The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Neurophysiological investigation of the basis of the fMRI signal
Abstract
Functional magnetic resonance imaging (fMRI) is widely used to study the operational organization of the human brain, but the exact relationship between the measured fMRI signal and the underlying neural activity is unclear. Here we present simultaneous intracortical recordings of neural signals and fMRI responses. We compared local field potentials (LFPs), single- and multi-unit spiking activity with highly spatio-temporally resolved blood-oxygen-level-dependent (BOLD) fMRI responses from the visual cortex of monkeys. The largest magnitude changes were observed in LFPs, which at recording sites characterized by transient responses were the only signal that significantly correlated with the haemodynamic response. Linear systems analysis on a trial-by-trial basis showed that the impulse response of the neurovascular system is both animal- and site-specific, and that LFPs yield a better estimate of BOLD responses than the multi-unit responses. These findings suggest that the BOLD contrast mechanism reflects the input and intracortical processing of a given area rather than its spiking output.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Importantly, local field potentials and tissue oxygen response, which directly contribute to the generation of the BOLD signals (Logothetis et al., 2001), were preserved at both frequencies.”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Logothetis et al., 2001
In the citing paper
“Although the electrophysiological activity in V1 could not be directly assessed in our experiment, based on the literature (Logothetis et al., 2001) we can obtain a rough surrogate of V1 output by evaluating fMRI signals in the secondary visual areas, which receive input directly from V1.”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Logothetis et al., 2001
In the citing paper
“and EEG oscillations are associated with hemodynamic signals (29-32).”
From Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep (2019) · cites this paper as [29]
In the citing paper
“When recorded simultaneously during sensory stimulation, the BOLD response is more correlated with LFP than MUA (129, 130).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [129]
In the citing paper
“Increasing evidence suggests that the primary source of fMRI is synaptic activity, rather than spiking activity, in the gray matter (129, 130).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [129]
In the citing paper
“The BOLD response is thought to be generated by local excitatory synaptic activity (Logothetis et al., 2001), leading to precisely localised changes in blood flow in response to the release of glutamate (Attwell and Iadecola, 2002).”
From The social brain in adolescence: evidence from functional magnetic resonance imaging and behavioural studies (2011) · cites this paper as Logothetis et al., 2001
In the citing paper
“Under the view that the fMRI BOLD signal reflects in part the input into an area and intrinsic computations within it (Logothetis et al., 2001)”
From States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning (2010) · cites this paper as Logothetis et al., 2001
In the citing paper
“which was also observed under anesthesia in previous EEG-fMRI and intrinsic optical signal (IOS)-fMRI studies35,36.”
From Local hippocampal fast gamma rhythms precede brain-wide hyperemic patterns during spontaneous rodent REM sleep (2018) · cites this paper as [35]
In the citing paper
“Gradient echo T2*-weighted echo-planar images (EPIs) sensitive to the BOLD contrast were acquired as an index of local increases in synaptic activity (48)”
From Threatening a rubber hand that you feel is yours elicits a cortical anxiety response. (2007) · cites this paper as [48]
In the citing paper
“fMRI is one the most common and reliable methods of measuring brain function at decent spatial and temporal resolutions, but given that it is an indirect measure of brain activity, reflecting a paradigm related change in metabolic consumption (Logothetis, Pauls et al. 2001), interpretation of gene effects is limited.”
From Developmental imaging genetics: Linking dopamine function to adolescent behavior (2014) · cites this paper as Logothetis, Pauls et al. 2001
Citations
Cites
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.
Kwong, K. K., Belliveau, J. W., Chesler, D. A., Goldberg, I. E., Weisskoff, R. M., Poncelet, B. P., Kennedy, D. N., Hoppel, B. E., Cohen, M. S., & Turner, R. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.12.5675 · Cited by 4,212
Pellerin, L., & Magistretti, P. J. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.22.10625 · Cited by 2,927
Neuronal Synchrony: A Versatile Code for the Definition of Relations?
Singer, W. (1999) · Neuron · doi:10.1016/s0896-6273(00)80821-1 · Cited by 2,581
Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1
Boynton, G., Engel, S., Glover, G., & Heeger, D. (1996) · Journal of Neuroscience · doi:10.1523/jneurosci.16-13-04207.1996 · Cited by 2,522
Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex
Gray, C. M., & Singer, W. (1989) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.86.5.1698 · Cited by 2,463
Coherent oscillations: A mechanism of feature linking in the visual cortex?
Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., & Reitboeck, H. J. (1988) · Biological Cybernetics · doi:10.1007/bf00202899 · Cited by 2,329
Time course EPI of human brain function during task activation
Bandettini, P. A., Wong, E. C., Hinks, R. S., Tikofsky, R. S., & Hyde, J. S. (1992) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910250220 · Cited by 1,935
Multi-planar image formation using NMR spin echoes
Mansfield, P. (1977) · Journal of Physics C Solid State Physics · doi:10.1088/0022-3719/10/3/004 · Cited by 1,809
Synchronization of cortical activity and its putative role in information processing and learning
Singer, W. (1993) · Annual Review of Physiology · doi:10.1146/annurev.ph.55.030193.002025 · Cited by 1,685
Dynamics of blood flow and oxygenation changes during brain activation: the Balloon model
Buxton, R. B., Wong, E. C., & Frank, L. R. (1998) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910390602 · Cited by 1,665
Flagged first, then by citations
Research works printed but not linked: 2
- Juergens, E., Eckhorn, R., Frien, A. & Woelbern, T. Brain and Evolution 418 (Thieme, Berlin, 1996).
- Sokoloff, L. in Basic Neurochemistry (eds Siegel, G., Agranoff, B., Albers, R. W. & Molinoff, P.) 565–590 (Raven, New York, 1989).
Cited by
Sorted by citations
Items 1,301–1,400 of 6,331
Brain Activity Fluctuations Propagate as Waves Traversing the Cortical Hierarchy
Gu, Y., Sainburg, L. E., Kuang, S., Han, F., Williams, J. W., Liu, Y., Zhang, N., Zhang, X., Leopold, D. A., & Liu, X. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab064 · Cited by 95
Liu, R., Huang, Z.-A., Hu, Y. F., Zhu, Z., Wong, K., & Tan, K. C. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3243000 · Cited by 92
The cognitive auditory cortex: Task-specificity of stimulus representations
Scheich, H., Brechmann, A., Brosch, M., Budinger, E., & Ohl, F. W. (2007) · Hearing Research · doi:10.1016/j.heares.2007.01.025 · Cited by 92
Macefield, V. G., & Henderson, L. A. (2009) · Human Brain Mapping · doi:10.1002/hbm.20885 · Cited by 92
A Guide to Delineate the Logic of Neurovascular Signaling in the Brain
Kleinfeld, D., Blinder, P., Drew, P. J., Driscoll, J. D., Muller, A., Tsai, P. S., & Shih, A. Y. (2011) · Frontiers in Neuroenergetics · doi:10.3389/fnene.2011.00001 · Cited by 94
Correlation Between BOLD fMRI and Theta-Band Local Field Potentials in the Human Hippocampal Area
Ekstrom, A. D., Suthana, N., Millett, D., Fried, I., & Bookheimer, S. Y. (2009) · Journal of Neurophysiology · doi:10.1152/jn.91252.2008 · Cited by 96
fMRI of sensitization to angry faces
Strauss, M., Makris, N., Aharon, I., Vangel, M. G., GOODMAN, J., Kennedy, D. W., Gasic, G. P., & BREITER, H. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.01.053 · Cited by 94
The Optimality of Sensory Processing during the Speed-Accuracy Tradeoff
Ho, T. C., Brown, S. D., van Maanen, L., Forstmann, B. U., Wagenmakers, E., & Serences, J. T. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0340-12.2012 · Cited by 95
Ojemann, G. A., Ojemann, J., & Ramsey, N. F. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00034 · Cited by 92
Dynamic relationships between spontaneous and evoked electrophysiological activity
Wainio‐Theberge, S., Wolff, A., & Northoff, G. (2021) · Communications Biology · doi:10.1038/s42003-021-02240-9 · Cited by 101
Functional Connectivity of the Brain Across Rodents and Humans
Xu, N., LaGrow, T. J., Anumba, N., Lee, A., Zhang, X., Yousefi, B., Bassil, Y., Clavijo, P. G., Sharghi, V. K., Maltbie, E. A., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.816331 · Cited by 100
Ultrasonic Deep Brain Neuromodulation in Acute Disorders of Consciousness: A Proof-of-Concept
