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Decoding Sound and Imagery Content in Early Visual Cortex
Open accessAbstract
Human early visual cortex was traditionally thought to process simple visual features such as orientation, contrast, and spatial frequency via feedforward input from the lateral geniculate nucleus (e.g., [1]). However, the role of nonretinal influence on early visual cortex is so far insufficiently investigated despite much evidence that feedback connections greatly outnumber feedforward connections [2-5]. Here, we explored in five fMRI experiments how information originating from audition and imagery affects the brain activity patterns in early visual cortex in the absence of any feedforward visual stimulation. We show that category-specific information from both complex natural sounds and imagery can be read out from early visual cortex activity in blindfolded participants. The coding of nonretinal information in the activity patterns of early visual cortex is common across actual auditory perception and imagery and may be mediated by higher-level multisensory areas. Furthermore, this coding is robust to mild manipulations of attention and working memory but affected by orthogonal, cognitively demanding visuospatial processing. Crucially, the information fed down to early visual cortex is category specific and generalizes to sound exemplars of the same category, providing evidence for abstract information feedback rather than precise pictorial feedback. Our results suggest that early visual cortex receives nonretinal input from other brain areas when it is generated by auditory perception and/or imagery, and this input carries common abstract information. Our findings are compatible with feedback of predictive information to the earliest visual input level (e.g., [6]), in line with predictive coding models [7-10].
Overview
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Written from the paper’s full text.
TL;DR
Using fMRI and multivariate pattern analysis in blindfolded participants, this paper shows that category-specific information from natural sounds and auditory imagery can be decoded from early visual cortex activity without feedforward visual stimulation. The feedback appears abstract/categorical rather than pictorial, is robust to mild attention/working-memory interference, and is disrupted by demanding visuospatial processing.
Key findings
- In experiment 1, a linear SVM discriminated three natural sounds (bird singing, traffic noise, talking crowd) from early visual cortex, particularly V2 and V3, at about 42%; classification also succeeded in auditory cortex but not motor cortex.
- In experiment 2, imagined sounds were decoded from V1 and auditory cortex, and cross-classification between sound perception and imagery succeeded in V1 and V2, indicating shared activity patterns across real and imagined sounds.
- In experiment 3, decoding during natural sound stimulation remained successful mainly in peripheral regions and consistently in V2 despite an orthogonal auditory working-memory task; in experiment 4, a demanding visuospatial imagery task left only residual above-chance classification in far-peripheral V2.
- In experiment 5, “human” versus “inanimate” sound categories were classified in several early visual areas for eight out of nine exemplar combinations, and cross-classification across different exemplars within a category succeeded in V2 and V3 in two out of three combinations, supporting abstract/categorical feedback rather than precise pictorial reinstatement.
Methods
- Five fMRI experiments with blindfolded participants omitted visual stimulation while subjects listened to natural sounds, imagined sounds from word cues, or performed orthogonal cognitive tasks during sound stimulation.
- Activity patterns were extracted from retinotopically mapped V1, V2, and V3 and analyzed with multivariate pattern classification, primarily a linear support vector machine; whole-brain searchlight analyses identified other regions carrying sound/imagery content.
- Univariate GLM analyses tested whether decoding was driven by positive activation or deactivation; cross-classification tested generalization between perception and imagery and across sound exemplars within categories.
Limitations
- The paper states that classification accuracies were relatively low, describing the results as proof of principle and robust across subject and stimulus samples.
- The paper notes that without feedforward stimulation, it is difficult to study the functional role of nonretinal feedback in actual visual perception.
