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907 Research products

  • Neuroinformatics
  • Open Access
  • Canadian Institutes of Health Research
  • Natural Sciences and Engineering Research Council of Canada

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: B. Ogan Mancarci; Lilah Toker; Shreejoy J. Tripathy; Brenna Li; +3 Authors

    Establishing the molecular diversity of cell types is crucial for the study of the nervous system. We compiled a cross-laboratory database of mouse brain cell type-specific transcriptomes from 36 major cell types from across the mammalian brain using rigorously curated published data from pooled cell type microarray and single-cell RNA-sequencing (RNA-seq) studies. We used these data to identify cell type-specific marker genes, discovering a substantial number of novel markers, many of which we validated using computational and experimental approaches. We further demonstrate that summarized expression of marker gene sets (MGSs) in bulk tissue data can be used to estimate the relative cell type abundance across samples. To facilitate use of this expanding resource, we provide a user-friendly web interface at www.neuroexpresso.org. Visual Abstract

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    Europe PubMed Central
    Article . 2017
    Data sources: PubMed Central
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    bioRxiv
    Preprint . 2016
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    eNeuro
    Article . Preprint
    License: CC BY
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    eNeuro
    Article . 2017 . Peer-reviewed
    License: CC BY NC SA
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Europe PubMed Central
      Article . 2017
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      bioRxiv
      Preprint . 2016
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      eNeuro
      Article . Preprint
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      eNeuro
      Article . 2017 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Elena, Choleris; Liisa A M, Galea; Farida, Sohrabji; Karyn M, Frick;

    Abstract Biological differences between males and females are found at multiple levels. However, females have too often been under-represented in behavioral neuroscience research, which has stymied the study of potential sex differences in neurobiology and behavior. This review focuses on the study of sex differences in the neurobiology of social behavior, memory, emotions, and recovery from brain injury, with particular emphasis on the role of estrogens in regulating forebrain function. This work, presented by the authors at the 2016 meeting of the International Behavioral Neuroscience Society, emphasizes varying approaches from several mammalian species in which sex differences have not only been documented, but also become the focus of efforts to understand the mechanistic basis underlying them. This information may provide readers with useful experimental tools to successfully address recently introduced regulations by granting agencies that either require (e.g. the National Institutes of Health in the United States and the Canadian Institutes of Health Research in Canada) or recommend (e.g. Horizon 2020 in Europe) the inclusion of both sexes in biomedical research.

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    Europe PubMed Central
    Other literature type . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Neuroscience & Biobehavioral Reviews
    Article . 2018 . Peer-reviewed
    License: Elsevier TDM
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Neuroscience & Biobe...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Europe PubMed Central
      Other literature type . 2018
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Neuroscience & Biobehavioral Reviews
      Article . 2018 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Parikshat Sirpal; Rafat Damseh; Ke Peng; Dang Khoa Nguyen; +1 Authors

    AbstractIn this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model’s fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.

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    Neuroinformatics
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    Neuroinformatics; PolyPublie
    Other literature type . Article . 2021 . 2022 . Peer-reviewed
    License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Neuroinformaticsarrow_drop_down
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      Neuroinformatics
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      Neuroinformatics; PolyPublie
      Other literature type . Article . 2021 . 2022 . Peer-reviewed
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    Authors: Hatton, Sean N; Huynh, Khoa H; Bonilha, Leonardo; Abela, Eugenio; +70 Authors

    AbstractThe epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analyzed from 1,069 non-epileptic controls and 1,249 patients: temporal lobe epilepsy with hippocampal sclerosis (N=599), temporal lobe epilepsy with normal MRI (N=275), genetic generalized epilepsy (N=182) and nonlesional extratemporal epilepsy (N=193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fiber tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at p<0.001). Across “all epilepsies” lower fractional anisotropy was observed in most fiber tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. Less robust effects were seen with mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Those with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced differences in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and in mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of microstructural abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibers in a large multicentre study of epilepsy. Overall, epilepsy patients showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding new insights into pathological substrates that may be used to guide future therapeutic and genetic studies.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ bioRxivarrow_drop_down
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    bioRxiv
    Preprint . 2019
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      bioRxiv
      Preprint . 2019
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    Authors: Parikshat Sirpal; Ali Kassab; Philippe Pouliot; Dang Khoa Nguyen; +1 Authors

