Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Progress in Neurobiology - Tập 207 - Trang 102174 - 2021
Jonathan R. Polimeni1,2,3, Laura D. Lewis1,4
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
2Department of Radiology, Harvard Medical School, Boston, MA USA
3Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
4Department of Biomedical Engineering, Boston University, Boston, MA, USA

Tài liệu tham khảo

Achermann, 1997, Low-frequency (< 1 Hz) oscillations in the human sleep electroencephalogram, Neuroscience, 81, 213, 10.1016/S0306-4522(97)00186-3 Agrawal, 2020, Model-based physiological noise removal in fast fMRI, Neuroimage, 205, 10.1016/j.neuroimage.2019.116231 Aguirre, 1998, The variability of human, BOLD hemodynamic responses, Neuroimage, 8, 360, 10.1006/nimg.1998.0369 Arcaro, 2015, The anatomical and functional organization of the human visual pulvinar, J. Neurosci., 35, 9848, 10.1523/JNEUROSCI.1575-14.2015 Ashburner, 2012, SPM: a history, Neuroimage, 62, 791, 10.1016/j.neuroimage.2011.10.025 Attwell, 2002, The neural basis of functional brain imaging signals, Trends Neurosci., 25, 621, 10.1016/S0166-2236(02)02264-6 Attwell, 2016, What is a pericyte?, J. Cereb. Blood Flow Metab., 36, 451, 10.1177/0271678X15610340 Báez-Yánez, 2017, The impact of vessel size, orientation and intravascular contribution on the neurovascular fingerprint of BOLD bSSFP fMRI, Neuroimage, 163, 13, 10.1016/j.neuroimage.2017.09.015 Bandettini, 1999, The temporal resolution of functional MRI, 205 Bandettini, 2002, The spatial, temporal, and interpretive limits of functional MRI, 343 Bandettini, 2000, Event-related fMRI contrast when using constant interstimulus interval: theory and experiment, Magn. Reson. Med., 43, 540, 10.1002/(SICI)1522-2594(200004)43:4<540::AID-MRM8>3.0.CO;2-R Bandettini, 1995, Effects of biophysical and physiologic parameters on brain activation-induced R2* and R2 changes: simulations using a deterministic diffusion model, Int. J. Imaging Syst. Technol., 6, 133, 10.1002/ima.1850060203 Bandettini, 2015, The future of functional MRI, 895 Bandettini, 1993, Processing strategies for time-course data sets in functional MRI of the human brain, Magn. Reson. Med., 30, 161, 10.1002/mrm.1910300204 Bandettini, 1997, Characterization of cerebral blood oxygenation and flow changes during prolonged brain activation, Hum. Brain Mapp., 5, 93, 10.1002/(SICI)1097-0193(1997)5:2<93::AID-HBM3>3.0.CO;2-H Bartels, 2004, The chronoarchitecture of the human brain--natural viewing conditions reveal a time-based anatomy of the brain, Neuroimage, 22, 419, 10.1016/j.neuroimage.2004.01.007 Barth, 2015, Simultaneous multislice (SMS) imaging techniques, Magn. Reson. Med., 75, 63, 10.1002/mrm.25897 Batterink, 2016, Phase of spontaneous slow oscillations during sleep influences memory-related processing of auditory cues, J. Neurosci., 36, 1401, 10.1523/JNEUROSCI.3175-15.2016 Bause, 2020, Impact of prospective motion correction, distortion correction methods and large vein bias on the spatial accuracy of cortical laminar fMRI at 9.4 Tesla, Neuroimage, 208, 10.1016/j.neuroimage.2019.116434 Behzadi, 2005, An arteriolar compliance model of the cerebral blood flow response to neural stimulus, Neuroimage, 25, 1100, 10.1016/j.neuroimage.2004.12.057 Bell, 1985, Laminar variation in the microvascular architecture of normal human visual cortex (area 17), Brain Res., 335, 139, 10.1016/0006-8993(85)90284-7 Bellgowan, 2003, Understanding neural system dynamics through task modulation and measurement of functional MRI amplitude, latency, and width, Proc. Natl. Acad. Sci. U. S. A., 100, 1415, 10.1073/pnas.0337747100 Berman, 2018, Gas-free calibrated fMRI with a correction for vessel-size sensitivity, Neuroimage, 169, 176, 10.1016/j.neuroimage.2017.12.047 Bernier, 2018, The morphology of the human cerebrovascular system, Hum. Brain Mapp., 39, 4962, 10.1002/hbm.24337 Berwick, 2005, Neurovascular coupling investigated with two-dimensional optical imaging spectroscopy in rat whisker barrel cortex, Eur. J. Neurosci., 22, 1655, 10.1111/j.1460-9568.2005.04347.x Birn, 2005, The effect of stimulus duty cycle and “off” duration on BOLD response linearity, Neuroimage, 27, 70, 10.1016/j.neuroimage.2005.03.040 Birn, 2001, Spatial heterogeneity of the nonlinear dynamics in the FMRI BOLD response, Neuroimage, 14, 817, 10.1006/nimg.2001.0873 Birn, 2006, Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI, Neuroimage, 31, 1536, 10.1016/j.neuroimage.2006.02.048 Błażejewska, 2019, Testing temporal dependence of spatial specificity in BOLD fMRI at 7T: comparing short versus long stimulus duration, Proc. Intl. Soc. Mag. Reson. Med., 27, 0536 Blinder, 2013, The cortical angiome: an interconnected vascular network with noncolumnar patterns of blood flow, Nat. Neurosci., 16, 889, 10.1038/nn.3426 Boas, 2003, Can the cerebral metabolic rate of oxygen be estimated with near-infrared spectroscopy?, Phys. Med. Biol., 48, 2405, 10.1088/0031-9155/48/15/311 Boas, 2008, A vascular anatomical network model of the spatio-temporal response to brain activation, Neuroimage, 40, 1116, 10.1016/j.neuroimage.2007.12.061 Boillat, 2019, Whole brain measurements of the positive BOLD response variability during a finger tapping task at 7 T show regional differences in its profiles, Magn. Reson. Med., 81, 2720, 10.1002/mrm.27566 Bollmann, 2018, Serial correlations in single-subject fMRI with sub-second TR, Neuroimage, 166, 152, 10.1016/j.neuroimage.2017.10.043 Bollmann, 2020, Geometrically accurate imaging of the pial arterial vasculature of the human brain in vivo using high-resolution non-contrast angiography at 7T, Proc. Intl. Soc. Mag. Reson. Med., 28, 1105 Boxerman, 1995, The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusion-weighted studies in vivo, Magn. Reson. Med., 34, 4, 10.1002/mrm.1910340103 Boynton, 1996, Linear systems analysis of functional magnetic resonance imaging in human V1, J. Neurosci., 16, 4207, 10.1523/JNEUROSCI.16-13-04207.1996 Boynton, 2012, Linear systems analysis of the fMRI signal, Neuroimage, 10.1016/j.neuroimage.2012.01.082 Buckner, 1996, Detection of cortical activation during averaged single trials of a cognitive task using functional magnetic resonance imaging, Proc. Natl. Acad. Sci. U. S. A., 93, 14878, 10.1073/pnas.93.25.14878 Budinger, 2018, MRI and MRS of the human brain at magnetic fields of 14 T to 20 T: technical feasibility, safety, and neuroscience horizons, Neuroimage, 168, 509, 10.1016/j.neuroimage.2017.01.067 Buxton, 2001, The elusive initial dip, Neuroimage, 13, 953, 10.1006/nimg.2001.0814 Buxton, 2009 Buxton, 2010, Interpreting oxygenation-based neuroimaging signals: the importance and the challenge of understanding brain oxygen metabolism, Front. Neuroenergetics, 2, 8 Buxton, 2012, Dynamic models of BOLD contrast, Neuroimage, 62, 953, 10.1016/j.neuroimage.2012.01.012 Buxton, 1997, A model for the coupling between cerebral blood flow and oxygen metabolism during neural stimulation, J. Cereb. Blood Flow Metab., 17, 64, 10.1097/00004647-199701000-00009 Buxton, 1998, Dynamics of blood flow and oxygenation changes during brain activation: the balloon model, Magn. Reson. Med., 39, 855, 10.1002/mrm.1910390602 Buxton, 2004, Modeling the hemodynamic response to brain activation, Neuroimage, 23, S220, 10.1016/j.neuroimage.2004.07.013 Buxton, 2014, Variability of the coupling of blood flow and oxygen metabolism responses in the brain: a problem for interpreting BOLD studies but potentially a new window on the underlying neural