Speed of processing in the human visual system
Abstract
How long does it take for the human visual system to process a complex natural image? Subjectively, recognition of familiar objects and scenes appears to be virtually instantaneous, but measuring this processing time experimentally has proved difficult. Behavioural measures such as reaction times can be used, but these include not only visual processing but also the time required for response execution. However, event-related potentials (ERPs) can sometimes reveal signs of neural processing well before the motor output. Here we use a go/no-go categorization task in which subjects have to decide whether a previously unseen photograph, flashed on for just 20 ms, contains an animal. ERP analysis revealed a frontal negativity specific to no-go trials that develops roughly 150 ms after stimulus onset. We conclude that the visual processing needed to perform this highly demanding task can be achieved in under 150 ms.
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?
Ultra rapid categorization is a task for which back projections are likely to be inactive.
“Thus, a natural paradigm for comparing the performance of human observers in an object-recognition task to that of a feedforward model of visual processing is ultra rapid categorization, a task for which back projections are likely to be inactive (30, 31).”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [30]
The accuracy of the human observers is well within the range of data previously obtained with go/no-go tasks on similar tasks.
“The accuracy of the human observers is well within the range of data previously obtained with go/no-go tasks on similar tasks (30, 31, 33).”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [30]
Animal- vs. non-animal-recognition is a well established experiment.
“A well established experiment is an animal- vs. non-animal-recognition task (30-34).”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [30]
Cited by
Sorted by citations
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380 · see citing works
A Bayesian Hierarchical Model for Learning Natural Scene Categories
Fei-Fei, L., & Perona, P. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2005.16 · Cited by 3,657 · see citing works
Dynamic predictions: Oscillations and synchrony in top–down processing
Engel, A. K., Fries, P., & Singer, W. (2001) · Nature Reviews Neuroscience · doi:10.1038/35094565 · Cited by 3,454 · see citing works
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309 · see citing works
A sensorimotor account of vision and visual consciousness
O'Regan, J. K., & Noë, A. (2001) · Behavioral and Brain Sciences · doi:10.1017/s0140525x01000115 · Cited by 3,126 · see citing works
On the Opportunities and Risks of Foundation Models
Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv · doi:10.48550/arxiv.2108.07258 · Cited by 2,676 · see citing works
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 · see citing works
First Impressions: Making Up Your Mind After a 100-Ms Exposure to a Face
Willis, J., & Todorov, A. (2006) · Psychological Science · doi:10.1111/j.1467-9280.2006.01750.x · Cited by 2,300 · see citing works
The spatial and temporal signatures of word production components
Indefrey, P., & Levelt, W. J. M. (2004) · Cognition · doi:10.1016/j.cognition.2002.06.001 · Cited by 2,144 · see citing works
Event-Related fMRI: Characterizing Differential Responses
Friston, K. J., Fletcher, P. C., Josephs, O., Holmes, A., Rugg, M. D., & Turner, R. (1998) · NeuroImage · doi:10.1006/nimg.1997.0306 · Cited by 2,017 · see citing works
How does the brain solve visual object recognition?