    Abstract. In the context of epilepsy monitoring, electroencephalography (EEG) remains the modality of choice. Functional near-infrared spectroscopy (fNIRS) is a relatively innovative modality that cannot only characterize hemodynamic profiles of seizures but also allow for long-term recordings. We employ deep learning methods to investigate the benefits of integrating fNIRS measures for seizure detection. We designed a deep recurrent neural network with long short-term memory units and subsequently validated it using the CHBMIT scalp EEG database—a compendium of 896 h of surface EEG seizure recordings. After validating our network using EEG, fNIRS, and multimodal data comprising a corpus of 89 seizures from 40 refractory epileptic patients was used as model input to evaluate the integration of fNIRS measures. Following heuristic hyperparameter optimization, multimodal EEG-fNIRS data provide superior performance metrics (sensitivity and specificity of 89.7% and 95.5%, respectively) in a seizure detection task, with low generalization errors and loss. False detection rates are generally low, with 11.8% and 5.6% for EEG and multimodal data, respectively. Employing multimodal neuroimaging, particularly EEG-fNIRS, in epileptic patients, can enhance seizure detection performance. Furthermore, the neural network model proposed and characterized herein offers a promising framework for future multimodal investigations in seizure detection and prediction.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    Europe PubMed Central
    Article . 2019
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    Journal of Biomedical Optics; PolyPublie
    Other literature type . Article . 2019 . Peer-reviewed
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    Journal of Biomedical Optics
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      Europe PubMed Central
      Article . 2019
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      Journal of Biomedical Optics; PolyPublie
      Other literature type . Article . 2019 . Peer-reviewed
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      Journal of Biomedical Optics
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    Authors: Yoshihiro Noda; Mera S. Barr; Reza Zomorrodi; Robin F.H. Cash; +5 Authors

    AbstractGABAergic and glutamatergic dysfunction in the dorsolateral prefrontal cortex (DLPFC) are thought to be the core pathophysiological mechanisms of schizophrenia. Recently, we have established a method to index these functions from the DLPFC using the paired transcranial magnetic stimulation (TMS) paradigms of short interval intracortical inhibition (SICI) and facilitation (ICF) combined with electroencephalography (EEG). In this study, we aimed to evaluate neurophysiological indicators related to GABAA and glutamate receptor-mediated functions respectively from the DLPFC in patients with schizophrenia using these paradigms, compared to healthy controls. Given that these activities contribute to cognitive functions, the relationship between the TMS-evoked potential (TEP) modulations by SICI/ICF and cognitive/clinical measures were explored. Compared to controls, patients showed reduced inhibition in P60 (t22 = −4.961, p < 0.0001) by SICI and reduced facilitation in P60 (t22 = 5.174, p < 0.0001) and N100 (t22 = 3.273, p = 0.003) by ICF. In patients, the modulation of P60 by SICI was correlated with the longest span of the Letter-Number Span Test (r = −0.775, p = 0.003), while the modulation of N100 by ICF was correlated with the total score of the Positive and Negative. Syndrome Scale (r = 0.817, p = 0.002). These findings may represent the pathophysiology, which may be associated with prefrontal GABAA and glutamatergic dysfunctions, in the expression of symptoms of schizophrenia.

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    Europe PubMed Central
    Article . 2017
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    Scientific Reports
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    Authors: Domenichiello, Anthony F.; Kitson, Alex P.; Bazinet, Richard P.;

    AbstractDocosahexaenoic acid (DHA) is important for brain function, and can be obtained directly from the diet or synthesized in the body from α-linolenic acid (ALA). Debate exists as to whether DHA synthesized from ALA can provide sufficient DHA for the adult brain, as measures of DHA synthesis from ingested ALA are typically <1% of the oral ALA dose. However, the primary fate of orally administered ALA is β-oxidation and long-term storage in adipose tissue, suggesting that DHA synthesis measures involving oral ALA tracer ingestion may underestimate total DHA synthesis. There is also evidence that DHA synthesized from ALA can meet brain DHA requirements, as animals fed ALA-only diets have brain DHA concentrations similar to DHA-fed animals, and the brain DHA requirement is estimated to be only 2.4–3.8mg/day in humans. This review summarizes evidence that DHA synthesis from ALA can provide sufficient DHA for the adult brain by examining work in humans and animals involving estimates of DHA synthesis and brain DHA requirements. Also, an update on methods to measure DHA synthesis in humans is presented highlighting a novel approach involving steady-state infusion of stable isotope-labeled ALA that bypasses several limitations of oral tracer ingestion. It is shown that this method produces estimates of DHA synthesis that are at least 3-fold higher than brain uptake rates in rats.

