How Much Cortex Can a Vein Drain? Downstream Dilution of Activation-Related Cerebral Blood Oxygenation Changes

Measuring the thickness of the human cerebral cortex from magnetic resonance images

Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,995

The Fourth Dimension of Life: Fractal Geometry and Allometric Scaling of Organisms

West, G. B., Brown, J. H., & Enquist, B. J. (1999) · Science · doi:10.1126/science.284.5420.1677 · Cited by 1,718 · cited 1×

Mr contrast due to intravascular magnetic susceptibility perturbations

Boxerman, J. L., Hamberg, L. M., Rosen, B. R., & Weisskoff, R. M. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340412 · Cited by 1,009

The Human Brain

Duvernoy, H. M. (1999) · Springer eBooks · doi:10.1007/978-3-7091-6792-2 · Cited by 759

Blood velocity and volumetric flow rate in human retinal vessels.

Riva, C. E., Grunwald, J. E., Sinclair, S. H., & Petrig, B. L. (1985) · PubMed · Cited by 441

Identification of vascular structures as a major source of signal contrast in high resolution 2D and 3D functional activation imaging of the motor cortex at l.5T preliminary results

Lai, S., Hopkins, A. L., Haacke, E. M., Li, D., Wasserman, B. A., Buckley, P., Friedman, L., Meltzer, H., Hedera, P., & Friedland, R. (1993) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910300318 · Cited by 390

Blood Flow in the Cerebral Capillary Network: A Review Emphasizing Observations with Intravital Microscopy

Hudetz, A. G. (1997) · Microcirculation · doi:10.3109/10739689709146787 · Cited by 237

Diffusion weighted fMRI at 1.5 T

Song, A. W., Wong, E. C., Tan, S. G., & Hyde, J. S. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910350204 · Cited by 208

Microvascular blood flow: evidence indicating a cubic dependence on arteriolar diameter

MAYROVITZ, H. N., & Roy, J. (1983) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.1983.245.6.h1031 · Cited by 149

THE EVIDENCE FOR A CEREBRAL VASCULAR MECHANISM IN EPILEPSY

Penfield, W. G. (1933) · Annals of Internal Medicine · doi:10.7326/0003-4819-7-3-303 · Cited by 149

Techniques for imaging neuroscience

Turner, R., & Jones, T. (2003) · British Medical Bulletin · doi:10.1093/bmb/65.1.3 · Cited by 60

Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course

Sliwinska, M. W., Vitello, S., & Devlin, J. T. (2014) · Journal of Visualized Experiments · doi:10.3791/51735 · Cited by 78

Proceedings of the Third International Workshop on Advances in Electrocorticography

Ritaccio, A. L., Beauchamp, M. S., Bosman, C. A., Brunner, P., Chang, E. F., Crone, N. E., Gunduz, A., Gupta, D., Knight, R. T., Leuthardt, E. C., et al. (2012) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2012.09.016 · Cited by 56

New acquisition techniques and their prospects for the achievable resolution of fMRI

Bollmann, S., & Barth, M. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101936 · Cited by 57

A NO way to BOLD?: Dietary nitrate alters the hemodynamic response to visual stimulation

Aamand, R., Dalsgaard, T., Ho, Y.-C. L., Møller, A., Roepstorff, A., & Lund, T. E. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.069 · Cited by 55

Comparison of BOLD and CBV using 3D EPI and 3D GRASE for cortical layer functional MRI at 7 T

Beckett, A. J. S., Dadakova, T., Townsend, J. D., Huber, L., Park, S., & Feinberg, D. A. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28347 · Cited by 55

EEG-fMRI Methods for the Study of Brain Networks during Sleep

Duyn, J. H. (2012) · Frontiers in Neurology · doi:10.3389/fneur.2012.00100 · Cited by 61

Using forward calculations of the magnetic field perturbation due to a realistic vascular model to explore the BOLD effect

Marques, J. P., & Bowtell, R. W. (2007) · NMR in Biomedicine · doi:10.1002/nbm.1224 · Cited by 49