- The paper states that whether the proposed pathways play a causal role in inducing differential activity patterns remains to be investigated; the provided text also does not report exact sample sizes per experiment.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Crucially, cross-classification succeeded in V2 and V3 in two out of three combinations, i.e., training the classifier for the pair “traffic 1” versus “people 1” lead to successful classification of “traffic 2” versus “people 2,” and training the classifier for the pair “traffic 2” versus “people 2” lead to successful classification of “airplane” versus “kids” (Figure 3H; Table S1).”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Category Specificity of the Information Fed Back to Early Visual Cortex
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In the paper
“Cross-classification succeeded in V1 and V2 (Figure 2G).”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sound and Imagery Content in Early Visual Cortex
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In the paper
“In auditory cortex, cross-classification did not succeed, indicating that activity patterns induced by feedforward auditory stimulation are coded differently than those induced by feedback through auditory imagery.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sound and Imagery Content in Early Visual Cortex
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In the paper
“In experiments 3 and 4, the secondary tasks activated early visual areas consistent with an engagement of object attention.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Univariate Activation Profile
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In the paper
“In experiments 1 and 2, real and imagined sounds could be decoded in parts of the precuneus and in posterior superior temporal sulcus (pSTS) (see overlapping regions in Figure 4).”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Whole-Brain Searchlight Results
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In the paper
“Sounds and, to a lesser extent, imagined sounds were successfully classified in a network of frontal regions, including superior and middle frontal sulci.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Whole-Brain Searchlight Results
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Activity patterns during natural sound stimulation were again successfully decoded from early visual cortex, mainly in peripheral regions and consistently in V2 (Figures 3B and 3C). This demonstrates that simultaneous retention of orthogonal contents in working memory did not strongly affect classification.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sounds while Manipulating Cognitive Resources
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In the paper
“The classifier successfully discriminated the three different sounds in early visual cortex, particularly in V2 and V3 (at ∼42%; see Figure 2; for results with increased statistical power, see Figure S1A).”
- Also stated in: § Decoding of Sound and Imagery Content in Early Visual Cortex · plain
“Hence, activity patterns in early visual cortex contained sufficient information from auditory stimulation to allow the content-specific discrimination of natural sounds.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sound and Imagery Content in Early Visual Cortex
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The univariate activity profile also showed that classification was not driven by one sound eliciting more attention-related activity than another sound (Figure S3).”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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In the paper
“Unsurprisingly, sounds could be decoded in a large part of bilateral superior temporal sulcus mostly belonging to auditory cortex (Figure 4).”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Whole-Brain Searchlight Results
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- It may state two separate claims as one. 24
- The quote only partly states this claim. 1
- Probably not a substantial claim. 5
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Even at very liberal thresholds (p < 0.05 uncorrected; Figure S3), listening to sounds in the absence of visual stimulation elicited no positive activation in early visual areas but instead elicited a weak deactivation, consistent with previous findings (e.g.,[16]) and in contrast to classical findings for visual mental imagery [17, 18].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Univariate Activation Profile
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In the paper
“Successful discrimination of imagined sounds was observed in both foveal and peripheral areas of early visual cortex (but not far periphery), in V1 and auditory cortex (Figures 2E and 2F; classification of real sounds replicated the results of experiment 1, cf. Figure S1B).”
- Also stated in: § Decoding of Sound and Imagery Content in Early Visual Cortex · hedged
“Therefore, even in the absence of both visual and auditory stimulation, the contents of mental imagery could be decoded from both V1 and auditory cortex.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sound and Imagery Content in Early Visual Cortex
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- Also stated in: § Decoding of Sound and Imagery Content in Early Visual Cortex · hedged
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In the paper
“Imagery (experiment 2) elicited no positive activity but exhibited weak deactivations in both early visual and auditory cortices.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Univariate Activation Profile
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In the paper
“Although the classifier failed to discriminate the three natural sounds in most of early visual cortex, residual above-chance classification remained in the far periphery of V2 (Figures 3E and 3F) despite the orthogonal engagement of attentionally demanding active visuospatial processing.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sounds while Manipulating Cognitive Resources
