Behavioural neurology

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1875-8584261-22013Behavioural neurologyBehav NeurolDisentangling the neuroanatomical correlates of perseveration from unilateral spatial neglect.131138131-810.3233/BEN-2012-110235Perseverative behavior, manifest as re-cancelling or re-visiting targets, is distinct from spatial neglect. Perseveration is thought to reflect frontal or parietal lobe dysfunction, but the neuroanatomical correlates remain poorly defined and the interplay between neglect and perseveration is incompletely understood. We enrolled 87 consecutive patients with diffusion-weighted, perfusion-weighted imaging, and spatial neglect testing within 24 hours of right hemisphere ischemic stroke. The degrees of spatial neglect and perseveration were analyzed. Perseveration was apparent in 46% (40/87) of the patients; 28% (24/87) showed perseveration only; 18% (16/87) showed both perseveration and neglect; and 3% (3/87) showed neglect only. Perseverative behaviors occur in an inverted "U" shape: little neglect was associated with few perseverations; moderate neglect with high perseverations; and in severe neglect targets may not enter consciousness and perseverative responses decrease. Brodmann areas of dysfunction, and the caudate and putament, were assessed and volumetrically measured. In this study, the caudate and putamen were not associated with perseveration. After controlling for neglect, and volume of dysfunctional tissue, only Brodmann area 46 was associated with perseveration. Our results further support the notion that perseveration and neglect are distinct entities; while they often co-occur, acute dorsolateral prefrontal cortex ischemia is associated with perseveration specifically.KleinmanJonathan TJTDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.DuBoisJeffery CJCNewhartMelissaMHillisArgye EAEengR01 NS047691NSNINDS NIH HHSUnited StatesR01 NS047691-08NSNINDS NIH HHSUnited StatesR01NS47691NSNINDS NIH HHSUnited StatesJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov't