activity, Front. Neurosci., 8, 139 Cai, 2018, Stimulation-induced increases in cerebral blood flow and local capillary vasoconstriction depend on conducted vascular responses, Proc. Natl. Acad. Sci. U. S. A., 115, E5796, 10.1073/pnas.1707702115 Cao, 2019, Gastric stimulation drives fast BOLD responses of neural origin, Neuroimage, 197, 200, 10.1016/j.neuroimage.2019.04.064 Chang, 2008, Mapping and correction of vascular hemodynamic latency in the BOLD signal, Neuroimage, 43, 90, 10.1016/j.neuroimage.2008.06.030 Chang, 2009, Influence of heart rate on the BOLD signal: the cardiac response function, Neuroimage, 44, 857, 10.1016/j.neuroimage.2008.09.029 Chen, 2005, Temporal dynamics of cerebro-cerebellar network recruitment during a cognitive task, Neuropsychologia, 43, 1227, 10.1016/j.neuropsychologia.2004.12.015 Chen, 2015, BOLD fractional contribution to resting-state functional connectivity above 0.1 Hz, Neuroimage, 107, 207, 10.1016/j.neuroimage.2014.12.012 Chen, 2009, BOLD-specific cerebral blood volume and blood flow changes during neuronal activation in humans, NMR Biomed., 22, 1054, 10.1002/nbm.1411 Chen, 2011, High-speed vascular dynamics of the hemodynamic response, Neuroimage, 54, 1021, 10.1016/j.neuroimage.2010.09.036 Chen, 2014, A critical role for the vascular endothelium in functional neurovascular coupling in the brain, J. Am. Heart Assoc., 3, 10.1161/JAHA.114.000787 Chen, 2019, On the analysis of rapidly sampled fMRI data, Neuroimage, 188, 807, 10.1016/j.neuroimage.2019.02.008 Chen, 2019, Fast fMRI responses supported by inter-voxel variability of hemodynamic response functions, Proc. Intl. Soc. Mag. Reson. Med., 27, 3726 Chen, 2020, Probing the neuronal and vascular origins of task contrast-dependent hemodynamic response functions, Proc. Intl. Soc. Mag. Reson. Med., 28, 1107 Chen, 2020, Resting-state “physiological networks”, Neuroimage, 213, 10.1016/j.neuroimage.2020.116707 Cheng, 2019, Dependence of the MR signal on the magnetic susceptibility of blood studied with models based on real microvascular networks, Magn. Reson. Med., 81, 3865, 10.1002/mrm.27660 Chiew, 2018, Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints, Neuroimage, 174, 97, 10.1016/j.neuroimage.2018.02.062 Cohen, 2002, Effect of basal conditions on the magnitude and dynamics of the blood oxygenation level-dependent fMRI response, J. Cereb. Blood Flow Metab., 22, 1042, 10.1097/00004647-200209000-00002 Corbin, 2018, Accurate modeling of temporal correlations in rapidly sampled fMRI time series, Hum. Brain Mapp., 39, 3884, 10.1002/hbm.24218 D’Esposito, 1999, The effect of normal aging on the coupling of neural activity to the bold hemodynamic response, Neuroimage, 10, 6, 10.1006/nimg.1999.0444 D’Esposito, 2003, Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging, Nat. Rev. Neurosci., 4, 863, 10.1038/nrn1246 Dale, 1999, Optimal experimental design for event-related fMRI, Hum. Brain Mapp., 8, 109, 10.1002/(SICI)1097-0193(1999)8:2/3<109::AID-HBM7>3.0.CO;2-W Dale, 1997, Selective averaging of rapidly presented individual trials using fMRI, Hum. Brain Mapp., 5, 329, 10.1002/(SICI)1097-0193(1997)5:5<329::AID-HBM1>3.0.CO;2-5 Davis, 1998, Calibrated functional MRI: mapping the dynamics of oxidative metabolism, Proc. Natl. Acad. Sci. U. S. A., 95, 1834, 10.1073/pnas.95.4.1834 De Martino, 2013, Spatial organization of frequency preference and selectivity in the human inferior colliculus, Nat. Commun., 4, 1386, 10.1038/ncomms2379 De Martino, 2015, Frequency preference and attention effects across cortical depths in the human primary auditory cortex, Proc. Natl. Acad. Sci. U. S. A., 112, 16036, 10.1073/pnas.1507552112 de Munck, 2007, The hemodynamic response of the alpha rhythm: an EEG/fMRI study, Neuroimage, 35, 1142, 10.1016/j.neuroimage.2007.01.022 de Zwart, 2005, Temporal dynamics of the BOLD fMRI impulse response, Neuroimage, 24, 667, 10.1016/j.neuroimage.2004.09.013 de Zwart, 2009, Hemodynamic nonlinearities affect BOLD fMRI response timing and amplitude, Neuroimage, 47, 1649, 10.1016/j.neuroimage.2009.06.001 de Zwart, 2018, Impulse response timing differences in BOLD and CBV weighted fMRI, Neuroimage, 181, 292, 10.1016/j.neuroimage.2018.07.011 Deneux, 2006, Using nonlinear models in fMRI data analysis: model selection and activation detection, Neuroimage, 32, 1669, 10.1016/j.neuroimage.2006.03.006 Denison, 2014, Functional mapping of the magnocellular and parvocellular subdivisions of human LGN, Neuroimage, 102, 358, 10.1016/j.neuroimage.2014.07.019 Destexhe, 2011, The fine structure of slow-wave sleep oscillations: from single neurons to large networks, 69 Devonshire, 2012, Neurovascular coupling is brain region-dependent, Neuroimage, 59, 1997, 10.1016/j.neuroimage.2011.09.050 Devor, 2003, Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex, Neuron, 39, 353, 10.1016/S0896-6273(03)00403-3 Devor, 2007, Suppressed neuronal activity and concurrent arteriolar vasoconstriction may explain negative blood oxygenation level-dependent signal, J. Neurosci., 27, 4452, 10.1523/JNEUROSCI.0134-07.2007 Drew, 2019, Vascular and neural basis of the BOLD signal, Curr. Opin. Neurobiol., 58, 61, 10.1016/j.conb.2019.06.004 Drew, 2011, Fluctuating and sensory-induced vasodynamics in rodent cortex extend arteriole capacity, Proc. Natl. Acad. Sci. U. S. A., 108, 8473, 10.1073/pnas.1100428108 Duong, 2000, Spatiotemporal dynamics of the BOLD fMRI signals: toward mapping submillimeter cortical columns using the early negative response, Magn. Reson. Med., 44, 231, 10.1002/1522-2594(200008)44:2<231::AID-MRM10>3.0.CO;2-T Duvernoy, 1999 Duvernoy, 1999 Duvernoy, 1981, Cortical blood vessels of the human brain, Brain Res. Bull., 7, 519, 10.1016/0361-9230(81)90007-1 Dux, 2006, Isolation of a central bottleneck of information processing with time-resolved fMRI, Neuron, 52, 1109, 10.1016/j.neuron.2006.11.009 Eickhoff, 2018, Imaging-based parcellations of the human brain, Nat. Rev. Neurosci., 10.1038/s41583-018-0071-7 Engel, 1994, fMRI of human visual cortex, Nature, 369, 525, 10.1038/369525a0 Faull, 2017, The cortical connectivity of the periaqueductal gray and the conditioned response to the threat of breathlessness, Elife, 6, 10.7554/eLife.21749 Faull, 2015, Functional subdivision of the human periaqueductal grey in respiratory control using 7 Tesla fMRI, Neuroimage, 113, 356, 10.1016/j.neuroimage.2015.02.026 Feinberg, 2010, Multiplexed echo planar imaging for sub-second whole brain fMRI and fast diffusion imaging, PLoS One, 5, 10.1371/journal.pone.0015710 Fernández-Klett, 2010, Pericytes in capillaries are contractile in vivo, but arterioles mediate functional hyperemia in the mouse brain, Proc. Natl. Acad. Sci. U. S. A., 107, 22290, 10.1073/pnas.1011321108 Figueroa, 2007, Are voltage-dependent ion channels involved in the endothelial cell control of vasomotor tone?, Am. J. Physiol. Heart Circ. Physiol., 293, H1371, 10.1152/ajpheart.01368.2006 Finn, 2019, Layer-dependent activity in human prefrontal cortex during working memory, Nat. Neurosci., 22, 1687, 10.1038/s41593-019-0487-z Finn, 2020, Idiosynchrony: from shared responses to individual differences during naturalistic neuroimaging, Neuroimage, 215, 10.1016/j.neuroimage.2020.116828 Fisel, 1991, MR contrast due to microscopically heterogeneous magnetic susceptibility: numerical simulations and applications to cerebral physiology, Magn. Reson. Med., 17, 336, 10.1002/mrm.1910170206 Friston, 1995, Characterizing evoked hemodynamics with fMRI, Neuroimage, 2, 157, 10.1006/nimg.1995.1018 Friston, 1998, Nonlinear