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 801–900 of 6,331
Atypical intrinsic neural timescale in autism
Watanabe, T., Rees, G., & Masuda, N. (2019) · eLife · doi:10.7554/elife.42256 · Cited by 150
It was the best of times, it was the worst of times: A psychophysiologist's view of cognitive aging
Fabiani, M. (2012) · Psychophysiology · doi:10.1111/j.1469-8986.2011.01331.x · Cited by 161
Functional activity mapping of the mesial hemispheric wall during anticipation of pain
Porro, C. A., Cettolo, V., Francescato, M. P., & Baraldi, P. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00184-8 · Cited by 150
The Brain–Cognitive Behavior Problem: A Retrospective
Buzsáki, G. (2020) · eNeuro · doi:10.1523/eneuro.0069-20.2020 · Cited by 150
A new look at domain specificity: Insights from social neuroscience
Spunt, R. P., & Adolphs, R. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.76 · Cited by 149
The mechanisms of action of deep brain stimulation and ideas for the future development
Udupa, K., & Chen, R. E. (2015) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2015.08.001 · Cited by 149
On the Foundations of NeuroIS: Reflections on the Gmunden Retreat 2009
Riedl, R., Banker, R. D., Benbasat, I., Davis, F. D., Dennis, A. R., Dimoka, A., Gefen, D., Gupta, A., Ischebeck, A. K., Kenning, P. H., et al. (2010) · Communications of the Association for Information Systems · doi:10.17705/1cais.02715 · Cited by 149
Neuroimaging Biomarkers of Neurodegenerative Diseases and Dementia
Risacher, S. L., & Saykin, A. J. (2013) · Seminars in Neurology · doi:10.1055/s-0033-1359312 · Cited by 155
The neuroscience of meditation: classification, phenomenology, correlates, and mechanisms
Brandmeyer, T., Arnaud Delorme, A., & Wahbeh, H. (2019) · Progress in brain research · doi:10.1016/bs.pbr.2018.10.020 · Cited by 164
Vascular and neural basis of the BOLD signal
Drew, P. J. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.06.004 · Cited by 165
Perceptual grouping and the interactions between visual cortical areas
Murray, S. O., Schrater, P., & Kersten, D. (2004) · Neural Networks · doi:10.1016/j.neunet.2004.03.010 · Cited by 153
Aslin, R. N., & Mehler, J. (2005) · Journal of Biomedical Optics · doi:10.1117/1.1854672 · Cited by 148
The “Task B problem” and other considerations in developmental functional neuroimaging
Church, J. A., Petersen, S. E., & Schlaggar, B. L. (2010) · Human Brain Mapping · doi:10.1002/hbm.21036 · Cited by 148
Bettus, G., Ranjeva, J., Wendling, F., Bénar, C., Sylviane Confort-gouny, A., Régis, J. M., Chauvel, P., Cozzone, P. J., Lemieux, L., Bartoloméi, F., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020071 · Cited by 153
Influence of early attentional modulation on working memory
Gazzaley, A. H. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2010.12.022 · Cited by 166
Energy landscape and dynamics of brain activity during human bistable perception
Watanabe, T., Masuda, N., Megumi, F., Kanai, R., & Rees, G. E. (2014) · Nature Communications · doi:10.1038/ncomms5765 · Cited by 153
Bartels, A., Zeki, S., & Logothetis, N. K. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm107 · Cited by 148
Self-citationLi, L. M., Violante, I. R., Leech, R., Ross, E., Hampshire, A., Opitz, A., Rothwell, J. C., Carmichael, D. W., & Sharp, D. J. (2018) · Human Brain Mapping · doi:10.1002/hbm.24420 · Cited by 159
Why is everyone talking about brain state?
Greene, A. S., Horien, C. L., Barson, D. G., Scheinost, D., & Constable, R. T. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.04.001 · Cited by 161
A Parametric Study of Mental Spatial Transformations of Bodies
Zacks, J. M. (2002) · NeuroImage · doi:10.1006/nimg.2002.1129 · Cited by 148
Dynamics of gamma-band activity in human magnetoencephalogram during auditory pattern working memory
Kaiser, J., Ripper, B., Birbaumer, N., & Lutzenberger, W. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00350-1 · Cited by 148
Is Gamma-Band Activity in the Local Field Potential of V1 Cortex a "Clock" or Filtered Noise?
