Layer-fMRI VASO worldwide

This blog post gives an overview of the scientific network of researchers that are using the VASO (vascular space occupancy) for applications in layer-fMRI. I tried to give an overview of all layer-fMRI VASO papers published so far and provide a map of all layer-fMRI VASO labs around the globe.

Acknowledgements

This overview blog post is partly motivated as an education for grant reviewers that think that layer-fMRI is merely done by “one guy in one lab”.

Popularity of layer-fMRI VASO across years and countries

The first layer-fMRI VASO studies in humans were presented in 2014/2015. In the five years that followed, VASO became a credible contrast for the emerging field of layer-fMRI.

fig7_vaso_worldwide-01-1.png
Temporal evolution of VASO for layer-fMRI studies. The numbers are developing in one direction: ⇑ UP ⇑
As of today (Jan 2020) there are 31 labs around the world that are using layer-fMRI VASO with 25 published layer-fMRI VASO papers in peer-reviewed journals

The vast majority of layer-fMRI VASO research is happening in Europe, followed by Asia. The higher 7T density in USA is not represented in a correspondingly many layer-fMRI VASO studies. This it might be due to the medical-application driven research funding environment.

Google map to browse interactively: https://layerfmri.page.link/VASO_worldwide (in case of missing sites, suggestions are welcome to layerfmri@gmail.com).

Fourty current users of layer-dependent VASO fMRI

  1. Max Planck Institute CBS, Leipzig, Germany: 
    • Daniel Haenelt and Robert Trampel are using VASO (along with GE-BOLD and SE-BOLD) to investigate ocular dominance columns.

      Heanelt.png
      This figure kindly provided by Daniel Haenelt and Robert Trampel
    • Reference: ISMRM 2020, submitted
  2. SFIM, NIMH, NIH, Bethesda, USA:
    • Yuhui Chai and Peter Bandettini are using VASO as a ground truth method to compare it with the VAPER contrast.

      Yuhui.png
      This figure kindly provided by Yuhui Chai
    • Reference: NeuroImage Paper
  3. Cardiff University, Cardiff, UK:
    • Marcello Venzi, Joseph Whittaker, and Kevin Murphy are using high-resolution VASO to investigate the effect of CSF and veins in superficial voxels vs. parenchyma voxels.

      Venti.png
      This figure kindly provided by Marcello Venzi
    • Reference: ISMRM abstract 2019
  4. MBIC, Maastricht University, Netherlands:
    • Renzo Huber and Benedikt Poser are working on sequence approaches to make layer-fMRI VASO easier applicable.

      Huber.png
      Whole brain VASO acquisition for easy applicability in neuroscience studies.
    • Reference: ISMRM abstract 2020, submitted
  5. VA SF, USA: 
    • Alex Beckett and David Feinberg are using VASO as a ‘gold standard’ to compare it to 3D-GRASE.
      Beckett.png

        • This figure is taken from the BioRxiv preprint

      here.

    • Reference: BioArchive Preprint.
  6. Spinoza/UMC, Utrecht/Amsterdam, Netherlands:
    • Icaro Oliviera, Jorien Siero, and Wietske van der Zwaag are using VASO to investigate the linearity of the hemodynamic response at very high resolutions.Screenshot 2020-12-09 at 09.54.25
    • Reference: Oliviera NeuroImage 2020
  7. University of Sheffield: Sheffield, UK:
    • Aneurin Kennerley is using layer-dependent VASO to validate it against iron-based contrast agent fMRI in rodents.

      Kennerley_1
      Figure kindly provided by Aneurin Kennerley.
    • Reference: ISMRM abstract 2017
  8. University of York, York, UK 
    • Aneurin Kennerley and Renzo Huber are working on layer-fMRI VASO to make it doable at 3T.

      Kennerley_2.png
      Figure taken from Kennerley’s submitted ISMRM abstract (2020).
    • Reference: ISMRM abstract 2020, submitted
  9. Lab of Brain and Cognition, NIMH, NIH, Bethesda, USA
    • Eli Merriam and Zvi Roth use sub-millimeter VASO to map the visual topography.

      Eli.png
      This figure is kindly provided by Eli Merriam.
    • Reference data shown here
  10. Martinos Center, MGH, Boston, USA:
    • Saskia Bollmann and Jonathan Polimeni use sub-millimeter VASO to investigate the temporal features of CBV across depth.

