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  • 2020-2024
  • Research data
  • EU
  • ZENODO
  • Neuroinformatics

  • 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: Amoruso, Lucia;

    Understanding object-directed actions performed by others is central to everyday life. This ability is thought to rely on the interaction between the dorsal action observation network (AON) and a ventral object recognition pathway. On this view, the AON would encode action kinematics, and the ventral pathway, the most likely intention afforded by the objects. However, experimental evidence supporting this model is still scarce. Here, we aimed to disentangle the contribution of dorsal vs. ventral pathways to action comprehension by exploiting their differential tuning to lowspatial frequencies (LSFs) and high-spatial frequencies (HSFs). We filtered naturalistic action images to contain only LSF or HSF and measured behavioral performance and corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS). Actions were embedded in congruent or incongruent scenarios as defined by the compatibility between grips and intentions afforded by the contextual objects. Behaviorally, participants were better at discriminating congruent actions in intact than LSF images. This effect was reversed for incongruent actions, with better performance for LSF than intact and HSF. These modulations were mirrored at the neurophysiological level, with greater CSE facilitation for congruent than incongruent actions for HSF and the opposite pattern for LSF images. Finally, only for LSF did we observe CSE modulations according to grip kinematics. While results point to differential dorsal (LSF) and ventral (HSF) contributions to action comprehension for grip and context encoding, respectively, the negative congruency effect for LSF images suggests that object processing may influence action perception not only through ventral-to-dorsal connections, but also through a dorsal-to-dorsal route involved in predictive processing.

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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/
    ZENODO; DRYAD
    Dataset . 2020
    License: CC 0
    Data sources: Datacite; ZENODO
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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/ ZENODO; DRYADarrow_drop_down
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      ZENODO; DRYAD
      Dataset . 2020
      License: CC 0
      Data sources: Datacite; ZENODO
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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: Mergenthaler, Philipp; Hariharan, Santosh; Pemberton, James M.; Lourenco, Corey; +2 Authors

    Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Malinin, Andrey; Athanasopoulos, Andreas; Barakovic, Muhamed; Bach Cuadra, Meritxell; +14 Authors

    This archive contains part 2 of Shift Benchmark on Multiple Sclerosis lesion segmentation data. This dataset is provided by the Shifts Project to enable assessment of the robustness of models to distributional shift and the quality of their uncertainty estimates. This part is contains data collected from several different sources and distributed under a CC BY NC SA 4.0 license. Part 1 of the data is available here. A full description of the benchmark is available in https://arxiv.org/pdf/2206.15407. To find out more about the Shifts Project, please visit https://shifts.ai . {"references": ["Malinin, Andrey et al. (2022). \u00a0Shifts 2.0: Extending The Dataset of Real Distributional Shifts, arXiv:2206.15407"]} This work is supported by the Hasler Foundation, Cambridge University Press and Cambridge Assessment and DeepSea

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    ZENODO
    Dataset . 2022
    License: CC BY NC SA
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY NC SA
    Data sources: Sygma; ZENODO
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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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2022
      License: CC BY NC SA
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2022
      License: CC BY NC SA
      Data sources: Sygma; ZENODO
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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: David, Olivier; Lemaréchal, Jean-Didier; Jedynak, Maciej; Trebaul, Lena; +39 Authors

    F-TRACT atlas release - December 2021 ====================================== The F-TRACT atlas is provided as .csv (comma-separated values) files that can be read in any table editor. In addition, we provide a Matlab routine allowing to read the features of the atlas as Matlab variables. The atlas is provided for free use for research use only, with limited accuracy, which hopefully will improve with subsequent releases. Please cite David et al. (2013) Probabilistic functional tractography of the human cortex, NeuroImage, and Trebaul et al. (2018) Probabilistic functional tractography of the human cortex revisited, NeuroImage, Lemarechal et al. (2022) A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials, Brain, when using the F-TRACT atlas. - f-tract_v2112 : Connectivity probability as well as features describing fibers biophysical properties, estimated from CCEP data recorded in 780 patients, in the AAL, AICHA, Brodmann, Freesurfer, Hammers, HCP-MMP1, Lausanne2008 (resolutions 33, 60, 125, 250, 500) and MarsAtlas parcellation schemes. The CCEP features are: peak and onset latency (LatStart), amplitude, duration, integral, velocity estimated from the onset latency and the fibers distance between the parcels and axonal conduction delays. Synaptic excitatory and inhibitory delays are also provided for each parcel. All features have been estimated separately for patients younger than 15 y.o. (group "0-15") and patients older than 15 y.o. (group "15-100"). - Features maps : Images representing the connectivity probability and response features for all the regions in the Lausanne2008-60 parcellation.

