Feature-based attention influences motion processing gain in macaque visual cortex
Open accessAbstract
Changes in neural responses based on spatial attention have been demonstrated in many areas of visual cortex, indicating that the neural correlate of attention is an enhanced response to stimuli at an attended location and reduced responses to stimuli elsewhere. Here we demonstrate non-spatial, feature-based attentional modulation of visual motion processing, and show that attention increases the gain of direction-selective neurons in visual cortical area MT without narrowing the direction-tuning curves. These findings place important constraints on the neural mechanisms of attention and we propose to unify the effects of spatial location, direction of motion and other features of the attended stimuli in a 'feature similarity gain model' of attention.
Integrity signals
Registry
Cites
Statistics
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?
Gain modulation (wherein attention multiplicatively scales neural activity) has been found in many neural systems.
“Similar to self-attention, gain modulation (wherein attention multiplicatively scales neural activity) has been found in many neural systems (Treue & Trujillo 1999, Reynolds & Heeger 2009).”
From Consciousness in Artificial Intelligence: Insights from the Science of Consciousness (2023) · cites this paper as Treue & Trujillo 1999
Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration.
“Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration1–3,7,8,13–17.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [16]
Cites
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388 · see citing works
Selective Attention Gates Visual Processing in the Extrastriate Cortex
Moran, J., & Desimone, R. (1985) · Science · doi:10.1126/science.4023713 · Cited by 2,433 · see citing works
Selective Attention Gates Visual Processing in the Extrastriate Cortex
Moran, J., & Desimone, R. (2003) · The MIT Press eBooks · doi:10.7551/mitpress/2834.003.0024 · Cited by 2,164 · see citing works
Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex
Luck, S. J., Chelazzi, L., Hillyard, S. A., & Desimone, R. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.1.24 · Cited by 1,615 · see citing works
Newsome, W., & Pare, E. (1988) · The Journal of Neuroscience · doi:10.1523/jneurosci.08-06-02201.1988 · Cited by 1,615 · see citing works
Competitive Mechanisms Subserve Attention in Macaque Areas V2 and V4
Reynolds, J. H., Chelazzi, L., & Desimone, R. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-05-01736.1999 · Cited by 1,236 · see citing works
Effects of Attention on Orientation-Tuning Functions of Single Neurons in Macaque Cortical Area V4
McAdams, C. J., & Maunsell, J. H. R. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-01-00431.1999 · Cited by 1,214 · see citing works
A neural basis for visual search in inferior temporal cortex
Chelazzi, L., Miller, E. K., Duncan, J., & Desimone, R. (1993) · Nature · doi:10.1038/363345a0 · Cited by 1,114 · see citing works
Motter, B. C. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.70.3.909 · Cited by 1,055 · see citing works
A relationship between behavioral choice and the visual responses of neurons in macaque MT
Britten, K. H., Newsome, W. T., Shadlen, M. N., Celebrini, S., & Movshon, J. A. (1996) · Visual Neuroscience · doi:10.1017/s095252380000715x · Cited by 1,049 · see citing works
Attentional modulation of visual motion processing in cortical areas MT and MST
Treue, S., & Maunsell, J. H. R. (1996) · Nature · doi:10.1038/382539a0 · Cited by 1,025 · see citing works
Self-citationIncreased Attention Enhances Both Behavioral and Neuronal Performance
Spitzer, H., Desimone, R., & Moran, J. (1988) · Science · doi:10.1126/science.3353728 · Cited by 815 · see citing works
