Brain Organoid and Systems Neuroscience Journal最新文献

{"title":"Mapping brain networks and cognitive functioning after stroke: A systematic review","authors":"Anna Tsiakiri ,&nbsp;Christos Giantsios ,&nbsp;Pinelopi Vlotinou ,&nbsp;Anna Nikolaidou ,&nbsp;John Atanbori ,&nbsp;Behnaz Sohani ,&nbsp;Aliyu Aliyu ,&nbsp;Anastasia Mournou ,&nbsp;Eleni Peristeri ,&nbsp;Christos Frantzidis","doi":"10.1016/j.bosn.2024.08.001","DOIUrl":"10.1016/j.bosn.2024.08.001","url":null,"abstract":"<div><p>Stroke, the second leading cause of death, exhibits no significant sex differences and primarily affects the elderly, with sociodemographic and income factors playing a role. Lifestyle patterns, including elevated blood pressure, weight, glucose levels, air pollution exposure, smoking, and nutrition, contribute to stroke risk. Stroke's impact on the brain's functional and structural integrity leads to cognitive deficits and challenges in daily activities. Rehabilitation is crucial for functional recovery. This review explores the association between brain networks and behavioral deficits post-stroke, aiming to establish a cartographic approach for predicting rehabilitation outcomes. Methodologically, a systematic review following PRISMA-ScR guidelines was conducted, searching PUBMED and SCOPUS for relevant studies from 2003 to 2023. The synthesis of 29 studies reveals insights into language, comprehension, general cognition, praxis, and complex cognitive abilities after stroke. Language recovery involves networks like the presupplementary motor area, Default Mode Network, and sensorimotor integration. Comprehension deficits result from focal lesions and left hemisphere stroke, with connectivity training showing potential. General cognition studies emphasize the role of working memory, connectivity patterns predicting ischemic attacks, and cognitive impairment post-subtentorial strokes. Praxis studies highlight the importance of spared left hemisphere regions, interhemispheric connectivity, and cognitive mechanisms in complex figure copying tasks. The intricate relationship between complex cognitive abilities and brain networks is explored, revealing the impact of damage on verbal creativity, mental state judgments, affordance-based processing, and beta-band phase synchronization in memory retrieval. Strengths include a systematic search strategy and inclusion of original English studies. Limitations include the lack of statistical analysis due to heterogeneity and varying methodologies. The synthesis underscores the shift toward understanding brain function through network perspectives, combining neuroimaging with neuropsychological assessments. The integration of artificial intelligence offers promise in processing complex datasets. Future implications involve standardizing methodologies, interdisciplinary collaboration, and leveraging AI for personalized interventions, with broad applications in clinical, research, and policy domains.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"2 ","pages":"Pages 43-52"},"PeriodicalIF":0.0,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949921624000061/pdfft?md5=60e2a018a112c6f97fc7e8ce3ab19ba1&pid=1-s2.0-S2949921624000061-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Studying estrogen effects in an in vitro-model of traumatic brain injury (TBI)","authors":"Houman Hemmat ,&nbsp;Lisanne Bongarts ,&nbsp;Paula Meiringer ,&nbsp;Roland A. Bender","doi":"10.1016/j.bosn.2024.07.001","DOIUrl":"10.1016/j.bosn.2024.07.001","url":null,"abstract":"<div><p>In traumatic brain injury (TBI), mechanical forces trigger a series of detrimental processes in the affected brain, which eventually result in substantial neuronal death. TBI has thus become a leading cause of death and disability worldwide. Here we utilized organotypic hippocampal slice cultures from mice to simulate mild diffuse TBI, the most common type, <em>in vitro</em>. We specifically used this model to examine the potential of 17β-estradiol (E2), which is considered to be neuroprotective, to influence injury-induced events, such as astrocyte and microglia activation, and to reduce cell death, if applied acutely after TBI. We found that established consequences of mechanical brain injury are replicated in the model, as increased apoptosis was observed 8 h and PI-uptake was significantly enhanced 24 h after <em>in vitro</em> TBI in CA1 pyramidal layer. GFAP expression was not overall increased, but correlated with cell death, indicating a confined activation of astrocytes associated with cell injury. Similarly, no general increase of microglia was detected, but activated microglia was observed in the vicinity of dying cells. Notably, application of E2 (20 nM) increased GFAP expression after 48 h, but did not significantly reduce cell death at any of the studied time points. We conclude that the presented <em>in vitro</em> TBI model is generally suited to study processes triggered by diffuse mechanical forces acting on brain tissue. Our data further support a stimulating effect of E2 on GFAP expression in astrocytes, but they do not confirm a neuroprotective role of E2 in the early phase of TBI.