      Bollmann.png
      This figure is kindly provided by Saskia Bollmann.
    • Reference data shown here
  11. University of Queensland, Australia:
    • Atena Akbari and Markus Barth are investigating the layer-dependent fMRI response of VASO in V1.

      Akbari.png
      This figure is kindly provided by Atena Akbari.
    • OHBM abstract 2019
  12. University of Glasgow, Glasgow, UK:
    • Nils Nothnagel, Andrew Morgan, and Jozien Goense implemented a 3D-EPI sequence for layer-dependent VASO imaging.
    • The first layer-fMRI VASO experiments were conducted early 2019.
    • Screenshot 2020-05-07 at 11.36.25.png
      0.6mm VASO during a visual paradigm acquired in Glasgow from Nils Nothnagel and Andrew Morgan
  13. SKKU, Suwon, South Korea:
    • Insub Kim, Won Mok Shim, and Seong Gi Kim are using layer-dependent VASO for orientation decoding across cortical depth.

      Kim.png
      This figure is kindly provided by Insub Kim.
    • Reference data shown here
  14. Max Planck Institute for Biological Cybernetics, Tuebingen, Germany:
  15. University of Nottingham, Nottingham, UK:
    • Rosa Panchuelo and Susan Francis are using ultra-high resolution VASO in order to map the sensory system.
    • The grant is described here
  16. National Institute of Mental Health:
    • Andrew Persichetti, Jason Avery, and Alex Martin are using layer-fMRI VASO to investigate the intra-cortical processing of imagined and executed motor actions.

      Persichetti.png
      This figure is kindly provided by Andrew Persichetti.
    • Current Biology paper
  17. CiNet, Osaka, Japan
    • Ikuhiro Kida is using high-resolution VASO to investigate the neuro-vascular coupling features of fMRI.
    • Sequence approved from SIEMENS in Feb 2019, ethical approval received in fall 2019.

      Screenshot 2020-03-20 at 17.53.10
      Double stripe of tapping induced activity.
  18. NYU, New York USA
    • Hanzhang Lu performed the first sub-millimeter VASO when he was graduating and leaving to NYC at that time.
      donahue.png

        • This figure from Hanzhang Lu’s scans are taken from a paper published by Donahue

      2006 MRM.

    • References 1, and 2.
  19. University Magdeburg
    • Esther Kuehn and Oliver Speck are piloting layer-fMRI VASO to investigate sensory-motor representations across cortical depth.

      Kuehn.png
      Figure credits: Esther Kuehn
    • Pilot study in June 2018
  20. Christian Doppler Klinik, Salzburg
    • Martin Kronbichler is investigating the usability of layer-dependent VASO at 3T.

      Kronbichler.png
      Figure credits: Martin Kronbichler
    • Reference data shown here
  21. NIPS, Okazaki, Japan
    • Masaki Fukunaga is using layer-fMRI VASO in the sensory motor system, in the insual, and the visual cortex.

      Fukunaga.png
      Figure credits: Masaki Fukunaga
    • Layer-fMRI VASO research agreement
  22. Okayama University Hospital, Japan
    • Yinghua Yu is using layer-dependent VASO with predictive coding in the sensory system.

      Yu.png
      This figure is kindly provided by Yinghua Yu
    • Reference
  23. Max-Delbrueck-Centrum, Berlin, Germany
    • Henning Reimann and Jurjen Heij are investigating layer-dependent processing of pain.
    • Screenshot 2020-05-19 at 16.01.56
      Example activation map from Henning Reimann at 0.8×0.8×0.7mm
  24. Zhejiang University, China
  25. Institute of Biophysics, Chinese Academy of Sciences, China
  26. University of Cambridge, UK 
    • Bingjiang Lyu and Chris Roger are working on the implementation of layer-fMRI VASO for application in speech fMRI.
  27. University of Cambridge, UK 
    • Catarina Rua and Zoe Kourtzi are setting up layer-dependent VASO in the visual cortex.
    • Screenshot 2020-05-09 at 10.43.05.png
      0.8mm VASO data from Cat Rua
  28. Oxford Centre for Functional MRI of the Brain, UK
    • James Kolasinsky and Olivia Viessmann acquired high-resolution VASO with SMS readout for application in the somatosensory system.
  29. Kennedy Krieger Institute, Johns Hopkins University, Baltimore, USA
    • Jun Hua developed a high-resolution 7T VASO sequence and is applying it with working memory tasks in dementia patients.

      hua-e1578059635188.png
      This figure is taken from Hua’s MRM 2012 paper.
    • Reference
  30. Uniklinik Freiburg, Germany.
    • Burak Akin and Ali Özen are acquiring layer-fMRI VASO at 3T with micro-stip RF-coils.
  31. Klinikum Erlangen, Germany
    • Velentin Riedl, as collaborator from TUM, used VASO for quantitative fMRI at 7T.
  32. DZNE, Bonn, Germany:
    • Ruediger Strinberg and Tony Stoecker implemented a VASO sequence with segmented 3D-EPI readout for SIEMENS VE systems.

