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 5,001–5,100 of 6,331
Clinical applications of deep learning in neurology and its enhancements with future predictions
Olaniyan, O. T., Adetunji, C. O., Dare, A., Adeyomoye, O., Adeniyi, M. J., & Enoch, A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90277-9.00016-x · Cited by 1
Cognitive Functions as Revealed by Imaging of the Human Brain
Martín, R. S., & Huettel, S. A. (2022) · Springer eBooks · doi:10.1007/978-3-030-88832-9_82 · Cited by 1
Neuronal Models for EEG–fMRI Integration
Hermes, D., & Siero, J. C. W. (2022) · Springer eBooks · doi:10.1007/978-3-031-07121-8_25 · Cited by 1
Пономарева, Н. В., Андреева, Т. В., Protasova, M., Станиславовна, К. С., Kuznetsova, I. L., Kolesnikova, E. P., Malina, D. D., Алексеевич, М. А., Fokin, V. F., Illarioshkin, S. N., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24076790 · Cited by 1
Stephane, M., Džemidžić, M., & Yoon, G. (2024) · Schizophrenia Research · doi:10.1016/j.schres.2024.03.001 · Cited by 1
Shehan, A., Anjali, S., Sanjula, L., Lavanya, M., Thelijjagoda, S., & Krishara, J. (2023) · International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) · doi:10.1109/icses60034.2023.10465399 · Cited by 1
No observation of DIANA signals in rats at 7.0 and 17.2 Tesla
Cloos, M. A., Selingue, E., Hodono, S., Gaudin, R., & Ciobanu, L. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00136 · Cited by 1
Hong, T., Zhou, H., Xi, W., Li, X., Du, Y., Liu, J., Geng, F., & Hu, Y. (2024) · Neuroscience · doi:10.1016/j.neuroscience.2024.11.054 · Cited by 1
Enhancing fMRI quality control
van den Berg, L., Ramsey, N. F., & Raemaekers, M. A. H. (2024) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2024.110337 · Cited by 1
High-efficiency co-registration of OPM-MEG and MRI using point cloud processing
Qi, J., Shang, S., Chen, K., He, J., Yang, S., Wang, A., Wei, C., Zhao, T., Jiao, H., Feng, L., et al. (2025) · Optics Express · doi:10.1364/oe.553202 · Cited by 1
Li, M., Yang, Y., Zheng, H., Mo, D., Wen, X., Liu, L., Jiang, X., & Zhong, H. (2025) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2025.111962 · Cited by 1
Behzadfar, N., Mathalon, D. H., Preda, A., Iraji, A., & Calhoun, V. D. (2025) · Aperture Neuro · doi:10.52294/001c.129695 · Cited by 1
NINFA: Non-commercial interface for neuro-feedback acquisitions
Iester, C., Banzhaf, C., Eldably, A., Schopp, B., Fallgatter, A. J., Bonzano, L., Bove, M., Ehlis, A., & Barth, B. (2025) · Neurophotonics · doi:10.1117/1.nph.12.2.026601 · Cited by 1
Khan, Z. A., Shafiq, M. A., Singh, J., Rehman, Z., & Bardutz, H. A. (2025) · Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · doi:10.1017/cjn.2025.10110 · Cited by 1
Physiology of Cerebral Blood Flow
Khazaal, O., & Kofke, W. A. (2025) · Oxford University Press eBooks · doi:10.1093/med/9780198864714.003.0002 · Cited by 1
Time-resolved large-scale neural coactivations in macaque monkey
Ivey, V., Yuan, H., & Ding, L. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121408 · Cited by 1
Moon, H. S., Vo, T. T., Im, G. H., Hong, S., & Kim, S. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2505294122 · Cited by 1
Song, J.-Y., Lin, Q., Zhou, C., Wang, Y., Wang, Y.-P., & Calhoun, V. D. (2025) · Medical Image Analysis · doi:10.1016/j.media.2025.103803 · Cited by 1
Zhao, Y., Wang, M., Lyu, M., Wu, E. X., & Liu, Y. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.108701 · Cited by 1
Smith, J. C., Callow, D. D., Pena, G. S., & Purcell, J. J. (2025) · Advances in neurobiology · doi:10.1007/978-981-95-0066-6_14 · Cited by 1
