The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity
Abstract
In noninvasive neuroimaging, neural activity is inferred from local fluctuations in deoxyhemoglobin. A fundamental question of functional magnetic resonance imaging (fMRI) is whether the inferred neural activity is driven primarily by synaptic or spiking activity. The answer is critical for the interpretation of the blood oxygen level-dependent (BOLD) signal in fMRI. Here, we have used well-established visual-system circuitry to create a stimulus that elicits synaptic activity without associated spike discharge. In colocalized recordings of neural and metabolic activity in cat primary visual cortex, we observed strong coupling between local field potentials (LFPs) and changes in tissue oxygen concentration in the absence of spikes. These results imply that the BOLD signal is more closely coupled to synaptic activity.
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
“Thus, V1 exhibited the same BOLD signal despite known differences in visual processing for PF and UF (Viswanathan and Freeman, 2007).”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Viswanathan and Freeman, 2007
In the citing paper
“High (30 Hz) frequency visual stimulation has been found to selectively suppress multiunit activity (MUA) in cat V1 as compared to low frequency (4 Hz) visual stimulation (Viswanathan and Freeman, 2007).”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Viswanathan and Freeman, 2007
In the citing paper
“Our results suggest that lactate and glutamate may be dissociated from BOLD changes when cortical input and output are differentially modulated by for example, intracortical (Viswanathan and Freeman, 2007) or thalamocortical (Min et al., 2020) inhibition.”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Viswanathan and Freeman, 2007
In the citing paper
“This conclusion is supported by the fact that high-frequency flickering (30–60 Hz) abolished MUA, a measure of neuronal spiking (putatively from layer II/III) (Viswanathan and Freeman, 2007), but not single neuron recordings from layer IV (Gur and Snodderly, 1997).”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Viswanathan and Freeman, 2007
In the citing paper
“oxidative metabolism and CMRO2 are enhanced at both low and high flickering frequencies (Viswanathan and Freeman, 2007)”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Viswanathan and Freeman, 2007
In the citing paper
“Notably, the MAS does not necessarily correlate with mitochondrial respiration and cerebral blood flow, as evidenced by the findings that (1) oxidative metabolism and CMRO2 are enhanced at both low and high flickering frequencies (Viswanathan and Freeman, 2007), and (2) glutamate and aspartate, but not lactate, correlate with BOLD signals during low frequency (~8 Hz) visual stimulation (Bednařík”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Viswanathan and Freeman, 2007
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 [130]
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 [130]
Citations
Cites
Neurophysiological investigation of the basis of the fMRI signal
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001) · Nature · doi:10.1038/35084005 · Cited by 6,551
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
Ogawa, S., Tank, D. W., Menon, R., Ellermann, J. M., Kim, S. G., Merkle, H., & Ugurbil, K. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.13.5951 · Cited by 3,681
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
Logothetis, N. K., & Wandell, B. A. (2004) · Annual Review of Physiology · doi:10.1146/annurev.physiol.66.082602.092845 · Cited by 1,568
Malonek, D., & Grinvald, A. (1996) · Science · doi:10.1126/science.272.5261.551 · Cited by 1,109
