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
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 501–600 of 6,331
Hand use predicts the structure of representations in sensorimotor cortex
Ejaz, N., Hamada, M., & Diedrichsen, J. (2015) · Nature Neuroscience · doi:10.1038/nn.4038 · Cited by 233
Simultaneous BOLD fMRI and fiber-optic calcium recording in rat neocortex
Schulz, K., Sydekum, E., Krueppel, R., Engelbrecht, C. J., Schlegel, F., Schroeter, A., Rudin, M., & Helmchen, F. (2012) · Nature Methods · doi:10.1038/nmeth.2013 · Cited by 245
Neural dynamics for facial threat processing as revealed by gamma band synchronization using MEG
Luo, Q., Holroyd, T., Jones, M., Hendler, T., & Blair, J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.023 · Cited by 242
Berman, S. M., Naliboff, B. D., Suyenobu, B. Y., Labus, J. S., Stains, J., Ohning, G., Kilpatrick, L. A., Bueller, J. A., Ruby, K., Jarcho, J. M., et al. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.2500-07.2008 · Cited by 235
Figley, C. R., & Stroman, P. W. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07584.x · Cited by 246
How Well Do Clinical Pain Assessment Tools Reflect Pain in Infants?
Slater, R., Cantarella, A., Franck, L. S., Meek, J. H., & Fitzgerald, M. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050129 · Cited by 232
Apolipoprotein E and Alzheimer’s disease: Findings, hypotheses, and potential mechanisms
Koutsodendris, N., Nelson, M. R., Rao, A., & Huang, Y. (2022) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-030421-112756 · Cited by 231
Infraslow LFP correlates to resting-state fMRI BOLD signals
Pan, W.-J., Thompson, G. J., Magnuson, M. E., Jaeger, D., & Keilholz, S. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.035 · Cited by 231
Functional Imaging Reveals Numerous Fields in the Monkey Auditory Cortex
Petkov, C. I., Kayser, C., Augath, M. A., & Logothetis, N. K. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040215 · Cited by 231
Self-citationFunctional Imaging Reveals Visual Modulation of Specific Fields in Auditory Cortex
Kayser, C., Petkov, C., Augath, M., & Logothetis, N. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.4737-06.2007 · Cited by 280
Self-citationElectroencephalography and High-Density Electrophysiological Source Localization
Pizzagalli, D. A. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511546396.003 · Cited by 239
Functional Imaging of the Human Lateral Geniculate Nucleus and Pulvinar
Kastner, S., O'Connor, D. H., Fukui, M. M., Fehd, H. M., Herwig, U., & Pinsk, M. A. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00553.2003 · Cited by 228
Naito, E. (2002) · doi:10.1016/s0896-6273(02)00980-7 · Cited by 227
fMRI “deactivation” of the posterior cingulate during generalized spike and wave
Archer, J. S. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00294-5 · Cited by 227
Neural mechanisms of information storage in visual short-term memory
Serences, J. T. (2016) · Vision Research · doi:10.1016/j.visres.2016.09.010 · Cited by 247
Rangarajan, V., Hermes, D., Foster, B. L., Weiner, K. S., Jacques, C., Grill-Spector, K., & Parvizi, J. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0527-14.2014 · Cited by 226
Increased Gamma Brainwave Amplitude Compared to Control in Three Different Meditation Traditions
Braboszcz, C., Cahn, B. R., Levy, J., Fernandez, M., & Delorme, A. (2017) · PLoS ONE · doi:10.1371/journal.pone.0170647 · Cited by 225