Cain, J. A., Spivak, N. M., Coetzee, J. P., Crone, J. S., Johnson, M. A., Lutkenhoff, E. S., Real, C. R., Buitrago‐Blanco, M., Vespa, P. M., Schnakers, C., et al. (2022) · Brain Sciences · doi:10.3390/brainsci12040428 · Cited by 91
Muthukumaraswamy, S. D., & Singh, K. D. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.01.052 · Cited by 91
Mazerolle, E. L., Beyea, S., Gawryluk, J. R., Brewer, K., Bowen, C. V., & D’Arcy, R. C. N. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.102 · Cited by 91
Lipton, M. L., Fu, K.-M. G., Branch, C. A., & Schroeder, C. E. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.1073-05.2006 · Cited by 91
Coding of Stereoscopic Depth Information in Visual Areas V3 and V3A
Anzai, A., Chowdhury, S. A., & DeAngelis, G. C. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5956-10.2011 · Cited by 91
Natural grouping of neural responses reveals spatially segregated clusters in prearcuate cortex
Kiani, R., Cueva, C. J., Reppas, J., Peixoto, D., Ryu, S., & Newsome, W. (2015) · Neuron · doi:10.1016/j.neuron.2015.02.014 · Cited by 96
Multimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle
Babiloni, F., Mattia, D., Babiloni, C., Astolfi, L., Salinari, S., Basilisco, A., Rossini, P. M., Marciani, M. G., & Cincotti, F. (2004) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2004.10.007 · Cited by 91
Abbott, C., Jaramillo, A. A., Wilcox, C. E., & Hamilton, D. A. (2013) · Current Medicinal Chemistry · doi:10.2174/092986713804870864 · Cited by 93
Learning to Select Actions with Spiking Neurons in the Basal Ganglia
Stewart, T. C., Bekolay, T., & Eliasmith, C. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00002 · Cited by 95
Spikes, BOLD, Attention, and Awareness: A comparison of electrophysiological and fMRI signals in V1
Boynton, G. M. (2011) · Journal of Vision · doi:10.1167/11.5.12 · Cited by 97
Automatic Semantic Facilitation in Anterior Temporal Cortex Revealed through Multimodal Neuroimaging
Lau, E. F., Gramfort, A., Hämäläinen, M., & Kuperberg, G. R. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1018-13.2013 · Cited by 93
Amplitude of low-frequency fluctuations in bipolar disorder: A resting state fMRI study
Xu, K., Liu, H., Li, H., Tang, Y., Womer, F. Y., Jiang, X., Chen, K., Zhou, Y., Jiang, W., Luο, X., et al. (2013) · Journal of Affective Disorders · doi:10.1016/j.jad.2013.09.017 · Cited by 90
Large-Scale Organization of Rat Sensorimotor Cortex Based on a Motif of Large Activation Spreads
Frostig, R. D., Xiong, Y., Chen‐Bee, C. H., Kvašňák, E., & Stehberg, J. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.4074-08.2008 · Cited by 90
The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex
Self, M. W., Peters, J. C., Possel, J. K., Reithler, J., Goebel, R., Ris, P., Jeurissen, D., Reddy, L., Claus, S., Baayen, J. C., et al. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002420 · Cited by 92
Characterizing the role of the structural connectome in seizure dynamics
Shah, P., Ashourvan, A., Mikhail, F., Pines, A. R., Kini, L. G., Oechsel, K. F., Das, S. R., Stein, J. M., Shinohara, R. T., Bassett, D. S., et al. (2019) · Brain · doi:10.1093/brain/awz125 · Cited by 94
Auletta, G. (2011) · doi:10.1093/acprof:oso/9780199608485.001.0001 · Cited by 91
Boyd, R. N., Sakzewski, L., Ziviani, J. M., Abbott, D. F., Badawy, R. A. B., Gilmore, R., Provan, K., Tournier, J., Macdonell, R. A. L., & Jackson, G. D. (2010) · BMC Neurology · doi:10.1186/1471-2377-10-4 · Cited by 90
Mizuhara, H., Wang, L., KOBAYASHI, K., & Yamaguchi, Y. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.04.030 · Cited by 90
Neural Correlates of Disparity-Defined Shape Discrimination in the Human Brain