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"2 ","pages":"Pages 31-42"},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294992162400005X/pdfft?md5=de6f0fc05caec4de2bf2bf309642750d&pid=1-s2.0-S294992162400005X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring motor cortex functional connectivity in Parkinson's disease using fNIRS","authors":"Edgar Guevara ,&nbsp;Eleazar Samuel Kolosovas-Machuca ,&nbsp;Ildefonso Rodríguez-Leyva","doi":"10.1016/j.bosn.2024.04.001","DOIUrl":"https://doi.org/10.1016/j.bosn.2024.04.001","url":null,"abstract":"<div><p>This work proposes using functional Near-Infrared Spectroscopy (fNIRS) as a non-invasive alternative to study the motor cortex's functional connectivity in Parkinson’s Disease (PD). The bilateral motor regions were covered with the fNIRS probe, and graph theoretical network analysis and network-based statistics were applied to investigate differences in network topology and specific sub-networks between groups. Small-world properties like clustering coefficient, characteristic path length, and small-world index were computed and compared between PD patients and controls across various sparsity thresholds. PD patients exhibited a lower clustering coefficient and small-world index than controls. Network-based statistics identified a disconnected, mostly bilateral subnetwork in the PD group comprising nine edges and ten nodes. Mean functional connectivity was positively correlated with both groups' clustering coefficient and small world index, albeit this correlation was greater in the control group. A strong coupling between these two properties suggests that greater functional connectivity within the subnetwork may cause a more effective functional motor network in controls. The results provide insights into alterations in functional connectivity and network organization in the motor cortex of individuals with PD, demonstrating the potential of fNIRS for studying the neural basis of symptoms in this disease.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"2 ","pages":"Pages 23-30"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949921624000048/pdfft?md5=83d250d2e6d9149f67979658d0b2367b&pid=1-s2.0-S2949921624000048-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140631634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized user authentication system using wireless EEG headset and machine learning","authors":"Tron Baraku ,&nbsp;Christos Stergiadis ,&nbsp;Simos Veloudis ,&nbsp;Manousos A. Klados","doi":"10.1016/j.bosn.2024.03.003","DOIUrl":"https://doi.org/10.1016/j.bosn.2024.03.003","url":null,"abstract":"<div><p>In the realm of authentication, biometric verification has gained widespread adoption, especially within high-security user authentication systems. Although convenient, existing biometric systems are susceptible to a number of security vulnerabilities, including spoofing tools such as gummy fingers for fingerprint systems and voice coders for voice recognition systems. In this regard, brainwave-based authentication has emerged as a novel form of biometric scheme that has the potential to overcome the security limitations of existing systems while facilitating additional capabilities, such as continuous user authentication. In this study, we focus on a data-driven approach to Electroencephalography (EEG)-based authentication, guided by the power of machine learning algorithms. Our methodology addresses the fundamental challenge of distinguishing real users from intruders by training classification algorithms to the unique EEG signatures of every individual. The system is characterized by its convenience, ensuring real-time applicability without compromising its efficiency. By employing a commercially available single-channel EEG sensor and extracting a set of 8 power spectral features (delta [0–4 Hz], theta [4–8 Hz], low alpha [8–10 Hz], high alpha [10–12 Hz], low beta [12–20 Hz], high beta [20–30 Hz], low gamma [30–60 Hz], high gamma [60–100 Hz]), a commendable mean accuracy of 85.4% was achieved.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"2 ","pages":"Pages 17-22"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949921624000036/pdfft?md5=9b787ca7af4f85e21fd52236d2baf78d&pid=1-s2.0-S2949921624000036-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140549559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Charting paths to recovery: Navigating traumatic brain injury comorbidities through graph theory–exploring benefits and challenges","authors":"Shyam Kumar Sudhakar,&nbsp;Kaustav Mehta","doi":"10.1016/j.bosn.2024.03.002","DOIUrl":"10.1016/j.bosn.2024.03.002","url":null,"abstract":"<div><p>Traumatic brain injuries (TBIs) are characterized by widespread complications that exert a debilitating effect on the well-being of the affected individual. TBIs are associated with a multitude of psychiatric and medical comorbidities over the long term. Furthermore, no medications prevent secondary