      Strinberg
      Data of this figure were acquired with Stirnberg’s sequence at the 7T Terra at NIH.
  33. Essen/Donders, Germany
    • Victor Pfaffenrot and Oliver Kraft are using MAGEC VASO for layer-fMRI
  34. TUM, Munich, Germany
    • Valentin Riedl is using VASO to avoid administration of contrast agents.
  35. Weizmann institute, Israel
    • Edna Furman-Haran uses VE VASO on the Terra
  36. Aarhus University, Denmark
    • Torben Lund is using layer-fMRI VASO at 3T.
  37. Berkeley, USA
    • Prof. Feinberg is using layer-fMRI VASO on his Terra. This is to compare it with the results after the Terra is upgraded to the next-generation scanner.
  38. MPI Tuebingen, Germany,
    • Vinod Kumar requested VASO for 9.4T scanning.
  39. UC-Davis, USA
    • Audrey Fan is using 3D-EPI VASO for vascular physiology mapping.
  40. NTNU, Trondheim, Norway
    • Desmond Tse and Pål Erik Goa are ramping up a layer-fMRI VASO grant for application in aging population.
    • Reference

Twenty seven peer-reviewed journal papers showing data with layer-dependent VASO

  1. Donahue, Manus J. et al. 2006. “Theoretical and Experimental Investigation of the VASO Contrast Mechanism.” Magnetic Resonance in Medicine 56(6): 1261–73. https://doi.org/10.1002/mrm.21072.

  2. Jin, Tao, and Seong Gi Kim. 2006. “Spatial Dependence of CBV-FMRI: A Comparison between VASO and Contrast Agent Based Methods.” Annual International Conference of the IEEE Engineering in Medicine and Biology – Proceedings (10): 25–28.

  3. Jin, Tao, and Seong Gi Kim. 2008. “Improved Cortical-Layer Specificity of Vascular Space Occupancy FMRI with Slab Inversion Relative to Spin-Echo BOLD at 9.4 T.” NeuroImage 40(1): 59–67.

  4. Goense, Jozien B M, Hellmut Merkle, and Nikos K. Logothetis. 2012. “High-Resolution FMRI Reveals Laminar Differences in Neurovascular Coupling between Positive and Negative BOLD Responses.” Neuron 76(3): 629–39. http://dx.doi.org/10.1016/j.neuron.2012.09.019 (January 17, 2014).

  5. Bandettini, Peter A. 2012. “The BOLD Plot Thickens: Sign- and Layer-Dependent Hemodynamic Changes with Activation.” Neuron 76(3): 468–69. http://dx.doi.org/10.1016/j.neuron.2012.10.026.

  6. Huber, Laurentius et al. 2014. “Slab-Selective, BOLD-Corrected VASO at 7 Tesla Provides Measures of Cerebral Blood Volume Reactivity with High Signal-to-Noise Ratio.” Magnetic Resonance in Medicine 72(1): 137–48. https://doi.org/10.1002/mrm.24916.

  7. Huber, Laurentius et al. 2014. “Investigation of the Neurovascular Coupling in Positive and Negative BOLD Responses in Human Brain at 7T.” NeuroImage 97: 349–62. http://dx.doi.org/10.1016/j.neuroimage.2014.04.022.

  8. Huber, Laurentius et al. 2015. “Cortical Lamina-Dependent Blood Volume Changes in Human Brain at 7T.” NeuroImage 107: 23–33. http://dx.doi.org/10.1016/j.neuroimage.2014.11.046.

  9. Guidi, Maria et al. 2016. “Lamina-Dependent Calibrated BOLD Response in Human Primary Motor Cortex.” NeuroImage 141: 250–61. http://dx.doi.org/10.1016/j.neuroimage.2016.06.030.

  10. Huber, Laurentius et al. 2016. “Functional Cerebral Blood Volume Mapping with Simultaneous Multi-Slice Acquisition.” NeuroImage 125: 1159–68.