What the success of brain imaging implies about the neural code

Guest, O., & Love, B. C. (2017) · eLife · doi:10.7554/elife.21397 · Cited by 53

Reducing the unwanted draining vein BOLD contribution in fMRI with statistical post-processing methods

Nencka, A. S., & Rowe, D. B. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.075 · Cited by 49

The present and the future of microstructure MRI: From a paradigm shift to normal science

Novikov, D. S. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108947 · Cited by 52

Spatial specificity of the functional MRI blood oxygenation response relative to neuronal activity

Chaimow, D., Yacoub, E. S., Uǧurbil, K., & Shmuel, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.077 · Cited by 48

Investigation of BOLD fMRI resonance frequency shifts and quantitative susceptibility changes at 7 T

Bianciardi, M., van Gelderen, P., & Duyn, J. H. (2013) · Human Brain Mapping · doi:10.1002/hbm.22320 · Cited by 46

Intracortical depth analyses of frequency-sensitive regions of human auditory cortex using 7T fMRI

Ahveninen, J., Chang, W., Huang, S., Keil, B. R., Kopčo, N., Rossi, S., Bonmassar, G., Witzel, T., & Polimeni, J. R. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.010 · Cited by 45

A temporal decomposition method for identifying venous effects in task-based fMRI

Kay, K., Jamison, K. W., Zhang, R., & Uǧurbil, K. (2020) · Nature Methods · doi:10.1038/s41592-020-0941-6 · Cited by 45

Sub-millimetre resolution laminar fMRI using Arterial Spin Labelling in humans at 7 T

Kashyap, S., Ivanov, D., Havlíček, M., Huber, L., Poser, B. A., & Uludaǧ, K. (2021) · PLoS ONE · doi:10.1371/journal.pone.0250504 · Cited by 45

High resolution atlas of the venous brain vasculature from 7 T quantitative susceptibility maps

Huck, J., Wanner, Y., Fan, A. P., Jäger, A., Grahl, S., Schneider, U., Villringer, A., Steele, C. J., Tardif, C. L., Bazin, P., et al. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01919-4 · Cited by 44

Evidencing a place for the hippocampus within the core scene processing network

Hodgetts, C. J., Shine, J. P., Lawrence, A. D., Downing, P. E., & Graham, K. S. (2016) · Human Brain Mapping · doi:10.1002/hbm.23275 · Cited by 48

Functional Magnetic Resonance Imaging of the Spinal Cord: Current Status and Future Developments

Cohen‐Adad, J. (2016) · Seminars in Ultrasound CT and MRI · doi:10.1053/j.sult.2016.07.007 · Cited by 43

Functional Connectivity Patterns of Visual Cortex Reflect its Anatomical Organization

Genç, E., Schölvinck, M. L., Bergmann, J., Singer, W., & Kohler, A. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv175 · Cited by 40

Comparing Like with Like: The Power of Knowing Where You Are

Turner, R., & Geyer, S. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0261 · Cited by 41

Layer-specific connectivity revealed by diffusion-weighted functional MRI in the rat thalamocortical pathway

Nunes, D., Ianuș, A., & Shemesh, N. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.09.050 · Cited by 37

Impact of prospective motion correction, distortion correction methods and large vein bias on the spatial accuracy of cortical laminar fMRI at 9.4 Tesla

Bause, J., Polimeni, J. R., Stelzer, J., In, M., Ehses, P., Fernandez, P. K., Aghaeifar, A., Lacosse, E., Pohmann, R., & Scheffler, K. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116434 · Cited by 41

Comparison of BOLD fMRI and MEG characteristics to vibrotactile stimulation

Tuunanen, P. I., Kavec, M., Jousmäki, V., Usenius, J., Hari, R., Salmelin, R. H., & Kauppinen, R. A. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00256-8 · Cited by 39

Seeing patterns through the hemodynamic veil — The future of pattern-information fMRI

Formisano, E., & Kriegeskorte, N. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.078 · Cited by 38

Decreases in ADC observed in tissue areas during activation in the cat visual cortex at 9.4 T using high diffusion sensitization