DiCarlo, J. J., Zoccolan, D., & Rust, N. C. (2012) · Neuron · doi:10.1016/j.neuron.2012.01.010 · Cited by 1,790 · see citing works
Pessoa, L., & Adolphs, R. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2920 · Cited by 1,794 · see citing works
Robust Object Recognition with Cortex-Like Mechanisms
Serre, T., Wolf, L., Bileschi, S., Riesenhuber, M., & Poggio, T. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.56 · Cited by 1,667 · see citing works
Torralba, A. B., Oliva, A., Castelhano, M. S., & Henderson, J. M. (2006) · Psychological Review · doi:10.1037/0033-295x.113.4.766 · Cited by 1,646 · see citing works
Affective picture processing: An integrative review of ERP findings
Olofsson, J. K., Nordin, S., Sequeira, H., & Polich, J. (2008) · Biological Psychology · doi:10.1016/j.biopsycho.2007.11.006 · Cited by 1,595 · see citing works
Top-down facilitation of visual recognition
Bar, M., Kassam, K. S., Ghuman, A. S., Boshyan, J., Schmid, A. M., Dale, A. M., Hämäläinen, M. S., Marinkovic, K., Schacter, D. L., Rosen, B. R., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507062103 · Cited by 1,489 · 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
Chapter 2 Building the gist of a scene: the role of global image features in recognition
Oliva, A., & Torralba, A. B. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)55002-2 · Cited by 1,441 · see citing works
The lateral occipital complex and its role in object recognition
Kalanit Grill-spector, A., Kourtzi, Z., & Kanwisher, N. (2001) · Vision Research · doi:10.1016/s0042-6989(01)00073-6 · Cited by 1,410 · see citing works
Human gaze control during real-world scene perception
Henderson, J. (2003) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2003.09.006 · Cited by 1,409 · see citing works
Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey
Kriegeskorte, N., Mur, M., Ruff, D. A., Kiani, R., Bodurka, J., Esteky, H., Tanaka, K., & Bandettini, P. A. (2008) · Neuron · doi:10.1016/j.neuron.2008.10.043 · Cited by 1,334 · see citing works
Furber, S. B., Galluppi, F., Temple, S., & Plana, L. A. (2014) · Proceedings of the IEEE · doi:10.1109/jproc.2014.2304638 · Cited by 1,373 · see citing works
Is vision continuous with cognition?: The case for cognitive impenetrability of visual perception
Pylyshyn, Z. W. (1999) · Behavioral and Brain Sciences · doi:10.1017/s0140525x99002022 · Cited by 1,245 · see citing works
Kalanit Grill-spector, A., & Malach, R. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.27.070203.144220 · Cited by 1,191 · see citing works
Mass univariate analysis of event‐related brain potentials/fields I: A critical tutorial review
Groppe, D. M., Urbach, T. P., & Marta Kutas, A. (2011) · Psychophysiology · doi:10.1111/j.1469-8986.2011.01273.x · Cited by 1,161 · see citing works
The Molecular and Systems Biology of Memory
Kandel, E. R., Dudai, Y., & Mayford, M. R. (2014) · Cell · doi:10.1016/j.cell.2014.03.001 · Cited by 1,134 · see citing works
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
Zhang, H., Berg, A. C., Maire, M., & Malik, J. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.301 · Cited by 1,128 · see citing works
The role of context in object recognition
Oliva, A., & Torralba, A. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.09.009 · Cited by 1,063 · see citing works
ERP components in Go/Nogo tasks and their relation to inhibition
Falkenstein, M., Hoormann, J., & Hohnsbein, J. (1999) · Acta Psychologica · doi:10.1016/s0001-6918(99)00008-6 · Cited by 1,106 · see citing works
Giard, M. H., & Peronnet, F. (1999) · Journal of Cognitive Neuroscience · doi:10.1162/089892999563544 · Cited by 1,072 · see citing works
Fries, P., Nikolić, D., & Singer, W. (2007) · Trends in Neurosciences · doi:10.1016/j.tins.2007.05.005 · Cited by 1,044 · see citing works
The visual N1 component as an index of a discrimination process
Vogel, E. K., & Luck, S. J. (2000) · Psychophysiology · doi:10.1111/1469-8986.3720190 · Cited by 1,068 · 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
Error-backpropagation in temporally encoded networks of spiking neurons
Bohté, S. M., Kok, J. N., & Poutré, H. L. (2002) · Neurocomputing · doi:10.1016/s0925-2312(01)00658-0 · Cited by 1,024 · see citing works
Emotion and attention: event-related brain potential studies
Schupp, H. T., Flaisch, T., Stockburger, J., & Junghöfer, M. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)56002-9 · Cited by 1,032 · see citing works
Integrated model of visual processing
Bullier, J. (2001) · Brain Research Reviews · doi:10.1016/s0165-0173(01)00085-6 · Cited by 1,016 · see citing works
A hierarchy of temporal receptive windows in human cortex