The Underpinnings of the BOLD Functional Magnetic Resonance Imaging Signal
Logothetis, N. K. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-10-03963.2003 · Cited by 1,024
Coupling Between Neuronal Firing, Field Potentials, and fMRI in Human Auditory Cortex
Mukamel, R., Gelbard, H., Arieli, A., Hasson, U., Fried, I., & Malach, R. (2005) · Science · doi:10.1126/science.1110913 · Cited by 1,023
Hemodynamic Signals Correlate Tightly with Synchronized Gamma Oscillations
Niessing, J., Ebisch, B., Schmidt, K. E., Niessing, M., Singer, W., & Galuske, R. A. W. (2005) · Science · doi:10.1126/science.1110948 · Cited by 806
Top-down processing mediated by interareal synchronization
von Stein, A., Chiang, C., & Peter König, B. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.26.14748 · Cited by 748
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–397 of 397
Woeppel, K. M., Krahe, D. D., Robbins, E. M., Vazquez, A. L., & Cui, X. T. (2023) · Advanced Healthcare Materials · doi:10.1002/adhm.202301221 · Cited by 6
A BIOCHEMICAL FRAMEWORK FOR MODELING THE FUNCTIONAL METABOLISM OF THE HUMAN BRAIN
DiNuzzo, M., Giove, F., & Maraviglia, B. (2009) · Cited by 6
Locking of correlated neural activity to ongoing oscillations
Kühn, T., & Helias, M. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005534 · Cited by 7
Xu, H., Dong, M., Nakai, Y., Asano, E., & Jeong, J. (2018) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2018.8363748 · Cited by 6
A comparison of monkey and human motion processing mechanisms
Lynn, C., & Curran, W. J. (2010) · Vision Research · doi:10.1016/j.visres.2010.08.007 · Cited by 6
Garrett, D. D., Epp, S. M., Perry, A., & Lindenberger, U. (2018) · Max Planck Digital Library · Cited by 7
(2009) · Nature Neuroscience · doi:10.1038/nn0209-99 · Cited by 6
Effects of the radio electric asymmetric conveyer (REAC) on motor disorders: An integrative review
Machado, V. G., Brun, A. B. S., & Manffra, E. F. (2023) · Frontiers in Medical Technology · doi:10.3389/fmedt.2023.1122245 · Cited by 5
Shatalina, E., Onwordi, E. C., Whitehurst, T., Whittington, A., Mansur, A., Arumuham, A., Statton, B. K., Berry, A., Marques, T. R., Gunn, R. N., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00190 · Cited by 6
Weber, B. (2015) · Biological magnetic resonance · doi:10.1007/978-1-4899-7591-1_5 · Cited by 6
Michmizos, K. P., Sakas, D. E., & Nikita, K. S. (2011) · Measurement Science and Technology · doi:10.1088/0957-0233/22/11/114021 · Cited by 5
Garrett, D. D., Epp, S. M., Perry, A., & Lindenberger, U. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/184739 · Cited by 5
Distinct neurochemical influences on fMRI response polarity in the striatumPreprint
Cerri, D. H., Albaugh, D. L., Walton, L. R., Katz, B. M., Wang, T.-W. W., Chao, T.-H. H., Zhang, W., Nonneman, R. J., Jiang, J., Lee, S., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.20.529283 · Cited by 5
Local Field Potential, Relationship to BOLD Signal
Logothetis, N. K., & Panzeri, S. (2014) · Springer eBooks · doi:10.1007/978-1-4614-7320-6_726-1 · Cited by 5
What Can Neuroimaging Tell Us about Central Pain?
Veldhuijzen, D. S., Lenz, F. A., LaGraize, S. C., & Greenspan, J. D. (2009) · Frontiers in neuroscience · doi:10.1201/9781439812105-c14 · Cited by 4
Locally Measured Neuronal Correlates of Functional MRI Signals
Shmuel, A., & Maier, A. (2015) · Biological magnetic resonance · doi:10.1007/978-1-4899-7591-1_6 · Cited by 6
Nakamura, N. H., Fukunaga, M., Nakamura, N. H., & Oku, Y. (2023) · Progress in Neurobiology · doi:10.60124/j.pneuro.2023.10.01 · Cited by 4
Linking Neural Activity to Visual Perception: Separating Sensory and Attentional Contributions
T., J., Nicolas, Y., Changan, A., & Erik, P. (2012) · InTech eBooks · doi:10.5772/48806 · Cited by 4