Yacoub, E. S., Uludaǧ, K., Uǧurbil, K., & Harel, N. (2008) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2008.01.046 · Cited by 38

Contribution of animal models toward understanding resting state functional connectivity

Pais‐Roldán, P., Matéo, C., Pan, W., Acland, B. T., Kleinfeld, D., Snyder, L. H., Yu, X., & Keilholz, S. D. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118630 · Cited by 35

Fast optical signals in the sensorimotor cortex: General Linear Convolution Model applied to multiple source–detector distance-based data

Chiarelli, A. M., Romani, G. L., & Merla, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.021 · Cited by 36

Dynamic hysteresis between gradient echo and spin echo attenuations in dynamic susceptibility contrast imaging

Xu, C., Kiselev, V. G., Möller, H. E., & Fiebach, J. B. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24326 · Cited by 36

Interactions between hemodynamic responses to scanner acoustic noise and auditory stimuli in functional magnetic resonance imaging

Langers, D. R. M., van Dijk, P., & Backes, W. H. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20315 · Cited by 36

Brain–heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field

Chang, C., Raven, E. P., & Duyn, J. H. (2016) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2015.0188 · Cited by 39

Probing neuronal activation by functional quantitative susceptibility mapping under a visual paradigm: A group level comparison with BOLD fMRI and PET

Özbay, P. S., Warnock, G., Rossi, C., Kuhn, F. P., Akın, B., Pruessmann, K. P., & Nanz, D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.013 · Cited by 35

Investigation of brain hemodynamic changes induced by active and passive movements: A combined arterial spin labeling–BOLD fMRI study

Galazzo, I. B., Storti, S. F., Formaggio, E., Pizzini, F. B., Fiaschi, A., Beltramello, A., Bertoldo, A., & Manganotti, P. (2013) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24432 · Cited by 35

Gradient‐echo and spin‐echo blood oxygenation level–dependent functional MRI at ultrahigh fields of 9.4 and 15.2 Tesla

Han, S., Son, J. P., Cho, H., Park, J., & Kim, S. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27457 · Cited by 34

Cortical laminar resting‐state signal fluctuations scale with the hypercapnic blood oxygenation level‐dependent response

Guidi, M., Huber, L., Lampe, L., Merola, A., Ihle, K., & Möller, H. E. (2020) · Human Brain Mapping · doi:10.1002/hbm.24926 · Cited by 34

Improved sensitivity and microvascular weighting of 3T laminar fMRI with GE-BOLD using NORDIC and phase regression

Knudsen, L., Bailey, C. J., Blicher, J. U., Yang, Y. T., Zhang, P., & Lund, T. E. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120011 · Cited by 34

Give Me a Sign: Decoding Complex Coordinated Hand Movements Using High-Field fMRI

Bleichner, M. G., Jansma, J. M., Sellmeijer, J., Raemaekers, M. A. H., & Ramsey, N. F. (2013) · Brain Topography · doi:10.1007/s10548-013-0322-x · Cited by 33

3-D chamfer distances and norms in anisotropic grids

Fouard, C., & Malandain, G. (2004) · Image and Vision Computing · doi:10.1016/j.imavis.2004.06.009 · Cited by 33

Determining laminar neuronal activity from BOLD fMRI using a generative model

Uludaǧ, K., & Havlíček, M. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102055 · Cited by 35

Presurgical Mapping of Verbal Language in Brain Tumors with Functional MR Imaging and MR Tractography

Bizzi, A. (2009) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2009.08.010 · Cited by 32

The human social cognitive network contains multiple regions within the amygdala

Edmonds, D., Salvo, J. J., Anderson, N. L., Lakshman, M., Yang, Q., Kay, K., Zelano, C., & Braga, R. M. (2024) · Science Advances · doi:10.1126/sciadv.adp0453 · Cited by 35

Mesoscopic in vivo human T 2 * dataset acquired using quantitative MRI at 7 Tesla

Gülban, Ö. F., Bollmann, S., Huber, L., Wagstyl, K., Goebel, R., Poser, B. A., Kay, K., & Ivanov, D. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119733 · Cited by 31