event-related responses in fMRI, Magn. Reson. Med., 39, 41, 10.1002/mrm.1910390109 Friston, 2000, Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics, Neuroimage, 12, 466, 10.1006/nimg.2000.0630 Frostig, 1990, Cortical functional architecture and local coupling between neuronal activity and the microcirculation revealed by in vivo high-resolution optical imaging of intrinsic signals, Proc. Natl. Acad. Sci. U. S. A., 87, 6082, 10.1073/pnas.87.16.6082 Frühholz, 2020, Neural oscillations in human auditory cortex revealed by fast fMRI during auditory perception, Neuroimage, 207, 10.1016/j.neuroimage.2019.116401 Fukuda, 2021, Time-dependent spatial specificity of high-resolution fMRI: insights into mesoscopic neurovascular coupling, Philos. Trans. R. Soc. B Biol. Sci., 376, 10.1098/rstb.2019.0623 Gagnon, 2015, Quantifying the microvascular origin of bold-fMRI from first principles with two-photon microscopy and an oxygen-sensitive nanoprobe, J. Neurosci., 35, 3663, 10.1523/JNEUROSCI.3555-14.2015 Gagnon, 2016, Validation and optimization of hypercapnic-calibrated fMRI from oxygen-sensitive two-photon microscopy, Philos. Trans. R. Soc. B Biol. Sci., 371, 10.1098/rstb.2015.0359 Gagnon, 2016, Modeling of cerebral oxygen transport based on in vivo microscopic imaging of microvascular network structure, blood flow, and oxygenation, Front. Comput. Neurosci., 10.3389/fncom.2016.00082 Gao, 2015 Gao, 2015, Mechanical restriction of intracortical vessel dilation by brain tissue sculpts the hemodynamic response, Neuroimage, 115, 162, 10.1016/j.neuroimage.2015.04.054 Gao, 2017, Time to wake up: studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal, Neuroimage, 10.1016/j.neuroimage.2016.11.069 Glasser, 2016, A multi-modal parcellation of human cerebral cortex, Nature, 536, 171, 10.1038/nature18933 Glover, 1999, Deconvolution of impulse response in event-related BOLD fMRI, Neuroimage, 9, 416, 10.1006/nimg.1998.0419 Gomez, 2020, Apparent attenuation of BOLD macro-vascular contributions with high-frequency stimuli, Proc. Intl. Soc. Mag. Reson. Med., 28, 3826 Gonzalez-Castillo, 2012, Whole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysis, Proc. Natl. Acad. Sci. U. S. A., 109, 5487, 10.1073/pnas.1121049109 Gonzalez-Castillo, 2015, Task dependence, tissue specificity, and spatial distribution of widespread activations in large single-subject functional MRI datasets at 7T, Cereb. Cortex, 25, 4667, 10.1093/cercor/bhu148 Goodyear, 1998, Effect of luminance contrast on BOLD fMRI response in human primary visual areas, J. Neurophysiol., 79, 2204, 10.1152/jn.1998.79.4.2204 Goodyear, 2001, Brief visual stimulation allows mapping of ocular dominance in visual cortex using fMRI, Hum. Brain Mapp., 14, 210, 10.1002/hbm.1053 Gould, 2015, Hematocrit distribution and tissue oxygenation in large microcirculatory networks, Microcirculation, 22, 1, 10.1111/micc.12156 Gould, 2017, The capillary bed offers the largest hemodynamic resistance to the cortical blood supply, J. Cereb. Blood Flow Metab., 37, 52, 10.1177/0271678X16671146 Green, 1966 Greve, 2013, A survey of the sources of noise in fMRI, Psychometrika, 78, 396, 10.1007/s11336-012-9294-0 Griffeth, 2011, A theoretical framework for estimating cerebral oxygen metabolism changes using the calibrated-BOLD method: modeling the effects of blood volume distribution, hematocrit, oxygen extraction fraction, and tissue signal properties on the BOLD signal, Neuroimage, 58, 198, 10.1016/j.neuroimage.2011.05.077 Grill-Spector, 2001, fMR-adaptation: a tool for studying the functional properties of human cortical neurons, Acta Psychol. (Amst), 107, 293, 10.1016/S0001-6918(01)00019-1 Grinvald, 1986, Functional architecture of cortex revealed by optical imaging of intrinsic signals, Nature, 324, 361, 10.1038/324361a0 Grubb, 1974, The effects of changes in PaCO2 on cerebral blood volume, blood flow, and vascular mean transit time, Stroke, 5, 630, 10.1161/01.STR.5.5.630 Gruber, 2005, Oscillatory brain activity dissociates between associative stimulus content in a repetition priming task in the human EEG, Cereb. Cortex, 15, 109, 10.1093/cercor/bhh113 Grutzendler, 2019, Cellular control of brain capillary blood flow: in vivo imaging veritas, Trends Neurosci., 42, 528, 10.1016/j.tins.2019.05.009 Gu, 2005, Nonlinear responses of cerebral blood volume, blood flow and blood oxygenation signals during visual stimulation, Magn. Reson. Imaging, 23, 921, 10.1016/j.mri.2005.09.007 Gutiérrez-Jiménez, 2016, Effect of electrical forepaw stimulation on capillary transit-time heterogeneity (CTH), J. Cereb. Blood Flow Metab., 36, 2072, 10.1177/0271678X16631560 Hall, 2014, Capillary pericytes regulate cerebral blood flow in health and disease, Nature, 508, 55, 10.1038/nature13165 Hamilton, 2010, Pericyte-mediated regulation of capillary diameter: a component of neurovascular coupling in health and disease, Front. Neuroenergetics, 2, 10.3389/fnene.2010.00005 Handwerker, 2004, Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses, Neuroimage, 21, 1639, 10.1016/j.neuroimage.2003.11.029 Handwerker, 2012, The continuing challenge of understanding and modeling hemodynamic variation in fMRI, Neuroimage, 62, 1017, 10.1016/j.neuroimage.2012.02.015 Hansen, 2004, Parametric reverse correlation reveals spatial linearity of retinotopic human V1 BOLD response, Neuroimage, 23, 233, 10.1016/j.neuroimage.2004.05.012 Harms, 2003, Detection and quantification of a wide range of fMRI temporal responses using a physiologically-motivated basis set, Hum. Brain Mapp., 20, 168, 10.1002/hbm.10136 Hartmann, 2021, Brain capillary pericytes exert a substantial but slow influence on blood flow, Nat. Neurosci., 24, 633, 10.1038/s41593-020-00793-2 Hasson, 2004, Intersubject synchronization of cortical activity during natural vision, Science (80-.), 303, 1634, 10.1126/science.1089506 Hathout, 1999, The lag of cerebral hemodynamics with rapidly alternating periodic stimulation: modeling for functional MRI, Magn. Reson. Imaging, 17, 9, 10.1016/S0730-725X(98)00150-7 Hathout, 1999, The early response in fMRI: a modeling approach, Magn. Reson. Med., 41, 550, 10.1002/(SICI)1522-2594(199903)41:3<550::AID-MRM18>3.0.CO;2-Q Havlíček, 2020, A dynamical model of the laminar BOLD response, Neuroimage, 204, 10.1016/j.neuroimage.2019.116209 Havlíček, 2015, Physiologically informed dynamic causal modeling of fMRI data, Neuroimage, 122, 355, 10.1016/j.neuroimage.2015.07.078 Havlíček, 2017, Echo-time dependence of the BOLD response transients – a window into brain functional physiology, Neuroimage, 159, 355, 10.1016/j.neuroimage.2017.07.034 Havlíček, 2017, Determining excitatory and inhibitory neuronal activity from multimodal fMRI data using a generative hemodynamic model, Front. Neurosci., 11, 10.3389/fnins.2017.00616 He, 2009, The fMRI signal, slow cortical potential and consciousness, Trends Cogn. Sci., 13, 302, 10.1016/j.tics.2009.04.004 He, 2007, Quantitative BOLD: mapping of human cerebral deoxygenated blood volume and oxygen extraction fraction: default state, Magn. Reson. Med., 57, 115, 10.1002/mrm.21108 He, 2008, Electrophysiological correlates of the brain’s intrinsic large-scale functional architecture, Proc. Natl. Acad. Sci. U. S. A., 105, 16039, 10.1073/pnas.0807010105 Heckman, 2007, Nonlinearities in rapid event-related fMRI explained by stimulus scaling, Neuroimage, 34, 651, 10.1016/j.neuroimage.2006.09.038 Heinzle, 2015, A hemodynamic model for layered BOLD signals, Neuroimage, 125, 556, 10.1016/j.neuroimage.2015.10.025 Helstrom, 