Central Nervous System Physiology
Raz, A., & Perouansky, M. A. (2013) · Elsevier eBooks · doi:10.1016/b978-1-4377-1679-5.00007-7 · Cited by 4
Armony, J. L., & Han, J. E. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9780511843716.008 · Cited by 4
1.2 Physiological Basis of the BOLD Signal
Goense, J. B. M., & Logothetis, N. K. (2010) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195372731.003.0002 · Cited by 4
Reply to “BOLD and spiking activity”
Viswanathan, A., & Freeman, R. D. (2008) · Nature Neuroscience · doi:10.1038/nn0508-524 · Cited by 3
Self-citationPhysiological Foundations of Neural Signals
Whittingstall, K., & Logothetis, N. K. (2013) · CRC Press eBooks · doi:10.1201/b14756-3 · Cited by 3
Huang, J. (2022) · Brain Sciences · doi:10.3390/brainsci13010006 · Cited by 3
High-frequency neuronal signal better explains multi-phase BOLD response
Zhang, Q., Cramer, S. R., Turner, K. L., Neuberger, T., Drew, P. J., & Zhang, N. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119887 · Cited by 3
What We Can and What We Can’t Do with fMRI
Logothetis, N. K. (2012) · Max Planck Digital Library · Cited by 3
Neurovascular coupling and functional neuroimaging
Polimeni, J. R. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-820480-1.00213-8 · Cited by 3
Shatalina, E., Whitehurst, T., Onwordi, E. C., Whittington, A., Mansur, A., Arumuham, A., Marques, T. R., Gunn, R. N., Natesan, S., Nour, M. M., et al. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.02.007 · Cited by 2
Peretin, J. M., Cover, C. G., & Vazquez, A. L. (2025) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x251338407 · Cited by 2
McClure, S. M., & D’Ardenne, K. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374620-7.00010-8 · Cited by 5
Calcium Signaling in Cerebral Vasoregulation
Ghosh, S., & Basu, A. (2012) · Advances in experimental medicine and biology · doi:10.1007/978-94-007-2888-2_37 · Cited by 2
Heugel, N., Liebenthal, E., & Beardsley, S. A. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108401 · Cited by 2
Infra-slow brain dynamics as a marker for cognitive function and decline.
Ajmera, S., Rajagopal, S., Rehman, R. U., & Sridharan, D. (2019) · PubMed · Cited by 2
Oxygen Polarography in the Awake Macaque: Bridging BOLD fMRI and Electrophysiology
Bentley, W. J. (2014) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7rn35wg · Cited by 2
Intrinsic signal optical imaging
Frostig, R. D., & Chen‐Bee, C. H. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9780511979958.008 · Cited by 2
Shatalina, E., Onwordi, E. C., Whitehurst, T., Whittington, A., Mansur, A., Arumuham, A., Marques, T. R., Gunn, R. N., Natesan, S., Rabiner, E. A., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.25.614893 · Cited by 2
Leicht, G., & Mulert, C. (2014) · Springer eBooks · doi:10.1007/978-3-642-54542-9_4 · Cited by 1
Yen, C. C. (2011) · D-Scholarship@Pitt (University of Pittsburgh) · 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
Self-citationevidencein 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
Scheeringa, R., & Laufs, H. (2022) · Springer eBooks · doi:10.1007/978-3-031-07121-8_15 · Cited by 2
Deng, H., Liao, L., Li, X., Liu, Y., He, Z., & Sun, H. (2025) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2025.111576 · Cited by 1
Functional magnetic resonance imaging
Bartels, A., Goense, J. B. M., & Logothetis, N. K. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9780511979958.011 · Cited by 1
Combination of Brain Functional Imaging Techniques
Seeck, M., Spinelli, L., Gotman, J., & Lopes, F. H. D. S. (2017) · Oxford University Press eBooks · doi:10.1093/med/9780190228484.003.0046 · Cited by 1
Locally Measured Neuronal Correlates of Functional MRI Signals