Recent Advances in High-Resolution MR Application and Its Implications for Neurovascular Coupling Research

Harel, N., Bolan, P. J., Turner, R., Uǧurbil, K., & Yacoub, E. S. (2010) · Frontiers in Neuroenergetics · doi:10.3389/fnene.2010.00130 · Cited by 35

Water-diffusion slowdown in the human visual cortex on visual stimulation precedes vascular responses

Kohno, S., Sawamoto, N., Urayama, S.-I., Aso, T., Aso, K., Seiyama, A., Fukuyama, H., & Le Bihan, D. (2009) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2009.45 · Cited by 30

Statistical Maps for EEG Dipolar Source Localization

Bénar, C., Gunn, R. N., Grova, C., Champagne, B., & Gotman, J. (2005) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.841263 · Cited by 30

Reliability of the depth-dependent high-resolution BOLD hemodynamic response in human visual cortex and vicinity

Kim, J. H., & Ress, D. B. (2017) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2017.01.019 · Cited by 32

Reliability of task-specific neuronal activation assessed with functional PET, ASL and BOLD imaging

Rischka, L., Godbersen, G. M., Pichler, V., Michenthaler, P., Klug, S., Klöbl, M., Ritter, V., Wadsak, W., Hacker, M., Kasper, S. F., et al. (2021) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x211020589 · Cited by 29

Surgically Relevant Localization of the Central Sulcus With High-Density Somatosensory-Evoked Potentials Compared With Functional Magnetic Resonance Imaging

Lascano, A. M., Grouiller, F., Genetti, M., Spinelli, L., Seeck, M., Schaller, K., & Michel, C. M. (2014) · Neurosurgery · doi:10.1227/neu.0000000000000298 · Cited by 29

Mapping and characterization of positive and negative BOLD responses to visual stimulation in multiple brain regions at 7T

Jorge, J., Figueiredo, P., Rolf Gruetter, A., & van der Zwaag, W. (2018) · Human Brain Mapping · doi:10.1002/hbm.24012 · Cited by 28

Functional Mapping of the Human Visual Cortex with Intravoxel Incoherent Motion MRI

Federau, C., O’Brien, K., Birbaumer, A., Meuli, R. A., Hagmann, P., & Maeder, P. P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117706 · Cited by 29

Investigations on maladaptive plasticity in the sensorimotor cortex of unilateral upper limb CRPS I patients

Pfannmöller, J. P., Strauß, S., Langner, I., Usichenko, T. I., & Lotze, M. (2019) · Restorative Neurology and Neuroscience · doi:10.3233/rnn-180886 · Cited by 27

Are brain currents detectable by means of low-field NMR? A phantom study

Höfner, N., Albrecht, H.-H., Cassara, A. M., Curio, G., Hartwig, S., Haueisen, J., Hilschenz, I., Körber, R., Martens, S., Scheer, H.-J., et al. (2011) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2011.07.009 · Cited by 27

Increasing specificity in functional magnetic resonance imaging by estimation of vessel size based on changes in blood oxygenation

Jochimsen, T. H., & Möller, H. E. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.050 · Cited by 27

SEVEN TOPICS IN FUNCTIONAL MAGNETIC RESONANCE IMAGING

Bandettini, P. A. (2009) · Journal of Integrative Neuroscience · doi:10.1142/s0219635209002186 · Cited by 28

Validation and optimization of hypercapnic-calibrated fMRI from oxygen-sensitive two-photon microscopy

Gagnon, L., Sakadžić, S., Lesage, F., Pouliot, P., Dale, A. M., Devor, A., Buxton, R. B., & Boas, D. A. (2016) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2015.0359 · Cited by 25

Advances in High-Field BOLD fMRI

Barth, M., & Poser, B. A. (2011) · Materials · doi:10.3390/ma4111941 · Cited by 31

On the numerically predicted spatial BOLD fMRI specificity for spin echo sequences

Pflugfelder, D., Vahedipour, K., Uludaǧ, K., Shah, N. J., & Stöcker, T. (2011) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2011.07.015 · Cited by 27

