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 5,801–5,900 of 6,331
The Notion of Person in Neuroscience: From Cognitivism to a Comprehensive Phenomenology
Bernácer, J., & Güell, F. (2021) · Springer eBooks · doi:10.1007/978-3-030-61721-9_11
Revised supplementary material
Kupiainen-Määttä, O. (2016) · Atmospheric chemistry and physics · doi:10.5194/acp-2016-168-ac4
Yan, W., Zhao, D., Liu, K., Deng, Y., Xie, L., Lai, Y., Li, J., Huang, W., Mo, C., Zeng, T., et al. (2020) · Research Square · doi:10.21203/rs.2.19796/v1
ОГРАНИЧЕНИЯ МЕТОДА фМРТ В ПСИХОФИЗИОЛОГИЧЕСКИХ ИССЛЕДОВАНИЯХ
Горкин, А. Г. (2020) · Институт психологии Российской академии наук eBooks · doi:10.38098/ergo.2020.005
Dissociable oscillatory networks support gain and loss processing in human orbitofrontal cortexPreprint
Sáez, I., Lin, J. J., Chang, E. F., Parvizi, J., Knight, R. T., & Hsu, M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.25.432874
Neural substrates of visual and tactile integration about the object recognition by fMRI
Provincial, J., & Iu, S.-F. (2009)
Removing Artifacts of Invasive Neural Recording Induced by MRI Scanning
Zhang, Y., Song, L., Guo, J., Song, Z., Fang, T., Zhang, X., Zhan, G., Wang, S., Li, H., Tao, J., et al. (2021) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/bci51272.2021.9385337
Hemington, K. S. (2018) · TSpace (University of Toronto)
Brain Regions Associated with Long-Term Memory
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.004
Evaluation of BOLD effects in the rat cortexPreprint
Just, N. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.12.443862
Spatial demonstratives in brain and behaviorPreprint
Rocca, R. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/fwsg5
Driving with Distraction: Brain Activity and Oculomotor Behaviour using fMRI and Eye-tracking
Yuen, N. H. (2021) · TSpace (University of Toronto)
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.006
Saccades in Alzheimer’s disease: an MRI study.
Wright, S. L. (2011) · Otago University Research Archive (University of Otago)
LisNRs : a novel class of liposomal contrast agents for molecular MRI
Simon, J. C. (2021)
Laubenthal, H., Valet, M., Sprenger, T., Wöller, A. A., Tölle, T. R., Röpcke, H., Wirz, S., Schröter, C., Schiltenwolf, M., Henningsen, P., et al. (2007) · Der Schmerz · doi:10.1007/s00482-007-0535-6
Zulfiqar, I. (2021) · doi:10.26481/dis.20210609iz
Ji, J. L., Repovš, G., Yang, G., Savic, A., Murray, J. D., & Anticevic, A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.03.446811
What do we learn about CEOs’ behaviour through neurofinance?
Baechler, G., & Germain, L. (2021) · Bankers Markets & Investors · doi:10.54695/bmi.164.0039
A primate model of human cortical analysis of auditory objects
Dheerendra, P. (2019) · doi:10.13140/rg.2.2.27306.36801
Seeing faces: evidence suggesting cortical disinhibition in the genesis of visual hallucinations.Preprint
Iaria, G., Fox, C., & Barton, J. J. S. (2008) · Nature Precedings · doi:10.1038/npre.2008.1827.1
Reliability and response assessment of brain responses in fNIRSPreprint
Jiang, X., Chen, Y., Zhou, C., & Ao, N. (2021) · doi:10.31234/osf.io/ye623
The Effect of Crystal Dependence on Brain Activity Related to the Perception of Pleasure Using fMRI
Yoonessi, A., Batouli, S. A. H., Ahmadnezhad, I., & Hamid Soltanian-zadeh, A. (2021) · Archives of Neuroscience · doi:10.5812/ans.100907
Exercise and executive function in older adults: exploring the mechanisms
Slutsky, A. B. (2019) · NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro)
Multivariate characterization of brain dynamics for disorders of consciousness
Castaño, R., & Eliécer, J. (2021)
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.011
Rampley, M. (2021) · Springer eBooks · doi:10.1007/978-3-030-71830-5_44
Functional Magnetic Resonance Imaging of Pain in the Spinal Cord and Brainstem
Ghazni, N. F. (2008)
Aso, T., & Fukuyama, H. (2021) · Creative economy · doi:10.1007/978-981-16-4457-3_18
Kritikos, M., & Clouston, S. (2021) · Springer eBooks · doi:10.1007/978-3-030-82367-2_5
Connecting the dots: Structural and functional connections in healthy and diseased brain
Straathof, M. (2021) · Utrecht University Repository (Utrecht University) · doi:10.33540/877
Benwell, N. M. (2006) · UWA Profiles and Research Repository (UWA)
Category-Specific Item Recognition and the Medial Temporal Lobe
Martin, C. B. (2015) · Scholarship@Western (Western University)
Intermediate Level Mechanisms Supporting Face Perception
Feczko, E. (2013) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7j38qkk
Ressonância Magnética Funcional em Epilepsia
Martin, M. D. G. M., Amaro, E., & Portela, L. A. P. (2019) · Revista Neurociências · doi:10.34024/rnc.2002.v10.8900
Restani, D. (2010) · AMS Campus - AlmaDL
MacIntosh, B. J., & Graham, S. J. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7672-6_14
fMRI in the evaluation of the irritative zone
Diehl, B., Salek‐Haddadi, A., & Fish, D. R. (2003) · Handbook of clinical neurophysiology · doi:10.1016/s1567-4231(03)03035-1