NetherlandsBehav Neurol89145850953-4180IMAdultAgedAged, 80 and overCaudate NucleuspathologyCerebral CortexpathologyDiffusion Magnetic Resonance ImagingmethodsFemaleHumansMagnetic Resonance AngiographymethodsMaleMiddle AgedNeuroimagingmethodsPerceptual DisorderscomplicationspathologyPsychomotor PerformancePutamenpathologyStereotypic Movement DisordercomplicationspathologyStrokecomplicationspathology201262160201262160201351560201311ppublish22713393NIHMS366489PMC345928810.3233/BEN-2012-1102359U36225842633760J Cogn Neurosci. 2009 Nov;21(11):2073-8419016599Cortex. 2009 Mar;45(3):300-1218708187Brain. 2010 Mar;133(Pt 3):880-9420028714Neuropsychologia. 2010 Jul;48(9):2758-6320433859Stroke. 2010 Dec;41(12):2817-2121030699Neurology. 2001 Mar 13;56(5):670-211245724Neuropsychologia. 2002;40(6):594-60411792401Neuropsychologia. 2002;40(11):1794-80312062891Brain Cogn. 2003 Nov;53(2):117-2014607129Neurology. 2004 Aug 10;63(3):468-7415304577Brain. 1967 Jun;90(2):429-486028255Neurology. 1973 Jun;23(6):658-644736313Neuropsychologia. 1971 Dec;9(4):451-85164380Neuropsychologia. 1980;18(2):123-327383304J Neurosci. 1984 Jul;4(7):1863-746737043J Clin Exp Neuropsychol. 1986 Dec;8(6):710-263782451Neurology. 1987 Nov;37(11):1736-413670611Cortex. 1989 Jun;25(2):231-72758849J Neurol Neurosurg Psychiatry. 1990 Jun;53(6):487-912380729Cortex. 1990 Sep;26(3):307-172249435J Neurol Neurosurg Psychiatry. 1992 Jun;55(6):431-61619406Brain. 1998 Sep;121 ( Pt 9):1759-709762963Neurology. 1999 May 12;52(8):1569-7610331680Brain. 1965 Mar;88:1-1014280275J Neurosci. 2005 Mar 23;25(12):3161-715788773J Cogn Neurosci. 2005 Feb;17(2):340-5415811244Brain. 2006 Aug;129(Pt 8):2148-5716870885J Neurosci. 2006 Aug 2;26(31):8069-7316885220Cortex. 2006 Aug;42(6):911-2017131597Brain Res. 2006 Nov 6;1118(1):106-1516979143Brain Cogn. 2007 Jun;64(1):50-917174459Brain Cogn. 2008 Oct;68(1):49-5218406504Neurology. 2008 Oct 28;71(18):1439-4418955687Cogn Behav Neurol. 2008 Dec;21(4):249-5319057176Cortex. 2009 Mar;45(3):293-918708186Neurocase. 2009 Aug;15(4):311-719370480trying2...
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5013501MCID_676f085c2bf57d487f0c91b3 39726305 39724139 39720230 39715878 39715271 spatial "spatial"[All Fields] OR "spatialization"[All Fields] OR "spatializations"[All Fields] OR "spatialized"[All Fields] OR "spatially"[All Fields] neglect "neglect"[All Fields] OR "neglected"[All Fields] OR "neglectful"[All Fields] OR "neglecting"[All Fields] OR "neglects"[All Fields] ("spatial"[All Fields] OR "spatialization"[All Fields] OR "spatializations"[All Fields] OR "spatialized"[All Fields] OR "spatially"[All Fields]) AND ("neglect"[All Fields] OR "neglected"[All Fields] OR "neglectful"[All Fields] OR "neglecting"[All Fields] OR "neglects"[All Fields]) trying2...
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1613-68292024Dec26Small (Weinheim an der Bergstrasse, Germany)SmallLabel-Free SERS Analysis of Biological and Physical Information Heterogeneity of Nanoscale Extracellular Vesicle by Matching Specific Sizes of Enhanced Particles.e2409806e240980610.1002/smll.202409806The heterogeneity of extracellular vesicles (EVs) surface information represents different functions, which is neglected in previous studies. In this study, a label-free SERS analysis approach is demonstrated to study fundamental EV biological and physical information heterogeneity by matching specific sizes of nano-enhanced particles. This strategy reveals informative, comprehensive, and high-quality SERS spectra of the overall exosome surface, and effectively circumvents the key information loss caused by the spatial resistance of NPs binding to the 293 exosomes' concave structure. The classification of normal and cancerous cell-derived exosomes by PCA method, the accuracy is improved from 91.2% to 95.1% by optimizing sizes of nano-enhanced particles. In addition, stem cell-derived EVs of diverse sizes and morphologies similarly show acuity of spectrum variation to NPs size, which is conductive to qualitative studies. This new strategy will offer a widened in-depth understanding of the surface information, size, and morphology of EVs, which can be applied to the study of biological functions.© 2024 Wiley‐VCH GmbH.ZhangRuiyuanRKey Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China.GuoYuYKey Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China.HuangChenCDepartment of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China.FangJixiangJ0000-0003-3618-2144Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China.eng21874104National Natural Science Foundation of China22074115National Natural Science Foundation of China22474106National Natural Science Foundation of Chinaxtr062022002Fundamental Research Funds for the Central Universities2024SF-GJHX-36Shaanxi Province Key Core Technology projectJournal Article20241226