Shmuel, A., & Maier, A. (2022) · Springer eBooks · doi:10.1007/978-3-031-07121-8_4 · Cited by 1
Clarifying the neurophysiological basis of the other-race effect
Vizioli, L. (2012) · Enlighten: Theses (The University of Glasgow) · Cited by 1
Kaliukhovich, D. A., & Vogels, R. (2013) · PLoS ONE · doi:10.1371/annotation/411033ae-4884-42db-826f-b9dda6564860 · Cited by 1
H215O PET responses to deep brain stimulation
Montgomery, E. B. (2012) · Brain stimulation · doi:10.1016/j.brs.2011.11.003 · Cited by 1
The processing of sounds in auditory cortex during sleep
Issa, E. B. (2008) · Cited by 1
Raafat, R. (2015) · UCL Discovery (University College London) · Cited by 1
Correlated activity of periodically driven binary networksPreprint
Kühn, T., & Helias, M. (2016) · arXiv (Cornell University) · Cited by 1
The timing of hemodynamic changes reliably reflects spiking activityPreprint
Zaidi, A. D., Birbaumer, N., Fetz, E. E., Logothetis, N. K., & Sitaram, R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/269696 · Cited by 1
Investigations on bottom-up and top-down processing in early visual cortex with high-resolution fMRI
Marquardt, I. (2019) · Research Publications (Maastricht University) · doi:10.26481/dis.20190829im · Cited by 1
Mercadal, B., Guasch-Morgades, M., Mencarelli, L., Koch, G., Ruffini, G., & Initiative, A. D. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.09.663817 · Cited by 1
NEURONAL ENSEMBLE MODELING AND ANALYSIS WITH VARIABLE ORDER MARKOV MODELS
Zippo, A. G. (2010) · Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) · doi:10.13130/zippo-antonio-giuliano_phd2010-12-17 · Cited by 1
Experience Dependent Plasticity over short and long timescales
Lyness, C. R. (2015) · UCL Discovery (University College London)
Phase-based Regional Oxygen Metabolism in Magnetic Resonance Imaging at High Field
Fan, A. P. (2010) · DSpace@MIT (Massachusetts Institute of Technology)
Neural Basis of Functional Connectivity MRI
Li, J. (2015) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7cc0xw8
The role of regret and responsibility in decision-making
Nicolle, A. (2010) · UCL Discovery (University College London)
Sturzbecher, M. J. (2011) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.59.2011.tde-08072011-174951
Local action for global vision
Volgushev, M. (2011) · The Journal of Physiology · doi:10.1113/jphysiol.2011.212670
Atabaki, A., Dicke, P. W., Karnath, H. ‐., & Thier, P. (2013) · European Journal of Neuroscience · doi:10.1111/ejn.12139
More on fMRI and the locus of perceptual learning
Dorjee, D., & Bowers, J. S. (2011) · Cortex · doi:10.1016/j.cortex.2011.11.004
Kjelvik, G. (2012) · NORA - Norwegian Open Research Archives
"Overshoot"ofO 2 IsRequiredtoMaintainBaselineTissue OxygenationatLocationsDistaltoBloodVessels
Vinogradov, S. S., & Buxton, R. B. (2011)
differences in spoken language learning Human inferior colliculus activity relates to individual
Kraus, N., Wong, P. C. M., Skoe, E., Oxenham, A. J., Anderson, S., White‐Schwoch, T., Parbery‐Clark, A., Weiss, M. W., & Bidelman, G. M. (2012)
The role of regret and responsibility in
Nicolle, A. (2010)
Experience-related effects on the response selectivity of macaque inferior neurons
Baene, W. D. (2008) · Lirias
Hemodynamic Imaging: Functional Magnetic Resonance Imaging
Talavage, T. M., Johnsrude, I. S., & González-Castillo, J. (2012) · Springer handbook of auditory research · doi:10.1007/978-1-4614-2314-0_6
White noise analysis of visual selectivity in area MT during fixation and eye movements
Hartmann, T. S. (2012) · Rutgers University Community Repository (Rutgers University) · doi:10.7282/t3nv9h98
Combining DTI and fMRI to investigate language lateralisation
Barsaglini, A. (2013) · Padua@research (University of Padova)
Processing of quantitative information, investigated with fMRI.