Burns, S. P., Xing, D., & Shapley, R. M. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.0660-11.2011 · Cited by 152
Detection and scaling of task-induced fMRI-BOLD response using resting state fluctuations
Kannurpatti, S. S., & Biswal, B. B. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.040 · Cited by 147
Big data and the industrialization of neuroscience: A safe roadmap for understanding the brain?
Frégnac, Y. (2017) · Science · doi:10.1126/science.aan8866 · Cited by 152
Ritchie, J. B., Kaplan, D. M., & Klein, C. (2017) · The British Journal for the Philosophy of Science · doi:10.1093/bjps/axx023 · Cited by 161
Soft and MRI Compatible Neural Electrodes from Carbon Nanotube Fibers
Lu, L., Fu, X., Liew, Y., Zhang, Y., Zhao, S., Xu, Z., Zhao, J., Li, D., Li, Q., Stanley, G. B., et al. (2019) · Nano Letters · doi:10.1021/acs.nanolett.8b04456 · Cited by 146
Rauch, A., Rainer, G., & Logothetis, N. K. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800312105 · Cited by 146
Self-citationSehatpour, P., Molholm, S., Javitt, D. C., & Foxe, J. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.07.049 · Cited by 146
Tai, K., & Chau, T. T. (2009) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-6-39 · Cited by 151
Lewis, M. M., Du, G., Sen, S., Kawaguchi, A., Truong, Y., Lee, S., Mailman, R. B., & Huang, X. (2011) · Neuroscience · doi:10.1016/j.neuroscience.2010.12.060 · Cited by 149
Yoon, J. H., Minzenberg, M., Raouf, S., D’Esposito, M., & Carter, C. S. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.11.018 · Cited by 146
Human intracranial high-frequency activity maps episodic memory formation in space and time
Burke, J. F., Long, N. M., Zaghloul, K. A., Sharan, A. D., Sperling, M. R., & Kahana, M. J. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.067 · Cited by 149
fMRI and its interpretations: an illustration on directional selectivity in area V5/MT
Bartels, A., Logothetis, N. K., & Moutoussis, K. (2008) · Trends in Neurosciences · doi:10.1016/j.tins.2008.06.004 · Cited by 150
Self-citationKocharyan, A., Fernandes, P., Tong, X., Vaucher, E., & Hamel, É. (2007) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600558 · Cited by 146
Human Scalp Electroencephalography Reveals that Repetition Suppression Varies with Expectation
Summerfield, C., Wyart, V., Johnen, V. M., & de Gardelle, V. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00067 · Cited by 145
Simultaneous intracranial EEG and fMRI of interictal epileptic discharges in humans
Vulliémoz, S., Carmichael, D. W., Rosenkranz, K., Diehl, B., Rodionov, R., Walker, M. C., McEvoy, A. W., & Lemieux, L. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.004 · Cited by 153
Northoff, G., & Sibille, E. L. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.68 · Cited by 148
Chee, M. W. L., Soon, C. S., & Lee, H. L. (2003) · Journal of Cognitive Neuroscience · doi:10.1162/089892903321107846 · Cited by 148
Schmidt, M., Bakker, R., Shen, K., Bezgin, G., Diesmann, M., & van Albada, S. J. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006359 · Cited by 157
The power of spectral density analysis for mapping endogenous BOLD signal fluctuations
Duff, E. P., Johnston, L. A., Xiong, J., Fox, P. T., Mareels, I., & Egan, G. F. (2008) · Human Brain Mapping · doi:10.1002/hbm.20601 · Cited by 145
Neural activity in the visual thalamus reflects perceptual suppression
Wilke, M., Mueller, K.-M., & Leopold, D. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900714106 · Cited by 144
Drew, P. J., Matéo, C., Turner, K. L., Yu, X., & Kleinfeld, D. (2020) · Neuron · doi:10.1016/j.neuron.2020.07.020 · Cited by 152
Understanding the Neural Basis of Amblyopia
Barrett, B. T., Bradley, A., & McGraw, P. V. (2004) · The Neuroscientist · doi:10.1177/1073858403262153 · Cited by 144
Attentional modulation of oscillatory activity in human visual cortex