Newsome, W. T., Wurtz, R. H., Dürsteler, M., & Mikami, A. (1985) · Journal of Neuroscience · doi:10.1523/jneurosci.05-03-00825.1985 · Cited by 669 · see citing works
Neural correlates of attentive selection for color or luminance in extrastriate area V4
Motter, B. C. (1994) · Journal of Neuroscience · doi:10.1523/jneurosci.14-04-02178.1994 · Cited by 482 · see citing works
Voluntary Attention Modulates fMRI Activity in Human MT–MST
O’Craven, K. M., Rosen, B. R., Kwong, K. K., Treisman, A., & Savoy, R. L. (1997) · Neuron · doi:10.1016/s0896-6273(00)80300-1 · Cited by 452 · see citing works
Beauchamp, M. S., Cox, R. W., & DeYoe, E. A. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.78.1.516 · Cited by 267 · see citing works
The response of neurons in areas V1 and MT of the alert rhesus monkey to moving random dot patterns
Snowden, R. J., Treue, S., & Andersen, R. A. (1992) · Experimental Brain Research · doi:10.1007/bf02259114 · Cited by 263 · see citing works
Self-citationValdés-Sosa, M. J., Bobes, M. A., Rodrı́guez, V., & Pinilla, T. (1998) · Journal of Cognitive Neuroscience · doi:10.1162/089892998563743 · Cited by 209 · see citing works
Attentional modulation of adaptation to two-component transparent motion
Lankheet, M. J., & Verstraten, F. A. J. (1995) · Vision Research · doi:10.1016/0042-6989(95)98720-t · Cited by 132 · see citing works
Objects and attributes in divided attention: Surface and boundary systems
Duncan, J., & Nimmo‐Smith, I. (1996) · Perception & Psychophysics · doi:10.3758/bf03206834 · Cited by 66 · see citing works
Itti, L., Braun, J., Lee, D. K., et al. (1998) · CaltechAUTHORS (California Institute of Technology) · Cited by 25 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Computational modelling of visual attention
Itti, L., & Koch, C. (2001) · Nature Reviews Neuroscience · doi:10.1038/35058500 · Cited by 4,733 · see citing works
Mechanisms of visual attention in the human cortex
Ungerleider, S. K. A. L. G. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.315 · Cited by 2,159 · see citing works
Decoding the visual and subjective contents of the human brain
Kamitani, Y., & Tong, F. (2005) · Nature Neuroscience · doi:10.1038/nn1444 · Cited by 1,829 · see citing works
The Normalization Model of Attention
Reynolds, J. H., & Heeger, D. J. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.002 · Cited by 1,457 · see citing works
A taxonomy of external and internal attention.
Chun, M. M., Golomb, J. D., & Turk-Browne, N. B. (2011) · Annual Review of Psychology · doi:10.1146/annurev.psych.093008.100427 · Cited by 1,472 · see citing works
Top-down influences on visual processing
Gilbert, C. D., & Li, W. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3476 · Cited by 1,224 · see citing works
Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit
Hahnloser, R. H. R., Sarpeshkar, R., Mahowald, M. A., Douglas, R. J., & Seung, H. S. (2000) · Nature · doi:10.1038/35016072 · Cited by 1,293 · see citing works
Consciousness, accessibility, and the mesh between psychology and neuroscience
Block, N. (2007) · Behavioral and Brain Sciences · doi:10.1017/s0140525x07002786 · Cited by 1,146 · see citing works
Expectation (and attention) in visual cognition
Summerfield, C., & Egner, T. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.06.003 · Cited by 950 · see citing works
STRUCTURE AND FUNCTION OF VISUAL AREA MT
Born, R. T., & Bradley, D. C. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131052 · Cited by 1,023 · see citing works
Gain Modulation from Background Synaptic Input
Chance, F. S., Abbott, L. F., & Reyes, A. D. (2002) · Neuron · doi:10.1016/s0896-6273(02)00820-6 · Cited by 1,012 · see citing works
