Aperture neuro最新文献

{"title":"A stage for neuroscience and art: the OHBM BrainArt SIG.","authors":"V. Borghesani, Z. Nagy, D. Lussier, Ting Xu, R. Chauvin, P. Kochunov, Anastasia Brovkin, A. Dagher, S. Narayanan, A. Badhwar","doi":"10.31234/osf.io/uywc5","DOIUrl":"https://doi.org/10.31234/osf.io/uywc5","url":null,"abstract":"Science and art have been intertwined for centuries, both embodying means for humans to represent, communicate and interpret our external and internal worlds. The collective effort to gather and organize knowledge about the brain blends well with a wide array of human creative activities, from visual and performing arts to interactive media. It thus comes as no surprise that the Organization for Human Brain Mapping has a Special Interest Group (SIG) dedicated to providing a platform for (neuro)sci-art: the BrainArt SIG.Here, after properly introducing all the main characters, we follow the development of this captivating script: from its grassroots prelude within the Neuro Bureau to its recent online instantiations. In particular, we highlight our three latest Exhibitions (Ars Cerebri, 2019; Neurodiversity, 2020; BigData & me, 2021) and the associated Competitions, not forgetting the scientific visualization sessions that have contributed to the making of brainart a distinguishing feature of the OHBM annual meeting.","PeriodicalId":72250,"journal":{"name":"Aperture neuro","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87843308","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":"Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at Work","authors":"Eneko Uruñuela, T. Bolton, D. Ville, C. Caballero-Gaudes","doi":"10.52294/001c.87574","DOIUrl":"https://doi.org/10.52294/001c.87574","url":null,"abstract":"Deconvolution of the hemodynamic response is an important step to access short timescales of brain activity recorded by functional magnetic resonance imaging (fMRI). Albeit conventional deconvolution algorithms have been around for a long time (e.g., Wiener deconvolution), recent state-of-the-art methods based on sparsity-pursuing regularization are attracting increasing interest to investigate brain dynamics and connectivity with fMRI. This technical note revisits the main concepts underlying two main methods, paradigm free mapping and total activation, in the most accessible way. Despite their apparent differences in the formulation, these methods are theoretically equivalent as they represent the synthesis and analysis sides of the same problem, respectively. We demonstrate this equivalence in practice with their best-available implementations using both simulations, with different signal-to-noise ratios, and experimental fMRI data acquired during a motor task and resting state. We evaluate the parameter settings that lead to equivalent results and showcase the potential of these algorithms compared to other common approaches. This note is useful for practitioners interested in gaining a better understanding of state-of-the-art hemodynamic deconvolution and aims to answer questions that practitioners often have regarding the differences between the two methods.","PeriodicalId":72250,"journal":{"name":"Aperture neuro","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84324115","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":"Prenatal and Childhood Adverse Events and Child Brain Morphology: A Population-Based Study","authors":"A. Hidalgo, Scott W. Delaney, Stavroula A. Kourtalidi, A. Neumann, Runyu Zou, R. Muetzel, M. Bakermans-Kranenburg, Marinus H. van IJzendoorn, H. Tiemeier, T. White","doi":"10.1101/2021.02.25.21252442","DOIUrl":"https://doi.org/10.1101/2021.02.25.21252442","url":null,"abstract":"Background: Prenatal and childhood adverse events have been shown to be related to children's cognitive and psychological development. However, the influence of early-life adversities on child brain morphology is not well understood and most studies are based on small samples and often examine only one adversity. Thus, the goal of our study is to examine the relationship between cumulative exposures to prenatal and childhood adversities and brain morphology in a large population-based study. Methods: Participants included 2,993 children in whom prenatal adversities were reported by mothers at 20-25 weeks of pregnancy and the child's lifetime exposure to adversities was reported by mothers when the children were 10 years-of-age. The total brain, grey and white matter volumes and the volume of the cerebellum, amygdala and hippocampus were assessed with magnetic resonance imaging when children were 10 years old. Results: In total, 36% of children had mothers who were exposed to at least one adversity during pregnancy and 35% of children were exposed to adversities in childhood. In our study sample, the cumulative number of prenatal adversities was not related to any brain outcome. In contrast, per each additional childhood adverse event, the total brain volume was 0.07 standard deviations smaller (SE = 0.02, p = 0.001), with differences in both grey and white matter volumes. Childhood adversities were not related to the amygdala or hippocampal volumes. Additionally, the link between childhood events and the preadolescent brain was not modified by prenatal events and was not explained by maternal psychopathology. Conclusions: Our results suggest that childhood adversities, but not prenatal adverse events, are associated with smaller global brain volumes in preadolescence. Notably, this is the first large population-based study to prospectively assess the association between the cumulative number of prenatal adversities and the preadolescent brain morphology. The study findings extend the evidence from high-risk samples, providing support for a link between cumulative childhood adverse events and brain morphology in children from the general population.","PeriodicalId":72250,"journal":{"name":"Aperture neuro","volume":"10 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76324893","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":"Evaluating the Reliability of Human Brain White Matter Tractometry.","authors":"John Kruper,&nbsp;Jason D Yeatman,&nbsp;Adam Richie-Halford,&nbsp;David Bloom,&nbsp;Mareike Grotheer,&nbsp;Sendy Caffarra,&nbsp;Gregory Kiar,&nbsp;Iliana I Karipidis,&nbsp;Ethan Roy,&nbsp;Bramsh Q Chandio,&nbsp;Eleftherios Garyfallidis,&nbsp;Ariel Rokem","doi":"10.52294/e6198273-b8e3-4b63-babb-6e6b0da10669","DOIUrl":"https://doi.org/10.52294/e6198273-b8e3-4b63-babb-6e6b0da10669","url":null,"abstract":"<p><p>The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections <i>in vivo</i>, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging.</p>","PeriodicalId":72250,"journal":{"name":"Aperture neuro","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/fd/ae/nihms-1737034.PMC8785971.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39949694","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":"BrainIAK: The Brain Imaging Analysis Kit.","authors":"Manoj Kumar, Michael J Anderson, James W Antony, Christopher Baldassano, Paula P Brooks, Ming Bo Cai, Po-Hsuan Cameron Chen, Cameron T Ellis, Gregory Henselman-Petrusek, David Huberdeau, J Benjamin Hutchinson, Y Peeta Li, Qihong Lu, Jeremy R Manning, Anne C Mennen, Samuel A Nastase, Hugo Richard, Anna C Schapiro, Nicolas W Schuck, Michael Shvartsman, Narayanan Sundaram, Daniel Suo, Javier S Turek, David Turner, Vy A Vo, Grant Wallace, Yida Wang, Jamal A Williams, Hejia Zhang, Xia Zhu, Mihai Capotă, Jonathan D Cohen, Uri Hasson, Kai Li, Peter J Ramadge, Nicholas B Turk-Browne, Theodore L Willke, Kenneth A Norman","doi":"10.52294/31bb5b68-2184-411b-8c00-a1dacb61e1da","DOIUrl":"10.52294/31bb5b68-2184-411b-8c00-a1dacb61e1da","url":null,"abstract":"<p><p>Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally optimized solutions to key problems in advanced fMRI analysis. A variety of techniques are presently included in BrainIAK: intersubject correlation (ISC) and intersubject functional connectivity (ISFC), functional alignment via the shared response model (SRM), full correlation matrix analysis (FCMA), a Bayesian version of representational similarity analysis (BRSA), event segmentation using hidden Markov models, topographic factor analysis (TFA), inverted encoding models (IEMs), an fMRI data simulator that uses noise characteristics from real data (fmrisim), and some emerging methods. These techniques have been optimized to leverage the efficiencies of high-performance compute (HPC) clusters, and the same code can be se amlessly transferred from a laptop to a cluster. For each of the aforementioned techniques, we describe the data analysis problem that the technique is meant to solve and how it solves that problem; we also include an example Jupyter notebook for each technique and an annotated bibliography of papers that have used and/or described that technique. In addition to the sections describing various analysis techniques in BrainIAK, we have included sections describing the future applications of BrainIAK to real-time fMRI, tutorials that we have developed and shared online to facilitate learning the techniques in BrainIAK, computational innovations in BrainIAK, and how to contribute to BrainIAK. We hope that this manuscript helps readers to understand how BrainIAK might be useful in their research.</p>","PeriodicalId":72250,"journal":{"name":"Aperture neuro","volume":"1 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40678701","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":"Linking vestibular function and sub-cortical grey matter volume changes in a longitudinal study of aging adults","authors":"Dominic Padova, J. Ratnanather, Q. Xue, S. Resnick, Y. Agrawal","doi":"10.1101/2020.11.17.20233684","DOIUrl":"https://doi.org/10.1101/2020.11.17.20233684","url":null,"abstract":"Emerging evidence suggests a relationship between impairments of the vestibular (inner ear balance) system and decline in visuospatial cognitive performance in older adults. However, it is unclear whether age-related vestibular loss is associated with volume loss in brain regions known to receive vestibular input. To address this gap, we investigated the association between vestibular function and the volumes of four structures that process vestibular information (the hippocampus, entorhinal cortex, thalamus, and basal ganglia) in a longitudinal study of 97 healthy, older participants from the Baltimore Longitudinal Study of Aging. Vestibular testing included cervical vestibular-evoked myogenic potentials (cVEMP) to measure saccular function, ocular VEMP (oVEMP) to measure utricular function, and video head-impulse tests to measure the horizontal semi-circular canal vestibulo-ocular reflex (VOR). Participants in the sample had vestibular and brain MRI data for a total of 1 (18.6%), 2 (49.5%) and 3 (32.0%) visits. Linear mixed-effects regression was used to model regional volume over time as a function of vestibular physiological function, correcting for age, sex, intracranial volume, and inter-subject random variation in the baseline levels of and rates of change of volume over time. We found that poorer saccular function, characterized by lower cVEMP amplitude, is associated with reduced bilateral volumes of the thalamus and basal ganglia at each time point, demonstrated by a 0.0714 cm3 {+/-} 0.0344 (p=0.038; 95% CI: 0.00397-0.139) lower bilateral-mean volume of the basal ganglia and a 0.0440 cm3 {+/-} 0.0221 (p=0.046; 95% CI: 0.000727-0.0873) lower bilateral-mean volume of the thalamus for each 1 unit lower cVEMP amplitude. There were no significant associations between volume and oVEMP or mean VOR gain. These findings provide insight into the potential neural substrates for the observed link between age-related vestibular loss and spatial cognition.","PeriodicalId":72250,"journal":{"name":"Aperture neuro","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74665601","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}