Yamagishi, N., Callan, D. E., Goda, N., Anderson, S. J., Yoshida, Y., & Kawato, M. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00341-0 · Cited by 151
Brown, M. R. G., Goltz, H. C., Vilis, T., Ford, K. A., & Everling, S. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.07.002 · Cited by 143
Functional transcranial Doppler sonography as a tool in psychophysiological research
Duschek, S., & Schandry, R. (2003) · Psychophysiology · doi:10.1111/1469-8986.00046 · Cited by 146
Neurophysiology and neuroanatomy of reflexive and voluntary saccades in non-human primates
Johnston, K., & Everling, S. (2008) · Brain and Cognition · doi:10.1016/j.bandc.2008.08.017 · Cited by 152
Adaptive Changes in Cortical Receptive Fields Induced by Attention to Complex Sounds
Fritz, J. B., Elhilali, M., & Shamma, S. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00552.2007 · Cited by 145
Endless Fluctuations: Temporal Dynamics of the Amplitude of Low Frequency Fluctuations
Liao, W., Chen, H., Li, J., Ji, G., Wu, G., Long, Z., Xu, Q., Duan, X., Cui, Q., & Biswal, B. B. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2904555 · Cited by 143
Dynamics of motor-related functional integration during motor sequence learning
Coynel, D., Marrelec, G., Perlbarg, V., Pélégrini‐Issac, M., de Moortele, P. V., Uǧurbil, K., Doyon, J., Benali, H., & Lehéricy, S. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.048 · Cited by 143
Bledowski, C., Kadosh, K. C., Wibral, M., Rahm, B., Bittner, R. A., Hoechstetter, K., Scherg, M., Maurer, K., Goebel, R., & Linden, D. E. J. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.3542-05.2006 · Cited by 143
White-matter functional networks changes in patients with schizophrenia
Jiang, Y., Luo, C., Li, X., Li, Y., Yang, H., Li, J., Chang, X., Li, H., Yang, H., Wang, J., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.018 · Cited by 145
Coding of Natural Scenes in Primary Visual Cortex
Weliky, M., Fiser, J., Hunt, R. H., & Wagner, D. N. (2003) · Neuron · doi:10.1016/s0896-6273(03)00022-9 · Cited by 144
Spatial goal coding in the hippocampal formation
Nyberg, N., Duvelle, É., Barry, C., & Spiers, H. J. (2022) · Neuron · doi:10.1016/j.neuron.2021.12.012 · Cited by 141
Reward-related processing in the human brain: developmental considerations
Fareri, D. S., Martin, L. N., & Delgado, M. R. (2008) · Development and Psychopathology · doi:10.1017/s0954579408000576 · Cited by 141
Towards a framework for the study of the neural correlates of aesthetic preference
Capó, M. À., Cela‐Conde, C. J., Munar, E., Rosselló, J., & Nadal, M. (2008) · Spatial Vision · doi:10.1163/156856808784532653 · Cited by 144
Physiological measurements using ultra-high field fMRI: a review
Francis, S., & Sánchez-Panchuelo, R.-M. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/9/r167 · Cited by 142
Sensory system interactions during simultaneous vestibular and visual stimulation in PET
Deutschlander, A. B., Bense, S., Stephan, T., Schwaiger, M., Brandt, T., & Dieterich, M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10030 · Cited by 141
Lui, S., Yao, L., Xiao, Y., Keedy, S., Reilly, J. L., Keefe, R. S. E., Tamminga, C. A., Keshavan, M. S., Pearlson, G. D., Gong, Q., et al. (2014) · Psychological Medicine · doi:10.1017/s003329171400110x · Cited by 141
Non-BOLD contrast for laminar fMRI in humans: CBF, CBV, and CMRO2
Huber, L., Uludaǧ, K., & Möller, H. E. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.041 · Cited by 141
Cao, J., Chen, X., Chen, J., Ai, M., Gan, Y., Wang, W., Lv, Z., Zhang, S., Zhang, S., Wang, S., et al. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.07.002 · Cited by 140
Pourtois, G., Spinelli, L., Seeck, M., & Vuilleumier, P. O. (2010) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.10.1.83 · Cited by 152
