneously collected P-CR signals.</div></div><div><h3>Comparison with existing methods</h3><div>OpenIrisDPI is provided as open-source software and operates on consumer-grade hardware, making it more accessible than previously described DPI eye trackers and less costly than many P-CR systems. To our knowledge, OpenIrisDPI is the first eye tracker to perform both pupillography and DPI eye tracking.</div></div><div><h3>Conclusion</h3><div>OpenIrisDPI makes high-precision eye tracking readily available to the research community. It is well suited for visual neuroscience applications, where accurate knowledge of the retinal image during experiments is critical.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110693"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046760","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":"Artificial intelligence and machine learning driven nanorobotics for targeted brain delivery: Redefining blood-brain barrier navigation","authors":"Suraj Kumar ,&nbsp;Rishabha Malviya ,&nbsp;Sathvik Belagodu Sridhar ,&nbsp;Tarun Wadhwa ,&nbsp;Javedh Shareef","doi":"10.1016/j.jneumeth.2026.110695","DOIUrl":"10.1016/j.jneumeth.2026.110695","url":null,"abstract":"<div><div>The blood-brain barrier (BBB) plays a central role in preserving central nervous system (CNS) homeostasis, and its dysfunction is implicated in various neurological disorders and brain malignancies. To emulate the complex architecture and signaling environment of the BBB, researchers have developed advanced <em>in vitro</em> models incorporating three-dimensional (3D) cell cultures, organoid technologies, and microfluidic platforms. These innovations have significantly expanded the scope of neuropharmacological research, particularly in understanding BBB transport mechanisms and enhancing drug delivery strategies. The following review highlights the integration of biomolecular tools and nanomaterial-based engineering approaches to facilitate the targeted delivery of theranostic agents across the BBB. Specifically, it discusses the emerging role of nanorobots and nanosystems in mediating cellular interactions that enable precise modulation and penetration of the barrier. Case studies addressing therapeutic applications in brain tumors and cognitive dysfunctions are also evaluated. Moreover, the review explores the intersection of artificial intelligence (AI), machine learning (ML), and robotics, which together offer transformative potential in designing intelligent nanorobots capable of efficient and safe BBB traversal. Collectively, this work serves as a consolidated resource for clinicians, biomedical scientists, and technologists aiming to develop innovative strategies for BBB-targeted therapies and biopharmaceutical applications.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110695"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025588","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":"Advances in rodent oligodendrocyte precursor cells isolation and culture: From traditional methods to modern approaches","authors":"Hoda Akbari,&nbsp;Iraj Ragerdi Kashani,&nbsp;Farzaneh Rezaei Yazdi,&nbsp;Parichehr Pasbakhsh,&nbsp;Sina Mojaverrostami","doi":"10.1016/j.jneumeth.2026.110706","DOIUrl":"10.1016/j.jneumeth.2026.110706","url":null,"abstract":"<div><h3>Introduction</h3><div>Oligodendrocyte progenitor cells (OPCs) are responsible for the generation of myelinating oligodendrocytes and are essential for myelination and repair of the central nervous system (CNS). In past decades, many methods have been presented for the reliable isolation and culture of OPCs to facilitate research into oligodendroglial biology and the development of effective therapeutic strategies such as cell transplantation and drug therapy in demyelinating and neurodegenerative diseases. However, challenges of purity, yield, and phenotypic stability still persist for each method.</div></div><div><h3>Methods</h3><div>A literature review was conducted using related keywords in the Scopus, Google Scholar, PubMed, and PubMed/Medline databases from the date of beginning until 1 November 2025. We examined preclinical research in rodent models that fit our search parameters, including in vitro and in vivo rat or mouse models, for both neonatal and adult CNS studies.</div></div><div><h3>Results</h3><div>This review systematically describes the methodological progress of OPC isolation from mechanical isolation methods to advanced immunopanning culture systems, magnetic-activated cell sorting (MACS), and serum-free or growth factor-based culture systems. Additionally, it mentions important novel methods, like 3D or normoxic culture models, that have improved cell purity, function, and physiological relevance.</div></div><div><h3>Discussion</h3><div>This article compares the principles, advantages, and disadvantages of each method to create a single set of guidelines for selecting the best methods regarding the equipment and goals of an investigation. It also suggests ways to design OPC isolation systems that are more standardized, scalable, and ethically acceptable, which may accelerate in the use of these systems in regenerative neuroscience.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110706"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146157406","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 multimodal depression recognition method based on EEG-fNIRS-SDS","authors":"Yuan Tang ,&nbsp;Youhai Li ,&nbsp;Rui Yi ,&nbsp;Yanxin Mu ,&nbsp;Maoyue Lu ,&nbsp;Binlu Deng ,&nbsp;Xia Deng","doi":"10.1016/j.jneumeth.2025.110668","DOIUrl":"10.1016/j.jneumeth.2025.110668","url":null,"abstract":"<div><h3>Background:</h3><div>Traditional depression diagnosis relies heavily on clinical interviews and subjective questionnaires, leading to concerns about subjectivity and limited accuracy. While recent advances in multimodal physiological signal analysis (using data such as EEG, fNIRS, and eye-tracking) have shown promise, existing fusion approaches often suffer from inflexible weight allocation, feature redundancy, and inadequate cross-modal interaction.