Hasson, U., Yang, E., Vallines, I., Heeger, D. J., & Rubin, N. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.5487-07.2008 · Cited by 874 · see citing works
Untangling invariant object recognition
DiCarlo, J. J., & Cox, D. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.06.010 · Cited by 948 · see citing works
Neural mechanisms for the recognition of biological movements
Giese, M. A., & Poggio, T. (2003) · Nature Reviews Neuroscience · doi:10.1038/nrn1057 · Cited by 955 · see citing works
Peripheral vision and pattern recognition: A review
Strasburger, H., Rentschler, I., & Jüttner, M. (2011) · Journal of Vision · doi:10.1167/11.5.13 · Cited by 939 · see citing works
A feedforward architecture accounts for rapid categorization
Serre, T., Oliva, A., & Poggio, T. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0700622104 · Cited by 918 · see citing works
The bilingual adaptation: How minds accommodate experience
Bialystok, E. (2017) · Psychological Bulletin · doi:10.1037/bul0000099 · Cited by 906 · see citing works
A cortical mechanism for triggering top-down facilitation in visual object recognition
Bar, M. (2003) · Journal of Cognitive Neuroscience · doi:10.1162/089892903321662976 · Cited by 900 · see citing works
The functional architecture of the ventral temporal cortex and its role in categorization
Kalanit Grill-spector, A., & Weiner, K. S. (2014) · Nature reviews. Neuroscience · doi:10.1038/nrn3747 · Cited by 845 · see citing works
Cadieu, C. F., Hong, H., Yamins, D. L. K., Pinto, N., Ardila, D., Solomon, E. A., Majaj, N. J., & DiCarlo, J. J. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003963 · Cited by 824 · see citing works
Rapid natural scene categorization in the near absence of attention
Fei-Fei, L., Rufin Vanrullen, A., Christof Koch, A., & Perona, P. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.092277599 · Cited by 833 · see citing works
Resolving human object recognition in space and time
Cichy, R. M., Pantazis, D., & Oliva, A. (2014) · Nature Neuroscience · doi:10.1038/nn.3635 · Cited by 832 · see citing works
Eye Smarter than Scientists Believed: Neural Computations in Circuits of the Retina
Gollisch, T., & Meister, M. (2010) · Neuron · doi:10.1016/j.neuron.2009.12.009 · Cited by 795 · see citing works
Konishi, S., Nakajima, K., Uchida, I., Kikyo, H., Kameyama, M., & Miyashita, Y. (1999) · Brain · doi:10.1093/brain/122.5.981 · Cited by 823 · see citing works
Cichy, R. M., Khosla, A., Pantazis, D., Torralba, A., & Oliva, A. (2016) · Scientific Reports · doi:10.1038/srep27755 · Cited by 716 · see citing works
Statistics of natural image categories
Torralba, A. B., & Oliva, A. (2003) · Network Computation in Neural Systems · doi:10.1088/0954-898x_14_3_302 · Cited by 845 · see citing works
STDP-based spiking deep convolutional neural networks for object recognition
Kheradpisheh, S. R., Ganjtabesh, ., Thorpe, S. J., & Masquelier, T. (2017) · Neural Networks · doi:10.1016/j.neunet.2017.12.005 · Cited by 772 · see citing works
Self-citationDeep Learning With Spiking Neurons: Opportunities and Challenges
Pfeiffer, M., & Pfeil, T. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00774 · Cited by 765 · see citing works
The Spatial and Temporal Signatures of Word Production Components: A Critical Update
Indefrey, P. (2011) · Frontiers in Psychology · doi:10.3389/fpsyg.2011.00255 · Cited by 767 · see citing works
Spike-based strategies for rapid processing
Thorpe, S. J., Delorme, A., & Rullen, R. V. (2001) · Neural Networks · doi:10.1016/s0893-6080(01)00083-1 · Cited by 740 · see citing works
Self-citationStatistically optimal perception and learning: from behavior to neural representations
Fiser, J., Berkes, P., Orbán, G., & Lengyel, M. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.003 · Cited by 672 · see citing works
Synchronization of neural activity across cortical areas correlates with conscious perception
Melloni, L., Molina, C., Pena, M., Torres, D., Singer, W., & Rodriguez, E. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.4623-06.2007 · Cited by 716 · see citing works
The Time Course of Visual Processing: From Early Perception to Decision-Making
Rufin Vanrullen, A., & Thorpe, S. J. (2001) · Journal of Cognitive Neuroscience · doi:10.1162/08989290152001880 · Cited by 703 · see citing works
Self-citationGuided Search 6.0: an updated model of visual search
Wolfe, J. M. (2021) · Psychonomic Bulletin & Review · doi:10.3758/s13423-020-01859-9 · Cited by 703 · see citing works
Stages of processing in face perception: an MEG study
Jia Liu, B., Harris, A. M., & Kanwisher, N. (2002) · Nature Neuroscience · doi:10.1038/nn909 · Cited by 683 · see citing works
Brain mechanisms for emotional influences on perception and attention: What is magic and what is not