Differential Localization of Hic-5 and Paxillin in the Brain of Alzheimer's Disease Subjects
Caltagarone, J. (2008) · D-Scholarship@Pitt (University of Pittsburgh)
Klink, P. C., Chen, X., Vanduffel, W., & Roelfsema, P. R. (2021) · eLife · doi:10.7554/elife.67304.sa2
Matchin, W. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108569620.028
Joint Analysis of EEG and Other Simultaneously Recorded Brain Functional Neuroimaging Modalities
Sanei, S., & Chambers, J. A. (2021) · Wiley eBooks · doi:10.1002/9781119386957.ch18
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0016
Allgemeine Physiologie der Großhirnrinde
Birbaumer, N., & Schmidt, R. F. (2007) · Springer eBooks · doi:10.1007/3-540-26416-7_8
Schutter, E. D. (2006) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1031973.371880
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0012
Auletta, G. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199608485.003.0018
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.013
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.007
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.015
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.002
Bermúdez, J. L. (2019) · Cognitive Science · doi:10.1017/9781108339216.001
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.021
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.018
Challenges in fMRI and Its Limitations
Constable, R. T. (2014) · Springer eBooks · doi:10.1007/978-1-4939-1995-6_4
The Cognitive Science of Consciousness
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.017
The Prehistory of Cognitive Science
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.003
Applications of MRI to Psychopharmacology
Stein, D. J., Yang, Y., & Salmeron, B. J. (2014) · Springer eBooks · doi:10.1007/978-1-4939-1995-6_19
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.005
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.006
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.020
MEG and Multimodal Integration
Ahlfors, S. P. (2019) · Springer eBooks · doi:10.1007/978-3-319-62657-4_7-1
Physical Symbol Systems and the Language of Thought
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.006
(2001) · NMR in Biomedicine · doi:10.1002/nbm.673
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.003
Applying Dynamical Systems Theory to Model the Mind
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.008
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.005
Bermúdez, J. L. (2019) · Cognitive Science · doi:10.1017/9781108339216.020
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.001
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.011
Cunningham, D. W., & Wallraven, C. (2011) · A K Peters/CRC Press eBooks · doi:10.1201/b11308-20
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.001
(2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.014
Rutten, G.-J. M. (2017) · Springer eBooks · doi:10.1007/978-3-319-54633-9_8
Neural Networks and Distributed Information Processing
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.007
Funktionelle Bildgebung bei Schmerz
Stankewitz, A., Sprenger, T., Valet, M., & Tölle, T. R. (2014) · Springer eBooks · doi:10.1007/978-3-642-54670-9_11-1
Index for Cognitive Science (3rd edition)
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.022
(2014) · Monographs of the Society for Research in Child Development · doi:10.1002/mono.12104
Wald, L. L. (2013) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.717964008.793465774
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.021
fMRI of the Sensorimotor System
Filippi, M., & Rocca, M. A. (2009) · Neuromethods · doi:10.1007/978-1-60327-919-2_16
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.015
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.002
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.016
Experimental and Biological Approaches
(2020) · Cambridge University Press eBooks · doi:10.1017/9781316995808.011
Bihan, D. L., & Fukuyama, H. (2010) · Pan Stanford Publishing eBooks · doi:10.1201/b11671-23
de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.007 · Cited by 1
Singer, W. (2006) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1030549.357603
Attention and Adaptation in Visual Motion Processing
Pieper, F. (2007) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-239
Peripheral nervous system control for neuroprostheses
Buil, J. (2017) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-6491
Xu, F., Lin, P., Su, X., Peng, Q., & Tang, G. (2022) · Research Square · doi:10.21203/rs.3.rs-1376251/v1
Rasmijn, A. (2022) · Research Publications (Maastricht University) · doi:10.26481/dis.20220315ar
Koeda, M. (2022) · Nihon Ika Daigaku Igakkai Zasshi · doi:10.1272/manms.18.72
Rajput, R., Kaur, R., Chadha, R., Mani, S., Rachana, R., Kaur, H., & Singh, M. (2022) · IGI Global eBooks · doi:10.4018/978-1-6684-5295-0.ch008
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