Primary visual cortex activity along the apparent-motion trace reflects illusory perception
Muckli, L., Kohler, A., Kriegeskorte, N., & Singer, W. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030265 · Cited by 225
Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback
Zotev, V. S., Phillips, R., Yuan, H., Misaki, M., & Bodurka, J. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.126 · Cited by 225
Albouy, P., Weiss, A., Baillet, S., & Zatorre, R. J. (2017) · Neuron · doi:10.1016/j.neuron.2017.03.015 · Cited by 241
Goghari, V. M., Sponheim, S. R., & MacDonald, A. W. (2009) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2009.09.004 · Cited by 233
Luo, H., Liu, Z., & Poeppel, D. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000445 · Cited by 233
Tonotopic mapping of human auditory cortex
Sàenz, M., & Langers, D. R. M. (2013) · Hearing Research · doi:10.1016/j.heares.2013.07.016 · Cited by 222
Functional connectivity of cortical motor areas in the resting state in Parkinson's disease
Wu, T., Long, X., Wang, L. Y., Hallett, M., Zang, Y., Li, K., & Chan, P. (2010) · Human Brain Mapping · doi:10.1002/hbm.21118 · Cited by 229
Guterstam, A., Gentile, G., & Ehrsson, H. H. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00393 · Cited by 238
Ferris, C. F., Kulkarni, P. P., Sullivan, J. M., Harder, J. A., Messenger, T. L., & Febo, M. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.3156-04.2005 · Cited by 222
Spatiotemporal dynamics of word processing in the human brain
Canolty, R. T. (2007) · Frontiers in Neuroscience · doi:10.3389/neuro.01.1.1.014.2007 · Cited by 226
The Evolution of Language: A Comparative Review
Fitch, W. T. (2005) · Biology & Philosophy · doi:10.1007/s10539-005-5597-1 · Cited by 137
Gentile, G., Guterstam, A., Brozzoli, C., & Ehrsson, H. H. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1363-13.2013 · Cited by 221
A Neural System for Learning about Object Function
Weisberg, J., van Turennout, M., & Martin, A. D. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhj176 · Cited by 221
Layer-specific BOLD activation in human V1
Koopmans, P. J., Barth, M., & Norris, D. G. (2010) · Human Brain Mapping · doi:10.1002/hbm.20936 · Cited by 220
The Frontal Generator of the Mismatch Negativity Revisited
Deouell, L. Y. (2007) · Journal of Psychophysiology · doi:10.1027/0269-8803.21.34.188 · Cited by 220
Lack of long-term cortical reorganization after macaque retinal lesions
Smirnakis, S. M., Brewer, A. A., Schmid, M. C., Tolias, A. S., Schüz, A., Augath, M. A., INHOFFEN, W., Wandell, B. A., & Logothetis, N. K. (2005) · Nature · doi:10.1038/nature03495 · Cited by 230
Self-citationVisual Areas in Macaque Cortex Measured Using Functional Magnetic Resonance Imaging
Brewer, A. A., Press, W., Logothetis, N. K., & Wandell, B. A. (2002) · Journal of Neuroscience · doi:10.1523/jneurosci.22-23-10416.2002 · Cited by 219
Self-citationThe mechanisms of tinnitus: Perspectives from human functional neuroimaging
Adjamian, P., Sereda, M., & Hall, D. A. (2009) · Hearing Research · doi:10.1016/j.heares.2009.04.001 · Cited by 232
Top‐Down Modulation and Normal Aging
Gazzaley, A. H., & D’Esposito, M. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1379.010 · Cited by 238
Panteleimon Ekkekakis, A. (2009) · Journal of Sport and Exercise Psychology · doi:10.1123/jsep.31.4.505 · Cited by 233
Repetition suppression: a means to index neural representations using BOLD?
