Prediction suppression in monkey inferotemporal cortex depends on the conditional probability between images
Open accessAbstract
When monkeys view two images in fixed sequence repeatedly over days and weeks, neurons in area TE of the inferotemporal cortex come to exhibit prediction suppression. The trailing image elicits only a weak response when presented following the leading image that preceded it during training. Induction of prediction suppression might depend either on the contiguity of the images, as determined by their co-occurrence and captured in the measure of joint probability P( A, B), or on their contingency, as determined by their correlation and as captured in the measures of conditional probability P( A| B) and P( B| A). To distinguish between these possibilities, we measured prediction suppression after imposing training regimens that held P( A, B) constant but varied P( A| B) and P( B| A). We found that reducing either P( A| B) or P( B| A) during training attenuated prediction suppression as measured during subsequent testing. We conclude that prediction suppression depends on contingency, as embodied in the predictive relations between the images, and not just on contiguity, as embodied in their co-occurrence.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
A series of single- and multiunit recording studies have reported evidence of ES in macaque IT neurons.
“A series of single‐ and multiunit recording studies have also reported evidence of ES in macaque IT neurons. 85 , 88 , 89 , 90 , 91 , 92”
From Evaluating the neurophysiological evidence for predictive processing as a model of perception (2020) · cites this paper as [85]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Statistical learning by 8-month-old infants
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996) · Science · doi:10.1126/science.274.5294.1926 · Cited by 5,659 · see citing works
A theory of cortical responses.
Friston, K. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1622 · Cited by 4,578 · see citing works
Pearce, J. M., & Hall, G. (1980) · Psychological Review · doi:10.1037/0033-295x.87.6.532 · Cited by 3,023 · see citing works
Punishment and aversive behavior
Campbell, B. A., & Church, R. M. (1969) · Appleton-Century-Crofts eBooks · Cited by 2,000 · see citing works
Neuronal Coding of Prediction Errors
Schultz, W., & Dickinson, A. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.473 · Cited by 1,427 · see citing works
Computation of conditional probability statistics by 8-month-old infants
Aslin, R. N., Saffran, J. R., & Newport, E. L. (1998) · Psychological Science · doi:10.1111/1467-9280.00063 · Cited by 1,189 · see citing works
Visual statistical learning in infancy: evidence for a domain general learning mechanism
Kirkham, N. Z., Slemmer, J. A., & Johnson, S. P. (2002) · Cognition · doi:10.1016/s0010-0277(02)00004-5 · Cited by 1,072 · see citing works
Probability of shock in the presence and absence of cs in fear conditioning.
Rescorla, R. A. (1968) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0025984 · Cited by 1,067 · see citing works
Hawkins, J., & Blakeslee, S. (2004) · Cited by 1,012 · 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
The Automaticity of Visual Statistical Learning.
Turk‐Browne, N. B., Junge, J. A., & Scholl, B. J. (2005) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.134.4.552 · Cited by 817 · see citing works
Unsupervised Statistical Learning of Higher-Order Spatial Structures from Visual Scenes
Fiser, J., & Aslin, R. Ν. (2001) · Psychological Science · doi:10.1111/1467-9280.00392 · Cited by 806 · see citing works
Statistical learning of higher-order temporal structure from visual shape sequences.
Fiser, J., & Aslin, R. (2002) · Journal of Experimental Psychology. Learning, Memory and Cognition · doi:10.1037//0278-7393.28.3.458 · Cited by 641 · see citing works
The Neocortex of Macaca mulatta
Romanes, G. (1948) · JAMA · doi:10.1001/jama.1948.02890460089032 · Cited by 551 · see citing works
Storing covariance with nonlinearly interacting neurons
Sejnowski, T. J. (1977) · Journal of Mathematical Biology · doi:10.1007/bf00275079 · Cited by 546 · see citing works
A neuronal model of predictive coding accounting for the mismatch negativity.
Wacongne, C., Changeux, J.-P., & Dehaene, S. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.5003-11.2012 · Cited by 542 · see citing works
Statistical learning and language acquisition
Romberg, A. R., & Saffran, J. R. (2010) · WIREs Cognitive Science · doi:10.1002/wcs.78 · Cited by 517 · see citing works
How prediction errors shape perception, attention, and motivation
den Ouden, H. E. M., Kok, P., & de Lange, F. P. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00548 · Cited by 512 · see citing works
Statistical learning of higher-order temporal structure from visual shape sequences.
