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.
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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).
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Items 2,801–2,900 of 6,331
Tomasi, D. G., Wang, G., Studentsova, Y., & Volkow, N. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu269 · Cited by 29
Wang, L., Chen, D., Olson, J. J., Ali, S., Fan, T., & Mao, H. Z. (2012) · Acta Radiologica · doi:10.1258/ar.2012.120118 · Cited by 27
Adjamian, P., Hadjipapas, A., Barnes, G. R., Hillebrand, A., & Holliday, I. E. (2008) · Journal of Vision · doi:10.1167/8.7.4 · Cited by 27
Shen, G., Zhang, J., Wang, M., Lei, D., Yang, G., Zhang, S., & Du, X. (2014) · European Journal of Neuroscience · doi:10.1111/ejn.12547 · Cited by 27
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Nevado, Á., Young, M. P., & Panzeri, S. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.10.043 · Cited by 27
Flexible, phase-matched, linear receive arrays for high-field MRI in monkeys
Goense, J. B. M., Logothetis, N. K., & Merkle, H. (2010) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2010.03.026 · Cited by 27
Self-citationHenderson, L. A., James, C., & Macefield, V. G. (2012) · The Anatomical Record · doi:10.1002/ar.22513 · Cited by 27
Nonlinearities in rapid event-related fMRI explained by stimulus scaling
Heckman, G. M., Bouvier, S. E., Carr, V. A., Harley, E. M., Cardinal, K. S., & Engel, S. A. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.038 · Cited by 27
Nihashi, T., Kakigi, R., Okada, T., Sadato, N., Kashikura, K., Kajita, Y., & Yoshida, J. (2002) · NeuroImage · doi:10.1006/nimg.2002.1216 · Cited by 27
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Overduin, S. A., & Servos, P. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001505 · Cited by 27
A review on the inferior temporal cortex of the macaque
Tompa, T., & Sáry, G. (2009) · Brain Research Reviews · doi:10.1016/j.brainresrev.2009.10.001 · Cited by 28
Padraic Monaghan, B., & Pollmann, S. (2003) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.132.3.379 · Cited by 27
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Chen, H., Yao, D., & Liu, Z. (2004) · Brain Topography · doi:10.1023/b:brat.0000047335.00110.6a · Cited by 27
Gutschalk, A., Hämäläinen, M., & Melcher, J. R. (2010) · Journal of Neurophysiology · doi:10.1152/jn.01005.2009 · Cited by 27
Thilo, K. V., Kleinschmidt, A. K., & Gresty, M. A. (2003) · Journal of Neurophysiology · doi:10.1152/jn.00880.2002 · Cited by 27
A Wavelet-Based Statistical Analysis of fMRI Data: I. Motivation and Data Distribution Modeling
Dinov, I. D., Boscardin, W. J., Mega, M. S., Sowell, E. R., & Toga, A. W. (2005) · Neuroinformatics · doi:10.1385/ni:3:4:319 · Cited by 27
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Roebroeck, A. F., Seth, A. K., & Valdes-Sosa, P. A. (2009) · Research Publications (Maastricht University) · Cited by 27
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Rönnqvist, K. C., McAllister, C. J., Woodhall, G. L., Stanford, I. M., & Hall, S. D. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00132 · Cited by 29
Borowsky, R., Owen, W. J., Wile, T. L., Friesen, C. K., Martin, J. L., & Sarty, G. E. (2005) · PubMed · Cited by 27
Febo, M., & Foster, T. C. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00158 · Cited by 28
Murta, T., Hu, L., Tierney, T. M., Chaudhary, U. J., Walker, M. C., Carmichael, D. W., Figueiredo, P., & Lemieux, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.001 · Cited by 27
Poplawsky, A. J., Fukuda, M., & Kim, S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.05.023 · Cited by 27
Zaldivar, D., Rauch, A., Logothetis, N. K., & Goense, J. B. M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1808507115 · Cited by 27
Self-citationSaboo, K., Varatharajah, Y., Berry, B. M., Křemen, V., Sperling, M. R., Davis, K. A., Jobst, B. C., Gross, R. E., Lega, B. C., Sheth, S. A., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-53925-5 · Cited by 28
