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 3,001–3,100 of 6,331
Zhang, H., Zhao, R., Hu, X., Guan, S., Margulies, D. S., Meng, C., & Biswal, B. B. (2022) · Brain Structure and Function · doi:10.1007/s00429-022-02564-0 · Cited by 23
Stability of motor representations after paralysis
Guan, C., Aflalo, T., Zhang, C. Y., Amoruso, E., Rosario, E. R., Pouratian, N., & Andersen, R. A. (2022) · eLife · doi:10.7554/elife.74478 · Cited by 23
Structural, functional, and metabolic signatures of postpartum depression: A systematic review
Hořáková, A., Němcová, H., Mohr, P., & Šebela, A. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1044995 · Cited by 25
Fabri, M., & Polonara, G. (2023) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2023.108533 · Cited by 23
Network targets for therapeutic brain stimulation: towards personalized therapy for pain
Motzkin, J. C., Kanungo, I., D’Esposito, M., & Shirvalkar, P. R. (2023) · Frontiers in Pain Research · doi:10.3389/fpain.2023.1156108 · Cited by 25
Pressure Pulsatility Links Cardio-Respiratory and Brain Rhythmicity
Hamill, O. P. (2023) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2206143 · Cited by 23
Magnetoelectric composites for medical application
Paluszek, M., Avirovik, D., Zhou, Y., Kundu, S., Chopra, A., Montague, P. R., & Priya, S. (2015) · Elsevier eBooks · doi:10.1016/b978-1-78242-254-9.00011-1 · Cited by 23
K-space reconstruction of magnetic resonance inverse imaging (K-InI) of human visuomotor systems
Lin, F., Witzel, T., Chang, W., Tsai, K. W., Wang, Y.-H., Kuo, W.-J., & Belliveau, J. W. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.016 · Cited by 23
Near-Infrared Neuroimaging with NinPy
Strangman, G. E. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.012.2009 · Cited by 23
Network connectivity modulates power spectrum scale invariance
Rǎdulescu, A., & Mujica-Parodi, L. R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.001 · Cited by 23
The neural mechanisms of reciprocal communication
Nagy, E., Mario Liotti, A., Brown, S., Waiter, G. D., Bromiley, A., Trevarthen, C., & Bárdos, G. (2010) · Brain Research · doi:10.1016/j.brainres.2010.07.066 · Cited by 24
Animal models and high field imaging and spectroscopy
Öz, G., Tkáč, I., & Uǧurbil, K. (2013) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2013.15.3/goz · Cited by 23
What Makes a Pattern? Matching Decoding Methods to Data in Multivariate Pattern Analysis
Kragel, P. A., Carter, R., & Huettel, S. A. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00162 · Cited by 23
Sensory information processing may be neuroenergetically more demanding in migraine patients
Gantenbein, A. R., Sándor, P. S., Fritschy, J., Turner, R., Goadsby, P. J., & Kaube, H. (2013) · Neuroreport · doi:10.1097/wnr.0b013e32835eba81 · Cited by 23
Fine-scale functional connectivity in somatosensory cortex revealed by high-resolution fMRI
Chen, L., Mishra, A., Newton, A. T., Morgan, V. L., Stringer, E. A., Rogers, B. P., & Gore, J. C. (2011) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2011.08.001 · Cited by 23
Costagli, M., Ueno, K., Sun, P., Gardner, J. L., Wan, X., Ricciardi, E., Pietrini, P., Tanaka, K., & Cheng, K. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs294 · Cited by 24
Sanganahalli, B. G., Rebello, M. R., Hermán, P., Papademetris, X., Shepherd, G. M., Verhagen, J. V., & Hyder, F. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.048 · Cited by 23
Hu, D., & Huang, L. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00246.2015 · Cited by 23
Mayhew, S. D., Mullinger, K. J., Ostwald, D., Porcaro, C., Bowtell, R. W., Bagshaw, A. P., & Francis, S. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.077 · Cited by 23