Chandrasekaran, C., Canon, V., Dahmen, J. C., Kourtzi, Z., & Welchman, A. E. (2006) · Journal of Neurophysiology · doi:10.1152/jn.01074.2006 · Cited by 90
Efficient foot motor control by Neymar’s brain
Naito, E., & Hirose, S. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00594 · Cited by 90
Own-Song Recognition in the Songbird Auditory Pathway: Selectivity and Lateralization
Poirier, C., Boumans, T., Verhoye, M., Balthazart, J., & der Linden, A. V. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.4650-08.2009 · Cited by 90
Enhanced brain motor activity in patients with MS after a single dose of 3,4-diaminopyridine
Mainero, C., Inghilleri, M., Pantano, P., Conte, A., Lenzi, A., Frasca, V., Bozzao, L., & Pozzilli, C. (2004) · Neurology · doi:10.1212/01.wnl.0000129263.14219.a8 · Cited by 91
Self, M. W., van Kerkoerle, T., Goebel, R., & Roelfsema, P. R. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.045 · Cited by 94
Gean, A. D., & Fischbein, N. J. (2010) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2010.08.001 · Cited by 90
Morgan, V. L., Sonmezturk, H. H., Gore, J. C., & Abou-Khalil, B. W. (2012) · Epilepsia · doi:10.1111/j.1528-1167.2012.03590.x · Cited by 89
Masterton, R. A. J., Harvey, A. S., Archer, J. S., Lillywhite, L. M., Abbott, D. F., Scheffer, I. E., & Jackson, G. D. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.109 · Cited by 89
Visual Quality Determines the Direction of Neural Repetition Effects
Turk‐Browne, N. B., Yi, D.-J., Leber, A. B., & Chun, M. M. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhj159 · Cited by 89
Functional MRI for Surgery of Gliomas
Castellano, A., Cirillo, S., Bello, L., Riva, M., & Falini, A. (2017) · Current Treatment Options in Neurology · doi:10.1007/s11940-017-0469-y · Cited by 95
Neuroimaging in alcohol use disorder: From mouse to man
Fritz, M., Klawonn, A. M., & Zahr, N. M. (2019) · Journal of Neuroscience Research · doi:10.1002/jnr.24423 · Cited by 89
Deng, G. E., Hou, B. L., Holodny, A. I., & Cassileth, B. R. (2008) · BMC Complementary and Alternative Medicine · doi:10.1186/1472-6882-8-37 · Cited by 89
Epileptic Discharges Affect the Default Mode Network – fMRI and Intracerebral EEG Evidence
Fahoum, F., Zelmann, R., Tyvaert, L., Dubeau, F., & Gotman, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068038 · Cited by 90
Chen, L. M., Turner, G. H., Friedman, R. M., Zhang, N., Gore, J. C., Roe, A. W., & Avison, M. J. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.1588-07.2007 · Cited by 89
Volition to Action—An Event-Related fMRI Study
Winterer, G., Adams, C. M., Jones, D. W., & Knutson, B. D. (2002) · NeuroImage · doi:10.1006/nimg.2002.1232 · Cited by 91
Bilek, E., Schäfer, A., Ochs, E., Esslinger, C., Zangl, M., Plichta, M. M., Braun, U., Kirsch, P., Schulze, T. G., Rietschel, M., et al. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.3081-12.2013 · Cited by 92
Linear and nonlinear relationships between visual stimuli, EEG and BOLD fMRI signals
Liu, Z., Rios, C., Zhang, N., Yang, L., Chen, W., & He, B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.017 · Cited by 88
Cortical layers, rhythms and BOLD signals
Scheeringa, R., & Fries, P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.002 · Cited by 88
Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data
Dähne, S., Bieszmann, F., Samek, W., Haufe, S., Goltz, D., Gundlach, C., Villringer, A., Fazli, S., & Müller, K. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2425807 · Cited by 88
The combination of EEG Source Imaging and EEG‐correlated functional MRI to map epileptic networks
Vulliémoz, S., Lemieux, L., Jean Daunizeau, A., Michel, C. M., & Duncan, J. S. (2009) · Epilepsia · doi:10.1111/j.1528-1167.2009.02342.x · Cited by 92