Expectation in perceptual decision making: neural and computational mechanisms
Summerfield, C., & de Lange, F. P. (2014) · Nature Reviews Neuroscience · doi:10.1038/nrn3838 · Cited by 832 · see citing works
Long-range and local circuits for top-down modulation of visual cortex processing
Zhang, S., Xu, M., Kamigaki, T., Hoang Do, J. P., Chang, W.-C., Jenvay, S., Miyamichi, K., Luo, L., & Dan, Y. (2014) · Science · doi:10.1126/science.1254126 · Cited by 804 · see citing works
fMRI evidence for objects as the units of attentional selection
O'Craven, K. M., Downing, P. E., & Kanwisher, N. (1999) · Nature · doi:10.1038/44134 · Cited by 846 · see citing works
Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4
Mitchell, J. F., Sundberg, K. A., & Reynolds, J. H. (2009) · Neuron · doi:10.1016/j.neuron.2009.09.013 · Cited by 710 · see citing works
Feature-Based Attention Increases the Selectivity of Population Responses in Primate Visual Cortex
Martinez-Trujillo, J. C., & Treue, S. (2004) · Current Biology · doi:10.1016/j.cub.2004.04.028 · Cited by 697 · see citing works
Self-citationParvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli
Atallah, B. V., Bruns, W., Carandini, M., & Scanziani, M. (2012) · Neuron · doi:10.1016/j.neuron.2011.12.013 · Cited by 612 · see citing works
Sarter, M., Hasselmo, M. E., Bruno, J. P., & Givens, B. (2005) · Brain Research Reviews · doi:10.1016/j.brainresrev.2004.08.006 · Cited by 667 · see citing works
Gain control by layer six in cortical circuits of vision
Olsen, S. R., Bortone, D. S., Adesnik, H., & Scanziani, M. (2012) · Nature · doi:10.1038/nature10835 · Cited by 539 · see citing works
More attention must be paid: The neurobiology of attentional effort
Sarter, M., Gehring, W. J., & Kozak, R. (2006) · Brain Research Reviews · doi:10.1016/j.brainresrev.2005.11.002 · Cited by 552 · see citing works
Learning and selective attention
Dayan, P., Kakade, S., & Montague, P. R. (2000) · Nature Neuroscience · doi:10.1038/81504 · Cited by 495 · see citing works
Silver, R. A. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2864 · Cited by 481 · see citing works
Attention reverses the effect of prediction in silencing sensory signals
Kok, P., Rahnev, D., Jehee, J. F. M., Lau, H. C., & de Lange, F. P. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr310 · Cited by 430 · see citing works
Neural mechanisms of selective visual attention.
Moore, T., & Zirnsak, M. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033400 · Cited by 471 · see citing works
Convergence of biological and psychological perspectives on cognitive coordination in schizophrenia
Phillips, W. A., & Silverstein, S. M. (2003) · Behavioral and Brain Sciences · doi:10.1017/s0140525x03000025 · Cited by 445 · see citing works
Rapid Neocortical Dynamics: Cellular and Network Mechanisms
Haider, B., & McCormick, D. A. (2009) · Neuron · doi:10.1016/j.neuron.2009.04.008 · Cited by 441 · see citing works
Mechanisms of top-down attention
Baluch, F., & Itti, L. (2011) · Trends in Neurosciences · doi:10.1016/j.tins.2011.02.003 · Cited by 437 · see citing works
Salinas, E., & Thier, P. (2000) · Neuron · doi:10.1016/s0896-6273(00)00004-0 · Cited by 400 · see citing works
Neuronal representations of cognitive state: reward or attention?
Maunsell, J. H. R. (2004) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.04.003 · Cited by 404 · see citing works
The brain circuitry of attention
Shipp, S. (2004) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.03.004 · Cited by 402 · see citing works
Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream
Egner, T., Monti, J. M., & Summerfield, C. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2770-10.2010 · Cited by 350 · see citing works
Selection history: How reward modulates selectivity of visual attention.