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    Authors: Ana L. Manera; Mahsa Dadar; D. Louis Collins; Simon Ducharme; +1 Authors

    Objective To objectively quantify how cerebral volume loss could assist with clinical diagnosis and clinical trial design in the behavioural variant of frontotemporal dementia (bvFTD). Methods We applied deformation-based morphometric analyses with robust registration to precisely quantify the magnitude and pattern of atrophy in patients with bvFTD as compared to cognitively normal controls (CNCs), to assess the progression of atrophy over one year follow up and to generate clinical trial sample size estimates to detect differences for the structures most sensitive to change. This study included 203 subjects - 70 bvFTD and 133 CNCs - with a total of 482 timepoints from the Frontotemporal Lobar Degeneration Neuroimaging Initiative. Results Deformation based morphometry (DBM) revealed significant atrophy in the frontal lobes, insula, medial and anterior temporal regions bilaterally in bvFTD subjects compared to controls with outstanding subcortical involvement. We provide detailed information on regional changes per year. In both cross-sectional analysis and over a one-year follow-up period, ventricle expansion was the most prominent differentiator of bvFTD from controls and a sensitive marker of disease progression. Conclusions Automated measurement of ventricular expansion is a sensitive and reliable marker of disease progression in bvFTD to be used in clinical trials for potential disease modifying drugs, as well as possibly to implement in clinical practice. Ventricular expansion measured with DBM provides the lowest published estimated sample size for clinical trial design to detect significant differences over one and two years. Highlights • The expected atrophy was shown in the frontal lobes and anterior temporal regions. • Subcortical structures were notably affected in our bvFTD cohort. • Ventricles and sulci within frontotemporal regions were larger in the bvFTD cohort. • Ventricles and sulci showed significant enlargement and over a one-year period. • Ventricular expansion was the most prominent differentiator of bvFTD from controls.

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    bioRxiv
    Preprint . 2019
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    Europe PubMed Central
    Article . 2019
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    NeuroImage: Clinical
    Article . 2019
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    NeuroImage: Clinical
    Article . Preprint . 2019 . Peer-reviewed
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    Authors: Adrian Danescu; Elisabeth G. Rens; Jaspreet Rehki; Johnathan Woo; +4 Authors

    ABSTRACT In the face, symmetry is established when bilateral streams of neural crest cells leave the neural tube at the same time, follow identical migration routes and then give rise to the facial prominences. However, developmental instability exists, particularly surrounding the steps of lip fusion. The causes of instability are unknown but inability to cope with developmental fluctuations are a likely cause of congenital malformations, such as non-syndromic orofacial clefts. Here, we tracked cell movements over time in the frontonasal mass, which forms the facial midline and participates in lip fusion, using live-cell imaging of chick embryos. Our mathematical examination of cell velocity vectors uncovered temporal fluctuations in several parameters, including order/disorder, symmetry/asymmetry and divergence/convergence. We found that treatment with a Rho GTPase inhibitor completely disrupted the temporal fluctuations in all measures and blocked morphogenesis. Thus, we discovered that genetic control of symmetry extends to mesenchymal cell movements and that these movements are of the type that could be perturbed in asymmetrical malformations, such as non-syndromic cleft lip. This article has an associated ‘The people behind the papers’ interview. Highlighted Article: Live imaging of the chick embryo face followed by mathematical analysis of mesenchymal cell tracks captures novel fluctuations between states of order/disorder as well as symmetry/asymmetry, revealing developmental instabilities that are part of normal morphogenesis.