Lin, F., Polimeni, J. R., Lin, J.-F. L., Tsai, K. W., Chu, Y.-H., Wu, P., Li, Y.-T., Hsu, Y.-C., Tsai, S., & Kuo, W. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.041 · Cited by 23
Brain Network Dynamics Adhere to a Power Law
Tomasi, D. G., Kojori, E. S., & Volkow, N. D. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00072 · Cited by 23
The nature of early astroglial protection—Fast activation and signaling
Kardos, J., Héja, L., Jemnitz, K., Kovács, R., & Palkovits, M. (2017) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2017.03.005 · Cited by 23
The Blind Men and the Elephant: The Quest for Open Data Repositories
Vanduffel, W. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.039 · Cited by 23
Straathof, M., Sinke, M. R. T., Roelofs, T. J. M., Blezer, E. L. A., Sarabdjitsingh, R. A., van der Toorn, A., Schmitt, O., Otte, W. M., & Dijkhuizen, R. M. (2020) · Scientific Reports · doi:10.1038/s41598-019-56834-9 · Cited by 25
Kim, S.-Y., & Lim, W. (2020) · Cognitive Neurodynamics · doi:10.1007/s11571-020-09580-y · Cited by 24
The Relationship Between Cognition and Cerebrovascular Reactivity: Implications for Task-Based fMRI
Williams, R. J., MacDonald, M. E., Mazerolle, E. L., & Pike, G. B. (2021) · Frontiers in Physics · doi:10.3389/fphy.2021.645249 · Cited by 23
Validating layer-specific VASO across species
Huber, L., Poser, B. A., Kaas, A. L., Fear, E. J., Dresbach, S., Berwick, J., Goebel, R., Turner, R., & Kennerley, A. J. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118195 · Cited by 24
Neural mechanisms of foreign accent syndrome: Lesion and network analysis
Higashiyama, Y., Hamada, T., Saito, A., Morihara, K., Okamoto, M., Kimura, K., Joki, H., Kishida, H., Doi, H., Ueda, N., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102760 · Cited by 23
Fawcett, I. P., Hillebrand, A., & Singh, K. D. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05707.x · Cited by 23
Winder, R. K., Cortes, C. R., Reggia, J. A., & Tagamets, M.-A. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.10.008 · Cited by 23
BOLD responses to trigeminal nerve stimulation
Just, N., Petersen, C. C. H., & Rolf Gruetter, A. (2010) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2010.02.002 · Cited by 23
Hérard, A.-S., Dubois, A., Escartin, C., Tanaka, K., Delzescaux, T., Hantraye, P., & Bonvento, G. (2005) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2005.04346.x · Cited by 25
Cheng, R., Williams, C. L., & Meck, W. H. (2008) · Brain Research · doi:10.1016/j.brainres.2008.08.077 · Cited by 25
Fast modulation of alpha activity during visual processing and motor control
Sabaté, M., Llanos, C., Enriquez, E., Gonzalez, B., & Rodrı́guez, M. (2011) · Neuroscience · doi:10.1016/j.neuroscience.2011.05.011 · Cited by 23
Bernard, R. A., Goran, D. A., Sakai, S. T., Carr, T. H., McFarlane, D. K., Nordell, B., Cooper, T. G., & Potchen, E. J. (2002) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.2.3.271 · Cited by 23
Somatosensory Processing of the Tongue in Humans
Sakamoto, K., Nakata, H., Yumoto, M., & Kakigi, R. (2010) · Frontiers in Physiology · doi:10.3389/fphys.2010.00136 · Cited by 23
Salek‐Haddadi, A., Lemieux, L., & Fish, D. R. (2002) · Neurosurgery Clinics of North America · doi:10.1016/s1042-3680(02)80007-9 · Cited by 23
Imaging the Dynamics of Neocortical Population Activity in Behaving and Freely Moving Mammals
Grinvald, A., & Petersen, C. C. H. (2015) · Advances in experimental medicine and biology · doi:10.1007/978-3-319-17641-3_11 · Cited by 23
Abnormal Baseline Brain Activity in Patients with Pulsatile Tinnitus: A Resting-State fMRI Study
Lv, H., Zhaohui, L., Yan, F., Li, T., Pengfei, Z., Wang, D., Cheng, D., Pengde, G., Xiaoyi, H., Xiao, W., et al. (2014) · Neural Plasticity · doi:10.1155/2014/549162 · Cited by 25