Ultra-High Field Imaging of Human Visual Cognition

Jia, K., Goebel, R., & Kourtzi, Z. (2023) · Annual Review of Vision Science · doi:10.1146/annurev-vision-111022-123830 · Cited by 28

Leveraging ultra-high field (7T) MRI in psychiatric research

Calabro, F. J., Parr, A. C., Sydnor, V. J., Hetherington, H. P., Prasad, K. M. R., Ibrahim, T. S., Sarpal, D. K., Famalette, A., Verma, P., & Luna, B. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01980-6 · Cited by 29

Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential

Boubela, R. N., Kalcher, K., Našel, C., & Moser, E. (2014) · Frontiers in Physics · doi:10.3389/fphy.2014.00001 · Cited by 27

Tailored haemodynamic response function increases detection power of fMRI in awake dogs (Canis familiaris)

Boch, M., Karl, S., Sladky, R., Huber, L., Lamm, C., & Wagner, I. C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117414 · Cited by 26

Point-spread function of the BOLD response across columns and cortical depth in human extra-striate cortex

Fracasso, A., Dumoulin, S. O., & Petridou, N. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102034 · Cited by 26

Non-Neural Factors Influencing BOLD Response Magnitudes within Individual Subjects

Kurzawski, J. W., Gülban, Ö. F., Jamison, K. W., Winawer, J. A., & Kay, K. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.2532-21.2022 · Cited by 29

Advantages of using multiple-echo image combination and asymmetric triangular phase masking in magnetic resonance venography at 3 T

Brainovich, V., Sabatini, U., & Hagberg, G. E. (2008) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2008.05.006 · Cited by 26

Functional cerebral blood volume mapping with simultaneous multi-slice acquisition

Huber, L., Ivanov, D., Guidi, M., Turner, R., Uludaǧ, K., Möller, H. E., & Poser, B. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.082 · Cited by 25

Linear systems analysis for laminar fMRI: Evaluating BOLD amplitude scaling for luminance contrast manipulations

van Dijk, J. A., Fracasso, A., Petridou, N., & Dumoulin, S. O. (2020) · Scientific Reports · doi:10.1038/s41598-020-62165-x · Cited by 25

Validating layer-specific VASO across species

Huber, L., Poser, B. A., Kaas, A. L., Fear, E. J., Dresbach, S., Berwick, J., Goebel, R., Turner, R., & Kennerley, A. J. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118195 · Cited by 24

Vascular changes after stroke in the rat: a longitudinal study using optimized magnetic resonance imaging

Boehm‐Sturm, P., Farr, T. D., Adamczak, J. M., Jikeli, J. F., Mengler, L., Wiedermann, D., Kallur, T., Kiselev, V. G., & Hoehn, M. (2013) · Contrast Media & Molecular Imaging · doi:10.1002/cmmi.1534 · Cited by 24

MRI from A to Z: A Definitive Guide for Medical Professionals

Liney, G. P. (2010) · Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) · doi:10.1007/978-1-84996-135-6 · Cited by 24

Laminar fMRI using T2-prepared multi-echo FLASH

Pfaffenrot, V., Voelker, M. N., Kashyap, S., & Koopmans, P. J. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118163 · Cited by 23

High resolution SE-fMRI in humans at 3 and 7 T using a motor task

Schäfer, A., van der Zwaag, W., Francis, S., Head, K. E., Gowland, P. A., & Bowtell, R. W. (2007) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-007-0099-6 · Cited by 23

Somatosensory BOLD fMRI reveals close link between salient blood pressure changes and the murine neuromatrix

Reimann, H. M., Todiraş, M., Hodge, R., Huelnhagen, T., Millward, J. M., Turner, R., Seeliger, E., Bäder, M., Pohlmann, A., & Niendorf, T. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.02.002 · Cited by 23

Origins of 1/f-like tissue oxygenation fluctuations in the murine cortex

Zhang, Q., Gheres, K. W., & Drew, P. J. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001298 · Cited by 24