Barron, H. C., Garvert, M. M., & Behrens, T. E. J. (2016) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2015.0355 · Cited by 229
Human gamma-band activity: A window to cognitive processing
Kaiser, J., & Lutzenberger, W. (2005) · Neuroreport · doi:10.1097/00001756-200502280-00001 · Cited by 218
A quantitative theory of immediate visual recognition
Serre, T., Kreiman, G., Kouh, M., Cadieu, C. F., Knoblich, U., & Poggio, T. (2007) · Progress in brain research · doi:10.1016/s0079-6123(06)65004-8 · Cited by 221
Simultaneous EEG-fMRI during a Working Memory Task: Modulations in Low and High Frequency Bands
Michels, L., Bücher, K., Lüchinger, R., Klaver, P., Martin, E., Jeanmonod, D., & Brandeis, D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010298 · Cited by 217
Northoff, G., Heinzel, A., Bermpohl, F., Niese, R., Pfennig, A., Pascual‐Leone, Á., & Schlaug, G. (2004) · Human Brain Mapping · doi:10.1002/hbm.20002 · Cited by 216
Kishida, K. T., Sáez, I., Lohrenz, T. M., Witcher, M. R., Laxton, A. W., Tatter, S. B., White, J. P., Ellis, T. L., Phillips, P. E. M., & Montague, P. R. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1513619112 · Cited by 224
Gao, Y., Ma, Y., Zhang, Q., Winder, A. T., Liang, Z., Antinori, L., Drew, P. J., & Zhang, N. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.069 · Cited by 226
Bridging Neural and Computational Viewpoints on Perceptual Decision-Making
O’Connell, R. G., Shadlen, M. N., Wong‐Lin, K., & Kelly, S. P. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.06.005 · Cited by 217
Response Suppression in V1 Agrees with Psychophysics of Surround Masking
Zenger-Landolt, B., & Heeger, D. J. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-17-06884.2003 · Cited by 214
Neurovascular coupling in normal aging: A combined optical, ERP and fMRI study
Fabiani, M., Gordon, B. A., Maclin, E. L., Pearson, M. A., Brumback, C. R., Low, K. A., McAuley, E., Sutton, B. P., Kramer, A. F., & Gratton, G. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.113 · Cited by 230
Spatiotemporal imaging of cortical activation during verb generation and picture naming
Edwards, E., Nagarajan, S. S., Dalal, S. S., Canolty, R. T., Kirsch, H. E., Barbaro, N. M., & Knight, R. T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.035 · Cited by 219
Integrating new findings and examining clinical applications of pattern separation
Leal, S. L., & Yassa, M. A. (2018) · Nature Neuroscience · doi:10.1038/s41593-017-0065-1 · Cited by 228
The advantage of combining MEG and EEG: Comparison to fMRI in focally stimulated visual cortex
Sharon, D., Hämäläinen, M., Tootell, R. B. H., Halgren, E., & Belliveau, J. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.066 · Cited by 212
A Microsaccadic Rhythm Modulates Gamma-Band Synchronization and Behavior
Bosman, C. A., Womelsdorf, T., Desimone, R., & Fries, P. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1193-09.2009 · Cited by 212
Sabatinelli, D., Keil, A., Frank, D. W., & Lang, P. J. (2012) · Biological Psychology · doi:10.1016/j.biopsycho.2012.04.005 · Cited by 212
Human finger somatotopy in areas 3b, 1, and 2: A 7T fMRI study using a natural stimulus
Martuzzi, R., van der Zwaag, W., Farthouat, J., Rolf Gruetter, A., & Blanke, O. (2012) · Human Brain Mapping · doi:10.1002/hbm.22172 · Cited by 212
BOLD functional MRI in disease and pharmacological studies: room for improvement?
Iannetti, G. D., & Wise, R. G. (2007) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2007.03.018 · Cited by 220
Chouinard, P. A., van der Werf, Y. D., Leonard, G. T., & Paus, T. (2003) · Journal of Neurophysiology · doi:10.1152/jn.01105.2002 · Cited by 218
Task activations produce spurious but systematic inflation of task functional connectivity estimates
Cole, M. W., Ito, T., Schultz, D. H., Mill, R. D., Chen, R. J., & Cocuzza, C. V. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.12.054 · Cited by 218
Inferring Spike Trains From Local Field Potentials
Rasch, M. J., Gretton, A., Murayama, Y., Maass, W., & Logothetis, N. K. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00919.2007 · Cited by 217
Self-citationHuman neural learning depends on reward prediction errors in the blocking paradigm.