GermanySmall1012353381613-6810IMbiological and physical informationenhanced particlesextracellular vesicleheterogeneitylabel‐free SERS analysis20241222024102120241227620202412276202024122732aheadofprint3972630510.1002/smll.202409806G. Raposo, W. Stoorvogel, J. Cell Biol. 2013, 200, 373.M. Colombo, G. Raposo, C. Thery, Annu. Rev. Cell Biol. 2014, 30, 255.C. Théry, L. Zitvogel, S. Amigorena, Nat. Rev. Immunol. 2002, 2, 569.R. Crescitelli, C. Lasser, T. G. Szabo, A. Kittel, M. Eldh, I. Dianzani, E. I. Buzas, J. O. Lötvall, J. Extracell. Vesicles 2013, 2, 20677.H. Valadi, K. Ekstrom, A. Bossios, M. Sjöstrand, J. J. Lee, J. O. Lötvall, Nat. Cell Biol. 2007, 9, 654.D. W. Greening, S. K. Gopal, R. A. Mathias, L. Liu, J. Y. Sheng, H. J. Zhu, R. J. Simpson, Semin. Cell Dev. Biol. 2015, 40, 60.Z. Y. Abd Elmageed, Y. J. Yang, R. J. Thomas, M. Ranjan, D. Mondal, K. Moroz, Z. D. Fang, B. M. Rezk, K. Moparty, S. C. Sikka, O. Sartor, A. B. Abdel‐Mageed, Stem Cells 2014, 32, 983.B. H. Sung, T. 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1935-273518122024Dec26PLoS neglected tropical diseasesPLoS Negl Trop DisSpatial associations of Hansen's disease and schistosomiasis in endemic regions of Minas Gerais, Brazil.e0012682e001268210.1371/journal.pntd.0012682Brazil has the second highest case count of Hansen's disease (leprosy, HD), but factors contributing to transmission in highly endemic areas of the country remain unclear. Recent studies have shown associations of helminth infection and leprosy, supporting a biological plausibility for increased leprosy transmission in areas with helminths. However, spatial analyses of the overlap of these infections are limited. Therefore, we aimed to spatially analyze these two diseases in a co-endemic area of Minas Gerais, Brazil, in order to identify potential epidemiologic associations.An ecological study using public health surveillance records and census data was conducted to investigate whether the occurrence of HD -and specifically multibacillary (MB) disease- was associated with the presence of schistosomiasis in a community of 41 municipalities in eastern Minas Gerais, Brazil from 2011 to 2015. Multivariate logistic regression and spatial cluster analyses using geographic information systems (GIS) were performed.The average annual incidence of HD in the study area was 35.3 per 100,000 while Schistosoma mansoni average annual incidence was 26 per 100,000. Both HD and schistosomiasis were spatially distributed showing significant clustering across the study area. Schistosomiasis was present in 10.4% of the tracts with HD and thirteen high-high clusters of local bivariate autocorrelation for HD and schistosomiasis cases were identified. A multivariate non-spatial analysis found that census tracts with MB disease were more likely to have schistosomiasis when adjusted for population density, household density, and household income (aOR = 1.7, 95% CI 1.0, 2.7). This remained significant when accounting for spatial correlation (aOR = 1.1, 95% CI (1.0, 1.2)).We found clustering of both HD and schistosomiasis in this area with some statistically significant overlap of multibacillary HD with S. mansoni infection. Not only did we provide an effective approach to study the epidemiology of two endemic neglected tropical diseases with geographic spatial analyses, we highlight the need for further clinical and translational studies to study the potential epidemiologic associations uncovered.Copyright: © 2024 Stephens et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.StephensJessica LJLDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.FragaLucia A OLAOUniversidade Federal Juiz de Fora-Campus Governador Valadares, Governador Valadares, Minas Gerais, Brazil.Universidade Vale do Rio Doce, Governador Valadares, Minas Gerais, Brazil.FerreiraJosé AJAFaculdade da Saúde e Ecologia Humana (FASEH), Vespasiano, Minas Gerais, Brazil.De MondesertLauraLHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.KitronUrielUDepartment of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America.ClennonJulie AJADepartment of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America.FairleyJessica KJK0000-0003-4086-9272Universidade Vale do Rio Doce, Governador Valadares, Minas Gerais, Brazil.Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America.engJournal Article20241226

United StatesPLoS Negl Trop Dis1012914881935-2727IMThe authors have declared that no competing interests exist.20243252024116202412261816202412261816202412261552aheadofprint3972413910.1371/journal.pntd.0012682PNTD-D-24-004453972023020241225