Fiser, J., & Aslin, R. Ν. (2002) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.28.3.458 · Cited by 505 · see citing works
Statistical Learning in a Natural Language by 8-Month-Old Infants
Pelucchi, B., Hay, J. F., & Saffran, J. R. (2009) · Child Development · doi:10.1111/j.1467-8624.2009.01290.x · Cited by 476 · see citing works
Associative long-term depression in the hippocampus induced by hebbian covariance
Stanton, P. K., & B, T. J. S. A. (1989) · Nature · doi:10.1038/339215a0 · Cited by 461 · see citing works
Bayesian theories of conditioning in a changing world
Courville, A. C., Daw, N. D., & Touretzky, D. S. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.05.004 · Cited by 457 · see citing works
Statistical learning of visual transitions in monkey inferotemporal cortex
Meyer, T., & Olson, C. R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1112895108 · Cited by 325 · see citing works
Self-citationVisual statistical learning in the newborn infant
Bulf, H., Johnson, S. P., & Valenza, E. (2011) · Cognition · doi:10.1016/j.cognition.2011.06.010 · Cited by 281 · see citing works
Testing assumptions of statistical learning: Is it long-term and implicit?
Kim, R. S., Seitz, A. R., Feenstra, H., & Shams, L. B. (2009) · Neuroscience Letters · doi:10.1016/j.neulet.2009.06.030 · Cited by 256 · see citing works
Learned spatiotemporal sequence recognition and prediction in primary visual cortex
Gavornik, J. P., & Bear, M. F. (2014) · Nature Neuroscience · doi:10.1038/nn.3683 · Cited by 227 · see citing works
Multidimensional visual statistical learning.
Turk‐Browne, N. B., Isola, P., Scholl, B. J., & Treat, T. A. (2008) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.34.2.399 · Cited by 163 · see citing works
SUZUKI, W. A., & Naya, Y. (2014) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071013-014207 · Cited by 155 · see citing works
Predictions: a universal principle in the operation of the human brain
Bar, M. (2009) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2008.0321 · Cited by 139 · see citing works
Fear conditioning and LTP in the lateral amygdala are sensitive to the same stimulus contingencies
Bauer, E. P., LeDoux, J. E., & Nader, K. (2001) · Nature Neuroscience · doi:10.1038/89465 · Cited by 112 · see citing works
Christofi, G., Nowicky, A. V., Bolsover, S. R., & Bindman, L. J. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.69.1.219 · Cited by 87 · see citing works
Howard, J. H., Howard, D. V., Dennis, N. A., & Kelly, A. J. (2008) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0012797 · Cited by 80 · see citing works
Statistical Learning of Serial Visual Transitions by Neurons in Monkey Inferotemporal Cortex
Meyer, T., Ramachandran, S., & Olson, C. R. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1215-14.2014 · Cited by 70 · see citing works
Self-citationNovelty Enhances Visual Salience Independently of Reward in the Parietal Lobe
Foley, N. C., Jangraw, D. C., Peck, C., & Gottlieb, J. P. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4171-13.2014 · Cited by 63 · see citing works
Pockett, S., Brookes, N. H., & Bindman, L. J. (1990) · Experimental Brain Research · doi:10.1007/bf00228861 · Cited by 62 · see citing works
Bermúdez, M. A., & Schultz, W. (2009) · Journal of Neurophysiology · doi:10.1152/jn.00933.2009 · Cited by 56 · see citing works
Paulsen, O., Li, Y.-G., Hvalby, Ø., Andersen, P., & Bliss, T. (1993) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.1993.tb00909.x · Cited by 32 · see citing works
Kerr, D. S., & Abraham, W. C. (1993) · Synapse · doi:10.1002/syn.890140408 · Cited by 30 · see citing works
Buonomano, D. V., & Merzenich, M. M. (1996) · Journal of Neurophysiology · doi:10.1152/jn.1996.76.1.631 · Cited by 19 · see citing works
Statistical learning of action: The role of conditional probability
Meyer, M., & Baldwin, D. A. (2011) · Learning & Behavior · doi:10.3758/s13420-011-0033-7 · Cited by 15 · see citing works
The role of contextual associations in producing the partial reinforcement acquisition deficit.