</div></div><div><h3>New method:</h3><div>We propose a novel Mutual Information Maximization-based Weighted Multimodal Fusion Network (MI-WNet). This network is designed to synergistically analyze EEG, fNIRS, and clinical scale data. Its core innovation lies in leveraging mutual information maximization to automate and optimize modality weighting, effectively filter redundant features, and enhance meaningful cross-modal interactions.</div></div><div><h3>Results:</h3><div>Experimental results demonstrate that the proposed MI-WNet model achieves a high depression recognition accuracy of 95.52% ± 0.42%.</div></div><div><h3>Comparison with existing methods:</h3><div>The model’s performance shows a significant improvement over baseline models that rely on single modalities (EEG, fNIRS, or clinical data alone). This underscores the superiority of our adaptive fusion strategy over traditional methods with fixed weighting schemes.</div></div><div><h3>Conclusions:</h3><div>The MI-WNet framework presents a robust and effective solution for automated depression recognition. By addressing key limitations in existing multimodal fusion techniques, it significantly enhances diagnostic accuracy and paves the way for more objective and data-driven clinical decision support tools.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110668"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel transgenic reporter mouse line of astrocyte-derived small extracellular vesicles for investigating intercellular communication in vivo","authors":"Zhongwu Liu ,&nbsp;Yi Zhang ,&nbsp;Amy Kemper ,&nbsp;Yanfeng Li ,&nbsp;Andrew C. Dudley ,&nbsp;Michael Chopp ,&nbsp;Zheng Gang Zhang","doi":"10.1016/j.jneumeth.2026.110705","DOIUrl":"10.1016/j.jneumeth.2026.110705","url":null,"abstract":"<div><h3>Background</h3><div>Small extracellular vesicles (sEVs) mediate intercellular communication in the central nervous system, regulating processes ranging from homeostatic maintenance to injury repair. Although astrocytes are a major source of sEVs in the brain, in vivo investigation of their endogenous and cell-specific signaling remains technically challenging.</div></div><div><h3>New method</h3><div>To address this limitation, we developed a novel inducible transgenic reporter mouse line, GFAP-CD63-GFP, that enables specific labeling of astrocyte-derived sEVs. The mouse line was generated by crossing GFAP-CreERT2 mice with CD63-emGFPloxP/stop/loxP mice. This system enables Tamoxifen-inducible, astrocyte-specific expression of GFP-tagged CD63, a tetraspanin enriched in sEVs. The model allows visualization and quantification of astrocyte-derived CD63-positive sEVs in vivo.</div></div><div><h3>Results</h3><div>Following Tamoxifen induction, GFP expression was robustly detected in the brain and spinal cord. Immunogold transmission electron microscopy further identified GFP-positive sEVs within neurons, providing ultrastructural evidence of astrocyte-to-neuron vesicle transfer. As a proof-of-concept, ischemic stroke significantly increased astrocyte-derived sEVs in the ipsilesional cerebral hemisphere and the stroke-impaired side of the spinal cord, accompanied by enhanced neuronal endocytosis.</div></div><div><h3>Comparison with existing methods</h3><div>Current approaches rely primarily on in vitro EV isolation or nonspecific membrane dyes. The GFAP-CD63-GFP model enables cell type–specific, temporally controlled, and in situ tracking of astrocyte-derived sEVs.</div></div><div><h3>Conclusions</h3><div>These findings provide the first in vivo demonstration of increased astrocyte-to-neuron sEV communication during post-stroke recovery. The GFAP-CD63-GFP reporter mouse thus provides a powerful platform for investigating astrocyte-derived sEV signaling under both physiological and pathophysiological conditions of the CNS.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110705"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137544","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":"TPCNet: A Temporal Periodicity Convolutional Network for motor imagery EEG decoding in stroke patients","authors":"Junhui Wang,&nbsp;Mingai Li","doi":"10.1016/j.jneumeth.2026.110707","DOIUrl":"10.1016/j.jneumeth.2026.110707","url":null,"abstract":"<div><h3>Background:</h3><div>Stroke caused by vascular rupture or blockage has high incidence and leads to significant disability. Motor imagery (MI) electroencephalogram (EEG) is a promising approach to understanding and addressing stroke-related motor impairments. However, the practical application of EEG-based rehabilitation is hindered by an insufficient understanding of the task-specific features and complex temporal patterns inherent in the EEG signals of stroke patients.</div></div><div><h3>New method:</h3><div>In this study, we collected EEG signals from 24 stroke patients performing four unilateral upper limb MI tasks. Among them, 12 subjects performed forward arm raising and lowering, while the remaining 12 performed lateral arm raising and lowering. Moreover, we propose a Temporal Periodicity Convolutional Network (TPCNet) for EEG-based MI classification. TPCNet consists of a convolutional block for extracting shallow spatiotemporal features, a sliding window structure that ensures consistent action initiation across samples, and a temporal periodicity block for capturing variations in periodic patterns associated with MI tasks.