Unraveling the complexity of human brain: Structure, function in healthy and disease states
Sultana, O. F., Bandaru, M., Islam, M. A., & Reddy, P. H. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102414 · Cited by 92
Wengenroth, M., Blatow, M., Guenther, J., Akbar, M. B., Tronnier, V. M., & Stippich, C. (2011) · European Radiology · doi:10.1007/s00330-011-2067-9 · Cited by 88
Prefrontal cortex hemispheric specialization for categorical and coordinate visual spatial memory
Slotnick, S. D., & Moo, L. R. (2006) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2006.01.018 · Cited by 88
Takeuchi, M., Hori, E., Takamoto, K., Tran, A. H., Kohno, S., Ishikawa, A., Ono, T., Endo, S., & Nishijo, H. (2009) · Brain Topography · doi:10.1007/s10548-009-0109-2 · Cited by 88
Jacobi, B., Bongartz, G. M., Partovi, S., Schulte, A., Aschwanden, M., Lumsden, A. B., Davies, M. G., Loebe, M. M., Noon, G. P., Karimi, S., et al. (2012) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.23536 · Cited by 88
Jacobs, S., Danielmeier, C., & Frey, S. H. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21372 · Cited by 88
Handbook of Reward and Decision Making
Dreher, J., & Tremblay, L. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374620-7.x0001-5 · Cited by 88
An, L., Cao, X.-H., Cao, Q.-J., Sun, L., Yang, L., Zou, Q.-H., Katya, R., Zang, Y.-F., & Wang, Y.-F. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2013.27 · Cited by 88
Developmental imaging genetics: Linking dopamine function to adolescent behavior
Padmanabhan, A., & Luna, B. (2014) · Brain and Cognition · doi:10.1016/j.bandc.2013.09.011 · Cited by 87
The Role of Evolved Perceptual Biases in Art and Design
Coss, R. G. (2003) · Springer eBooks · doi:10.1007/978-3-662-07142-7_4 · Cited by 88
Brain functional magnetic resonance imaging response to glucose and fructose infusions in humans
Purnell, J. Q., Klopfenstein, B. A., Stevens, A. A., Havel, P. J., Adams, S. H., Dunn, T. N., Krisky, C. M., & Rooney, W. D. (2010) · Diabetes Obesity and Metabolism · doi:10.1111/j.1463-1326.2010.01340.x · Cited by 91
Korzeniewska, A., Franaszczuk, P. J., Crainiceanu, C. M., Kuś, R., & Crone, N. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.030 · Cited by 88
Robitaille, N., Marois, R., Todd, J., Grimault, S., Cheyne, D., & Jolicœur, P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.027 · Cited by 87
Fazli, S., Dähne, S., Samek, W., Bieszmann, F., & Müller, K. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2413993 · Cited by 90
Spontaneous Beta Band Rhythms in the Predictive Coding of Natural Stimuli
Betti, V., Penna, S. D., de Pasquale, F., & Corbetta, M. (2020) · The Neuroscientist · doi:10.1177/1073858420928988 · Cited by 97
Modulation of the BOLD-response in early recovery from sensorimotor stroke
Binkofski, F., & Seitz, R. J. (2004) · Neurology · doi:10.1212/01.wnl.0000140468.92212.be · Cited by 87
Comparison of hemodynamic response nonlinearity across primary cortical areas
Soltysik, D. A., Peck, K. K., White, K. D., Crosson, B., & Briggs, R. W. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.024 · Cited by 87
Generators of Movement-Related Cortical Potentials: fMRI-Constrained EEG Dipole Source Analysis
Toma, K., Matsuoka, T., Immisch, I., Mima, T., Waldvogel, D., Koshy, B., Hanakawa, T., Shill, H. A., & Hallett, M. (2002) · NeuroImage · doi:10.1006/nimg.2002.1165 · Cited by 87
Wan, X., Riera, J. J., Iwata, K., Takahashi, M. K., Wakabayashi, T., & Kawashima, R. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.03.040 · Cited by 87
Smart Magnetic Resonance Imaging Agents that Sense Extracellular Calcium Fluctuations
Angelovski, G., Fousková, P., Mamedov, I. S., Canals, S., Tóth, É., & Logothetis, N. K. (2008) · ChemBioChem · doi:10.1002/cbic.200800165 · Cited by 93