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In the paper
“Moreover, higher visual areas project back to V1 the associated color of grayscale objects [36] or the predicted motion path of an apparent motion illusion [37, 38].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [36] Bannert, 2013, Decoding the yellow of a gray banana, Curr. Biol. source
- Not checked yetcites [37] Muckli, 2005, Primary visual cortex activity along the apparent-motion trace reflects illusory perception, PLoS Biol. source
- Not checked yetcites [38] Vetter, 2013, TMS over V5 disrupts motion prediction, Cereb. Cortex
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Our findings are compatible with feedback of predictive information to the earliest visual input level (e.g., [6]), in line with predictive coding models [7–10].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Abstract
What the sources say
- Not checked yetcites [6] Mumford, 1992, On the computational architecture of the neocortex. II. The role of cortico-cortical loops, Biol. Cybern. source
- Not checked yetcites [7] Friston, 2010, The free-energy principle: a unified brain theory?, Nat. Rev. Neurosci. source
- Not checked yetcites [8] Clark, 2013, Whatever next? Predictive brains, situated agents, and the future of cognitive science, Behav. Brain Sci. source
- Not checked yetcites [9] Bar, 2007, The proactive brain: using analogies and associations to generate predictions, Trends Cogn. Sci. source
- Not checked yetcites [10] Bastos, 2012, Canonical microcircuits for predictive coding, Neuron source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Crucially, the information fed down to early visual cortex is category specific and generalizes to sound exemplars of the same category, providing evidence for abstract information feedback rather than precise pictorial feedback.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, this coding is robust to mild manipulations of attention and working memory but affected by orthogonal, cognitively demanding visuospatial processing.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Abstract
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This demonstrates that both sounds and imagery cues induced similar activity patterns in early visual cortex and that feedback information is coded consistently across imagery and auditory perception.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Decoding of Sound and Imagery Content in Early Visual Cortex
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Note that despite relatively low classification accuracies, our series of experiments replicated the successful decoding of sounds in early visual areas several times, demonstrating proof of principle and the robustness of our results across different subject and stimulus samples.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the context of our findings, we suggest that the content-specific information from sounds, when they are heard and/or imagined, is relayed from auditory cortex to early visual cortex via pSTS and precuneus, eliciting differential activity patterns in both of these regions.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The coding of nonretinal information in the activity patterns of early visual cortex is common across actual auditory perception and imagery and may be mediated by higher-level multisensory areas.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our results suggest that early visual cortex receives nonretinal input from other brain areas when it is generated by auditory perception and/or imagery, and this input carries common abstract information.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“The precuneus has been identified as an area responding to both visual and auditory stimuli and possibly serving as an audiovisual convergence area [25].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [25] Hertz, 2010, Disentangling unisensory and multisensory components in audiovisual integration using a novel multifrequency fMRI spectral analysis, Neuroimage source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results of experiment 5 suggest that the information that is fed down to early visual cortex is not only content specific but also category specific, i.e., related to the information shared by sound exemplars of the same category.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The findings of experiment 5 furthermore demonstrate that the successful decoding in experiment 1 was not specific to the first sound exemplars we used and could not be caused by differential low-level acoustic features of the sounds (e.g., frequency distribution).”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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In the paper
“This suggests that information feedback is unlikely to be caused by an exact pictorial representation but instead contains abstract and possibly semantic information.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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In the paper
“Apart from the route via multisensory areas, there is evidence for multisensory integration on the subcortical level [27] and for direct anatomical connections between early auditory and early visual areas [12, 28, 29], mostly reaching peripheral regions [12–14], consistent with both our eccentricity and searchlight results.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [27] van den Brink, 2013, Subcortical, modality-specific pathways contribute to multisensory processing in humans, Cereb. Cortex
- Not checked yetcites [12] Eckert, 2008, A cross-modal system linking primary auditory and visual cortices: evidence from intrinsic fMRI connectivity analysis, Hum. Brain Mapp. source
- Not checked yetcites [28] Beer, 2013, Combined diffusion-weighted and functional magnetic resonance imaging reveals a temporal-occipital network involved in auditory-visual object processing, Front Integr Neurosci source
- Not checked yetcites [29] Beer, 2011, Diffusion tensor imaging shows white matter tracts between human auditory and visual cortex, Exp. Brain Res. source