Failing, M., & Theeuwes, J. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1380-y · Cited by 345 · see citing works
“According to these models, attention is predominantly spatial (but see feature-based attention accounts, e.g., Maunsell & Treue, 2006; Treue and Trujillo, 1999) and hierarchical in the sense that the specific location with the highest activity on the priority map is most likely to attract attention…”
MethodEffects of Spatial Attention on Contrast Response Functions in Macaque Area V4
Williford, T., & Maunsell, J. H. R. (2006) · Journal of Neurophysiology · doi:10.1152/jn.01207.2005 · Cited by 353 · see citing works
Bottom-Up Dependent Gating of Frontal Signals in Early Visual Cortex
Ekstrom, L. B., Roelfsema, P. R., Arsenault, J. T., Bonmassar, G., & Vanduffel, W. (2008) · Science · doi:10.1126/science.1153276 · Cited by 329 · see citing works
Mechanisms underlying gain modulation in the cortex
Ferguson, K. A., & Cardin, J. A. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0253-y · Cited by 327 · see citing works
Areas Involved in Encoding and Applying Directional Expectations to Moving Objects
Shulman, G. L., Ollinger, J. M., Akbudak, E., Conturo, T. E., Snyder, A. Z., Petersen, S. E., & Corbetta, M. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-21-09480.1999 · Cited by 298 · see citing works
Barrages of Synaptic Activity Control the Gain and Sensitivity of Cortical Neurons
Shu, Y., Hasenstaub, A., Badoual, M., Bal, T., & McCormick, D. A. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-32-10388.2003 · Cited by 298 · see citing works
Prior expectations bias sensory representations in visual cortex
Kok, P., Brouwer, G. J., van Gerven, M. A. J., & de Lange, F. P. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.0742-13.2013 · Cited by 260 · see citing works
Gazzaley, A., Rissman, J., Cooney, J., Rutman, A., Seibert, T., Clapp, W., & D'Esposito, M. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm113 · Cited by 287 · see citing works
Attention deficits without cortical neuronal deficits
Zénon, A., & Krauzlis, R. J. (2012) · Nature · doi:10.1038/nature11497 · Cited by 234 · see citing works
A Normalization Model of Attentional Modulation of Single Unit Responses
Lee, J., & Maunsell, J. H. R. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004651 · Cited by 257 · see citing works
Figure—Ground Segregation in a Recurrent Network Architecture
Roelfsema, P. R., Lamme, V. A. F., Spekreijse, H., & Bosch, H. (2002) · Journal of Cognitive Neuroscience · doi:10.1162/08989290260045756 · Cited by 254 · see citing works
Representation of Concurrent Stimuli by Population Activity in Visual Cortex
Busse, L., Wade, A. R., & Carandini, M. (2009) · Neuron · doi:10.1016/j.neuron.2009.11.004 · Cited by 247 · see citing works
Feedback of visual object information to foveal retinotopic cortex
Williams, M. A., Baker, C. I., Op de Beeck, H. P., Mok Shim, W., Dang, S., Triantafyllou, C., & Kanwisher, N. (2008) · Nature Neuroscience · doi:10.1038/nn.2218 · Cited by 235 · see citing works
Gain control of firing rate by shunting inhibition: Roles of synaptic noise and dendritic saturation
Prescott, S. A., & De Koninck, Y. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0337591100 · Cited by 226 · see citing works
Hamker, F. H. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhh146 · Cited by 217 · see citing works
Neural tuning and representational geometry
Kriegeskorte, N., & Wei, X.-X. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-021-00502-3 · Cited by 187 · see citing works
Different glutamate receptors convey feedforward and recurrent processing in macaque V1
Self, M. W., Kooijmans, R. N., Supèr, H., Lamme, V. A., & Roelfsema, P. R. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1119527109 · Cited by 184 · see citing works
Attention Modulates the Responses of Simple Cells in Monkey Primary Visual Cortex
McAdams, C. J., & Reid, R. C. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.2904-05.2005 · Cited by 203 · see citing works
Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
Butlin, P., Long, R., Elmoznino, E., Bengio, Y., Birch, J., Constant, A., Deane, G., Fleming, S. M., Frith, C., Ji, X., et al. (2023) · arXiv · doi:10.48550/arxiv.2308.08708 · Cited by 196 · see citing works
High-Level Prediction Signals in a Low-Level Area of the Macaque Face-Processing Hierarchy