Spatial Attention Weakly Modulates Visual Responses in the Lateral Geniculate Nucleus
Alitto, H. J., Johnson, J. S., & Usrey, W. M. (2025) · eNeuro · doi:10.1523/eneuro.0153-25.2025 · Cited by 1
Liang, R., Fang, T., Wang, L., Ren, J., Meng, L., Zhao, M., Zheng, C., Fan, Q., Chen, Y., Yang, J., et al. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03538-6 · Cited by 1
Bell, N. M., Johnson, C., Yu, F. F., Urban, J. E., Proskovec, A. L., Madhuranthakam, A. J., Maldjian, J. A., & Davenport, E. M. (2025) · Neurotrauma Reports · doi:10.1177/2689288x251371125 · Cited by 1
Aberrant regional homogeneity in multiple frequency bands in patients with alcohol use disorder
Ruan, X., Yu, T., You, C., Yang, M., & Chen, J. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1549970 · Cited by 1
Intracranial functional near-infrared spectroscopy: an animal feasibility study
Heymann, S., Rein, N., Zurita, M., Shechter, R., Israel, Z. H., Balberg, M., Medvedovsky, M., & Rosenthal, G. (2025) · Frontiers in Medical Technology · doi:10.3389/fmedt.2025.1692573 · Cited by 1
Neurovascular Coupling in Neurological Disorders: A Comprehensive Review
Ye, Z., Wang, Y., & Zhang, Q. (2025) · Clinical Neurology and Neuroscience · doi:10.11648/j.cnn.20250904.11 · Cited by 1
Functional Neuroimaging in Clinical Neurology: A Comprehensive Review of Commonly Used Modalities
Salardini, A. (2025) · Seminars in Neurology · doi:10.1055/a-2773-5481 · Cited by 1
Pineda, A. M., Vicchietti, M. L., Carra, R. B., Thome-Souza, S., Salgado, D., Rodrigues, F. A., Campanharo, A. S. L. O., & Cury, R. G. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.109269 · Cited by 1
The Prompting Brain: Neurocognitive Markers of Expertise in Guiding Large Language Models
Al-Khalifa, H. S., Almansour, R., Alhuasini, L. A., Alsaleh, A., Temsah, M.-H., & Alruwaili, A. R. (2025) · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa66935.2025.11315303 · Cited by 1
Exploring cognitive workload recognition using CogRepLKNet with EEG-fMRI
Shao, Y. W., Zhou, Y., Wen, X., Gong, P., Dai, Q., & Zhang, D. (2026) · Neural Networks · doi:10.1016/j.neunet.2026.108575 · Cited by 1
Marshall, W. J., Conner, A. N., Key, A. P. F., & Rex, T. S. (2026) · Frontiers in Neurology · doi:10.3389/fneur.2025.1721726 · Cited by 1
Ali, M. U., Zafar, A., Kim, S. H., Kim, K. S., & Lee, S. W. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3660698 · Cited by 1
Altered functional connectivity underpins cognitive changes in chronic spinal cord injury
Sritharan, J., Diana, L., Vallesi, V., Brunello, N., Feuring, L., Ugowe, J. J., Oertli, R., Hoogland, I. E., Scheel‐Sailer, A., Moro, V., et al. (2026) · Brain Communications · doi:10.1093/braincomms/fcag050 · Cited by 1
van der Plas, E., Todorova, L., Heidlmayr, K. D.-M., Jansen, G., Rosema, M., & Sanfey, A. G. (2026) · Scientific Reports · doi:10.1038/s41598-026-43389-9 · Cited by 1
Zhang, J., Weiss, F., Kirsch, P., & Gerchen, M. F. (2026) · Imaging Neuroscience · doi:10.1162/imag.a.1215 · Cited by 1
Lactate Changes Quantified by fMRS: A Meta‐Analysis
Cairone, L., Guidi, M., Mancini, M., & Giove, F. (2026) · NMR in Biomedicine · doi:10.1002/nbm.70295 · Cited by 1
Dynamic and Context-Dependent Modulation of Somatosensory Input in the Primate Primary Motor Cortex
Yoshida, J., Kikuta, S., Hasegawa, W., Kubota, S., & Seki, K. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.1793-25.2026 · Cited by 1
Zhou, X., Wang, L., Tam, S. K. E., Ortiz-Rios, M., Yin, D., & Kwok, S. C. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.1605-25.2026 · Cited by 1