Míguez, G., Witnauer, J. E., & Miller, R. R. (2011) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0024410 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [35]35. Sejnowski TJ, Chattarji S, Stanton P. Induction of synaptic plasticity by Hebbian covariance in the hippocampus. In: The Computing Neuron, edited by Durbin R, Miall C, Mitchison G. Wokingham, UK: Addison-Wesley, 1989, p. 105-124.
Cited by
Sorted by citations
Evaluating the neurophysiological evidence for predictive processing as a model of perception
Walsh, K. S., McGovern, D. P., Clark, A., & O'Connell, R. G. (2020) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14321 · Cited by 333 · see citing works
Suppressed Sensory Response to Predictable Object Stimuli throughout the Ventral Visual Stream
Richter, D., Ekman, M., & de Lange, F. P. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.3421-17.2018 · Cited by 150 · see citing works
Human Inferences about Sequences: A Minimal Transition Probability Model
Meyniel, F., Maheu, M., & Dehaene, S. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005260 · Cited by 137 · see citing works
Kremláček, J., Kreegipuu, K., Tales, A., Astikainen, P., Põldver, N., Näätänen, R., & Stefanics, G. (2016) · Cortex · doi:10.1016/j.cortex.2016.03.017 · Cited by 138 · see citing works
Encoding of Stimulus Probability in Macaque Inferior Temporal Cortex
Bell, A. H., Summerfield, C., Morin, E. L., Malecek, N. J., & Ungerleider, L. G. (2016) · Current Biology · doi:10.1016/j.cub.2016.07.007 · Cited by 118 · see citing works
Statistical Learning Signals in Macaque Inferior Temporal Cortex
Kaposvari, P., Kumar, S., & Vogels, R. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhw374 · Cited by 91 · see citing works
Brain signatures of a multiscale process of sequence learning in humans
Maheu, M., Dehaene, S., & Meyniel, F. (2019) · eLife · doi:10.7554/elife.41541 · Cited by 98 · see citing works
Encoding of predictable and unpredictable stimuli by inferior temporal cortical neurons
Kumar, S., Kaposvari, P., & Vogels, R. (2017) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01135 · Cited by 75 · see citing works
Evaluating the evidence for expectation suppression in the visual system
Feuerriegel, D., Vogels, R., & Kovács, G. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.04.002 · Cited by 81 · see citing works
The empirical status of predictive coding and active inference
Hodson, R., Mehta, M., & Smith, R. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105473 · Cited by 69 · see citing works
A common probabilistic framework for perceptual and statistical learning
Fiser, J., & Lengyel, G. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.09.007 · Cited by 44 · see citing works
Feuerriegel, D., Churches, O. F., Coussens, S. W., & Keage, H. A. D. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.029 · Cited by 38 · see citing works
Repetition suppression to objects is modulated by stimulus-specific expectations
Utzerath, C., St. John-Saaltink, E., Buitelaar, J., & de Lange, F. P. (2017) · Scientific Reports · doi:10.1038/s41598-017-09374-z · Cited by 28 · see citing works
Prediction suppression and surprise enhancement in monkey inferotemporal cortex
Ramachandran, S., Meyer, T., & Olson, C. R. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00136.2017 · Cited by 29 · see citing works
Self-citationHigh-level visual prediction errors in early visual cortex
Richter, D., Kietzmann, T. C., & de Lange, F. P. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002829 · Cited by 28 · see citing works
Surprise and recency in novelty detection in the primate brain
Zhang, K., Bromberg-Martin, E. S., Sogukpinar, F., Kocher, K., & Monosov, I. E. (2022) · Current Biology · doi:10.1016/j.cub.2022.03.064 · Cited by 27 · see citing works
Predictable tones elicit stimulus-specific suppression of evoked activity in auditory cortex
Han, B., Mostert, P., & de Lange, F. P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.06.033 · Cited by 23 · see citing works
Statistical Learning Signals for Complex Visual Images in Macaque Early Visual Cortex
Vergnieux, V., & Vogels, R. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00789 · Cited by 16 · see citing works
Inferior temporal cortex leads prefrontal cortex in response to a violation of a learned sequence
Esmailpour, H., Raman, R., & Vogels, R. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac265 · Cited by 15 · see citing works
Beukema, P., & Verstynen, T. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.11.014 · Cited by 15 · see citing works
Hierarchical interactions between sensory cortices defy predictive coding