Pourtois, G., Schettino, A., & Vuilleumier, P. (2013) · Biological Psychology · doi:10.1016/j.biopsycho.2012.02.007 · Cited by 687 · see citing works
Rapid perceptual integration of facial expression and emotional body language
Meeren, H. K. M., van Heijnsbergen, C. C. R. J., & de Gelder, B. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507650102 · Cited by 678 · see citing works
Face Recognition by Humans: Nineteen Results All Computer Vision Researchers Should Know About
Sinha, P., Balas, B., Ostrovsky, Y., & Russell, R. (2006) · Proceedings of the IEEE · doi:10.1109/jproc.2006.884093 · Cited by 674 · see citing works
The Restless Engram: Consolidations Never End
Dudai, Y. (2012) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062111-150500 · Cited by 644 · see citing works
Electrophysiological Correlates of Rapid Spatial Orienting Towards Fearful Faces
Pourtois, G. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh023 · Cited by 655 · see citing works
Brain basis of human social interaction: from concepts to brain imaging
Hari, R., & Kujala, M. V. (2009) · Physiological Reviews · doi:10.1152/physrev.00041.2007 · Cited by 638 · see citing works
Rapid Neural Coding in the Retina with Relative Spike Latencies
Gollisch, T., & Meister, M. (2008) · Science · doi:10.1126/science.1149639 · Cited by 663 · see citing works
Riesenhuber, M., & Poggio, T. (2000) · Nature Neuroscience · doi:10.1038/81479 · Cited by 658 · see citing works
Embedded Devices for Neuromorphic Time-Series Assessment
Mazumder, A. N., Hosseini, M., & Mohsenin, T. (2022) · Research Explorer (The University of Manchester) · doi:10.13016/m2ksy0-wxr3 · Cited by 662 · see citing works
Ultra-rapid object detection with saccadic eye movements: Visual processing speed revisited
Kirchner, H., & Thorpe, S. J. (2005) · Vision Research · doi:10.1016/j.visres.2005.10.002 · Cited by 622 · see citing works
Self-citationFeedforward, horizontal, and feedback processing in the visual cortex
Lamme, V. A. F., Supèr, H., & Spekreijse, H. (1998) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(98)80042-1 · Cited by 624 · see citing works
Modeling the influence of task on attention
Navalpakkam, V., & Itti, L. (2004) · Vision Research · doi:10.1016/j.visres.2004.07.042 · Cited by 628 · see citing works
<i>The Neural Correlates of Consciousness</i>: <i>An Update</i>
Tononi, G., & Koch, C. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.004 · Cited by 627 · see citing works
Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program
Tetko, I. V., & Tanchuk, V. Y. (2002) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci025515j · Cited by 618 · see citing works
Shadlen, M. N., & Movshon, J. A. (1999) · Neuron · doi:10.1016/s0896-6273(00)80822-3 · Cited by 606 · see citing works
The attentional blink: A review of data and theory
Dux, P. E., & Marois, R. (2009) · Attention Perception & Psychophysics · doi:10.3758/app.71.8.1683 · Cited by 590 · see citing works
Rossion, B., & Jacques, C. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.011 · Cited by 582 · see citing works
The dynamics of object-selective activation correlate with recognition performance in humans
Kalanit Grill-spector, A., Kushnir, T., Hendler, T., & Malach, R. (2000) · Nature Neuroscience · doi:10.1038/77754 · Cited by 579 · see citing works
Recipes for the linear analysis of EEG
Parra, L. C., Spence, C. D., Gerson, A. D., & Sajda, P. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.05.032 · Cited by 570 · see citing works
Computational Neuroscience of Vision
Rolls, E. T., & Deco, G. (2001) · doi:10.1093/acprof:oso/9780198524885.001.0001 · Cited by 551 · see citing works
Unsupervised Learning of Visual Features through Spike Timing Dependent Plasticity
Masquelier, T., & Thorpe, S. J. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030031 · Cited by 549 · see citing works
Self-citationStimulus Dependence of Neuronal Correlation in Primary Visual Cortex of the Macaque
Kohn, A., & Smith, M. A. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.5106-04.2005 · Cited by 521 · see citing works
The Temporal Correlation Hypothesis of Visual Feature Integration
Gray, C. M. (1999) · Neuron · doi:10.1016/s0896-6273(00)80820-x · Cited by 541 · see citing works
Kalanit Grill-spector, A., & Kanwisher, N. (2005) · Psychological Science · doi:10.1111/j.0956-7976.2005.00796.x · Cited by 541 · see citing works
CIFAR10-DVS: An Event-Stream Dataset for Object Classification
Li, H., Liu, H., Ji, X., Li, G., & Shi, L. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00309 · Cited by 541 · see citing works
Grossberg, S. (2012) · Neural Networks · doi:10.1016/j.neunet.2012.09.017 · Cited by 542 · see citing works
Bilingual language control: an event-related brain potential study.