Kéri, S., & Gulyás, B. Z. (2003) · Neuroreport · doi:10.1097/00001756-200306110-00001 · Cited by 23
Hardware considerations for functional magnetic resonance imaging
Silva, A. C., & Merkle, H. (2003) · Concepts in Magnetic Resonance Part A · doi:10.1002/cmr.a.10052 · Cited by 23
Magnetoencephalography: In search of neural processes for visual motion information
Kaneoke, Y. (2006) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2006.10.001 · Cited by 23
When more means less: a paradox BOLD response in human visual cortex
Marcar, V. L., Straessle, A., Girard, F., Loenneker, T., & Martin, E. (2004) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2004.01.019 · Cited by 23
Functional source separation applied to induced visual gamma activity
Barbati, G., Porcaro, C., Hadjipapas, A., Adjamian, P., Pizzella, V., Romani, G. L., Seri, S., Tecchio, F., & Barnes, G. R. (2007) · Human Brain Mapping · doi:10.1002/hbm.20375 · Cited by 23
FUNCTIONAL IMAGING IN A LOW-FIELD, MOBILE INTRAOPERATIVE MAGNETIC RESONANCE SCANNER
Azmi, H., Biswal, B. B., Salas, S. J., & Schulder, M. (2007) · Neurosurgery · doi:10.1227/01.neu.0000258635.04917.fa · Cited by 23
Early Detection of Mental Stress Using Advanced Neuroimaging and Artificial IntelligencePreprint
Al-Shargie, F. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.08511 · Cited by 24
Keleş, Ü., Dubois, J., Le, K. J. M., Tyszka, J. M., Kahn, D. A., Reed, C. M., Chung, J. M., Mamelak, A. N., Adolphs, R., & Rutishauser, U. (2024) · Scientific Data · doi:10.1038/s41597-024-03029-1 · Cited by 23
Spatial dynamics of masked picture repetition effects
Eddy, M. D., Schnyer, D., Schmid, A., & Holcomb, P. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.10.031 · Cited by 22
Zhao, L. (2025) · Psychoradiology · doi:10.1093/psyrad/kkaf007 · Cited by 23
Wrenn, C. B. (2006) · Theoria · doi:10.1111/j.1755-2567.2006.tb00943.x · Cited by 22
Nelson, S. M., McDermott, K. B., Wig, G. S., Schlaggar, B. L., & Petersen, S. E. (2013) · The Neuroscientist · doi:10.1177/1073858413492389 · Cited by 22
Convex optimization of MRI exposure for mitigation of RF-heating from active medical implants
Córcoles, J., Zastrow, E., & Kuster, N. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/18/7293 · Cited by 22
An Advanced 2.5-D Heterogeneous Integration Packaging for High-Density Neural Sensing Microsystem
Hu, Y., Huang, Y., Huang, P.-T., Wu, S.-L., Chang, H.-C., Yang, Y.-T., You, Y.-H., Chen, J.-M., Huang, Y., Lin, Y., et al. (2017) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2017.2660763 · Cited by 22
Tu, Y., Fu, Z., Tan, A., Huang, G., Hu, L., Hung, Y.-S., & Zhang, Z. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.07.045 · Cited by 22
Thomaidou, M. A., Peerdeman, K. J., Koppeschaar, M. I., Evers, A. W. M., & Veldhuijzen, D. S. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.652552 · Cited by 22
The thalamus and tinnitus: Bridging the gap between animal data and findings in humans
Koops, E. A., & Eggermont, J. J. (2021) · Hearing Research · doi:10.1016/j.heares.2021.108280 · Cited by 22
Origins of 1/f-like tissue oxygenation fluctuations in the murine cortex
Zhang, Q., Gheres, K. W., & Drew, P. J. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001298 · Cited by 24
Carbon-Based Fiber Materials as Implantable Depth Neural Electrodes
Fu, X., Li, G., Niu, Y., Xu, J., Wang, P., Zhou, Z., Ye, Z., Liu, X., Xu, Z. J., Yang, Z., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.771980 · Cited by 22
Tracking Development of Connectivity in the Human Brain: Axons and Dendrites
Paus, T. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.08.019 · Cited by 24
Optogenetic fMRI for Brain-Wide Circuit Analysis of Sensory Processing
Lee, J.-Y., You, T., Woo, C., & Kim, S. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232012268 · Cited by 22