Roggeman, C. (2008) · Ghent University Academic Bibliography (Ghent University)
Editorial: Neural Signal Estimation in the Human Brain
Tyler, C. W., Howarth, C., & Likova, L. T. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00185
Simultane EEG - fMRT Untersuchung von schmerzevozierten Reaktionen
Falkai, P. (2013)
Noninvasive Neural Imaging and Tissue Oxygenation in the Visual System
Li, B., & Freeman, R. D. (2014) · Neuromethods · doi:10.1007/978-1-4939-0724-3_6
Self-citationArticle Neurophysiology of the BOLD fMRI Signal in Awake Monkeys
Logothetis, N. K. (2008)
Figley, C. R. (2010) · QSpace (Queen's University Library)
Functional Connectivity of the Rodent Striatum
Albaugh, D. L. (2016) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/jard-1g42
Lakshminarasimhan, K. J., Logothetis, N. K., & Keliris, G. A. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/150532
Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy
Laxpati, N. G. (2015) · SMARTech Repository (Georgia Institute of Technology)
Topographic Organization of Extraoccipital Visual Processing Areas in the MacaquePreprint
Patel, G. H., Snyder, L. H., & Corbetta, M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/345363
Hai, P. (2018) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7pk0fk9
Gamma-Aktivität und vaskuläre Antwort im visuellen Kortex des Menschen
Werner, P. (2010) · Universitätsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver · doi:10.17169/refubium-15178
Ultrafast functional magnetic resonance imaging reveals neuroplasticity-driven timing modulationsPreprint
Gil, R., Fernandes, F. F., & Shemesh, N. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.00086
Klink, P. C., Chen, X., Vanduffel, W., & Roelfsema, P. R. (2021) · eLife · doi:10.7554/elife.67304.sa2
Claron, J., Provansal, M., Salardaine, Q., Tissier, P., Dizeux, A., Deffieux, T., Picaud, S. A., Tanter, M., Arcizet, F., & Pouget, P. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.20.496840
Local Field Potential, Relationship to BOLD Signal
Logothetis, N. K., & Panzeri, S. (2022) · Springer eBooks · doi:10.1007/978-1-0716-1006-0_726
Karimova, E., Burkitbaev, S., Трифонов, И. С., Sinkin, M. V., Rider, F. K., Guekht, A. B., & Lebedeva, N. N. (2022) · Neuroscience and Behavioral Physiology · doi:10.1007/s11055-022-01292-6
Becker, R., Mayhew, S. D., Ritter, P., & Villringer, A. (2022) · Springer eBooks · doi:10.1007/978-3-031-07121-8_23
Pollmann, S., & Noesselt, T. (2023) · Springer eBooks · doi:10.1007/978-3-662-68025-4_2
Park, S., Wu, B., Zbaranska, S., Lee, J., Jacob, A. D., Hoorn, A., Mocle, A. J., Luchetti, A., Chen, M., Jung, J. H., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2602678123
Rochas, V., Montandon, M., Rodriguez, C. K., Herrmann, F. R., Eytan, A., Pegna, A. J., Michel, C. M., & Giannakopoulos, P. (2026) · Scientific Reports · doi:10.1038/s41598-026-64677-4
Metadata
- Authors
- Viswanathan, A., & Freeman, R. D.
- Affiliations
- University of California, Berkeley (US)
- Corresponding author
- Freeman, Ralph D
- ORCID
- Freeman, Ralph D
- Venue
- Nature Neuroscience
- Published
- 2007-09-09
- Volume
- 10
- Issue
- 10
- Pages
- 1308-1312
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2139354009
- Cited by
- 397
- References
- 32
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 9 · 2023: 12 · 2022: 13 · 2021: 7 · 2020: 14 · 2019: 9 · 2018: 16 · 2017: 15 · 2016: 23 · 2015: 25 · 2014: 22 · 2013: 28 · 2012: 31
- FWCI
- 32.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01ey003716-05)
- National Eye Institute (EY 03716, EY 01175, R01EY001175)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- neurometabolic coupling, BOLD signal, synaptic activity, spiking activity, local field potentials, cerebral cortex, primary visual cortex, tissue oxygen concentration, deoxyhemoglobin, functional MRI, cats
- MeSH terms
- Action Potentials, Animals, Cats, Dose-Response Relationship, Radiation, Evoked Potentials, Visual, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Oxygen, Photic Stimulation, Synapses, Visual Cortex, Visual Pathways
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