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    Authors: Prabhjot Dhami; Sravya Atluri; Jonathan C. Lee; Yuliya Knyahnytska; +4 Authors

    Background Theta burst stimulation (TBS) has recently been proposed as a novel treatment for youth depression. However, the impact of TBS on the youth brain and neurophysiological predictors of response to TBS in this population have not been investigated. Methods Cortical reactivity was assessed at baseline and following 2 weeks of bilateral dorsolateral prefrontal cortex (DLPFC) TBS treatment in 16 youth with depression (aged 16-24 years old). In 16 age-matched health youths, cortical reactivity was assessed twice, 2 weeks apart. Transcranial magnetic stimulation (TMS) combined with electroencephalography was used to assess TMS-evoked potentials in bilateral DLPFC, motor cortices, and intraparietal lobules (IPL). Resting-state functional magnetic resonance imaging (fMRI) data was also collected at baseline. Results Left DLPFC pretreatment cortical reactivity, specifically the negativity at 45 ms (i.e., N45), which is related to GABAA neurotransmission, was associated with changes in depressive symptoms. Furthermore, TBS treatment was found to alter the N45 in the right IPL, a site distal to the treatment sites. The magnitude of the right IPL N45 modulation was correlated with the baseline fMRI connectivity between the right IPL and right DLPFC. Conclusions TMS-probed cortical inhibition at the site of TBS application may have potential as a predictor of treatment response in youth depression. Furthermore, pre-treatment functional connectivity may predict the impact of TBS on the neurophysiology of regions distal to the stimulation site. Collectively, these results offer novel neurophysiological insights into the application of TBS for youth depression, which may facilitate its wider use in the youth population.

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    Depression and Anxiety
    Article . 2020 . Peer-reviewed
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      Europe PubMed Central
      Other literature type . 2020
      Data sources: PubMed Central
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Depression and Anxiety
      Article . 2020 . Peer-reviewed
      License: Wiley Online Library User Agreement
      Data sources: Crossref
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907 Research products
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: B. Ogan Mancarci; Lilah Toker; Shreejoy J. Tripathy; Brenna Li; +3 Authors

    Establishing the molecular diversity of cell types is crucial for the study of the nervous system. We compiled a cross-laboratory database of mouse brain cell type-specific transcriptomes from 36 major cell types from across the mammalian brain using rigorously curated published data from pooled cell type microarray and single-cell RNA-sequencing (RNA-seq) studies. We used these data to identify cell type-specific marker genes, discovering a substantial number of novel markers, many of which we validated using computational and experimental approaches. We further demonstrate that summarized expression of marker gene sets (MGSs) in bulk tissue data can be used to estimate the relative cell type abundance across samples. To facilitate use of this expanding resource, we provide a user-friendly web interface at www.neuroexpresso.org. Visual Abstract

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Europe PubMed Central
    Article . 2017
    Data sources: PubMed Central
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    bioRxiv
    Preprint . 2016
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    eNeuro
    Article . Preprint
    License: CC BY
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    eNeuro
    Article . 2017 . Peer-reviewed
    License: CC BY NC SA
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Europe PubMed Central
      Article . 2017
      Data sources: PubMed Central
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      bioRxiv
      Preprint . 2016
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      eNeuro
      Article . Preprint
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      eNeuro
      Article . 2017 . Peer-reviewed
      License: CC BY NC SA
      Data sources: Crossref
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Elena, Choleris; Liisa A M, Galea; Farida, Sohrabji; Karyn M, Frick;

    Abstract Biological differences between males and females are found at multiple levels. However, females have too often been under-represented in behavioral neuroscience research, which has stymied the study of potential sex differences in neurobiology and behavior. This review focuses on the study of sex differences in the neurobiology of social behavior, memory, emotions, and recovery from brain injury, with particular emphasis on the role of estrogens in regulating forebrain function. This work, presented by the authors at the 2016 meeting of the International Behavioral Neuroscience Society, emphasizes varying approaches from several mammalian species in which sex differences have not only been documented, but also become the focus of efforts to understand the mechanistic basis underlying them. This information may provide readers with useful experimental tools to successfully address recently introduced regulations by granting agencies that either require (e.g. the National Institutes of Health in the United States and the Canadian Institutes of Health Research in Canada) or recommend (e.g. Horizon 2020 in Europe) the inclusion of both sexes in biomedical research.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Europe PubMed Central
    Other literature type . 2018
    Data sources: PubMed Central
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Neuroscience & Biobehavioral Reviews
    Article . 2018 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
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