injuries associated with a primary insult. In this perspective article, we propose applying graph theory via the construction of disease comorbidity networks to identify high-risk patient groups, offer preventive care to affected populations, and reduce the disease burden. We describe the challenges associated with monitoring the development of comorbidities in TBI subjects and explain how disease comorbidity networks can reduce disease burden by preventing disease-related complications. We further discuss the various methods used to construct disease comorbidity networks and explain how features derived from a network can help identify subjects who might be at risk of developing post-traumatic comorbidities. Lastly, we address the potential challenges of using graph theory to successfully manage comorbidities following a TBI.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"2 ","pages":"Pages 10-16"},"PeriodicalIF":0.0,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949921624000024/pdfft?md5=9b493993309927962a8ce75a9a1bf518&pid=1-s2.0-S2949921624000024-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140405895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of blood oxygen-level-dependent signal data trimming on functional connectivity metrics","authors":"Duarte Oliveira-Saraiva,&nbsp;Hugo Alexandre Ferreira","doi":"10.1016/j.bosn.2024.03.001","DOIUrl":"10.1016/j.bosn.2024.03.001","url":null,"abstract":"<div><p>In the big data era, with a lack of comparable functional neuroimaging data, researchers try to combine heterogeneous data of different lengths, trimming those to the same number of timepoints (NTPs). However, the effects of trimming blood-oxygen-level dependent (BOLD) signal data on functional connectivity (FC) are still poorly understood.</p><p>Resting-state functional magnetic resonance imaging data from thirty healthy subjects were pre-processed for five different NTPs, from which FC matrices were computed. These BOLD signal correlation matrices were binarized for several thresholds, excluding weak correlations. Graph metrics were computed to study FC differences between different NTPs. The study included node degree analysis for each brain region and assessment of small-worldness coefficients (<span><math><mi>σ</mi></math></span> and <span><math><mi>ω</mi></math></span>), whereas in small-world networks, characteristic values are <span><math><mi>σ</mi></math></span> &gt; 1 and <span><math><mi>ω</mi></math></span> <span><math><mo>≈</mo></math></span> 0, indicating a balance between high clustering coefficients and short characteristic path lengths.</p><p>A tendency of decreasing global network degrees for higher NTPs was observed, translating the loss of stronger correlations with longer BOLD signals. Trimming such data affects brain regions differently, probably due to brain network dynamics. Regarding small-worldness, we observed that <span><math><mi>σ</mi></math></span> was greater than 1 for all the different NTPs, showing an increasing trend for higher NTPs (median value: <span><math><mrow><mspace></mspace><msub><mrow><mi>σ</mi></mrow><mrow><mi>BRAIN</mi></mrow></msub><mo>=</mo></mrow></math></span> 3.05). In addition, <span><math><mi>ω</mi></math></span> consistently remained greater than 0 for all NTPs, gradually approaching 0 as the NTPs increased (median value <span><math><mrow><msub><mrow><mi>ω</mi></mrow><mrow><mi>BRAIN</mi></mrow></msub><mo>=</mo></mrow></math></span> 0.20). As such, the results suggest a tendency for an increase of small-world properties for increasing NTPs. Nonetheless, the overall properties of brain networks almost remain constant. In conclusion, trimming BOLD signal data leads to small differences in FC.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"2 ","pages":"Pages 1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949921624000012/pdfft?md5=bd5f31baae18e513ed72ef27a5f671ba&pid=1-s2.0-S2949921624000012-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140275891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional connectivity of interictal iEEG and the connectivity of high-frequency components in epilepsy","authors":"Christos Stergiadis ,&nbsp;David M. Halliday ,&nbsp;Dimitrios Kazis ,&nbsp;Manousos A. Klados","doi":"10.1016/j.bosn.2023.11.001","DOIUrl":"https://doi.org/10.1016/j.bosn.2023.11.001","url":null,"abstract":"<div><p>Epilepsy is a disease of altered brain networks. The monitoring and analysis of functional connectivity and network properties can yield a better understanding of the underlying pathology, and improve treatment and prognostics. Identifying hub network regions has been in the spotlight of network neuroscience studies in epilepsy, as monitoring these areas can provide a perspective of the network’s local and global organization. Functional network analysis can be especially useful in Medically Refractory Epilepsy (MRE) cases, where surgical intervention is necessary for seizure relief. In such cases, the delineation of the epileptogenic zone, which represents the surgical target, is a very crucial procedure, which can be enhanced by understanding the underlying network topology. In this review, we will explore the expanding body of literature on functional connectivity of interictal intracranial electrophysiologic data, focusing on the interpretation of network properties, global or local, for identifying epileptogenic tissue. We will emphasize functional connectivity at high frequencies (above 80 Hz), as during the past decade High-Frequency Oscillations (HFOs) have been increasingly recognized as a promising biomarker of the seizure onset zone. We will conclude the review with an assessment of current limitations and a discussion of future research paths.