</div></div><div><h3>Results:</h3><div>TPCNet achieved a classification accuracy of 86.53% on the stroke patient MI dataset and 82.21% on the BCI Competition IV 2a dataset (left hand, right hand, feet, and tongue). Gradient-weighted Class Activation Mapping (Grad-CAM) analysis suggests that stroke patients may exhibit longer task-specific MI periodicity than healthy subjects.</div></div><div><h3>Comparison with existing methods:</h3><div>The proposed method achieves superior performance on stroke patient MI tasks and competitive results on public MI datasets involving healthy subjects.</div></div><div><h3>Conclusions:</h3><div>The proposed TPCNet model effectively captures the spatiotemporal features and periodic patterns of EEG signals, leading to enhanced classification accuracy.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"429 ","pages":"Article 110707"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146142763","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":"Neonatal Brain MRI Atlas: current and future","authors":"Haohao Zhai ,&nbsp;Haoran Gao ,&nbsp;Xiaonan Zhuo ,&nbsp;Yazhou Chen ,&nbsp;Xinting Ge ,&nbsp;Yuchuan Qiao","doi":"10.1016/j.jneumeth.2026.110783","DOIUrl":"10.1016/j.jneumeth.2026.110783","url":null,"abstract":"<div><div>Neonatal brain atlases provide essential spatial references for studying early brain development and supporting atlas-based neuroimaging analysis. This paper presents a comprehensive review of the methodological evolution of neonatal brain template construction, which can be broadly categorized into five stages: static atlas generation, iterative groupwise averaging, spatiotemporal atlas modeling, probabilistic and multimodal integration, and deep learning–based data-driven approaches. This evolution reflects a shift in atlas construction strategies—from early linear registration frameworks to population-level nonlinear optimization, dynamic temporal trajectory modeling, and ultimately end-to-end neural network architectures. We discuss how these methodological developments address the rapid physiological changes of the neonatal brain and the challenges associated with MR image acquisition. In addition to reviewing atlas construction strategies, this work also examines commonly used atlas evaluation frameworks and highlights persistent challenges, including anatomical heterogeneity, data scarcity, and limitations in imaging hardware. Finally, future directions are discussed, emphasizing personalized atlas frameworks, generative modeling approaches, and unified benchmarking systems to support more reliable developmental assessment and broader clinical applications of neonatal brain atlases.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"433 ","pages":"Article 110783"},"PeriodicalIF":2.3,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147773963","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":"Feasibility of integrated transcranial doppler ultrasound-near-infrared spectroscopy to measure cerebral haemodynamics in dementia, delirium, and depression (the VESPAR Project): A pilot study.","authors":"Olivia Edwards, Jennifer K Nicholls, Bhavisha Desai, Ronney B Panerai, James D Ball, Yvonne Sensier, Elizabeta Mukaetova-Ladinska, Lucy Beishon","doi":"10.1016/j.jneumeth.2026.110784","DOIUrl":"10.1016/j.jneumeth.2026.110784","url":null,"abstract":"<p><strong>Background: </strong>Transcranial Doppler ultrasonography (TCD) and near-infrared spectroscopy (NIRS) are indirect measures of neurovascular coupling (NVC). No studies have assessed the feasibility of an integrated TCD-NIRS approach to measure NVC in patients with dementia, delirium, and depression.</p><p><strong>New method: </strong>TCD-NIRS was trialled in 10 healthy volunteers, 11 patients with depression, 8 with dementia, and 5 with delirium. Participants underwent continuous cerebral blood velocity measurements, measured from the dominant middle cerebral artery (MCAv) and non-dominant posterior cerebral artery (PCAv), at rest and in response to four cognitive tasks. Heart rate (HR), end-tidal carbon dioxide (EtCO₂), blood pressure (BP), prefrontal oxygenated (HbO₂) and deoxygenated (HbR) haemoglobin levels were measured.</p><p><strong>Results: </strong>Resting mean MCAv differed significantly between groups (healthy volunteers: 53.9 (SD=8.09) cm/s, depression: 41.9 (9.31) cm/s (p = 0.041), dementia: 42.5 (13.7) cm/s, (0.150) delirium: 32.6 (7.48) cm/s (p = 0.002), after correction for age and BP (p = 0.012). There were no significant differences in resting PCAv, BP, EtCO₂, HR, or prefrontal oxygenation. Participants with delirium were unable to complete the task-activated section of the protocol. All four tasks evoked indirect changes in NVC in healthy volunteers, and in patients with depression and dementia; only HbR differed in the depression group relative to the dementia group (p = 0.021).</p><p><strong>Comparison with existing methods: </strong>While these techniques have been used individually in the different patient groups, they have not been used in conjunction to assess differences in NVC between all three groups.</p><p><strong>Conclusions: </strong>An integrated TCD-NIRS protocol in this pilot study was feasible in these patient groups to measure NVC, but not in delirium.</p>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":" ","pages":"110784"},"PeriodicalIF":2.3,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147773921","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}