    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/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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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: Canepa, Elisabetta; Condia, Bob; Beighle, Kory; Djebbara, Zakaria; +1 Authors

    This dataset is an output of the ‘Designing Atmospheres: Theory and Science’ Symposium (ATS), an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on March 28, 2023. Speakers: Kory Beighle (Kansas State University), Elisabetta Canepa (University of Genoa | Kansas State University), Bob Condia (Kansas State University), Zakaria Djebbara (Aalborg University | TU Berlin), and Harry Francis Mallgrave (Illinois Institute of Technology). Recent advances in science confirm many of the architects’ deep-rooted intuitions, improving knowledge about the perception of space and the meaning of architectural and urban design. The symposium ‘Designing Atmospheres: Theory and Science‘ presented to an audience of students, educators, architects, and scientists a conversation about the experience of design and building, specifically speaking to the significance of atmospheres, affordances, and emotions. This dataset is made of seven files: no. 1 dataset summary (.pdf) no. 1 symposium poster (.pdf) no. 5 videos containing speakers’ presentations (.mp4) Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (@resonancesproject5777). 'Designing Atmospheres: Theory and Science' Symposium is an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the European Union's Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The RESONANCES project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of the produced and published material reflects only the authors' views. The Research Executive Agency and the European Commission are not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Sygma; Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Sygma; Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Tomaskinova, Judita; Geneletti, Davide; Dicks, Lynn; Grace, Miriam; +5 Authors

    Designing nature-based solutions for multifunctionality

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    ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC 0
      Data sources: ZENODO
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    Authors: Lajous, Hélène; Hilbert, Tom; Roy, Christopher W.; Ledoux, Jean-Baptiste; +3 Authors

    This dataset gathers synthetic T2-weighted magnetic resonance (MR) images generated using FaBiAN, a Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates fast spin echo (FSE) sequences of the developing fetal brain throughout gestation. This dataset is associated with the following paper: Lajous H. et al. (2022) A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN). Scientific Reports. https://doi.org/10.1038/s41598-022-10335-4 This dataset provides images simulated by FaBiAN based on the specific implementation of FSE sequences by two MR vendors (Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE), Siemens Healthcare, and Single-Shot Fast Spin Echo (SS-FSE), GE Healthcare) at 1.5 T or 3 T. Automated brain tissue annotations of the low-resolution series and super-resolution (SR) reconstructions are also included. Works using any of these data should cite the following references: - Lajous, H. et al. A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN). Scientific Reports (2022). https://doi.org/10.1038/s41598-022-10335-4 - Lajous, H., Roy, C. W., Yerly, J. & Bach Cuadra, M. Medical-Image-Analysis-Laboratory/FaBiAN: FaBiAN v1.2 (1.2). Zenodo (2022). https://doi.org/10.5281/zenodo.5471094 - Lajous, H. et al. Dataset A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN). Zenodo (2022). https://doi.org/10.5281/zenodo.6477946 Copyright (c) - All rights reserved. Medical Image Analysis Laboratory - Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland & CIBM Center for Biomedical Imaging. 2022. This work was supported by the Swiss National Science Foundation through grants 182602, 141283 and 173129. We acknowledge the expertise of the CIBM Center for Biomedical Imaging, a Swiss research center of excellence founded and supported by Lausanne University Hospital (CHUV), University of Lausanne (UNIL), Ecole Polytechnique Fédérale de Lausanne (EPFL), University of Geneva (UNIGE) and Geneva University Hospitals (HUG).