Multimodal EEG–MRI Neuroimaging in Schizophrenia—A Systematic and Mechanistic Review
Chmiel, J., & Kopańska, M. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15114306 · Cited by 1
Determining hemispheric language dominance from MEG beta-power modulations: Concordance with fMRI
Youssofzadeh, V., Binder, J. R., Heffernan, J., Bock, E. A., Jaiswal, A., Stout, J. D., Ustine, C., Chikara, R. K., Shah‐Basak, P. P., Humphries, C., et al. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.122051 · Cited by 1
Wiafe, S.-L., Kinsey, S., Soleimani, N., Nsafoa, R., Khasayeva, N., Harikumar, A., Miller, R. L., & Calhoun, V. D. (2026) · Translational Psychiatry · doi:10.1038/s41398-026-04278-x · Cited by 1
Zhang, J., Cogan, G. B., & Egner, T. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106872 · Cited by 1
Tarricone, C., Vallini, G., Baron, G., Facca, M., Silvestri, E., Volpi, T., Vlassenko, A. G., Goyal, M. S., & Bertoldo, A. (2026) · Human Brain Mapping · doi:10.1002/hbm.70651 · Cited by 1
Le, G. H., Wong, S., Luch, S. D. D., Orsini, D. K., Vasudeva, S., Agarwal, S. M., Llach, C.-D., Rosenblat, J. D., & McIntyre, R. S. (2026) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.70143 · Cited by 1
fMRT und DTI bei Entwicklungsverzögerung der Zahlenverarbeitung
Krick, C. M., Neuhaus, A., Klewin, C., Wörner, T., Kreis, S. M., & Reith, W. (2015) · Der Radiologe · doi:10.1007/s00117-015-2854-4 · Cited by 1
Degeneration of the Human Nervous System and Magnetic Resonance Neuroimaging
Lulé, D. E., & Albert, L. (2011) · InTech eBooks · doi:10.5772/24525 · Cited by 1
Cognitive Neuroscience Applications
D’Esposito, M. (2010) · Springer eBooks · doi:10.1007/978-1-4419-1329-6_10 · Cited by 1
Yen, C. C. (2011) · D-Scholarship@Pitt (University of Pittsburgh) · Cited by 1
Koval, M. J. (2012) · Scholarship@Western (Western University) · Cited by 1
Binocular activation elicits differences in neurometabolic coupling in visual cortex
Li, B., & Freeman, R. D. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.06.036 · Cited by 1
Yu, Z., Feng, B., Gu, Z., Xue, Z., Li, Y., & Wang, C. (2013) · Multidimensional Systems and Signal Processing · doi:10.1007/s11045-013-0254-3 · Cited by 1
Peterson, M., Das, K., Sy, J. L., Li, S., Giesbrecht, B., Kourtzi, Z., & Eckstein, M. P. (2010) · Journal of the Optical Society of America A · doi:10.1364/josaa.27.002670 · Cited by 1
Möglichkeiten moderner Bildgebungstechnologien im Rahmen der Frühdiagnostik von Alzheimererkrankung
Unschuld, P. G. (2015) · Therapeutische Umschau · doi:10.1024/0040-5930/a000674 · Cited by 1
Fusion of EEG Topograhic Features and fMRI Using Canonical Partial Least Squares
Michalopoulos, K., & Bourbakis, N. (2014) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2014.53 · Cited by 1
Investigating the Coupling between Stimulation and Neural Activity: a Dynamic Modeling Approach
Lefebvre, V. A., Zheng, Y., Devonshire, I. M., Martin, C. J., & Mayhew, J. E. W. (2007) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2007.4352489 · Cited by 1
Aggregated wavelet estimation and its application to ultra-fast fMRI
Efromovich, S., & Valdez-Jasso, Z. A. (2010) · Journal of nonparametric statistics · doi:10.1080/10485251003653468 · Cited by 1
DYNAMIC MAPPING OF AMPHETAMINE RESPONSE IN THE RAT BRAIN USING BOLD AND IRON TECHNIQUES
Shih, Y. I., Chen, Y., Hsieh, W.-Y., Huang, Y.-Y., Chang, C., Chen, J., Lin, C.-I., Wang, S.-J., & Jaw, F.-S. (2007) · Biomedical Engineering Applications Basis and Communications · doi:10.1142/s1016237207000203 · Cited by 1
Pearls & Oy-sters: Functional MRI