Tobler, P. N., O’Doherty, J. P., Dolan, R. J., & Schultz, W. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00762.2005 · Cited by 209
A universal role of the ventral striatum in reward-based learning: Evidence from human studies
Daniel, R., & Pollmann, S. (2014) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2014.05.002 · Cited by 225
Coherent Oscillatory Activity in Monkey Area V4 Predicts Successful Allocation of Attention
Taylor, K., Mandon, S., Freiwald, W. A., & Kreiter, A. K. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhi023 · Cited by 209
Touch, sound and vision in human superior temporal sulcus
Beauchamp, M. S., Yasar, N. E., Frye, R. E., & Ro, T. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.015 · Cited by 208
Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands
Gohel, S., & Biswal, B. B. (2014) · Brain Connectivity · doi:10.1089/brain.2013.0210 · Cited by 215
Translational and reverse translational research on the role of stress in drug craving and relapse
Sinha, R., Shaham, Y., & Heilig, M. A. (2011) · Psychopharmacology · doi:10.1007/s00213-011-2263-y · Cited by 218
Bestmann, S., Swayne, O. B. C., Blankenburg, F., Ruff, C. C., Haggard, P., Weiskopf, N., Josephs, O., Driver, J., Rothwell, J. C., & Ward, N. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm159 · Cited by 208
Ossandón, T., Jerbi, K., Vidal, J. R., Bayle, D. J., Hénaff, M., Jung, J., Minotti, L., Bertrand, O., Kahane, P., & Lachaux, J.-P. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.2483-11.2011 · Cited by 222
Neurophysiological investigation of the basis of the fMRI signal
(2001) · Nature · doi:10.1038/news010712-13 · Cited by 207
Hemodynamic correlates of EEG: a heuristic
Kilner, J. M., Mattout, J., Henson, R., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.008 · Cited by 206
Static and dynamic characteristics of cerebral blood flow during the resting state
Zou, Q., Wu, C. W., Stein, E. A., Zang, Y., & Yang, Y. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.07.006 · Cited by 209
Functional and cortical adaptations to central vision loss
Cheung, S. H., & Legge, G. E. (2005) · Visual Neuroscience · doi:10.1017/s0952523805222071 · Cited by 214
Total neuroenergetics support localized brain activity: Implications for the interpretation of fMRI
Hyder, F., Rothman, D. L., & Shulman, R. G. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.132272299 · Cited by 205
Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging
Nogay, H. S., & Adeli, H. (2020) · Reviews in the Neurosciences · doi:10.1515/revneuro-2020-0043 · Cited by 212
Studying spontaneous EEG activity with fMRI
Salek‐Haddadi, A., Friston, K. J., Lemieux, L., & Fish, D. R. (2003) · Brain Research Reviews · doi:10.1016/s0165-0173(03)00193-0 · Cited by 205
A template for spatial normalisation of MR images of the rat brain
Schweinhardt, P., Fransson, P., Olson, L., Spenger, C., & Andersson, J. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(03)00192-4 · Cited by 204
Laws of concatenated perception: Vision goes for novelty, decisions for perseverance
Pascucci, D., Mancuso, G., Santandrea, E., Libera, C. D., Plomp, G., & Chelazzi, L. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000144 · Cited by 217
A role for fMRI in optimizing CNS drug development
Borsook, D., Becerra, L. R., & Hargreaves, R. J. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2027 · Cited by 207
Cortical and subcortical blood flow effects of subthalamic nucleus stimulation in PD
Hershey, T. G., Revilla, F. J., Wernle, A., McGee‐Minnich, L., Antenor, J. V., Videen, T. O., Dowling, J. L., Mink, J. W., & Perlmutter, J. S. (2003) · Neurology · doi:10.1212/01.wnl.0000083991.81859.73 · Cited by 203
Induced Gamma-Band Activity and Human Brain Function
Kaiser, J., & Lutzenberger, W. (2003) · The Neuroscientist · doi:10.1177/1073858403259137 · Cited by 203
Optimizing real time fMRI neurofeedback for therapeutic discovery and development
Stoeckel, L. E., Garrison, K. A., Ghosh, S., Wighton, P., Hanlon, C. A., Gilman, J. M., Greer, S. M., Turk‐Browne, N. B., deBettencourt, M. T., Scheinost, D., et al. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.07.002 · Cited by 209
Emotional imagery: Assessing pleasure and arousal in the brain's reward circuitry
Costa, V. D., Lang, P. J., Sabatinelli, D., Versace, F., & Bradley, M. M. (2010) · Human Brain Mapping · doi:10.1002/hbm.20948 · Cited by 202
Lizier, J. T., Heinzle, J., Horstmann, A., Haynes, J., & Prokopenko, M. (2010) · Journal of Computational Neuroscience · doi:10.1007/s10827-010-0271-2 · Cited by 202
Deactivation of the Parahippocampal Gyrus Preceding Auditory Hallucinations in Schizophrenia
Diederen, K. M. J., Neggers, S. F. W., Daalman, K., Blom, J. D., Goekoop, R., Kahn, R. S., & Sommer, I. E. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2009.09040456 · Cited by 202
Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics?