Christoffels, I., Firk, C., & Schiller, N. (2007) · Brain Research · doi:10.1016/j.brainres.2007.01.137 · Cited by 509 · see citing works
Rapid Biologically-Inspired Scene Classification Using Features Shared with Visual Attention
Siagian, C., & Itti, L. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.40 · Cited by 526 · see citing works
Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior
Bair, W., Zohary, E., & Newsome, W. T. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-05-01676.2001 · Cited by 515 · see citing works
Kiani, R., Esteky, H., Mirpour, K., & Tanaka, K. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00024.2007 · Cited by 495 · see citing works
SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks
Zenke, F., & Ganguli, S. (2018) · Neural Computation · doi:10.1162/neco_a_01086 · Cited by 533 · see citing works
Image Parsing: Unifying Segmentation, Detection, and Recognition
Zhuowen Tu, A., Chen, X.-R., Yuille, A., & Zhu, S. C. (2005) · International Journal of Computer Vision · doi:10.1007/s11263-005-6642-x · Cited by 498 · see citing works
Kar, K., Kubilius, J., Schmidt, K., Issa, E. B., & DiCarlo, J. J. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0392-5 · Cited by 496 · see citing works
von der Malsburg, C. (1999) · Neuron · doi:10.1016/s0896-6273(00)80825-9 · Cited by 501 · see citing works
Detecting meaning in RSVP at 13 ms per picture
Potter, M. C., Wyble, B., Hagmann, C. E., & McCourt, E. S. (2013) · Attention Perception & Psychophysics · doi:10.3758/s13414-013-0605-z · Cited by 494 · see citing works
What Does Classifying More Than 10,000 Image Categories Tell Us?
Deng, J., Berg, A. C., Li, K., & Fei-Fei, L. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15555-0_6 · Cited by 487 · see citing works
Greene, M. R., & Oliva, A. (2009) · Psychological Science · doi:10.1111/j.1467-9280.2009.02316.x · Cited by 483 · see citing works
Rate Coding Versus Temporal Order Coding: What the Retinal Ganglion Cells Tell the Visual Cortex
Rullen, R. V., & Thorpe, S. J. (2001) · Neural Computation · doi:10.1162/08997660152002852 · Cited by 493 · see citing works
Self-citationGREENE, M., & OLIVA, A. (2009) · Cognitive Psychology · doi:10.1016/j.cogpsych.2008.06.001 · Cited by 467 · see citing works
Eye movements are functional during face learning
Henderson, J. M., Williams, C. C., & Falk, R. J. (2005) · Memory & Cognition · doi:10.3758/bf03195300 · Cited by 484 · see citing works
- Authors
- Thorpe, S., Fize, D., & Marlot, C.
- Affiliations
- Centre de recherche cerveau et cognition (FR)
- ORCID
- Thorpe, Simon
- Venue
- Nature
- Published
- 1996-06
- Volume
- 381
- Issue
- 6582
- Pages
- 520-522
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2091845343
- Cited by
- 3,538
- References
- 0
- Citations by year
- 2026: 97 · 2025: 121 · 2024: 127 · 2023: 116 · 2022: 117 · 2021: 149 · 2020: 147 · 2019: 151 · 2018: 172 · 2017: 165 · 2016: 143 · 2015: 155 · 2014: 169 · 2013: 157 · 2012: 174
- FWCI
- 20.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- visual processing speed, event-related potentials, go/no-go task, frontal negativity, object classification, natural scene recognition, reaction time
- MeSH terms
- Adult, Evoked Potentials, Visual, Female, Humans, Male, Middle Aged, Reaction Time, Vision, Ocular
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