1964, The detection and resolution of optical signals, IEEE Trans. Inf. Theory, 10, 275, 10.1109/TIT.1964.1053702 Hennig, 2007, MR-Encephalography: fast multi-channel monitoring of brain physiology with magnetic resonance, Neuroimage, 34, 212, 10.1016/j.neuroimage.2006.08.036 Hill, 2015, Regional blood flow in the normal and ischemic brain is controlled by arteriolar smooth muscle cell contractility and not by capillary pericytes, Neuron, 87, 95, 10.1016/j.neuron.2015.06.001 Hillman, 2014, Coupling mechanism and significance of the BOLD signal: a status report, Annu. Rev. Neurosci., 37, 161, 10.1146/annurev-neuro-071013-014111 Hillman, 2007, Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation, Neuroimage, 35, 89, 10.1016/j.neuroimage.2006.11.032 Hiltunen, 2014, Infra-slow EEG fluctuations are correlated with resting-state network dynamics in fMRI, J. Neurosci., 34, 356, 10.1523/JNEUROSCI.0276-13.2014 Hirano, 2011, Spatiotemporal evolution of the functional magnetic resonance imaging response to ultrashort stimuli, J. Neurosci., 31, 1440, 10.1523/JNEUROSCI.3986-10.2011 Hoge, 1999, Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex, Proc. Natl. Acad. Sci. U. S. A., 96, 9403, 10.1073/pnas.96.16.9403 Hua, 2018, MRI techniques to measure arterial and venous cerebral blood volume, Neuroimage Huber, 2017, High-resolution CBV-fMRI allows mapping of laminar activity and connectivity of cortical input and output in human M1, Neuron, 96, 10.1016/j.neuron.2017.11.005 Huber, 2019, Non-BOLD contrast for laminar fMRI in humans: CBF, CBV, and CMRO2, Neuroimage, 197, 742, 10.1016/j.neuroimage.2017.07.041 Huettel, 2000, Evidence for a refractory period in the hemodynamic response to visual stimuli as measured by MRI, Neuroimage, 11, 547, 10.1006/nimg.2000.0553 Huettel, 2001, Regional differences in the refractory period of the hemodynamic response: an event-related fMRI study, Neuroimage, 14, 967, 10.1006/nimg.2001.0900 Huettel, 2001, The effects of aging upon the hemodynamic response measured by functional MRI, Neuroimage, 13, 161, 10.1006/nimg.2000.0675 Hulvershorn, 2005, Spatial sensitivity and temporal response of spin echo and gradient echo bold contrast at 3 T using peak hemodynamic activation time, Neuroimage, 24, 216, 10.1016/j.neuroimage.2004.09.033 Hulvershorn, 2005, Temporal resolving power of spin echo and gradient echo fMRI at 3T with apparent diffusion coefficient compartmentalization, Hum. Brain Mapp., 25, 247, 10.1002/hbm.20094 Hutchinson, 2006, Spatial flow-volume dissociation of the cerebral microcirculatory response to mild hypercapnia, Neuroimage, 32, 520, 10.1016/j.neuroimage.2006.03.033 Huth, 2016, Natural speech reveals the semantic maps that tile human cerebral cortex, Nature, 532, 453, 10.1038/nature17637 Iadecola, 2004, Neurovascular regulation in the normal brain and in Alzheimer’s disease, Nat. Rev. Neurosci., 5, 347, 10.1038/nrn1387 Iadecola, 2017, The neurovascular unit coming of age: a journey through neurovascular coupling in health and disease, Neuron, 96, 17, 10.1016/j.neuron.2017.07.030 Inan, 2004, Hemodynamic correlates of stimulus repetition in the visual and auditory cortices: an fMRI study, Neuroimage, 21, 886, 10.1016/j.neuroimage.2003.10.029 Janz, 2001, Coupling of neural activity and BOLD fMRI response: New insights by combination of fMRI and VEP experiments in transition from single events to continuous stimulation, Magn. Reson. Med., 46, 482, 10.1002/mrm.1217 Jenkinson, 2012, FSL, Neuroimage, 62, 782, 10.1016/j.neuroimage.2011.09.015 Jones, 2001, Concurrent optical imaging spectroscopy and laser-Doppler flowmetry: the relationship between blood flow, oxygenation, and volume in rodent barrel cortex, Neuroimage, 13, 1002, 10.1006/nimg.2001.0808 Kang, 2003, Comparison of functional activation foci in children and adults using a common stereotactic space, Neuroimage, 19, 16, 10.1016/S1053-8119(03)00038-7 Katwal, 2013, Measuring relative timings of brain activities using fMRI, Neuroimage, 66, 436, 10.1016/j.neuroimage.2012.10.052 Kay, 2008, Modeling low-frequency fluctuation and hemodynamic response timecourse in event-related fMRI, Hum. Brain Mapp., 29, 142, 10.1002/hbm.20379 Kay, 2008, Identifying natural images from human brain activity, Nature, 452, 352, 10.1038/nature06713 Kemna, 2001, Effect of respiratory CO2 changes on the temporal dynamics of the hemodynamic response in functional MR imaging, Neuroimage, 14, 642, 10.1006/nimg.2001.0859 Kim, 2006, Quantification of cerebral arterial blood volume using arterial spin labeling with intravoxel incoherent motion-sensitive gradients, Magn. Reson. Med., 55, 1047, 10.1002/mrm.20867 Kim, 2011, Temporal dynamics and spatial specificity of arterial and venous blood volume changes during visual stimulation: implication for BOLD quantification, J. Cereb. Blood Flow Metab., 31, 1211, 10.1038/jcbfm.2010.226 Kim, 2011, Quantitative MRI of cerebral arterial blood volume, Open Neuroimag. J., 5, 136, 10.2174/1874440001105010136 Kim, 2016, Arterial impulse model for the BOLD response to brief neural activation, Neuroimage, 124, 394, 10.1016/j.neuroimage.2015.08.068 Kim, 2000, High-resolution mapping of iso-orientation columns by fMRI, Nat. Neurosci., 3, 164, 10.1038/72109 Kim, 2007, Arterial versus total blood volume changes during neural activity-induced cerebral blood flow change: implication for BOLD fMRI, J. Cereb. Blood Flow Metab., 27, 1235, 10.1038/sj.jcbfm.9600429 Kim, 2008, Functional MRI with magnetization transfer effects: determination of BOLD and arterial blood volume changes, Magn. Reson. Med., 60, 1518, 10.1002/mrm.21766 Kim, 2013, Model of the transient neurovascular response based on prompt arterial dilation, J. Cereb. Blood Flow Metab., 33, 1429, 10.1038/jcbfm.2013.90 Kim, 2020, Dynamics of the cerebral blood flow response to brief neural activity in human visual cortex, J. Cereb. Blood Flow Metab., 40, 1823, 10.1177/0271678X19869034 Kiselev, 1999, Analytical model of susceptibility-induced MR signal dephasing: effect of diffusion in a microvascular network, Magn. Reson. Med., 41, 499, 10.1002/(SICI)1522-2594(199903)41:3<499::AID-MRM12>3.0.CO;2-O Kiselev, 2005, Vessel size imaging in humans, Magn. Reson. Med., 53, 553, 10.1002/mrm.20383 Kleinfeld, 1998, Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex, Proc. Natl. Acad. Sci. U. S. A., 95, 15741, 10.1073/pnas.95.26.15741 Kleinfeld, 2011, A guide to delineate the logic of neurovascular signaling in the brain, Front. Neuroenergetics, 10.3389/fnene.2011.00001 Kohler, 2013, Pattern classification precedes region-average hemodynamic response in early visual cortex, Neuroimage, 78, 249, 10.1016/j.neuroimage.2013.04.019 Kok, 2016, Selective activation of the deep layers of the human primary visual cortex by top-down feedback, Curr. Biol., 26, 371, 10.1016/j.cub.2015.12.038 Krekelberg, 2006, Adaptation: from single cells to BOLD signals, Trends Neurosci., 10.1016/j.tins.2006.02.008 Krieger, 2012, Cerebral blood volume changes during brain activation, J. Cereb. Blood Flow Metab., 32, 1618, 10.1038/jcbfm.2012.63 Kriegeskorte, 2010, How does an fMRI voxel sample the neuronal activity pattern: compact-kernel or complex spatiotemporal filter?, Neuroimage, 49, 1965, 10.1016/j.neuroimage.2009.09.059 Lai, 1993, 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, Magn. Reson. Med., 30, 387, 10.1002/mrm.1910300318 Lambers, 2020, A cortical rat hemodynamic response function for improved detection of BOLD activation under common experimental conditions, Neuroimage, 208, 