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

Faes, L. K., Martino, F. D., & Huber, L. (2023) · PLoS ONE · doi:10.1371/journal.pone.0280855 · Cited by 22

Multi-channel NIRS of the primary motor cortex to discriminate hand from foot activity

Koenraadt, K. L. M., Duysens, J., Smeenk, M., & Keijsers, N. L. W. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/4/046010 · Cited by 22

Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration

Blinowska, K. J., Müller-Putz, G., Kaiser, V., Astolfi, L., Vanderperren, K., Huffel, S. V., & Lemieux, L. (2009) · Computational Intelligence and Neuroscience · doi:10.1155/2009/813607 · Cited by 22

High-resolution fMRI investigations of the fingertip somatotopy and variability in BA3b and BA1 of the primary somatosensory cortex

Pfannmöller, J. P., Greiner, M., Balasubramanian, M., & Lotze, M. (2016) · Neuroscience · doi:10.1016/j.neuroscience.2016.10.036 · Cited by 22

Relative latency and temporal variability of hemodynamic responses at the human primary visual cortex

Lin, F., Polimeni, J. R., Lin, J.-F. L., Tsai, K. W., Chu, Y.-H., Wu, P., Li, Y.-T., Hsu, Y.-C., Tsai, S., & Kuo, W. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.041 · Cited by 23

Modelling the depth‐dependent VASO and BOLD responses in human primary visual cortex

Akbari, A., Bollmann, S., Ali, T., & Barth, M. (2022) · Human Brain Mapping · doi:10.1002/hbm.26094 · Cited by 22

Physiological modeling of the BOLD signal and implications for effective connectivity: A primer

Uludaǧ, K. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120249 · Cited by 21

Calibrated BOLD using direct measurement of changes in venous oxygenation

Driver, I. D., Hall, E. L., Wharton, S., Pritchard, S. E., Francis, S., & Gowland, P. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.08.045 · Cited by 21

Regional reproducibility of calibrated BOLD functional MRI: Implications for the study of cognition and plasticity

Krieger, S. N., Gauthier, C. J., Ivanov, D., Huber, L., Roggenhofer, E., Sehm, B., Turner, R., & Egan, G. F. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.072 · Cited by 21

Gas-free calibrated fMRI with a correction for vessel-size sensitivity

Berman, A. J. L., Mazerolle, E. L., MacDonald, M. E., Blockley, N. P., Luh, W., & Pike, G. B. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.047 · Cited by 21

Do We Need a Human post mortem Whole-Brain Anatomical Ground Truth in in vivo Magnetic Resonance Imaging?

Alkemade, A., Groot, J. M., & Forstmann, B. U. (2018) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2018.00110 · Cited by 21

Skeletonization by blocks for large 3D datasets: application to brain microcirculation

Fouard, C., Malandain, G., Prohaska, S., Westerhoff, M., Cassot, F., Mazel, C., Asselot, D., & Marc-Vergnes, J. P. (2005) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2004.1398481 · Cited by 21

The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR , M , and CBV across cortical depth

Schellekens, W., Bhogal, A. A., Roefs, E. C. A., Báez‐Yáñez, M. G., Siero, J. C. W., & Petridou, N. (2022) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x221133972 · Cited by 20

High-resolution fMRI mapping of ocular dominance layers in cat lateral geniculate nucleus

Zhang, N., Zhu, X., Zhang, Y., Park, J.-K., & Chen, W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.053 · Cited by 20

Investigations on spinal cord fMRI of cats under ketamine

Cohen‐Adad, J., Hoge, R. D., Leblond, H., Xie, G., Beaudoin, G., SONG, A., KRUEGER, G., Doyon, J., Benali, H., & Rossignol, S. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.023 · Cited by 20

Medullary vein architecture modulates the white matter BOLD cerebrovascular reactivity signal response to CO2: Observations from high-resolution T2* weighted imaging at 7T

Bhogal, A. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118771 · Cited by 19

Effects of spatial fMRI resolution on the classification of naturalistic movies

Mandelkow, H., de Zwart, J. A., & Duyn, J. H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.053 · Cited by 22