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    ZENODO
    Dataset . 2022
    License: CC BY SA
    Data sources: ZENODO
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    ZENODO
    Dataset . 2022
    License: CC BY SA
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY SA
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY SA
      Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY SA
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY SA
      Data sources: ZENODO
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    Authors: Saponaro, Andrea; Gasparri, Federica; Bauer, Daniel; Gross, Christine; +7 Authors

    Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels control spontaneous electrical activity in heart and brain. Binding of cAMP to the cyclic nucleotide-binding domain (CNBD) facilitates channel opening by relieving a tonic inhibition exerted by the CNBD. Despite high resolution structures of the HCN1 channel in the cAMP bound and unbound states, the structural mechanism coupling ligand binding to channel gating is unknown. Here we show that the recently identified helical HCN-domain (HCND) mechanically couples the CNBD and channel voltage sensing domain (VSD), possibly acting as a sliding crank that converts the planar rotational movement of the CNBD into a rotational upward displacement of the VSD. This mode of operation and its impact on channel gating are confirmed by computational and experimental data showing that disruption of critical contacts between the three domains affects cAMP- and voltage-dependent gating in three HCN isoforms. Additional Information Provided external link to software package in all three files. Please follow license terms when using code. 

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    ZENODO; DRYAD
    Dataset . 2020
    License: CC 0
    Data sources: Datacite; ZENODO
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      ZENODO; DRYAD
      Dataset . 2020
      License: CC 0
      Data sources: Datacite; ZENODO
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    Authors: Hardisty, Alex; Addink, Wouter; Glöckler, Falko; Güntsch, Anton; +2 Authors

    Comparison of main roles and responsibilities in the two main categories of administration of a Handle-based PID scheme

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    ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC 0
      Data sources: ZENODO
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    Authors: Tomaskinova, Judita; Dicks, Lynn; Collier, Marcus; Geneletti, Davide; +6 Authors

    Nature-based solutions and environmental justice

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    ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: ZENODO
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      ZENODO
      Dataset . 2020
      License: CC 0
      Data sources: ZENODO
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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: Amoruso, Lucia;

    Understanding object-directed actions performed by others is central to everyday life. This ability is thought to rely on the interaction between the dorsal action observation network (AON) and a ventral object recognition pathway. On this view, the AON would encode action kinematics, and the ventral pathway, the most likely intention afforded by the objects. However, experimental evidence supporting this model is still scarce. Here, we aimed to disentangle the contribution of dorsal vs. ventral pathways to action comprehension by exploiting their differential tuning to lowspatial frequencies (LSFs) and high-spatial frequencies (HSFs). We filtered naturalistic action images to contain only LSF or HSF and measured behavioral performance and corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS). Actions were embedded in congruent or incongruent scenarios as defined by the compatibility between grips and intentions afforded by the contextual objects. Behaviorally, participants were better at discriminating congruent actions in intact than LSF images. This effect was reversed for incongruent actions, with better performance for LSF than intact and HSF. These modulations were mirrored at the neurophysiological level, with greater CSE facilitation for congruent than incongruent actions for HSF and the opposite pattern for LSF images. Finally, only for LSF did we observe CSE modulations according to grip kinematics. While results point to differential dorsal (LSF) and ventral (HSF) contributions to action comprehension for grip and context encoding, respectively, the negative congruency effect for LSF images suggests that object processing may influence action perception not only through ventral-to-dorsal connections, but also through a dorsal-to-dorsal route involved in predictive processing.

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    ZENODO; DRYAD
    Dataset . 2020
    License: CC 0
    Data sources: Datacite; ZENODO
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      ZENODO; DRYAD
      Dataset . 2020
      License: CC 0
      Data sources: Datacite; ZENODO
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    Authors: Mergenthaler, Philipp; Hariharan, Santosh; Pemberton, James M.; Lourenco, Corey; +2 Authors

    Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Malinin, Andrey; Athanasopoulos, Andreas; Barakovic, Muhamed; Bach Cuadra, Meritxell; +14 Authors