Pressman, P., & Gitelman, D. R. (2012) · Neurology · doi:10.1212/wnl.0b013e318248e57a · Cited by 1
Multimodal Integration: Constraining MEG Localization with EEG and fMRI
Henson, R. N. (2010) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-642-12197-5_18 · Cited by 1
Investigaton of the neuronal efficacy and EEG source power under steady-state visual stimulation
Duru, A. D., Erdoğan, S. B., Kaşikçi, I., Bayram, A., Ademoğlu, A., & Demıralp, T. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6091622 · Cited by 1
evidencein the human auditory system: fMRI Sensitivity to temporal modulation rate and spectral
Wang, Y., Ding, N., Ahmar, N. E., Xiang, J., Poeppel, D., Malone, B. J., Beitel, R. E., Vollmer, M., Heiser, M. A., Schreiner, C. E., et al. (2012) · Cited by 1
Functional Brain Reorganization and Recovery after Injury to White Matter
Matthews, P. M. (2005) · Elsevier eBooks · doi:10.1016/b978-012738761-1/50031-6 · Cited by 1
Advanced fMRI and the Brain Computer Interface
Paley, M. N. J., Kaka, S., Hilliard, H., Zaytsev, A., Bucur, A., Reynolds, S., Liu, W., Milne, E., & Cook, G. G. (2014) · Intelligent systems reference library · doi:10.1007/978-3-319-10978-7_7 · Cited by 1
Kristjansson, A. K. (2005) · Hirsla (Landspítali University Hospital) · Cited by 1
Overstreet, C. K. (2013) · Cited by 1
Functional MRI: Approaches to Cognitive Neuroscience Applications
D’Esposito, M., Sreenivasan, K. K., & Kayser, A. (2015) · Biological magnetic resonance · doi:10.1007/978-1-4899-7591-1_18 · Cited by 1
Pardo, P. J., Olman, C. A., & Pardo, J. V. (2008) · Humana Press eBooks · doi:10.1007/978-1-59745-252-6_38 · Cited by 1
Josephs, O., & Rees, G. E. (2007) · Cited by 1
Brain mapping and its techniques
Kalyan, R., & Kaushal, B. (2015) · International Conference on Recent Advances in Engineering & Computational Sciences · doi:10.1109/raecs.2015.7453364 · Cited by 1
Cerebellar Nonmotor Functions – Approaches and Significance
Šveljo, O., & Ćulić, M. (2015) · Neurophysiology · doi:10.1007/s11062-015-9541-y · Cited by 1
Commentary by Steven L. Bressler
Bressler, S. L. (2015) · Studies in systems, decision and control · doi:10.1007/978-3-319-24406-8_12 · Cited by 1
Design and implementation of happiness database for fMRI study
Ou, Y., Yeh, D.-R., Kung, C., Lin, P., Kuan, T.-W., & Wang, J.-F. (2015) · International Conference on Orange Technologies · doi:10.1109/icot.2015.7498493 · Cited by 1
Classification and diagnosis of epilepsy
Alarcón, G., & Valentı́n, A. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9781139103992.019 · Cited by 1
Modulation of ventral and dorsal attention networks during target detection: an EEG/fMRI study
Mantini, D., Corbetta, M., Cugini, S., Romani, G. L., & Gratta, C. D. (2007) · Cited by 1
Novel Imaging Techniques and Neuroradiologic Imaging
Aldusary, N., von Hartog-Keisker, B. V., & Kollias, S. (2017) · Springer eBooks · doi:10.1007/978-3-319-52284-5_6 · Cited by 1
Hemodynamic modelling of BOLD fMRI - A machine learning approach
Jacobsen, D. J., & Hansen, L. K. (2007) · Cited by 1
The Electrophysiology of Resting State fMRI Networks
Hacker, C. D. (2017) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k780512x · Cited by 1
Operating-level assessment for telerobotics based on electroencephalograph
Liu, S., & Xie, Y. (2017) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2017.1379094 · Cited by 1
Dynamic Generative Model of the Human Brain in Resting-State
Guo, D., Arora, V., Amico, E., Goñi, J., & Ventresca, M. (2017) · Studies in computational intelligence · doi:10.1007/978-3-319-72150-7_103 · Cited by 1