1662-4548182024Frontiers in neuroscienceFront NeurosciSTAFNet: an adaptive multi-feature learning network via spatiotemporal fusion for EEG-based emotion recognition.15199701519970151997010.3389/fnins.2024.1519970Emotion recognition using electroencephalography (EEG) is a key aspect of brain-computer interface research. Achieving precision requires effectively extracting and integrating both spatial and temporal features. However, many studies focus on a single dimension, neglecting the interplay and complementarity of multi-feature information, and the importance of fully integrating spatial and temporal dynamics to enhance performance.We propose the Spatiotemporal Adaptive Fusion Network (STAFNet), a novel framework combining adaptive graph convolution and temporal transformers to enhance the accuracy and robustness of EEG-based emotion recognition. The model includes an adaptive graph convolutional module to capture brain connectivity patterns through spatial dynamic evolution and a multi-structured transformer fusion module to integrate latent correlations between spatial and temporal features for emotion classification.Extensive experiments were conducted on the SEED and SEED-IV datasets to evaluate the performance of STAFNet. The model achieved accuracies of 97.89% and 93.64%, respectively, outperforming state-of-the-art methods. Interpretability analyses, including confusion matrices and t-SNE visualizations, were employed to examine the influence of different emotions on the model's recognition performance. Furthermore, an investigation of varying GCN layer depths demonstrated that STAFNet effectively mitigates the over-smoothing issue in deeper GCN architectures.In summary, the findings validate the effectiveness of STAFNet in EEG-based emotion recognition. The results emphasize the critical role of spatiotemporal feature extraction and introduce an innovative framework for feature fusion, advancing the state of the art in emotion recognition.Copyright © 2024 Hu, He, Qian, Liu, Qiao, Zhang and Xiong.HuFoFCollege of Information Engineering, Zhejiang University of Technology, Hangzhou, China.HeKailunKCollege of Information Engineering, Zhejiang University of Technology, Hangzhou, China.QianMengyuanMCollege of Information Engineering, Zhejiang University of Technology, Hangzhou, China.LiuXiaofengXCollege of Information Engineering, Zhejiang University of Technology, Hangzhou, China.QiaoZukangZDepartment of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.ZhangLekaiLThe School of Design and Architecture, Zhejiang University of Technology, Hangzhou, China.XiongJunlongJDepartment of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.engJournal Article20241210

SwitzerlandFront Neurosci1014784811662-453XEEGadaptive adjacency matrixdeep learningemotion recognitionspatiotemporal fusionThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.2024103020241118202412256212024122562020241225420202411epublish39720230PMC1166649110.3389/fnins.2024.1519970Algarni M., Saeed F., Al-Hadhrami T., Ghabban D., Al-Sarem M. (2022). Deep learning-based approach for emotion recognition using electroencephalography (EEG) signals using bi-directional long short-term memory (BI-LSTM). Sensors 22:2976. 10.3390/s2208297610.3390/s22082976PMC903305335458962Bagherzadeh S., Maghooli K., Shalbaf A., Maghsoudi A. (2022). Emotion recognition using effective connectivity and pre-trained convolutional neural networks in EEG signals. Cogn. 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1935-273518122024Dec23PLoS neglected tropical diseasesPLoS Negl Trop DisAfrican schistosomes in small mammal communities: Perspectives from a spatio-temporal survey in the vicinity of Lake Guiers, Senegal.e0012721e001272110.1371/journal.pntd.0012721Schistosomiasis is a neglected tropical disease of public health significance. In view of its elimination as a public health problem by 2030, adopting a One Health approach is necessary, considering its multidimensional nature. Animal reservoirs, in particular, pose a significant threat to schistosomiasis control in Africa and beyond. In this study, we conducted a spatio-temporal survey of Schistosoma infections in small mammal communities and intermediate snail hosts in the vicinity of Lake Guiers in northern Senegal. Sampling campaigns were undertaken four times between April 2021 and August 2022 around eight villages. A total of 534 small mammals of four species, primarily Hubert's multimammate mice Mastomys huberti, were captured. Out of 498 individuals examined, only 18 rodents (17 M. huberti and 1 Arvicanthis niloticus) were infected with schistosomes. The infection rates in M. huberti varied over time (prevalence range: 2.4% to 9.3%, intensity range: 4 to 132), and space (prevalence range: 3.1% to 40%, intensity range: 2 to 110) and were higher in adult hosts captured during or just after the rainy season, a time when older individuals dominate in rodent populations. Using a multi-locus molecular approach (cox1 and ITS) on Schistosoma larvae (cercariae and miracidia) and adult worms, we identified Schistosoma mansoni as the most widespread species. We also detected Schistosoma bovis and Schistosoma haematobium in M. huberti from one locality (Temeye). Although no Schistosoma hybrids were found, the discovery of a male S. mansoni and a female S. bovis pair raises concerns about potential hybridization patterns that could occur in rodents. Finally, three snail species were found infected (25 Biomphalaria pfeifferi, 3 Bulinus truncatus and 1 Bulinus senegalensis) including with S. mansoni, S. bovis, S. haematobium and S. haematobium x S. bovis hybrids. Our findings highlight the spatial-temporal variations of Schistosoma infections in rodents and emphasize the need for fine-scale monitoring over time and space for effective One Health measures and ensuring the sustainability of schistosomiasis control efforts.Copyright: © 2024 Kincaid-Smith et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Kincaid-SmithJulienJ0000-0002-7471-1724CBGP, IRD, CIRAD, INRAE, Institut Agro, Université de Montpellier, Montpellier, France.SavassiBoris Sègnito A EBSAECentre de Recherche pour la lutte contre les Maladies Infectieuses Tropicales (CReMIT/TIDRC), Université d'Abomey-Calavi, Abomey-Calavi, Bénin.IHPE, Univ Montpellier, CNRS, IFREMER, Univ Perpignan Via Domitia, Perpignan, France.SenghorBrunoBVITROME, Campus International IRD-UCAD de Hann, Dakar, Sénégal.DiagneChristopheCCBGP, IRD, CIRAD, INRAE, Institut Agro, Université de Montpellier, Montpellier, France.NiangYoussouphaYCBGP-BIOPASS 2, IRD, Campus IRD-ISRA de Bel-Air, Dakar, Sénégal.KaneMamadouMCBGP-BIOPASS 2, IRD, Campus IRD-ISRA de Bel-Air, Dakar, Sénégal.TatardCarolineCCBGP, IRD, CIRAD, INRAE, Institut Agro, Université de Montpellier, Montpellier, France.BrouatCarineCCBGP, IRD, CIRAD, INRAE, Institut Agro, Université de Montpellier, Montpellier, France.GranjonLaurentLCBGP, IRD, CIRAD, INRAE, Institut Agro, Université de Montpellier, Montpellier, France.engJournal Article20241223