    This archive contains part 2 of Shift Benchmark on Multiple Sclerosis lesion segmentation data. This dataset is provided by the Shifts Project to enable assessment of the robustness of models to distributional shift and the quality of their uncertainty estimates. This part is contains data collected from several different sources and distributed under a CC BY NC SA 4.0 license. Part 1 of the data is available here. A full description of the benchmark is available in https://arxiv.org/pdf/2206.15407. To find out more about the Shifts Project, please visit https://shifts.ai . {"references": ["Malinin, Andrey et al. (2022). \u00a0Shifts 2.0: Extending The Dataset of Real Distributional Shifts, arXiv:2206.15407"]} This work is supported by the Hasler Foundation, Cambridge University Press and Cambridge Assessment and DeepSea

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    ZENODO
    Dataset . 2022
    License: CC BY NC SA
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY NC SA
    Data sources: Sygma; ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY NC SA
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY NC SA
      Data sources: Sygma; ZENODO
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    Authors: David, Olivier; Lemaréchal, Jean-Didier; Jedynak, Maciej; Trebaul, Lena; +39 Authors

    F-TRACT atlas release - December 2021 ====================================== The F-TRACT atlas is provided as .csv (comma-separated values) files that can be read in any table editor. In addition, we provide a Matlab routine allowing to read the features of the atlas as Matlab variables. The atlas is provided for free use for research use only, with limited accuracy, which hopefully will improve with subsequent releases. Please cite David et al. (2013) Probabilistic functional tractography of the human cortex, NeuroImage, and Trebaul et al. (2018) Probabilistic functional tractography of the human cortex revisited, NeuroImage, Lemarechal et al. (2022) A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials, Brain, when using the F-TRACT atlas. - f-tract_v2112 : Connectivity probability as well as features describing fibers biophysical properties, estimated from CCEP data recorded in 780 patients, in the AAL, AICHA, Brodmann, Freesurfer, Hammers, HCP-MMP1, Lausanne2008 (resolutions 33, 60, 125, 250, 500) and MarsAtlas parcellation schemes. The CCEP features are: peak and onset latency (LatStart), amplitude, duration, integral, velocity estimated from the onset latency and the fibers distance between the parcels and axonal conduction delays. Synaptic excitatory and inhibitory delays are also provided for each parcel. All features have been estimated separately for patients younger than 15 y.o. (group "0-15") and patients older than 15 y.o. (group "15-100"). - Features maps : Images representing the connectivity probability and response features for all the regions in the Lausanne2008-60 parcellation.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Canepa, Elisabetta; Condia, Bob; Beighle, Kory; Djebbara, Zakaria; +1 Authors

    This dataset is an output of the ‘Designing Atmospheres: Theory and Science’ Symposium (ATS), an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the EU’s Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The symposium was hosted in the College of Architecture, Planning and Design (APDesign), Kansas State University, Manhattan (Kansas, USA), on March 28, 2023. Speakers: Kory Beighle (Kansas State University), Elisabetta Canepa (University of Genoa | Kansas State University), Bob Condia (Kansas State University), Zakaria Djebbara (Aalborg University | TU Berlin), and Harry Francis Mallgrave (Illinois Institute of Technology). Recent advances in science confirm many of the architects’ deep-rooted intuitions, improving knowledge about the perception of space and the meaning of architectural and urban design. The symposium ‘Designing Atmospheres: Theory and Science‘ presented to an audience of students, educators, architects, and scientists a conversation about the experience of design and building, specifically speaking to the significance of atmospheres, affordances, and emotions. This dataset is made of seven files: no. 1 dataset summary (.pdf) no. 1 symposium poster (.pdf) no. 5 videos containing speakers’ presentations (.mp4) Recorded videos of each lecture are also available on the RESONANCES project website (www.resonances-project.com/harvest) and its YouTube channel (@resonancesproject5777). 'Designing Atmospheres: Theory and Science' Symposium is an Interfaces event of the Academy of Neuroscience for Architecture (ANFA), sponsored by the European Union's Horizon 2020 MSCA Program — RESONANCES Project, the Perkins Eastman Studio, and the KSTATE APDesign. The RESONANCES project received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 101025132. The content of the produced and published material reflects only the authors' views. The Research Executive Agency and the European Commission are not responsible for any use that may be made of the information it contains.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Sygma; Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO; Sygma
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