10.1016/j.neuroimage.2019.116446 Lau, 2011, BOLD temporal dynamics of rat superior colliculus and lateral geniculate nucleus following short duration visual stimulation, PLoS One, 6, 10.1371/journal.pone.0018914 Lauwers, 2008, Morphometry of the human cerebral cortex microcirculation: general characteristics and space-related profiles, Neuroimage, 39, 936, 10.1016/j.neuroimage.2007.09.024 Lawrence, 2019, Laminar fMRI: applications for cognitive neuroscience, Neuroimage, 197, 785, 10.1016/j.neuroimage.2017.07.004 Lee, 2001, Relative changes of cerebral arterial and venous blood volumes during increased cerebral blood flow: implications for BOLD fMRI, Magn. Reson. Med., 45, 791, 10.1002/mrm.1107 Lee, 2013, Tracking dynamic resting-state networks at higher frequencies using MR-encephalography, Neuroimage, 65, 216, 10.1016/j.neuroimage.2012.10.015 Leite, 2006, Characterization of event-related designs using BOLD and IRON fMRI, Neuroimage, 29, 901, 10.1016/j.neuroimage.2005.08.022 Lewis, 2016, Fast fMRI can detect oscillatory neural activity in humans, Proc. Natl. Acad. Sci. U. S. A., 113, E6679, 10.1073/pnas.1608117113 Lewis, 2017, Identifying neural contributions to high frequency dynamics in the fMRI signal at 9.4 Tesla, 23 Lewis, 2018, Focal thalamic activity at the moment of awakening identified through simultaneous EEG and fast fMRI, Soc. Neurosci. Abstr. Lewis, 2018, Stimulus-dependent hemodynamic response timing across the human subcortical-cortical visual pathway identified through high spatiotemporal resolution 7T fMRI, Neuroimage, 181, 279, 10.1016/j.neuroimage.2018.06.056 Li, 2007, High-resolution neurometabolic coupling in the lateral geniculate nucleus, J. Neurosci., 27, 10223, 10.1523/JNEUROSCI.1505-07.2007 Li, 2019, Characterization of the hemodynamic response function in white matter tracts for event-related fMRI, Nat. Commun., 10 Liang, 2013, Luminance contrast of a visual stimulus modulates the BOLD response more than the cerebral blood flow response in the human brain, Neuroimage, 64, 104, 10.1016/j.neuroimage.2012.08.077 Lin, 2008, Event-related single-shot volumetric functional magnetic resonance inverse imaging of visual processing, Neuroimage, 42, 230, 10.1016/j.neuroimage.2008.04.179 Lin, 2013, fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG, Neuroimage, 78C, 372, 10.1016/j.neuroimage.2013.04.017 Lin, 2015, Significant feed-forward connectivity revealed by high frequency components of BOLD fMRI signals, Neuroimage, 121, 69, 10.1016/j.neuroimage.2015.07.036 Lin, 2018, Relative latency and temporal variability of hemodynamic responses at the human primary visual cortex, Neuroimage, 164, 194, 10.1016/j.neuroimage.2017.01.041 Lindauer, 2001, No evidence for early decrease in blood oxygenation in rat whisker cortex in response to functional activation, Neuroimage, 13, 988, 10.1006/nimg.2000.0709 Lindquist, 2009, Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling, Neuroimage, 45, S187, 10.1016/j.neuroimage.2008.10.065 Liu, 2000, An investigation of the impulse functions for the nonlinear BOLD response in functional MRI, Magn. Reson. Imaging, 18, 931, 10.1016/S0730-725X(00)00214-9 Liu, 2001, Detection power, estimation efficiency, and predictability in event-related fMRI, Neuroimage, 13, 759, 10.1006/nimg.2000.0728 Liu, 2004, Caffeine alters the temporal dynamics of the visual BOLD response, Neuroimage, 23, 1402, 10.1016/j.neuroimage.2004.07.061 Liu, 2010, Linear and nonlinear relationships between visual stimuli, EEG and BOLD fMRI signals, Neuroimage, 50, 1054, 10.1016/j.neuroimage.2010.01.017 Logothetis, 2008, What we can do and what we cannot do with fMRI, Nature, 453, 869, 10.1038/nature06976 Logothetis, 2001, Neurophysiological investigation of the basis of the fMRI signal, Nature, 412, 150, 10.1038/35084005 Logothetis, 2009, How not to study spontaneous activity, Neuroimage, 45, 1080, 10.1016/j.neuroimage.2009.01.010 Lorthois, 2011, Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network: part I: methodology and baseline flow, Neuroimage, 54, 1031, 10.1016/j.neuroimage.2010.09.032 Lorthois, 2011, Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: flow variations induced by global or localized modifications of arteriolar diameters, Neuroimage, 54, 2840, 10.1016/j.neuroimage.2010.10.040 Ma, 2016, Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons, Proc. Natl. Acad. Sci. U. S. A., 113, E8463, 10.1073/pnas.1525369113 Macdonald, 2011, Trial-by-trial variations in subjective attentional state are reflected in ongoing prestimulus EEG alpha oscillations, Front. Psychol., 2, 10.3389/fpsyg.2011.00082 Malonek, 1997, Vascular imprints of neuronal activity: relationships between the dynamics of cortical blood flow, oxygenation, and volume changes following sensory stimulation, Proc. Natl. Acad. Sci. U. S. A., 94, 14826, 10.1073/pnas.94.26.14826 Mandeville, 1998, Dynamic functional imaging of relative cerebral blood volume during rat forepaw stimulation, Magn. Reson. Med., 39, 615, 10.1002/mrm.1910390415 Mandeville, 1999, MRI measurement of the temporal evolution of relative CMRO(2) during rat forepaw stimulation, Magn. Reson. Med., 42, 944, 10.1002/(SICI)1522-2594(199911)42:5<944::AID-MRM15>3.0.CO;2-W Mandeville, 1999, Evidence of a cerebrovascular postarteriole windkessel with delayed compliance, J. Cereb. Blood Flow Metab., 19, 679, 10.1097/00004647-199906000-00012 Manuel, 2020, Deciphering the neural signature of human cardiovascular regulation, Elife, 9, 1, 10.7554/eLife.55316 Marcus, 1977, Regulation of total and regional spinal cord blood flow, Circ. Res., 41, 128, 10.1161/01.RES.41.1.128 Markuerkiaga, 2016, A cortical vascular model for examining the specificity of the laminar BOLD signal, Neuroimage, 132, 491, 10.1016/j.neuroimage.2016.02.073 Martin, 2006, Investigating neural-hemodynamic coupling and the hemodynamic response function in the awake rat, Neuroimage, 32, 33, 10.1016/j.neuroimage.2006.02.021 Marvel, 2012, From storage to manipulation: how the neural correlates of verbal working memory reflect varying demands on inner speech, Brain Lang., 120, 42, 10.1016/j.bandl.2011.08.005 Massimini, 2004, The sleep slow oscillation as a traveling wave, J. Neurosci., 24, 6862, 10.1523/JNEUROSCI.1318-04.2004 Mateo, 2017, Entrainment of arteriole vasomotor fluctuations by neural activity is a basis of blood-oxygenation-level-dependent “resting-state” connectivity, Neuron, 96, 10.1016/j.neuron.2017.10.012 Mazzoni, 2015, Dissecting the role of smooth muscle cells versus pericytes in regulating cerebral blood flow using in vivo optical imaging, Neuron, 87, 4, 10.1016/j.neuron.2015.06.024 Mchedlishvili, 1984, The modular organization of the pial arterial system in phylogeny, J. Cereb. Blood Flow Metab., 4, 391, 10.1038/jcbfm.1984.57 Menon, 1999, Submillimeter functional localization in human striate cortex using BOLD contrast at 4 Tesla: implications for the vascular point-spread function, Magn. Reson. Med., 41, 230, 10.1002/(SICI)1522-2594(199902)41:2<230::AID-MRM3>3.0.CO;2-O Menon, 1999, Spatial and temporal limits in cognitive neuroimaging with fMRI, Trends Cogn. Sci., 10.1016/S1364-6613(99)01329-7 Menon, 1995, BOLD based functional MRI at 4 Tesla includes a capillary bed contribution: echo‐planar imaging correlates with previous optical imaging using intrinsic signals, Magn. Reson. Med., 33, 453, 10.1002/mrm.1910330323 Menon, 1998, Mental chronometry using latency-resolved functional MRI, Proc. Natl. Acad. Sci. U. S. A., 95, 10902, 10.1073/pnas.95.18.10902 Miezin, 2000, Characterizing