Balconi, M., Fronda, G., & Bartolo, A. (2020) · Journal of Motor Behavior · doi:10.1080/00222895.2020.1774490 · Cited by 27
Kraft, A., Schira, M. M., Hagendorf, H., Schmidt, S. H., Olma, M. C., & Brandt, S. A. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.05.050 · Cited by 27
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Zarahn, E. (2002) · Human Brain Mapping · doi:10.1002/hbm.10036 · Cited by 27
Chen, H., Yao, D., Zhuo, Y., & Chen, L. (2003) · Brain Topography · doi:10.1023/a:1023958024689 · Cited by 27
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Nader, M. A., & Czoty, P. W. (2008) · ILAR Journal · doi:10.1093/ilar.49.1.89 · Cited by 27
Chapter 6 Brainstem functional imaging in humans
Tracey, I., & Iannetti, G. D. (2006) · Supplements to Clinical neurophysiology · doi:10.1016/s1567-424x(09)70059-5 · Cited by 27
ON AIMS AND METHODS IN THE NEUROIMAGING OF DERIVED RELATIONS
Dickins, D. W. (2005) · Journal of the Experimental Analysis of Behavior · doi:10.1901/jeab.2005.92-04 · Cited by 27
Bola, M., Barrett, A. B., Pigorini, A., Nobili, L., Seth, A. K., & Marchewka, A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.030 · Cited by 27
Imaging the medial temporal lobe: exploring new dimensions
Brewer, J. B., & Moghekar, A. (2002) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(02)01881-8 · Cited by 26
Ruan, Z., Sun, D., Zhou, X., Yu, M., Li, S., Sun, W., Li, Y., Gao, L., & Xu, H. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1224525 · Cited by 26
Carrig, M. M., Kolden, G. G., & Strauman, T. J. (2009) · Psychotherapy Research · doi:10.1080/10503300902735864 · Cited by 26
Resting network is composed of more than one neural pattern: An fMRI study
Lee, T.-W., Northoff, G., & Wu, Y.-T. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.05.035 · Cited by 26
Adult Cortical Plasticity Studied with Chronically Implanted Electrode Arrays
Abe, H., McManus, J. N. J., Ramalingam, N., Li, W., Marik, S. A., Meyer, S., & Gilbert, C. D. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.3579-14.2015 · Cited by 26
New and emerging imaging techniques for mapping brain circuitry
Pan, H., Epstein, J., Silbersweig, D., & Stern, E. R. (2011) · Brain Research Reviews · doi:10.1016/j.brainresrev.2011.02.004 · Cited by 26
Compartment-resolved imaging of cortical functional hyperemia with OCT angiography
Radhakrishnan, H., & Srinivasan, V. J. (2013) · Biomedical Optics Express · doi:10.1364/boe.4.001255 · Cited by 26
Huang, T., Zhao, Z., Yan, C., Lü, J., Li, X., Tang, C., Fan, M., & Luo, Y. (2016) · PLoS ONE · doi:10.1371/journal.pone.0151360 · Cited by 26
Schallmo, M., Grant, A., Burton, P. C., & Olman, C. A. (2016) · Journal of Vision · doi:10.1167/16.10.19 · Cited by 26
Cui, L., Chen, G., Xu, Z., Liu, L., Wang, H., Guo, L., Liu, W.-M., Liu, T., Qi, S., Liu, K., et al. (2016) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2016.12.006 · Cited by 26
Shirinbayan, S. I., Dreyer, A. M., & Rieger, J. W. (2018) · Human Brain Mapping · doi:10.1002/hbm.24361 · Cited by 26
Asanowicz, D., Gociewicz, K., Koculak, M., Finc, K., Bonna, K., Axel Cleeremans, B., & Binder, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-60268-z · Cited by 26
Maith, O., Villagrasa, F., Dinkelbach, H. Ü., Baladron, J., Horn, A., Irmen, F., Kühn, A. A., & Hamker, F. H. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14868 · Cited by 26
Lee, H. L., Stirnberg, R., Wu, S., Wang, X., Stöcker, T., Jung, S., Montag, C., & Axmacher, N. (2020) · Current Biology · doi:10.1016/j.cub.2020.08.042 · Cited by 27
Boch, M., Karl, S., Sladky, R., Huber, L., Lamm, C., & Wagner, I. C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117414 · Cited by 26
Hrybouski, S., Cribben, I., McGonigle, J., Olsen, F., Carter, R., Seres, P., Madan, C. R., & Malykhin, N. V. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02226-7 · Cited by 28
Zhao, C., Li, D., Guo, J., Li, B., Kong, Y., Hu, Y., Du, B., Ding, Y., Li, X., Liu, H., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab525 · Cited by 26