Self-citationDeciphering neuron-glia compartmentalization in cortical energy metabolism
Jolivet, R. (2009) · Frontiers in Neuroenergetics · doi:10.3389/neuro.14.004.2009 · Cited by 89
Pashaie, R., Anikeeva, P., Lee, J. H., Prakash, R., Yizhar, O., Prigge, M., Chander, D., Richner, T. J., & Williams, J. C. (2014) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2013.2294796 · Cited by 88
Validating an image-based fNIRS approach with fMRI and a working memory task
Wijeakumar, S., Huppert, T. J., Magnotta, V. A., Buss, A. T., & Spencer, J. P. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.007 · Cited by 86
Ponce‐Alvarez, A., He, B. J., Hagmann, P., & Deco, G. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004445 · Cited by 86
High field MRI in preclinical research
Marzola, P., Osculati, F., & Sbarbati, A. (2003) · European Journal of Radiology · doi:10.1016/j.ejrad.2003.08.007 · Cited by 86
Ances, B. M. (2003) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/01.wcb.0000103920.96801.12 · Cited by 86
Kim, H., Kim, Y. K., Gwak, A. R., Lim, J.-A., Lee, J., Jung, H. Y., Sohn, B. K., Choi, S., Kim, D., & Choi, J. (2015) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2015.02.004 · Cited by 86
Quantitative fMRI and oxidative neuroenergetics
Hyder, F., & Rothman, D. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.04.027 · Cited by 88
The BOLD post-stimulus undershoot, one of the most debated issues in fMRI
van Zijl, P. C. M., Hua, J., & Lu, H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.029 · Cited by 86
Structural and functional evaluation of cortical motor areas in Amyotrophic Lateral Sclerosis
Cosottini, M., Pesaresi, I., Piazza, S., Diciotti, S., Cecchi, P. C., Fabbri, S., Carlesi, C., Mascalchi, M., & Siciliano, G. (2011) · Experimental Neurology · doi:10.1016/j.expneurol.2011.12.024 · Cited by 86
Resting-state fMRI correlations: From link-wise unreliability to whole brain stability
Pannunzi, M., Hindriks, R., Bettinardi, R. G., Wenger, E., Lisofsky, N., Mårtensson, J., Butler, O., Filevich, E., Becker, M., Lochstet, M., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.006 · Cited by 93
Husain, F. T., Tagamets, M.-A., Fromm, S. J., Braun, A., & Horwitz, B. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.11.012 · Cited by 86
Anatomical and functional MR imaging in the macaque monkey using a vertical large-bore 7 Tesla setup
Pfeuffer, J., Merkle, H., Beyerlein, M., Steudel, T., & Logothetis, N. K. (2004) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2004.10.004 · Cited by 86
Self-citationVazquez, A. L., Fukuda, M., Crowley, J. C., & Kim, S.-G. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht147 · Cited by 85
Integration of local features into global shapes: monkey and human fMRI studies
Kourtzi, Z., Tolias, A. S., Altmann, C. F., Augath, M. A., & Logothetis, N. K. (2010) · Journal of Vision · doi:10.1167/3.9.191 · Cited by 85
Self-citationFunctional connectomics from a “big data” perspective
Xia, M., & Yong He, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.031 · Cited by 85
Yuan, C., Zhu, H., Ren, Z., Yuan, M., Gao, M., Zhang, Y., Li, Y., Meng, Y., Gong, Q., Lui, S., et al. (2017) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2017.12.002 · Cited by 85
Cross-species neuroscience: closing the explanatory gap
Barron, H. C., Mars, R. B., Dupret, D., Lerch, J. P., & Sampaio‐Baptista, C. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0633 · Cited by 89
Thalamus and focal to bilateral seizures
Caciagli, L., Allen, L. A., He, X., Trimmel, K., Vos, S. B., Centeno, M., Galovic, M., Sidhu, M. K., Thompson, P. J., Bassett, D. S., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000010645 · Cited by 85