the hemodynamic response: effects of presentation rate, sampling procedure, and the possibility of ordering brain activity based on relative timing, Neuroimage, 11, 735, 10.1006/nimg.2000.0568 Mildner, 2001, A qualitative test of the balloon model for BOLD-based MR signal changes at 3T, Magn. Reson. Med., 46, 891, 10.1002/mrm.1274 Miller, 2001, Nonlinear temporal dynamics of the cerebral blood flow response, Hum. Brain Mapp., 13, 1, 10.1002/hbm.1020 Misaki, 2013, Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns, Neuroimage, 66, 623, 10.1016/j.neuroimage.2012.10.069 Miyawaki, 2020, Event-related decoding of visual stimulus information using short-TR BOLD fMRI at 7T, Proc. Intl. Soc. Mag. Reson. Med., 28, 4015 Moeller, 2010, Multiband multislice GE-EPI at 7 Tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI, Magn. Reson. Med., 63, 1144, 10.1002/mrm.22361 Moerel, 2018, Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field, Neuroimage, 164, 18, 10.1016/j.neuroimage.2017.03.063 Mohamed, 2002, BOLD fMRI of the visual cortex: quantitative responses measured with a graded stimulus at 1.5 Tesla, J. Magn. Reson. Imaging, 16, 128, 10.1002/jmri.10155 Mölle, 2004, Learning increases human electroencephalographic coherence during subsequent slow sleep oscillations, Proc. Natl. Acad. Sci. U. S. A., 101, 13963, 10.1073/pnas.0402820101 Moon, 2007, Neural interpretation of blood oxygenation level-dependent fMRI maps at submillimeter columnar resolution, J. Neurosci., 27, 6892, 10.1523/JNEUROSCI.0445-07.2007 Moradi, 2013, Adaptation of cerebral oxygen metabolism and blood flow and modulation of neurovascular coupling with prolonged stimulation in human visual cortex, Neuroimage, 82, 182, 10.1016/j.neuroimage.2013.05.110 Moses, 2014, Developmental changes in resting and functional cerebral blood flow and their relationship to the BOLD response, Hum. Brain Mapp., 35, 3188, 10.1002/hbm.22394 Muckli, 2015, Contextual feedback to superficial layers of V1, Curr. Biol., 25, 2690, 10.1016/j.cub.2015.08.057 Mullinger, 2017, Post-stimulus fMRI and EEG responses: evidence for a neuronal origin hypothesised to be inhibitory, Neuroimage, 157, 388, 10.1016/j.neuroimage.2017.06.020 Murphy, 2013, Resting-state fMRI confounds and cleanup, Neuroimage, 80, 349, 10.1016/j.neuroimage.2013.04.001 Nangini, 2005, Assessing linear time-invariance in human primary somatosensory cortex with BOLD fMRI using vibrotactile stimuli, Magn. Reson. Med., 53, 304, 10.1002/mrm.20363 Nasr, 2016, Interdigitated color- and disparity-selective columns within human visual cortical areas V2 and V3, J. Neurosci., 36, 1841, 10.1523/JNEUROSCI.3518-15.2016 Ngo, 2013, Auditory closed-loop stimulation of the sleep slow oscillation enhances memory, Neuron, 78, 545, 10.1016/j.neuron.2013.03.006 Nishimoto, 2011, Reconstructing visual experiences from brain activity evoked by natural movies, Curr. Biol., 21, 1641, 10.1016/j.cub.2011.08.031 Nix, 1976, Comparison of vascular reactivity in spinal cord and brain, Stroke, 7, 560, 10.1161/01.STR.7.6.560 Nizar, 2013, In vivo stimulus-induced vasodilation occurs without IP3 receptor activation and may precede astrocytic calcium increase, J. Neurosci., 33, 8411, 10.1523/JNEUROSCI.3285-12.2013 Norris, 2019, Laminar (f)MRI: a short history and future prospects, Neuroimage, 197, 643, 10.1016/j.neuroimage.2019.04.082 Obata, 2004, Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the balloon model to the interpretation of BOLD transients, Neuroimage, 21, 144, 10.1016/j.neuroimage.2003.08.040 Ogawa, 1993, Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model, Biophys. J., 64, 803, 10.1016/S0006-3495(93)81441-3 Ogawa, 2000, An approach to probe some neural systems interaction by functional MRI at neural time scale down to milliseconds, Proc. Natl. Acad. Sci. U. S. A., 97, 11026, 10.1073/pnas.97.20.11026 Olszowy, 2019, Accurate autocorrelation modeling substantially improves fMRI reliability, Nat. Commun., 10, 1220, 10.1038/s41467-019-09230-w Oppenheim, 1997 Ou, 2009, Modeling adaptation effects in fMRI analysis, 1009 Pan, 2013, Infraslow LFP correlates to resting-state fMRI BOLD signals, Neuroimage, 74, 288, 10.1016/j.neuroimage.2013.02.035 Pedregosa, 2015, Data-driven HRF estimation for encoding and decoding models, Neuroimage, 104, 209, 10.1016/j.neuroimage.2014.09.060 Peppiatt, 2006, Bidirectional control of CNS capillary diameter by pericytes, Nature, 443, 700, 10.1038/nature05193 Petridou, 2019, Laminar fMRI: what can the time domain tell us?, Neuroimage, 197, 761, 10.1016/j.neuroimage.2017.07.040 Peyrounette, 2018, Multiscale modelling of blood flow in cerebral microcirculation: details at capillary scale control accuracy at the level of the cortex, PLoS One, 13, 10.1371/journal.pone.0189474 Pfannmoeller, 2019, Quantification of draining vein dominance across cortical depths in BOLD fMRI from first principles using realistic Vascular Anatomical Networks, Proc. Intl. Soc. Mag. Reson. Med., 27, 3715 Pfannmoeller, 2021, Simulations of the BOLD non-linearity based on a viscoelastic model for capillary and vein compliance, Proc. Intl. Soc. Mag. Reson. Med., 29, 2856 Pfeifer, 1928 Pfeuffer, 2003, Spatial dependence of the nonlinear BOLD response at short stimulus duration, Neuroimage, 18, 990, 10.1016/S1053-8119(03)00035-1 Piché, 2017, Tight neurovascular coupling in the spinal cord during nociceptive stimulation in intact and spinal rats, Neuroscience, 355, 1, 10.1016/j.neuroscience.2017.04.038 Pisauro, 2013, Fast hemodynamic responses in the visual cortex of the awake mouse, J. Neurosci., 33, 18343, 10.1523/JNEUROSCI.2130-13.2013 Polimeni, 2018, Neuroimaging with ultra-high field MRI: present and future, Neuroimage, 168, 1, 10.1016/j.neuroimage.2018.01.072 Polimeni, 2018, Magnetic Resonance Imaging technology — bridging the gap between noninvasive human imaging and optical microscopy, Curr. Opin. Neurobiol., 50, 250, 10.1016/j.conb.2018.04.026 Polimeni, 2018, Analysis strategies for high-resolution UHF-fMRI data, Neuroimage, 168, 296, 10.1016/j.neuroimage.2017.04.053 Pouliot, 2017, Magnetic resonance fingerprinting based on realistic vasculature in mice, Neuroimage, 149, 436, 10.1016/j.neuroimage.2016.12.060 Purdon, 1998, Effect of temporal autocorrelation due to physiological noise and stimulus paradigm on voxel-level false-positive rates in fMRI, Hum. Brain Mapp., 6, 239, 10.1002/(SICI)1097-0193(1998)6:4<239::AID-HBM4>3.0.CO;2-4 Reichold, 2009, Vascular graph model to simulate the cerebral blood flow in realistic vascular networks, J. Cereb. Blood Flow Metab., 29, 1429, 10.1038/jcbfm.2009.58 Richter, 2003, The shape of the fMRI BOLD response in children and adults changes systematically with age, Neuroimage, 20, 1122, 10.1016/S1053-8119(03)00347-1 Robson, 1998, Measurements of the temporal fMRI response of the human auditory cortex to trains of tones, Neuroimage, 7, 185, 10.1006/nimg.1998.0322 Rocca, 2020, Language beyond the language system: dorsal visuospatial pathways support processing of demonstratives and spatial language during naturalistic fast fMRI, Neuroimage, 216, 10.1016/j.neuroimage.2019.116128 Rungta, 2018, Vascular compartmentalization of functional hyperemia from the synapse to the pia, Neuron, 99, 10.1016/j.neuron.2018.06.012 Saad, 2003, Estimation of FMRI response delays, Neuroimage, 18, 494, 10.1016/S1053-8119(02)00024-1 Saalmann, 2015, The cognitive thalamus, Front. Syst. Neurosci., 9, 39, 10.3389/fnsys.2015.00039 Sadaghiani, 2009, Neural activity-induced modulation of BOLD poststimulus