</p></div>","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"1 ","pages":"Pages 3-12"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949921623000029/pdfft?md5=22c9949ed5f1212abc15d2e908316ed1&pid=1-s2.0-S2949921623000029-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138557776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating the frontiers of neuroscience","authors":"Manousos Klados,&nbsp;Luisa Pinto","doi":"10.1016/j.bosn.2023.10.001","DOIUrl":"https://doi.org/10.1016/j.bosn.2023.10.001","url":null,"abstract":"","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"1 ","pages":"Pages 1-2"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71714856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inkjet-based bioprinting for tissue engineering","authors":"J. A. Park, Yunji Lee, Sungjune Jung","doi":"10.51335/organoid.2023.3.e12","DOIUrl":"https://doi.org/10.51335/organoid.2023.3.e12","url":null,"abstract":"Inkjet bioprinting, a derivative of traditional inkjet technology, is gaining recognition in the fields of life sciences and tissue engineering due to its ability to produce picoliter volume droplets at high speeds in a non-contact fashion. This method has impressively evolved from enabling the production of 2-dimensional (2D) prints to complex 3-dimensional (3D) structures, and is increasingly being used in the manufacturing of electronic components. More recently, this technology has been effectively adapted for a variety of medical applications, such as cell patterning, scaffold construction, and 3D tissue fabrication. In this review, we delve into the principles and biological uses of inkjet technology. We provide an in-depth discussion on the latest developments in inkjet bioprinting, with a focus on cell patterning and 3D fabrication of tissue models, including multilayered lung, bladder, and skin. We also explore the potential of high-throughput 3D-bioprinted tissue models in toxicology and drug efficacy testing.","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86307540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel method for generating induced pluripotent stem cell (iPSC)-derived alveolar organoids: a comparison of their ability depending on iPSC origin","authors":"Min Jae Lim, A. Jo, Sung-Won Kim","doi":"10.51335/organoid.2023.3.e11","DOIUrl":"https://doi.org/10.51335/organoid.2023.3.e11","url":null,"abstract":"Background: Alveolar organoids may be useful tools in drug discovery for lung diseases, such as chronic obstructive pulmonary disease, and for studying the effects of respiratory viruses, such as severe acute respiratory syndrome coronavirus 2. Induced pluripotent stem cell (iPSC)-derived alveolar organoids offer ethical and cost-effective alternatives to animal testing and primary cell-based methods. In this study, we present generating alveolar organoids from iPSCs and compare the efficiency of generating iPSCs from alveolar type 2 (AT2) and umbilical cord blood (UCB) cells.Methods: The protocol started with a two-dimensional culture and transitioned to a three-dimensional culture using Matrigel after the endoderm stage. Organoid cultivation lasted for at least 40 days, and the characteristics of alveolar organoids were assessed using flow cytometry, real-time polymerase chain reaction, and immunostaining.Results: iPSCs derived from AT2 cells showed a better ability to generate alveolar organoids than those derived from UCB cells. This difference in the ability of AT2 iPSCs and UCB iPSCs to generate alveolar organoids appeared during the definitive endoderm differentiation stage. AT2 iPSCs showed higher expression of the anterior foregut endoderm marker SOX2 and lung progenitor gene expression markers, such as NKX2.1 and CPM, which are associated with the lung progenitor differentiation stage.Conclusion: This protocol successfully generated alveolar organoids from AT2 iPSCs; however, the efficiency of differentiation varied depending on the origin of the iPSCs. This study also found differences in gene expression and developmental potential between iPSCs, which may have contributed to the observed differences in differentiation efficiency.","PeriodicalId":100198,"journal":{"name":"Brain Organoid and Systems Neuroscience Journal","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76024380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}