United StatesPLoS Negl Trop Dis1012914881935-2727IMThe authors have declared that no competing interests exist.20245312024112520241223225920241223225920241223144aheadofprint3971527110.1371/journal.pntd.0012721PNTD-D-24-00765trying2...
Disentangling the neuroanatomical correlates of perseveration from unilateral spatial neglect. | LitMetric

Disentangling the neuroanatomical correlates of perseveration from unilateral spatial neglect.

Jonathan T Kleinman Jeffery C DuBois Melissa Newhart Argye E Hillis

Behav Neurol

Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Published: May 2013

Perseverative behavior, manifest as re-cancelling or re-visiting targets, is distinct from spatial neglect. Perseveration is thought to reflect frontal or parietal lobe dysfunction, but the neuroanatomical correlates remain poorly defined and the interplay between neglect and perseveration is incompletely understood. We enrolled 87 consecutive patients with diffusion-weighted, perfusion-weighted imaging, and spatial neglect testing within 24 hours of right hemisphere ischemic stroke. The degrees of spatial neglect and perseveration were analyzed. Perseveration was apparent in 46% (40/87) of the patients; 28% (24/87) showed perseveration only; 18% (16/87) showed both perseveration and neglect; and 3% (3/87) showed neglect only. Perseverative behaviors occur in an inverted "U" shape: little neglect was associated with few perseverations; moderate neglect with high perseverations; and in severe neglect targets may not enter consciousness and perseverative responses decrease. Brodmann areas of dysfunction, and the caudate and putament, were assessed and volumetrically measured. In this study, the caudate and putamen were not associated with perseveration. After controlling for neglect, and volume of dysfunctional tissue, only Brodmann area 46 was associated with perseveration. Our results further support the notion that perseveration and neglect are distinct entities; while they often co-occur, acute dorsolateral prefrontal cortex ischemia is associated with perseveration specifically.

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