Hutchison, R. M., & Everling, S. (2012) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2012.00029 · Cited by 143
Neurovascular coupling is brain region-dependent
Devonshire, I. M., Papadakis, N. G., Port, M., Berwick, J., Kennerley, A. J., Mayhew, J. E. W., & Overton, P. G. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.050 · Cited by 151
Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain
Ip, I. B., Berrington, A., Hess, A. T., Parker, A. J., Emir, U. E., & Bridge, H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.030 · Cited by 148
Temporal coupling of field potentials and action potentials in the neocortex
Watson, B. O., Ding, M., & Buzsáki, G. (2017) · European Journal of Neuroscience · doi:10.1111/ejn.13807 · Cited by 147
Joint independent component analysis for simultaneous EEG–fMRI: Principle and simulation
Moosmann, M., Eichele, T., Nordby, H., Hugdahl, K., & Calhoun, V. D. (2007) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2007.05.016 · Cited by 145
Rotshtein, P., Malach, R., Hadar, U., Graif, M., & Hendler, T. (2001) · Neuron · doi:10.1016/s0896-6273(01)00513-x · Cited by 141
Neurovascular coupling to D2/D3 dopamine receptor occupancy using simultaneous PET/functional MRI
Sander, C. Y. M., Hooker, J. M., Catana, C., Normandin, M. D., Alpert, N. M., Knudsen, G. M., Vanduffel, W., Rosen, B. R., & Mandeville, J. B. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1220512110 · Cited by 139
Investigating the post-stimulus undershoot of the BOLD signal—a simultaneous fMRI and fNIRS study
Schroeter, M. L., Kupka, T., Mildner, T., Uludaǧ, K., & von Cramon, D. Y. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.09.048 · Cited by 139
O’Neill, G. C., Barratt, E. L., Hunt, B. A. E., Tewarie, P. K. B., & Brookes, M. J. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/21/r271 · Cited by 149
Neural Basis for Priming of Pop-Out during Visual Search Revealed with fMRI
Kristjansson, A. K., Vuilleumier, P. O., Schwartz, S., Macaluso, E., & Driver, J. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhl072 · Cited by 148
Combining EEG and fMRI to investigate the post-movement beta rebound
Parkes, L. M., BASTIAANSEN, M. C. M., & Norris, D. G. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.08.018 · Cited by 139
Auditory hallucinations elicit similar brain activation in psychotic and nonpsychotic individuals
Diederen, K. M. J., Daalman, K., de Weijer, A. D., Neggers, S. F. W., van Gastel, W., Blom, J. D., Kahn, R. S., & Sommer, I. E. C. (2012) · Schizophrenia Bulletin · doi:10.1093/schbul/sbr033 · Cited by 138
fMRI of the Face-Processing Network in the Ventral Temporal Lobe of Awake and Anesthetized Macaques
Ku, S.-P., Tolias, A. S., Logothetis, N. K., & Goense, J. B. M. (2011) · Neuron · doi:10.1016/j.neuron.2011.02.048 · Cited by 147
Self-citationMultivariate Patterns in Object-Selective Cortex Dissociate Perceptual and Physical Shape Similarity
Haushofer, J., Livingstone, M. S., & Kanwisher, N. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060187 · Cited by 138
Functional brain imaging of swallowing: An activation likelihood estimation meta‐analysis
Sörös, P., Inamoto, Y., & Martin, R. E. (2008) · Human Brain Mapping · doi:10.1002/hbm.20680 · Cited by 138
Aubert, A., & Costalat, R. (2005) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600144 · Cited by 142
Vanni, S., Warnking, J. M., Michel Dojat, D., Delon‐Martin, C., Bullier, J., & Segebarth, C. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.10.047 · Cited by 138
Gatzke-Kopp, L. M., Beauchaine, T. P., Shannon, K. E., Chipman, J., Fleming, A. P., Crowell, S. E., Liang, O., Johnson, L. C., & Aylward, E. (2009) · Journal of Abnormal Psychology · doi:10.1037/a0014378 · Cited by 137
Neuronal mechanisms underlying control of a brain–computer interface