Role of anterior cingulate cortex inputs to periaqueductal gray for pain avoidance
Lee, J.-Y., You, T., Lee, C.-H., Im, G. H., Seo, H., Woo, C., & Kim, S. (2022) · Current Biology · doi:10.1016/j.cub.2022.04.090 · Cited by 91
Psychogenic nonepileptic seizures: A current overview
Dickinson, P., & Looper, K. J. (2012) · Epilepsia · doi:10.1111/j.1528-1167.2012.03606.x · Cited by 87
Vidal, J. R., Freyermuth, S., Jerbi, K., Hamamé, C. M., Ossandón, T., Bertrand, O., Minotti, L., Kahane, P., Berthoz, A., & Lachaux, J.-P. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.4363-11.2012 · Cited by 92
Manoach, D. S., Thakkar, K. N., Cain, M. S., Polli, F. E., Edelman, J. A., Fischl, B. R., & Barton, J. J. S. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.3662-06.2007 · Cited by 87
Temporal kernel CCA and its application in multimodal neuronal data analysis
Bießmann, F., Meinecke, F. C., Gretton, A., Rauch, A., Rainer, G., Logothetis, N. K., & Müller, K. (2009) · Machine Learning · doi:10.1007/s10994-009-5153-3 · Cited by 87
Self-citationCazalis, F., Valabrègue, R., Pélégrini‐Issac, M., Asloun, S., Robbins, T. W., & Granon, S. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02633.x · Cited by 85
Lotze, M., Kaethner, R. J., Erb, M., Cohen, L. G., Grodd, W., & Topka, H. R. (2003) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00380-2 · Cited by 85
Voluntary activation and cortical activity during a sustained maximal contraction: An fMRI study
Post, M., Steens, A., Renken, R. J., Maurits, N. M., & Zijdewind, I. (2008) · Human Brain Mapping · doi:10.1002/hbm.20562 · Cited by 85
MarsAtlas : A cortical parcellation atlas for functional mapping
Auzias, G., Coulon, O., & Brovelli, A. (2016) · Human Brain Mapping · doi:10.1002/hbm.23121 · Cited by 85
Lifting the veil on the dynamics of neuronal activities evoked by transcranial magnetic stimulation
Li, B., Virtanen, J. P., Oeltermann, A., Schwarz, C., Giese, M. A., Ziemann, U., & Benali, A. (2017) · eLife · doi:10.7554/elife.30552 · Cited by 88
Self-citationMacefield, V. G., Gandevia, S. C., & Henderson, L. A. (2005) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00588.2005 · Cited by 85
When frequencies never synchronize: the golden mean and the resting EEG
Pletzer, B., Kerschbaum, H., & Klimesch, W. (2010) · Brain Research · doi:10.1016/j.brainres.2010.03.074 · Cited by 84
Metadata
- Authors
- Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A.
- Affiliations
- Max Planck Institute for Biological Cybernetics (DE)
- Max Planck Society (DE)
- Corresponding author
- Logothetis, Nikos K.
- ORCID
- Logothetis, Nikos K.
- Venue
- Nature
- Published
- 2001-07-12
- Volume
- 412
- Issue
- 6843
- Pages
- 150-157
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2114104729
- Cited by
- 6,551
- References
- 50
- Citations by year
- 2026: 182 · 2025: 226 · 2024: 197 · 2023: 209 · 2022: 245 · 2021: 286 · 2020: 244 · 2019: 301 · 2018: 234 · 2017: 311 · 2016: 258 · 2015: 297 · 2014: 288 · 2013: 298 · 2012: 321
- FWCI
- 168.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Max-Planck-Gesellschaft
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- BOLD signal, local field potentials, intracortical recording, neurovascular coupling, hemodynamic response, visual cortex, linear systems analysis, impulse response, monkeys, neural activity estimation
- MeSH terms
- Action Potentials, Animals, Electrodes, Electrophysiology, Hemodynamics, Macaca mulatta, Magnetic Resonance Imaging, Synaptic Transmission, Neurons, Oxygen, Photic Stimulation, Signal Processing, Computer-Assisted, Visual Cortex, Contrast Sensitivity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