undershoot independent of the positive signal, Magn. Reson. Imaging, 27, 1030, 10.1016/j.mri.2009.04.003 Sahib, 2016, Effect of temporal resolution and serial autocorrelations in event-related functional MRI, Magn. Reson. Med., 76, 1805, 10.1002/mrm.26073 Sasai, 2021, Frequency-specific task modulation of human brain functional networks: a fast fMRI study, Neuroimage, 224, 10.1016/j.neuroimage.2020.117375 Sasaki, 2002, Optical imaging of intrinsic signals induced by peripheral nerve stimulation in the in vivo rat spinal cord, Neuroimage, 17, 1240, 10.1006/nimg.2002.1286 Satpute, 2013, Identification of discrete functional subregions of the human periaqueductal gray, Proc. Natl. Acad. Sci. U. S. A., 110, 17101, 10.1073/pnas.1306095110 Savoy, 2001, History and future directions of human brain mapping and functional neuroimaging, Acta Psychol. (Amst), 107, 9, 10.1016/S0001-6918(01)00018-X Savoy, 1994, Exploring the temporal resolution boundaries of fMRI: measuring responses to very brief visual stimuli, 20, 1264 Savoy, 1995, Pushing the temporal resolution of fMRI: studies of very brief visual stimuli, onset variability and asynchrony, and stimulus-correlated changes in noise, Proc. Soc. Magn. Reson. Third Sci. Meet. Exhib. VIII, 450 Schlegel, 2015, The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: implications on analysis of mouse fMRI data, Neuroimage, 116, 40, 10.1016/j.neuroimage.2015.05.013 Schmid, 2017, Depth-dependent flow and pressure characteristics in cortical microvascular networks, PLOS Comput. Biol., 13, 10.1371/journal.pcbi.1005392 Schmid, 2019, Vascular density and distribution in neocortex, Neuroimage, 197, 792, 10.1016/j.neuroimage.2017.06.046 Schneider, 2004, Retinotopic organization and functional subdivisions of the human lateral geniculate nucleus: a high-resolution functional magnetic resonance imaging study, J. Neurosci., 24, 8975, 10.1523/JNEUROSCI.2413-04.2004 Schölvinck, 2010, Neural basis of global resting-state fMRI activity, Proc. Natl. Acad. Sci. U. S. A., 107, 10238, 10.1073/pnas.0913110107 Sclocco, 2018, Challenges and opportunities for brainstem neuroimaging with ultrahigh field MRI, Neuroimage, 168, 412, 10.1016/j.neuroimage.2017.02.052 Secomb, 2004, Green’s function methods for analysis of oxygen delivery to tissue by microvascular networks, Ann. Biomed. Eng., 32, 1519, 10.1114/B:ABME.0000049036.08817.44 Segal, 1986, Flow control among microvessels coordinated by intercellular conduction, Science (80-.), 234, 868, 10.1126/science.3775368 Segal, 1989, Propagation of vasomotor responses coordinates arteriolar resistances, Am. J. Physiol., 256, H832 Sereno, 1995, Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging, Science (80-.), 268, 889, 10.1126/science.7754376 Setsompop, 2012, Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty, Magn. Reson. Med., 67, 1210, 10.1002/mrm.23097 Setsompop, 2016, Rapid brain MRI acquisition techniques at ultra-high fields, NMR Biomed., 29, 1198, 10.1002/nbm.3478 Shannon, 2013, Morning-evening variation in human brain metabolism and memory circuits, J. Neurophysiol., 109, 1444, 10.1152/jn.00651.2012 Sharpee, 2006, Adaptive filtering enhances information transmission in visual cortex, Nature, 439, 936, 10.1038/nature04519 Sheth, 2004, Columnar specificity of microvascular oxygenation and volume responses: implications for functional brain mapping, J. Neurosci., 24, 634, 10.1523/JNEUROSCI.4526-03.2004 Sheth, 2004, Linear and nonlinear relationships between neuronal activity, oxygen metabolism, and hemodynamic responses, Neuron, 42, 347, 10.1016/S0896-6273(04)00221-1 Shmuel, 2007, Spatio-temporal point-spread function of fMRI signal in human gray matter at 7 Tesla, Neuroimage, 35, 539, 10.1016/j.neuroimage.2006.12.030 Shokri-Kojori, 2019, Correspondence between cerebral glucose metabolism and BOLD reveals relative power and cost in human brain, Nat. Commun., 10, 690, 10.1038/s41467-019-08546-x Silva, 2002, Laminar specificity of functional MRI onset times during somatosensory stimulation in rat, Proc. Natl. Acad. Sci. U. S. A., 99, 15182, 10.1073/pnas.222561899 Silva, 2007, Functional MRI impulse response for BOLD and CBV contrast in rat somatosensory cortex, Magn. Reson. Med., 57, 1110, 10.1002/mrm.21246 Simon, 2015, Understanding the dynamic relationship between cerebral blood flow and the BOLD signal: implications for quantitative functional MRI, Neuroimage, 116, 158, 10.1016/j.neuroimage.2015.03.080 Simony, 2016, Dynamic reconfiguration of the default mode network during narrative comprehension, Nat. Commun., 7, 10.1038/ncomms12141 Sirotin, 2009, Spatiotemporal precision and hemodynamic mechanism of optical point spreads in alert primates, Proc. Natl. Acad. Sci. U. S. A., 106, 18390, 10.1073/pnas.0905509106 Smith, 2012, The danger of systematic bias in group-level FMRI-lag-based causality estimation, Neuroimage, 59, 1228, 10.1016/j.neuroimage.2011.08.015 Smith, 2012, Temporally-independent functional modes of spontaneous brain activity, Proc. Natl. Acad. Sci. U. S. A., 109, 3131, 10.1073/pnas.1121329109 Smith, 2019, Brain capillary networks across species: a few simple organizational requirements are sufficient to reproduce both structure and function, Front. Physiol., 10, 233, 10.3389/fphys.2019.00233 Soltysik, 2004, Comparison of hemodynamic response nonlinearity across primary cortical areas, Neuroimage, 22, 1117, 10.1016/j.neuroimage.2004.03.024 Soon, 2003, Stimulus repetition and hemodynamic response refractoriness in event-related fMRI, Hum. Brain Mapp., 20, 1, 10.1002/hbm.10122 Stephan, 2012, A short history of causal modeling of fMRI data, Neuroimage, 10.1016/j.neuroimage.2012.01.034 Steriade, 1993, A novel slow (< 1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components, J. Neurosci., 13, 3252, 10.1523/JNEUROSCI.13-08-03252.1993 Stigliani, 2017, Encoding model of temporal processing in human visual cortex, Proc. Natl. Acad. Sci. U. S. A., 114, E11047, 10.1073/pnas.1704877114 Su, 2004, Temporal resolving power of perfusion- and BOLD-based event-related functional MRI, Med. Phys., 31, 154, 10.1118/1.1634480 Tak, 2014, Dynamic and static contributions of the cerebrovasculature to the resting-state BOLD signal, Neuroimage, 84, 672, 10.1016/j.neuroimage.2013.09.057 Tak, 2015, Associations of resting-state fMRI functional connectivity with flow-BOLD coupling and regional vasculature, Brain Connect., 5, 137, 10.1089/brain.2014.0299 Thomas, 1998, Amplitude response and stimulus presentation frequency response of human primary visual cortex using BOLD EPI at 4 T, Magn. Reson. Med., 40, 203, 10.1002/mrm.1910400206 Thompson, 2014, Larger neural responses produce BOLD signals that begin earlier in time, Front. Neurosci., 8, 10.3389/fnins.2014.00159 Tian, 2010, Cortical depth-specific microvascular dilation underlies laminar differences in blood oxygenation level-dependent functional MRI signal, Proc. Natl. Acad. Sci. U. S. A., 107, 15246, 10.1073/pnas.1006735107 Troprès, 2001, Vessel size imaging, Magn. Reson. Med., 45, 397, 10.1002/1522-2594(200103)45:3<397::AID-MRM1052>3.0.CO;2-3 Tsai, 2009, Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels, J. Neurosci., 29, 14553, 10.1523/JNEUROSCI.3287-09.2009 Turner, 2002, How much cortex can a vein drain? Downstream dilution of activation-related cerebral blood oxygenation changes, Neuroimage, 16, 1062, 10.1006/nimg.2002.1082 Uğurbil, 2013, Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project, Neuroimage, 80, 80, 10.1016/j.neuroimage.2013.05.012 Uhlirova, 2016, Cell type