Laminar microcircuitry of visual cortex producing attention-associated electric fields
Westerberg, J. A., Schall, M. S., Maier, A., Woodman, G. F., & Schall, J. D. (2022) · eLife · doi:10.7554/elife.72139 · Cited by 26
Claron, J., Provansal, M., Salardaine, Q., Tissier, P., Dizeux, A., Deffieux, T., Picaud, S. A., Tanter, M., Arcizet, F., & Pouget, P. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112369 · Cited by 26
A rapid theta network mechanism for flexible information encoding
Johnson, E. L., Lin, J. J., King‐Stephens, D., Weber, P. B., Laxer, K. D., Sáez, I., Girgis, F., D’Esposito, M., Knight, R. T., & Badre, D. (2023) · Nature Communications · doi:10.1038/s41467-023-38574-7 · Cited by 26
Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sassa, Y., Sekuguchi, A., Kotozaki, Y., Nakagawa, S., Nagase, T., Miyauchi, C. M., et al. (2012) · Human Brain Mapping · doi:10.1002/hbm.22167 · Cited by 26
Linking variability in brain chemistry and circuit function through multimodal human neuroimaging
Fisher, P. M., & Hariri, A. R. (2012) · Genes Brain & Behavior · doi:10.1111/j.1601-183x.2012.00786.x · Cited by 27
Transverse patterning dissociates human EEG theta power and hippocampal BOLD activation
Meltzer, J. A., Fonzo, G. A., & Constable, R. T. (2008) · Psychophysiology · doi:10.1111/j.1469-8986.2008.00719.x · Cited by 26
Kim, H., Yoo, S., & Lee, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.049 · Cited by 26
Furubayashi, T., Mochizuki, H., Terao, Y., Arai, N., Hanajima, R., Hamada, M., Matsumoto, H., Nakatani‐Enomoto, S., Okabe, S., Yugeta, A., et al. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00980.2011 · Cited by 26
Chassagnon, S., Namer, I. J., Armspach, J., Nehlig, A., Kahane, P., Kehrli, P., Valenti, M., & Hirsch, É. (2009) · Epilepsy Research · doi:10.1016/j.eplepsyres.2009.03.020 · Cited by 26
Dong, M., Li, J., Shi, X., Gao, S., Fu, S., Liu, Z., Liang, F., Gong, Q., Shi, G., & Tian, J. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00099 · Cited by 26
Coupling electrophysiological and hemodynamic responses to errors
Doñamayor, N., Heilbronner, U., & Münte, T. F. (2011) · Human Brain Mapping · doi:10.1002/hbm.21305 · Cited by 27
Independent components of the haemodynamic response in intrinsic optical imaging
Schießl, I., Wang, W., & McLoughlin, N. P. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.022 · Cited by 26
Modeling of the Neurovascular Coupling in Epileptic Discharges
Voges, N., Blanchard, S., Wendling, F., Olivier David, A., Benali, H., Papadopoulo, T., Clerc, M., & Bénar, C. (2011) · Brain Topography · doi:10.1007/s10548-011-0190-1 · Cited by 26
Longitudinal fMRI analysis: A review of methods.
Skup, M. (2010) · PubMed · Cited by 26
Neuronal or Hemodynamic? Grappling with the Functional MRI Signal
Bandettini, P. A. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0288 · Cited by 27
Radial Biases in the Processing of Motion and Motion-Defined Contours by Human Visual Cortex
Clifford, C. W. G., Mannion, D. J., & McDonald, J. S. (2009) · Journal of Neurophysiology · doi:10.1152/jn.00411.2009 · Cited by 26
Li, N., van Zijl, P. C. M., Thakor, N. V., & Pelled, G. (2014) · Journal of Molecular Neuroscience · doi:10.1007/s12031-013-0221-3 · Cited by 26
Monocular signals in human lateral geniculate nucleus reflect the Craik-Cornsweet-O'Brien effect
Anderson, E. J., Dakin, S. C., & Rees, G. E. (2009) · Journal of Vision · doi:10.1167/9.12.14 · Cited by 26
Sato, J. R., Rondinoni, C., Sturzbecher, M. J., de Araújo, D. B., & Amaro, E. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.075 · Cited by 26
Lessons from fMRI about Mapping Cortical Columns
Kim, S., & Fukuda, M. (2007) · The Neuroscientist · doi:10.1177/1073858407309541 · Cited by 26
Murugan, M., Santhakumar, V., & Kannurpatti, S. S. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2016.00019 · Cited by 26
Metabolic demands of neural-hemodynamic associated and disassociated areas in brain