Neurovascular Coupling is Preserved in Chronic Stroke Recovery After Targeted Photothrombosis
Sunil, S., Jiang, J., Shah, S., Kura, S., Kılıç, K., Erdener, Ş. E., Ayata, C., Devor, A., & Boas, D. A. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103377 · Cited by 22
Assessing food-evoked emotions using functional magnetic resonance imaging: A systematic review
Luo, L., & Han, P. (2023) · Food Quality and Preference · doi:10.1016/j.foodqual.2023.104877 · Cited by 22
Herath, L., Meedeniya, D., Marasinghe, J. C., Weerasinghe, V. S., & Tan, T. (2024) · Expert Systems · doi:10.1111/exsy.13623 · Cited by 22
Herzberg, M. P., Nielsen, A. N., Luby, J. L., & Sylvester, C. M. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01947-7 · Cited by 24
Distal activity patterns shape the spatial specificity of neurovascular coupling
Martineau, É., Malescot, A., Elmkinssi, N., & Rungta, R. L. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01756-7 · Cited by 23
The impact of eye closure on somatosensory perception in the elderly
Brodoehl, S., Klingner, C. M., Stieglitz, K., & Witte, O. W. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.07.014 · Cited by 23
Wardman, D. L., Gandevia, S. C., & Colebatch, J. G. (2014) · Physiological Reports · doi:10.1002/phy2.270 · Cited by 22
Experimental design and interpretation of functional neuroimaging studies of cognitive processes
Caplan, D. N. (2007) · Human Brain Mapping · doi:10.1002/hbm.20489 · Cited by 22
Exploring BOLD Changes during Spatial Attention in Non-Stimulated Visual Cortex
Heinemann, L. V., Kleinschmidt, A. K., & Müller, N. G. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005560 · Cited by 24
Grön, G., Sokolov, A. N., Jonas, C., Roebling, R., & Spitzer, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019985 · Cited by 25
Balanced excitation and inhibition: Model based analysis of local field potentials
Zheng, Y., Luo, J., Harris, S., Kennerley, A. J., Berwick, J., Billings, S. A., & Mayhew, J. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.040 · Cited by 22
Degeneration of cortical function in the Royal College of Surgeons rat
Gias, C., Vugler, A., Lawrence, J. M., Carr, A. F., Chen, L., Ahmado, A., Semo, M., & Coffey, P. J. (2011) · Vision Research · doi:10.1016/j.visres.2011.08.012 · Cited by 22
Altered neurovascular coupling during information‐processing states
Jones, M., Devonshire, I. M., Berwick, J., Martin, C. J., Redgrave, P., & Mayhew, J. E. (2008) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2008.06212.x · Cited by 22
Siedentopf, C., Heubach, K., Ischebeck, A. K., Gallasch, E., Fend, M., Mottaghy, F. M., Koppelstaetter, F., Haala, I., Krause, B. J., Felber, S. R., et al. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.02.049 · Cited by 22
Utilizing temporal information in fMRI decoding: Classifier using kernel regression methods
Chu, C., Mourão-Miranda, J., Chiu, Y., Kriegeskorte, N., Tan, G. C.-Y., & Ashburner, J. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.06.053 · Cited by 22
Duncan, N. W., Wiebking, C., Muñoz‐Torres, Z., & Northoff, G. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.10.011 · Cited by 22
Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration
Blinowska, K. J., Müller-Putz, G., Kaiser, V., Astolfi, L., Vanderperren, K., Huffel, S. V., & Lemieux, L. (2009) · Computational Intelligence and Neuroscience · doi:10.1155/2009/813607 · Cited by 22
Effects of mobile phone signals over BOLD response while performing a cognitive task
Curcio, G., Nardo, D., Perrucci, M. G., Pasqualetti, P., Chen, T. L., Gratta, C. D., Romani, G. L., & Rossini, P. M. (2011) · Clinical Neurophysiology · doi:10.1016/j.clinph.2011.06.007 · Cited by 22
What Does Local Functional Hyperemia Tell about Local Neuronal Activation?