Westerberg, J. A., & Roelfsema, P. R. (2025) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2025.09.018 · Cited by 15 · see citing works
Computational components of visual predictive coding circuitry
Shipp, S. D. (2024) · Frontiers in Neural Circuits · doi:10.3389/fncir.2023.1254009 · Cited by 11 · see citing works
Expectation Suppression Dampens Sensory Representations of Predicted Stimuli
Walsh, K. S., & McGovern, D. P. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.2133-18.2018 · Cited by 10 · see citing works
Psychiatric and Neurological Disorders
Catrambone, V., & Valenza, G. (2021) · Functional Brain-Heart Interplay · doi:10.1007/978-3-030-79934-2_5 · Cited by 4 · see citing works
Traveling waves shape neural population dynamics enabling predictions and internal model updatingPreprint
Mohanta, S., Cleveland, D., Afrasiabi, M., Rhone, A. E., Górska, U., Borkenhagen, M. J. C., Sanders, R. D., Boly, M., Nourski, K. V., & Saalmann, Y. B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.09.574848 · Cited by 6 · see citing works
Recent Visual Experience Reshapes V4 Neuronal Activity and Improves Perceptual Performance
Stan, P. L., & Smith, M. A. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.1764-23.2024 · Cited by 6 · see citing works
Rethinking Predictive Processing
Furutachi, S., & Hofer, S. B. (2026) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-102124-031410 · Cited by 3 · see citing works
Perceptual Expectations Are Reflected by Early Alpha Power Reduction
Sáringer, S., Fehér, Á., Sáry, G., & Kaposvári, P. (2024) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02169 · Cited by 2 · see citing works
Expectation dynamically modulates the representational time course of objects and locations
Moore, M. J., Robinson, A. K., & Mattingley, J. B. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.999 · Cited by 3 · see citing works
Feature-specific predictive processing: What’s in a prediction error?
Richter, D., Uran, C., Vinck, M. A., & de Lange, F. P. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.1061 · Cited by 2 · see citing works
Adaptation of the inferior temporal neurons and efficient visual processing
Yamane, Y. (2024) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2024.1398874 · Cited by 2 · see citing works
Cortical and behavioral signatures of response binding during sequential skill learning
Beukema, P. (2018) · D-Scholarship@Pitt (University of Pittsburgh)
Location-specific deviant responses to object sequences in macaque inferior temporal cortex
Esmailpour, H., & Vogels, R. (2024) · Scientific Reports · doi:10.1038/s41598-024-54298-0
Neurons of Macaque Frontal Eye Field Signal Reward-Related Surprise
Shteyn, M. R., & Olson, C. R. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.0441-24.2024
Self-citationForward and backward prediction in learning and perception
de Lange, F. P., & Press, C. (2025) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2025.103144
What type of relationship is learned during visual statistical learning?
Nazlı, İ., & de Lange, F. P. (2026) · PLoS ONE · doi:10.1371/journal.pone.0342272
Perceiving regularity in sequences : behavioural, neural and computational signatures
Maheu, M. (2019) · theses.fr (ABES) · doi:10.70675/613538edz4e03z4a21za592z9859bfee3cff
Priming of probabilistic attentional templates II: Evidence from neuroscience
Kristjansson, A. K., & Tanrıkulu, Ö. D. (2026) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2026.101262
- Authors
- Ramachandran, S., Meyer, T., & Olson, C. R.
- Affiliations
- Center for the Neural Basis of Cognition (US)
- University of Pittsburgh (US)
- Corresponding author
- Ramachandran, Suchitra
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2016-01-01
- Volume
- 115
- Issue
- 1
- Pages
- 355-362
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- PMC
- PMC4760508
- OpenAlex
- W2264903079
- Cited by
- 38
- References
- 40
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 8 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 4 · 2018: 3 · 2017: 5 · 2016: 4
- FWCI
- 2.41
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Neurophysiology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | National Institutes of Health (NIH) (NIHRO1EY018620, NIHRO1EY024912, NIH K08 MH080329, NIHP30EY008098, NIHP50MH103204)
- Pennsylvania Department of Health (PDH) (P41RR03631)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- inferotemporal cortex, conditional probability, contingency, visual object recognition, neural prediction, co-occurrence, monkey visual cortex
- MeSH terms
- Action Potentials, Animals, Female, Macaca mulatta, Male, Models, Neurological, Neurons, Photic Stimulation, Probability, Temporal Lobe, Visual Perception
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