Friston, K. J., & Glaser, D. E. (2007) · Elsevier eBooks · doi:10.1016/b978-012372560-8/50027-9 · Cited by 1
Simultaneous Recording EEG and fMRI
Meletti, S. (2019) · Springer eBooks · doi:10.1007/978-3-030-04573-9_21 · Cited by 1
The Tools of Cognitive Neuroscience
Slotnick, S. D. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316026687.003 · Cited by 1
Functional MRI and Diffusion Tensor Imaging
Shah, G. V. (2021) · Springer eBooks · doi:10.1007/978-3-030-62120-9_6 · Cited by 1
Bermúdez, J. L. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108339216.012 · Cited by 1
Cognitive Neuroscience Applications
D’Esposito, M. (2006) · Springer eBooks · doi:10.1007/0-387-34665-1_18 · Cited by 1
Liebenthal, E., & Singhal, T. (2019) · Biological and medical physics, biomedical engineering · doi:10.1007/978-3-030-04996-6_3 · Cited by 1
Modelling neuron fiber interaction and coupling in non-myelinated bundled fiber
Baruah, S. M. B., & Roy, S. (2022) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ac620a · Cited by 1
Assessments and treatments for pedophilic disorder: a literature review
Yang, F. (2022) · International Conference on Biotechnology, Life Science and Medical Engineering (BLSME) · doi:10.23977/blsme.2022043 · Cited by 1
Physiological Self-regulation Using Biofeedback Training: From Concept to Clinical Applicability
Rodrigues, K. A., Moreira, J. V. D. S., Pinheiro, D. J. L. L., Contier, A. T., Cavalheiro, É. A., & Faber, J. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-08443-0_12 · Cited by 1
Transcranial brain stimulation and functional MRI
Windischberger, C., Tik, M., Thielscher, A., & Siebner, H. R. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198832256.013.23 · Cited by 2
Knösche, T. R., & Haueisen, J. (2022) · Springer eBooks · doi:10.1007/978-3-030-74918-7_2 · Cited by 1
Zhou, W., Wu, J., Li, Y., Li, J., Sun, M., Li, R., Yang, C., Zhang, M., Gong, L., Yu, J., et al. (2023) · Cognitive Computation · doi:10.1007/s12559-023-10150-7 · Cited by 1
Interacting spiral waves organize brain dynamics and have functional correlates to cognition
(2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01628-3 · Cited by 1
Brain-Computer Interfaces in Visualized Medicine
Si, X., Zhou, Y. L., Li, S., Zhang, X., Han, S., Xiang, S., & Ming, D. (2023) · Advances in experimental medicine and biology · doi:10.1007/978-981-32-9902-3_7 · Cited by 1
BOLD fMRI: Physiology and acquisition strategies
Uludaǧ, K., & Kasper, L. (2023) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-323-99898-7.00027-4 · Cited by 1
Tang, X., Li, Q., Tang, Y., Tian, L., Zheng, Y., Li, X., Jiang, N., Shang, P., Li, G., Peng, L., et al. (2023) · IEEE International Conference on Real-time Computing and Robotics (RCAR) · doi:10.1109/rcar58764.2023.10249626 · Cited by 1
AD/MCI classification using DMN connectivity networks-based HGCN with attention
Zuo, Z., & Kamata, S. (2023) · International Conference on Pattern Recognition and Artificial Intelligence (PRAI) · doi:10.1109/prai59366.2023.10331967 · Cited by 1
A Wasserstein Recipe for Replicable Machine Learning on Functional Neuroimages
Ding, J., Dan, T., Wei, Z., Laurienti, P. J., & Guorong Wu, A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72069-7_1 · Cited by 1
Lim, K., Slee, S. J., Kibler, A. B., Falowski, S. M., & Amirdelfan, K. (2025) · Journal of Pain Research · doi:10.2147/jpr.s502432 · Cited by 1
Lee, D. S., Kim, H. J., Huh, Y., Kang, Y. K., Whi, W., Lee, H., & Kang, H. (2025) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2025.1543854 · Cited by 1
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