Rossini, P. M. (2003) · Brain · doi:10.1093/brain/awh012 · Cited by 202
Contrast Adaptation and Representation in Human Early Visual Cortex
Gardner, J. L., Sun, P., Waggoner, R. A., Ueno, K., Tanaka, K., & Cheng, K. (2005) · Neuron · doi:10.1016/j.neuron.2005.07.016 · Cited by 208
Neural plasticity of development and learning
Galván, A. (2010) · Human Brain Mapping · doi:10.1002/hbm.21029 · Cited by 226
Changes in activity of striato–thalamo–cortical network precede generalized spike wave discharges
Moeller, F., Siebner, H. R., Wolff, S., Muhle, H., Boor, R., Granert, O., Jansen, O., Stephani, U., & Siniatchkin, M. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.058 · Cited by 201
Zhang, W., Jin, Z. H., Cui, G., Zhang, K.-L., Zhang, L., Zeng, Y., Luo, F., Chen, A. C. N., & Han, J. (2003) · Brain Research · doi:10.1016/s0006-8993(03)02983-4 · Cited by 201
Neural correlates of single-vessel haemodynamic responses in vivo
O’Herron, P. J., Chhatbar, P. Y., Levy, M. S., Shen, Z., Schramm, A. E., Lu, Z., & Kara, P. (2016) · Nature · doi:10.1038/nature17965 · Cited by 212
Golfinopoulos, E., Tourville, J. A., & Guenther, F. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.023 · Cited by 200
Change detection in children with autism: an auditory event-related fMRI study
Gomot, M., Bernard, F. A., Davis, M. H., Belmonte, M. K., Ashwin, C., Bullmore, E. T., & Baron-Cohen, S. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.07.027 · Cited by 199
Multivoxel Pattern Analysis for fMRI Data: A Review
Mahmoudi, A., Takerkart, S., Regragui, F., Boussaoud, D., & Brovelli, A. (2012) · Computational and Mathematical Methods in Medicine · doi:10.1155/2012/961257 · Cited by 206
Meltzer, J. A., Negishi, M., Mayes, L. C., & Constable, R. T. (2007) · Clinical Neurophysiology · doi:10.1016/j.clinph.2007.07.023 · Cited by 207
Representation, Pattern Information, and Brain Signatures: From Neurons to Neuroimaging
Kragel, P. A., Koban, L., Barrett, L. F., & Wager, T. D. (2018) · Neuron · doi:10.1016/j.neuron.2018.06.009 · Cited by 212
Neuroimaging Weighs In: Humans Meet Macaques in “Primate” Visual Cortex
Tootell, R. B. H., Tsao, D. Y., & Vanduffel, W. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-10-03981.2003 · Cited by 200
How accurate is magnetic resonance imaging of brain function?
Uǧurbil, K., Toth, L. J., & Kim, D. (2003) · Trends in Neurosciences · doi:10.1016/s0166-2236(02)00039-5 · Cited by 198
Human brain mapping: Hemodynamic response and electrophysiology
Shibasaki, H. (2008) · Clinical Neurophysiology · doi:10.1016/j.clinph.2007.10.026 · Cited by 197
Reddy, H. (2002) · Brain · doi:10.1093/brain/awf283 · Cited by 196
Laminar specificity in monkey V1 using high-resolution SE-fMRI
Goense, J. B. M., & Logothetis, N. K. (2006) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2005.12.032 · Cited by 195
Self-citationThe Radial Bias: A Different Slant on Visual Orientation Sensitivity in Human and Nonhuman Primates
Sasaki, Y., Rajimehr, R., Kim, B. W., Ekstrom, L. B., Vanduffel, W., & Tootell, R. B. H. (2006) · Neuron · doi:10.1016/j.neuron.2006.07.021 · Cited by 195
Gao, W., Gilmore, J. H., Shen, D., Smith, J. K., Zhu, H., & Lin, W. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs043 · Cited by 194
Endogenous brain oscillations and related networks detected by surface EEG‐combined fMRI
Laufs, H. (2008) · Human Brain Mapping · doi:10.1002/hbm.20600 · Cited by 194
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