Schwiedrzik, C. M., & Freiwald, W. A. (2017) · Neuron · doi:10.1016/j.neuron.2017.09.007 · Cited by 136 · see citing works
Neuronal coherence during selective attentional processing and sensory–motor integration
Womelsdorf, T., & Fries, P. (2006) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2007.01.005 · Cited by 156 · see citing works
Exogenous attention and color perception: Performance and appearance of saturation and hue
Fuller, S., & Carrasco, M. (2006) · Vision Research · doi:10.1016/j.visres.2006.07.014 · Cited by 157 · see citing works
Busse, L., Katzner, S., & Treue, S. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707369105 · Cited by 122 · see citing works
Self-citationPrior object-knowledge sharpens properties of early visual feature-detectors
Teufel, C., Dakin, S. C., & Fletcher, P. C. (2018) · Scientific Reports · doi:10.1038/s41598-018-28845-5 · Cited by 119 · see citing works
Higgs, M. H., Slee, S. J., & Spain, W. J. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1792-06.2006 · Cited by 124 · see citing works
Rapidly learned stimulus expectations alter perception of motion
Chalk, M., Seitz, A. R., & Series, P. (2010) · Journal of Vision · doi:10.1167/10.8.2 · Cited by 122 · see citing works
Lawrence, S. J., Norris, D. G., & de Lange, F. P. (2019) · eLife · doi:10.7554/elife.44422 · Cited by 95 · see citing works
Incremental grouping of image elements in vision
Roelfsema, P. R., & Houtkamp, R. (2011) · Attention, Perception, & Psychophysics · doi:10.3758/s13414-011-0200-0 · Cited by 112 · see citing works
Kiefer, M. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00061 · Cited by 103 · see citing works
Tang, M. F., Smout, C. A., Arabzadeh, E., & Mattingley, J. B. (2018) · eLife · doi:10.7554/elife.33123 · Cited by 83 · see citing works
On the Structure of Neuronal Population Activity under Fluctuations in Attentional State
Ecker, A. S., Denfield, G. H., Bethge, M., & Tolias, A. S. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.2044-15.2016 · Cited by 88 · see citing works
Determinants and mechanisms of attentional modulation of neural processing.
Schroeder, C. (2001) · Frontiers in bioscience · doi:10.2741/schroed · Cited by 87 · see citing works
Fast Remapping of Sensory Stimuli onto Motor Actions on the Basis of Contextual Modulation
Salinas, E. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.4569-03.2004 · Cited by 77 · see citing works
Tasks and their role in visual neuroscience
Kay, K., Bonnen, K., Denison, R. N., Arcaro, M. J., & Barack, D. L. (2023) · Neuron · doi:10.1016/j.neuron.2023.03.022 · Cited by 61 · see citing works
Response-dependent dynamics of cell-specific inhibition in cortical networks in vivo
El-Boustani, S., & Sur, M. (2014) · Nature Communications · doi:10.1038/ncomms6689 · Cited by 61 · see citing works
Dynamic representation of 3D auditory space in the midbrain of the free-flying echolocating bat
Kothari, N. B., Wohlgemuth, M. J., & Moss, C. F. (2018) · eLife · doi:10.7554/elife.29053 · Cited by 54 · see citing works
Guan, D., Armstrong, W. E., & Foehring, R. C. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00524.2014 · Cited by 47 · see citing works
Niyogi, R. K., & Wong-Lin, K. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003099 · Cited by 47 · see citing works
Modulation of neuronal responses by exogenous attention in macaque primary visual cortex
Wang, F., Chen, M., Yan, Y., Zhaoping, L., & Li, W. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.0527-15.2015 · Cited by 39 · see citing works
- Authors
- Treue, S., & Trujillo, J. C. M.
- Affiliations
- University of Tübingen (DE)
- ORCID
- Treue, Stefan
- Venue
- Nature
- Published
- 1999-06
- Volume
- 399
- Issue
- 6736
- Pages
- 575-579
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1675937554
- Cited by
- 1,465
- References
- 21
- Citations by year
- 2026: 41 · 2025: 44 · 2024: 44 · 2023: 47 · 2022: 41 · 2021: 58 · 2020: 49 · 2019: 79 · 2018: 61 · 2017: 60 · 2016: 51 · 2015: 54 · 2014: 76 · 2013: 57 · 2012: 65
- FWCI
- 17.49
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
- GRO (submittedVersion, cc-by)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Keywords
- feature-based attention, visual motion processing, direction-selective neurons, non-spatial attention, macaque
- MeSH terms
- Animals, Attention, Macaca, Motion Perception, Neurons, Visual Cortex
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