Jukovskaya, N., Tiret, P., Lecoq, J. A., & Charpak, S. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.3146-10.2011 · Cited by 22
Multiple sclerosis-related white matter microstructural change alters the BOLD hemodynamic response
Hubbard, N. A., Turner, M. P., Hutchison, J. L., Ouyang, A., Strain, J. F., Oasay, L., Patel, S. S., Davis, S. L., Remington, G. M., Brigante, R. M., et al. (2015) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x15615133 · Cited by 22
Wilson, G. H., Yang, P., Gore, J. C., & Chen, L. M. (2016) · Human Brain Mapping · doi:10.1002/hbm.23207 · Cited by 22
Functional MRI signal fluctuations highlight altered resting brain activity in Huntington’s disease
Sarappa, C., Salvatore, E., Filla, A., Cocozza, S., Russo, C. V., Saccà, F., Brunetti, A., Michele, G. D., & Quarantelli, M. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9630-6 · Cited by 22
Learning effective connectivity from fMRI using autoregressive hidden Markov model with missing data
Dang, S., Chaudhury, S., Lall, B., & Roy, P. K. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2016.12.019 · Cited by 23
Imaging TMS: antidepressant mechanisms and treatment optimization
Dubin, M. J. (2017) · International Review of Psychiatry · doi:10.1080/09540261.2017.1283297 · Cited by 22
Schalk, G., Marple, J., Knight, R. T., & Coon, W. G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.014 · Cited by 24
Resting‐state functional connectivity in the rat cervical spinal cord at 9.4 T
Wu, T., Wang, F., Mishra, A., Wilson, G. H., Byun, N. E., Chen, L. M., & Gore, J. C. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26905 · Cited by 22
Wu, R., Yang, P., & Chen, L. M. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.2318-17.2017 · Cited by 22
Chen, Y., Cha, Y., Li, C., Shou, G., Gleghorn, D., Ding, L., & Yuan, H. (2019) · Brain Connectivity · doi:10.1089/brain.2018.0647 · Cited by 22
Ramchandran, K., Zeien, E., & Andreasen, N. C. (2019) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2019.02.006 · Cited by 22
Chauveau, F., Claverie, D., Lardant, E., Varin, C., Hardy, E., Walter, A., Canini, F., Rouach, N., & Rancillac, A. (2019) · SLEEP · doi:10.1093/sleep/zsz189 · Cited by 22
Flook, E. A., Luchsinger, J. R., Silveri, M. M., Winder, D. G., Benningfield, M. M., & Blackford, J. U. (2020) · Addiction Biology · doi:10.1111/adb.12861 · Cited by 22
Ligneul, C., Fernandes, F. F., & Shemesh, N. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117973 · Cited by 22
Influences of negative BOLD responses on positive BOLD responses
Klingner, C. M., Ebenau, K., Hasler, C., Brodoehl, S., Görlich, Y., & Witte, O. W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.028 · Cited by 22
Habeck, C. G., Hilton, H. J., Zarahn, E., Brown, T. R., & Stern, Y. (2006) · Brain Research · doi:10.1016/j.brainres.2005.11.102 · Cited by 22
DiNuzzo, M., Gili, T., Maraviglia, B., & Giove, F. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00416.2011 · Cited by 22
Background and evoked activity and their interaction in the human brain
Nierhaus, T., Schön, T., Becker, R., Ritter, P., & Villringer, A. (2009) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2009.04.001 · Cited by 22
Advances in the diagnosis of anorexia nervosa and bulimia nervosa using brain imaging
Frank, G. (2012) · Expert Opinion on Medical Diagnostics · doi:10.1517/17530059.2012.673583 · Cited by 24
Zappe, A. C., Reichold, J., Burger, C., Weber, B., Buck, A., Pfeuffer, J., & Logothetis, N. K. (2007) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2006.11.028 · Cited by 22
Self-citationKosik, K. S. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1053 · Cited by 22
Salle, F. D., Esposito, F., Elefante, A., Scarabino, T., Volpicelli, A., Cirillo, S., Elefante, R., & Seifritz, E. (2003) · European Journal of Radiology · doi:10.1016/j.ejrad.2003.08.010 · Cited by 22
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