Investigation of the BOLD and CBV fMRI responses to somatosensory stimulation in awake marmosets ( Callithrix jacchus )

Hirano, Y., Yen, C. C., Liu, J. V., Mackel, J. B., Merkle, H., Nascimento, G., Stefanovic, B., & Silva, A. C. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3864 · Cited by 21

Reduced one‐dimensional modelling and numerical simulation for mass transport in fluids

Köppl, T., Wohlmuth, B. I., & Helmig, R. (2012) · International Journal for Numerical Methods in Fluids · doi:10.1002/fld.3728 · Cited by 19

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping

Zhao, Y., Gao, Y., Zu, Z., Li, M., Schilling, K. G., Anderson, A. W., Ding, Z., & Gore, J. C. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119399 · Cited by 18

Interhemispheric Plasticity Protects the Deafferented Somatosensory Cortex from Functional Takeover After Nerve Injury

Yu, X., & Koretsky, A. P. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0259 · Cited by 18

Variability of fMRI‐response patterns at different spatial observation scales

Ball, T., Breckel, T. P. K., Mutschler, I., Aertsen, A., Schulze‐Bonhage, A., Hennig, J., & Speck, O. (2011) · Human Brain Mapping · doi:10.1002/hbm.21274 · Cited by 19

Investigating the spatial specificity of S2-SSFP fMRI: A Monte Carlo simulation approach

Khajehim, M., & Moghaddam, A. (2016) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2016.11.016 · Cited by 18

A parametric model of the brain vascular system for estimation of the arterial input function (AIF) at the tissue level

Nejad‐Davarani, S. P., Bagher‐Ebadian, H., Ewing, J. R., Noll, D. C., Mikkelsen, T., Chopp, M., & Jiang, Q. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3695 · Cited by 17

Spinal Cord fMRI

Summers, P. E., Brooks, J. C. W., & Cohen‐Adad, J. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-396973-6.00015-0 · Cited by 16

Characterization of the hemodynamic response in the rat lumbar spinal cord using intrinsic optical imaging and laser speckle

Brieu, N., Beaumont, É., Dubeau, S., Cohen‐Adad, J., & Lesage, F. (2010) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2010.06.012 · Cited by 16

Does clinical memory fMRI provide a comprehensive map of medial temporal lobe structures?

Beisteiner, R., Drabeck, K., Foki, T., Geißler, A., Gartus, A., Lehner-Baumgartner, E., & Baumgartner, C. (2008) · Experimental Neurology · doi:10.1016/j.expneurol.2008.05.019 · Cited by 16

AJNR Am J Neuroradiol 20:1907–1914, November/December 1999 MR Blood Oxygenation Level–Dependent Signal Differences in Parenchymal and Large Draining Vessels: Implications for Functional MR Imaging

Krings, T., Erberich, S. G., Roessler, F., Reul, J., & Thron, A. (2013)

MR blood oxygenation level-dependent signal differences in parenchymal and large draining vessels: implications for functional MR imaging.

Krings, T., Erberich, S. G., Roessler, F. C., Reul, J., & Thron, A. (1999) · PubMed Central · Cited by 50

Vascular Origins of BOLD and CBV fMRI Signals: Statistical Mapping and Histological Sections Compared

Kennerley, A. J., Mayhew, J. E., Redgrave, P., & Berwick, J. (2010) · The Open Neuroimaging Journal · doi:10.2174/1874440001004010001 · Cited by 29

Open Access Vascular Origins of BOLD and CBV fMRI Signals: Statistical Mapping and Histological Sections Compared

Kennerley, A. J., Mayhew, J. E., Redgrave, P., & Berwick, J. (2016)

Cortical depth-specific microvascular dilation underlies laminar differences in blood oxygenation level-dependent functional MRI signal

Tian, P., Teng, I. C., May, L. D., Kurz, R., Lu, K., Scadeng, M., Hillman, E. M. C., de Crespigny, A. J., D'Arceuil, H. E., Mandeville, J. B., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1006735107 · Cited by 294