  11. Donahue, Manus J., Meher R. Juttukonda, and Jennifer M. Watchmaker. 2017. “Noise Concerns and Post-Processing Procedures in Cerebral Blood Flow (CBF) and Cerebral Blood Volume (CBV) Functional Magnetic Resonance Imaging.” NeuroImage 154: 43–58. http://dx.doi.org/10.1016/j.neuroimage.2016.09.007.

  12. Kazan, Samira M. et al. 2017. “Physiological Basis of Vascular Autocalibration (VasA): Comparison to Hypercapnia Calibration Methods.” Magnetic Resonance in Medicine 78(3): 1168–73.

  13. Huber, Laurentius et al. 2017. “High-Resolution CBV-FMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1.” Neuron 96(6): 1253-1263.e7. https://doi.org/10.1016/j.neuron.2017.11.005.

  14. Dumoulin, Serge O. 2017. “Layers of Neuroscience.” Neuron 96(6): 1205–6. https://doi.org/10.1016/j.neuron.2017.12.004.

  15. Poser, Benedikt A, and Kawin Setsompop. 2018. “Pulse Sequences and Parallel Imaging for High Spatiotemporal Resolution MRI at Ultra-High Field.” NeuroImage 168: 101–18. http://dx.doi.org/10.1016/j.neuroimage.2017.04.006.

  16. Huber, Laurentius et al. 2018. “Techniques for Blood Volume FMRI with VASO: From Low-Resolution Mapping towards Sub-Millimeter Layer-Dependent Applications.” NeuroImage 164(November): 131–43. https://doi.org/10.1016/j.neuroimage.2016.11.039.

  17. Huber, Laurentius et al. 2018. “Ultra-High Resolution Blood Volume FMRI and BOLD FMRI in Humans at 9.4T: Capabilities and Challenges.” NeuroImage 178(June): 769–79. https://doi.org/10.1016/j.neuroimage.2018.06.025.

  18. Finn, Emily S et al. 2019. “Layer-Dependent Activity in Human Prefrontal Cortex during Working Memory.” Nature Neuroscience 22: 1687–1695. https://doi.org/10.1038/s41593-019-0487-z.

  19. Chai, Yuhui et al. 2019. “Integrated VASO and Perfusion Contrast: A New Tool for Laminar Functional MRI.” NeuroImage: 116358. https://doi.org/10.1016/j.neuroimage.2019.116358.

  20. Huber, Laurentius, Kâmil Uludağ, and Harald E. Möller. 2019. “Non-BOLD Contrast for Laminar FMRI in Humans: CBF, CBV, and CMRO2.” NeuroImage (July): 1–19. https://doi.org/10.1016/j.neuroimage.2017.07.041.

  21. Persichetti, Andrew Steven et al. 2020. “Current Biology Layer-Specific Contributions to Imagined and Executed Hand Movements in Human Primary Motor Cortex.” Current Biology: preprint re-submitted. https://dx.doi.org/10.2139/ssrn.3482808.

  22. Beckett, Alexander et al. 2019. “Comparison of BOLD and CBV Using 3D EPI and 3D GRASE for Cortical Layer FMRI at 7T .” bioRxiv. https://doi.org/10.1101/778142

  23. Yu, Yinghua et al. 2019. “Layer-Specific Activation of Sensory Input and Predictive Feedback in the Human Primary Somatosensory Cortex.” Science Advances 5(5): eaav9053. https://doi.org/10.1126/sciadv.aav9053.

  24. Yang, Jiajia, and Yinghua Yu. 2019. “超高磁場・高精細レイヤー FMRI 技術による ヒト大脳皮質の層別活動の可視化.” Medical Science Digest 45(418): 418–21. http://hokuryukan-ns.co.jp/cms/books/medical-science-digest 2019年 6月臨時増刊号/.

  25. Huber, Laurentius et al. 2020. “Sub-Millimeter FMRI Reveals Multiple Topographical Digit Representations That Form Action Maps in Human Motor Cortex.” NeuroImage 208: 116463. https://www.biorxiv.org/content/10.1101/457002v2.

  26. Guidi, M et al. 2020. “Cortical Laminar Resting-State Fluctuations Scale with the Hypercapnic Bold Response.” HBM: ahead of print. https://doi.org/10.1002/hbm.24926.

  27. Huber, Laurentius et al. 2020. “Layer-Dependent Functional Connectivity Methods.” Zenodo: 3635355. https://doi.org/10.5281/zenodo.3635355.

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