specificity of neurovascular coupling in cerebral cortex, Elife, 5, 10.7554/eLife.14315 Uludağ, 2008, Transient and sustained BOLD responses to sustained visual stimulation, Magn. Reson. Imaging, 26, 863, 10.1016/j.mri.2008.01.049 Uludağ, 2010, To dip or not to dip: reconciling optical imaging and fMRI data, Proc. Natl. Acad. Sci. U. S. A., 107, 10.1073/pnas.0914194107 Uludağ, 2018, Linking brain vascular physiology to hemodynamic response in ultra-high field MRI, Neuroimage, 168, 279, 10.1016/j.neuroimage.2017.02.063 Uludağ, 2004, Coupling of cerebral blood flow and oxygen consumption during physiological activation and deactivation measured with fMRI, Neuroimage, 23, 148, 10.1016/j.neuroimage.2004.05.013 Uludağ, 2009, An integrative model for neuronal activity-induced signal changes for gradient and spin echo functional imaging, Neuroimage, 48, 150, 10.1016/j.neuroimage.2009.05.051 Vakorin, 2007, Inferring neural activity from BOLD signals through nonlinear optimization, Neuroimage, 38, 248, 10.1016/j.neuroimage.2007.06.033 Valdes-Sosa, 2011, Effective connectivity: influence, causality and biophysical modeling, Neuroimage., 10.1016/j.neuroimage.2011.03.058 Van De Ville, 2010, EEG microstate sequences in healthy humans at rest reveal scale-free dynamics, Proc. Natl. Acad. Sci. U. S. A., 107, 18179, 10.1073/pnas.1007841107 van Dijk, 2020, Linear systems analysis for laminar fMRI: evaluating BOLD amplitude scaling for luminance contrast manipulations, Sci. Rep., 10, 10.1038/s41598-020-62165-x van Raaij, 2012, Quantification of blood flow and volume in arterioles and venules of the rat cerebral cortex using functional micro-ultrasound, Neuroimage, 63, 1030, 10.1016/j.neuroimage.2012.07.054 Vazquez, 1998, Nonlinear aspects of the BOLD response in functional MRI, Neuroimage, 7, 108, 10.1006/nimg.1997.0316 Vazquez, 2006, Vascular dynamics and BOLD fMRI: CBF level effects and analysis considerations, Neuroimage, 32, 1642, 10.1016/j.neuroimage.2006.04.195 Vidaurre, 2016, Spectrally resolved fast transient brain states in electrophysiological data, Neuroimage, 126, 81, 10.1016/j.neuroimage.2015.11.047 Viessmann, 2019, Variability, BOLD temporal SNR bias and variance across the HCP population as a function of cortical B0-orientation and orientation, Proc. Intl. Soc. Mag. Reson. Med., 27, 0369 Viessmann, 2019, Dependence of resting-state fMRI fluctuation amplitudes on cerebral cortical orientation relative to the direction of B0 and anatomical axes, Neuroimage, 196, 337, 10.1016/j.neuroimage.2019.04.036 Villien, 2014, Dynamic functional imaging of brain glucose utilization using fPET-FDG, Neuroimage, 100, 10.1016/j.neuroimage.2014.06.025 Vizioli, 2018, Probing temporal information in fast-TR fMRI data during attention modulations, Proc. Intl. Soc. Mag. Reson. Med., 26, 0153 Vizioli, 2018, Temporal multivariate pattern analysis (tMVPA): a single trial approach exploring the temporal dynamics of the BOLD signal, J. Neurosci. Methods, 308, 74, 10.1016/j.jneumeth.2018.06.029 Vu, 2016, Using precise word timing information improves decoding accuracy in a multiband-accelerated multimodal reading experiment, Cogn. Neuropsychol., 33, 265, 10.1080/02643294.2016.1195343 Wager, 2005, Accounting for nonlinear BOLD effects in fMRI: parameter estimates and a model for prediction in rapid event-related studies, Neuroimage, 25, 206, 10.1016/j.neuroimage.2004.11.008 Wark, 2007, Sensory adaptation, Curr. Opin. Neurobiol., 10.1016/j.conb.2007.07.001 Wei, 2016, Erythrocytes are oxygen-sensing regulators of the cerebral microcirculation, Neuron, 91, 851, 10.1016/j.neuron.2016.07.016 Wenger, 2004, Comparison of sustained and transient activity in children and adults using a mixed blocked/event-related fMRI design, Neuroimage, 22, 975, 10.1016/j.neuroimage.2004.02.028 Wittkuhn, 2020, Faster than thought: detecting sub-second activation sequences with sequential fMRI pattern analysis, bioRxiv Woolrich, 2001, Temporal autocorrelation in univariate linear modeling of FMRI data, Neuroimage, 14, 1370, 10.1006/nimg.2001.0931 Woolrich, 2004, Constrained linear basis sets for HRF modelling using Variational Bayes, Neuroimage, 21, 1748, 10.1016/j.neuroimage.2003.12.024 Xie, 2020, Differential effects of anesthetics on resting state functional connectivity in the mouse, J. Cereb. Blood Flow Metab., 40, 875, 10.1177/0271678X19847123 Yablonskiy, 1994, Theory of NMR signal behavior in magnetically inhomogeneous tissues: the static dephasing regime, Magn. Reson. Med., 32, 749, 10.1002/mrm.1910320610 Yacoub, 2018, Pushing the spatio-temporal limits of MRI and fMRI, Neuroimage, 164, 1, 10.1016/j.neuroimage.2017.11.034 Yacoub, 2001, Investigation of the initial dip in fMRI at 7 Tesla, NMR Biomed., 14, 408, 10.1002/nbm.715 Yacoub, 2006, The spatial dependence of the poststimulus undershoot as revealed by high-resolution BOLD- and CBV-weighted fMRI, J. Cereb. Blood Flow Metab., 26, 634, 10.1038/sj.jcbfm.9600239 Yacoub, 2007, Robust detection of ocular dominance columns in humans using Hahn Spin Echo BOLD functional MRI at 7 Tesla, Neuroimage, 37, 1161, 10.1016/j.neuroimage.2007.05.020 Yacoub, 2008, High-field fMRI unveils orientation columns in humans, Proc. Natl. Acad. Sci. U. S. A., 105, 10607, 10.1073/pnas.0804110105 Yang, 2000, A CBF-based event-related brain activation paradigm: characterization of impulse-response function and comparison to BOLD, Neuroimage, 12, 287, 10.1006/nimg.2000.0625 Yang, 2019, High-resolution fMRI maps of columnar organization in human primary somatosensory cortex, Proc. Intl. Soc. Mag. Reson. Med., 27, 0617 Yen, 2011, BOLD responses to different temporal frequency stimuli in the lateral geniculate nucleus and visual cortex: insights into the neural basis of fMRI, Neuroimage, 58, 82, 10.1016/j.neuroimage.2011.06.022 Yeşilyurt, 2008, Dynamics and nonlinearities of the BOLD response at very short stimulus durations, Magn. Reson. Imaging, 26, 853, 10.1016/j.mri.2008.01.008 Yeşilyurt, 2010, Relationship of the BOLD signal with VEP for ultrashort duration visual stimuli (0.1 to 5 ms) in humans, J. Cereb. Blood Flow Metab., 30, 449, 10.1038/jcbfm.2009.224 Yu, 2012, Direct imaging of macrovascular and microvascular contributions to BOLD fMRI in layers IV-V of the rat whisker-barrel cortex, Neuroimage, 59, 1451, 10.1016/j.neuroimage.2011.08.001 Yu, 2014, Deciphering laminar-specific neural inputs with line-scanning fMRI, Nat. Methods, 11, 55, 10.1038/nmeth.2730 Yuan, 2012, Spatiotemporal dynamics of the brain at rest - exploring EEG microstates as electrophysiological signatures of BOLD resting state networks, Neuroimage, 60, 2062, 10.1016/j.neuroimage.2012.02.031 Zhang, 2008, Investigating the source of BOLD nonlinearity in human visual cortex in response to paired visual stimuli, Neuroimage, 43, 204, 10.1016/j.neuroimage.2008.06.033 Zhang, 2009, Linearity of blood-oxygenation-level dependent signal at microvasculature, Neuroimage, 48, 313, 10.1016/j.neuroimage.2009.06.071 Zheng, 2009, A time-invariant visco-elastic windkessel model relating blood flow and blood volume, Neuroimage, 47, 1371, 10.1016/j.neuroimage.2009.04.022 Zheng, 2005, A three-compartment model of the hemodynamic response and oxygen delivery to brain, Neuroimage, 28, 925, 10.1016/j.neuroimage.2005.06.042 Zhou, 2018, Compressive temporal summation in human visual cortex, J. Neurosci., 38, 691, 10.1523/JNEUROSCI.1724-17.2017 Zhou, 2019, Oxygen tension-mediated erythrocyte membrane interactions regulate cerebral capillary hyperemia, Sci. Adv., 5, 10.1126/sciadv.aaw4466