Sanganahalli, B. G., Hermán, P., Rothman, D. L., Blumenfeld, H., & Hyder, F. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x16664531 · Cited by 26
DCC Is Required for the Development of Nociceptive Topognosis in Mice and Humans
da Silva, R. V., Johannssen, H. C., Wyss, M. T., Roome, R. B., Bourojeni, F. B., Stifani, N., Marsh, A. P. L., Ryan, M. M., Lockhart, P. J., Leventer, R. J., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.01.004 · Cited by 27
Tuleasca, C., Najdenovska, E., Régis, J. M., Witjas, T., Girard, N. J., Champoudry, J., Faouzi, M., Thiran, J., Cuadra, M. B., Levivier, M., et al. (2018) · World Neurosurgery · doi:10.1016/j.wneu.2018.02.055 · Cited by 28
A guide to using functional magnetic resonance imaging to study Alzheimer's disease in animal models
Asaad, M., & Lee, J. H. (2018) · Disease Models & Mechanisms · doi:10.1242/dmm.031724 · Cited by 26
Klingbeil, J., Wawrzyniak, M., Stockert, A., Karnath, H., & Saur, D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116485 · Cited by 26
Guo, H., Zeng, W., Shi, Y., Deng, J., & Zhao, L. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.2984519 · Cited by 26
Power grip disinhibits the ipsilateral sensorimotor cortex: a TMS and fMRI study
Foltys, H., Meister, I. G., Weidemann, J., Sparing, R., Thron, A. K., Willmes, K., Töpper, R., Hallett, M., & Boroojerdi, B. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00107-1 · Cited by 26
Borsook, D., & Becerra, L. R. (2007) · Current Pain and Headache Reports · doi:10.1007/s11916-007-0191-7 · Cited by 26
Pimentel, M. A. F., Vilela, P. F., Sousa, I., & Figueiredo, P. (2011) · Human Brain Mapping · doi:10.1002/hbm.21418 · Cited by 26
Hood, D. C., Ghadiali, Q., Zhang, J. C., Graham, N., Wolfson, S., & Zhang, X. (2006) · Journal of Vision · doi:10.1167/6.5.4 · Cited by 26
Mapping brain development and aggression.
Paus, T. (2005) · PubMed Central · Cited by 26
Frankenstein, U. N., Wennerberg, A. B. A., Richter, W., Bernstein, C. N., Morden, D., Rémy, F., & McIntyre, M. (2003) · Concepts in Magnetic Resonance Part A · doi:10.1002/cmr.a.10054 · Cited by 26
Imaging the Neural Systems for Motivated Behavior and Their Dysfunction in Neuropsychiatric Illness
Breiter, H. C., Gasic, G. P., & Makris, N. (2007) · Springer eBooks · doi:10.1007/978-0-387-33532-2_33 · Cited by 27
Correlates of Stimulus-Response Congruence in the Posterior Parietal Cortex
Stoet, G., & Snyder, L. H. (2007) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2007.19.2.194 · Cited by 26
Retinotopic distribution of chromatic responses in human primary visual cortex
Vanni, S., Henriksson, L., Viikari, M., & James, A. C. (2006) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2006.05070.x · Cited by 26
Schutter, D. J. L. G., van Honk, J., & Panksepp, J. (2004) · Synthese · doi:10.1023/b:synt.0000042951.25087.16 · Cited by 26
Hierarchical substrates of prediction in visual cortical spikingPreprint
Westerberg, J. A., Xiong, Y., Sennesh, E., Nejat, H., Ricci, D., Azmi, M., Durand, S., Hardcastle, B., Cabasco, H., Belski, H., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.02.616378 · Cited by 31
Local Field Potentials, BOLD, and Spiking Activity: Relationships and Physiological MechanismsPreprint
Philipp, B., Logothetis, N., & Τόλιας, Α. (2010) · Nature Precedings · doi:10.1038/npre.2010.5216.1 · Cited by 26
Self-citationPerception is associated with the brain’s metabolic response to sensory stimulation
DiNuzzo, M., Mangia, S., Moraschi, M., Mascali, D., Hagberg, G. E., & Giove, F. (2022) · eLife · doi:10.7554/elife.71016 · Cited by 25
Recent advances in recording and modulation technologies for next-generation neural interfaces.
Hong, J.-W., Yoon, C., Jo, K., Won, J. H., & Park, S. (2021) · iScience · doi:10.1016/j.isci.2021.103550 · Cited by 25
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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
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