Hinterberger, T., Veit, R., Wilhelm, B., Weiskopf, N., Vatine, J., & Birbaumer, N. (2005) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2005.04092.x · Cited by 142
Pfeuffer, J., de Moortele, P. V., Yacoub, E. S., Shmuel, A., Adriany, G., Andersen, P. E., Merkle, H., Garwood, M., Uǧurbil, K., & Hu, X. P. (2002) · NeuroImage · doi:10.1006/nimg.2002.1103 · Cited by 137
High-Frequency Activity in Human Visual Cortex Is Modulated by Visual Motion Strength
Siegel, M., Donner, T. H., Oostenveld, R., Fries, P., & Engel, A. K. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhk025 · Cited by 141
Human visual cortex responds to invisible chromatic flicker
Jiang, Y., Zhou, K., & He, S. (2007) · Nature Neuroscience · doi:10.1038/nn1879 · Cited by 137
Dastjerdi, M., Foster, B. L., Nasrullah, S., Rauschecker, A. M., Dougherty, R. F., Townsend, J. D., Chang, C., Greicius, M. D., Menon, V., Kennedy, D. P., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017098108 · Cited by 137
Dietary Caffeine Consumption Modulates fMRI Measures
Laurienti, P. J., Field, A. S., Burdette, J. H., Maldjian, J. A., Yen, Y.-F., & Moody, D. M. (2002) · NeuroImage · doi:10.1006/nimg.2002.1237 · Cited by 136
Functional near Infrared Optical Imaging in Cognitive Neuroscience: An Introductory Review
Cutini, S., Moro, S. B., & Bisconti, S. (2012) · Journal of Near Infrared Spectroscopy · doi:10.1255/jnirs.969 · Cited by 140
Kong, F., Hu, S., Wang, X., Song, Y., & Liu, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.033 · Cited by 139
Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands
Deligianni, F., Centeno, M., Carmichael, D. W., & Clayden, J. D. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00258 · Cited by 136
van Oers, C. A. M. M., Vink, M., van Zandvoort, M. J. E., van der Worp, H. B., de Haan, E. H. F., Kappelle, L. J., Ramsey, N. F., & Dijkhuizen, R. M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.057 · Cited by 136
Which “neural activity” do you mean? fMRI, MEG, oscillations and neurotransmitters
Singh, K. D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.028 · Cited by 141
Obrig, H., Israel, H., Kohl‐Bareis, M., Uludaǧ, K., Wenzel, R., Müller, B., Arnold, G., & Villringer, A. (2002) · NeuroImage · doi:10.1006/nimg.2002.1177 · Cited by 136
Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism
Sotero, R. C., & Trujillo‐Barreto, N. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.001 · Cited by 136
Ciuciu, P., Poline, J.-B., Marrelec, G., Idier, J., Pallier, C., & Benali, H. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.817759 · Cited by 136
Meta-analysis of human prediction error for incentives, perception, cognition, and action
Corlett, P. R., Mollick, J. A., & Kober, H. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01264-3 · Cited by 135
Mesoscopic Imaging: Shining a Wide Light on Large-Scale Neural Dynamics
Cardin, J. A., Crair, M. C., & Higley, M. J. (2020) · Neuron · doi:10.1016/j.neuron.2020.09.031 · Cited by 135
Cortical dynamics of word recognition
Mainy, N., Jung, J., Baciu, M., Kahane, P., Schoendorff, B., Minotti, L., Hoffmann, D., Bertrand, O., & Lachaux, J.-P. (2007) · Human Brain Mapping · doi:10.1002/hbm.20457 · Cited by 139
Hutchison, R. M., Hutchison, M., Manning, K. Y., Menon, R. S., & Everling, S. (2014) · Human Brain Mapping · doi:10.1002/hbm.22583 · Cited by 141
Frontal and Temporal Dysfunction of Auditory Stimulus Processing in Schizophrenia
Gallinat, J., Mulert, C., Bajbouj, M., Herrmann, W. M., Schunter, J., Senkowski, D., Moukhtieva, R., Kronfeldt, D., & Winterer, G. (2002) · NeuroImage · doi:10.1006/nimg.2002.1213 · Cited by 135
Organization of the Visual Cortex in Human Albinism
Hoffmann, M. B., Tolhurst, D. J., Moore, A. T., & Morland, A. B. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-26-08921.2003 · Cited by 135
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