- Not checked yetcites [13] Rockland, 2003, Multisensory convergence in calcarine visual areas in macaque monkey, Int. J. Psychophysiol. source
- Not checked yetcites [14] Cate, 2009, Auditory attention activates peripheral visual cortex, PLoS ONE source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This also means that our results were not caused by an unspecific attention effect or a simple reactivation of early visual cortex due to pictorial visual mental imagery.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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In the paper
“Our results demonstrate that the information arriving in early visual cortex is categorical and independent of its exact source.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
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In the paper
“For example, activity patterns in nonstimulated parts of early visual cortex contain content-specific information from the surrounding visual context [31, 32], from objects presented in the periphery [33], and from visual stimuli solely held in working memory rather than being actively perceived [34, 35].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [31] Smith, 2010, Nonstimulated early visual areas carry information about surrounding context, Proc. Natl. Acad. Sci. USA source
- Not checked yetcites [32] Ban, 2013, Topographic representation of an occluded object and the effects of spatiotemporal context in human early visual areas, J. Neurosci. source
- Not checked yetcites [33] Williams, 2008, Feedback of visual object information to foveal retinotopic cortex, Nat. Neurosci. source
- Not checked yetcites [34] Harrison, 2009, Decoding reveals the contents of visual working memory in early visual areas, Nature source
- Not checked yetcites [35] Albers, 2013, Shared representations for working memory and mental imagery in early visual cortex, Curr. Biol. source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Also, hippocampal projections to peripheral early visual regions have been demonstrated in the context of boundary extension for scene processing [30].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [30] Chadwick, 2013, The hippocampus extrapolates beyond the view in scenes: an fMRI study of boundary extension, Cortex source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“pSTS is implicated in audiovisual integration and has been shown to feed down information to primary visual and auditory cortices [26].”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [26] Naumer, 2011, Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools, Exp. Brain Res. source
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“That is, the information contained in these activity patterns is generalizable across different sound exemplars within a category, demonstrating that sounds trigger shared categorical information transfer to early visual cortex rather than a fine-grained pictorial representation.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Results > Category Specificity of the Information Fed Back to Early Visual Cortex
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In the paper
“In fact, previous accounts suggested that prediction and mental imagery may involve overlapping brain mechanisms [6, 43, 44], and mental imagery might have evolved from predictive brain mechanisms.”
§ Decoding Sound and Imagery Content in Early Visual Cortex > Discussion
What the sources say
- Not checked yetcites [6] Mumford, 1992, On the computational architecture of the neocortex. II. The role of cortico-cortical loops, Biol. Cybern. source
- Not checked yetcites [43] Maguire, 2013, The hippocampus: a manifesto for change, J. Exp. Psychol. Gen. source
- Not checked yetcites [44] Moulton, 2009, Imagining predictions: mental imagery as mental emulation, Philos. Trans. R. Soc. Lond. B Biol. Sci. source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper relies on this without support.
The word cues “forest,” “traffic,” and “people” reliably elicit the intended mental imagery of the corresponding sounds and natural scenes in subjects.
“Subjects were instructed to engage in mental imagery of the sounds and a corresponding natural scene.”
“runs in which subjects solely imagined the sounds upon hearing the word cues “forest,” “traffic,” or “people””
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In the citing paper
“Functional magnetic resonance imaging (fMRI) has shown that feedback from higher- to lower-level sensory cortices carries spatiotemporally precise and context-specific predictions (25–29).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [28]
Experimental — accuracy not yet measured
Citations
Cites
The free-energy principle: a unified brain theory?
Friston, K. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2787 · Cited by 8,120 · cited 3×
“, [6]), in line with predictive coding models [7–10].”
Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
Whatever next? Predictive brains, situated agents, and the future of cognitive science
Clark, A. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x12000477 · Cited by 5,924 · cited 2×
“, [6]), in line with predictive coding models [7–10].”
Canonical Microcircuits for Predictive Coding
Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.038 · Cited by 2,421 · cited 2×
“, [6]), in line with predictive coding models [7–10].”
Decoding reveals the contents of visual working memory in early visual areas
Harrison, S. A., & Tong, F. (2009) · Nature · doi:10.1038/nature07832 · Cited by 1,347
The proactive brain: using analogies and associations to generate predictions
Bar, M. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.05.005 · Cited by 1,144
On the computational architecture of the neocortex: II The role of cortico-cortical loops
Mumford, D. (1992) · Biological Cybernetics · doi:10.1007/bf00198477 · Cited by 1,074
On the computational architecture of the neocortex: I. The role of the thalamo-cortical loop
Mumford, D. (1991) · Biological Cybernetics · doi:10.1007/bf00202389 · Cited by 929
Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex
Markov, N. T., Vezoli, J., Chameau, P., Falchier, A., Quilodran, R., Huissoud, C., Lamy, C., Misery, P., Giroud, P., Ullman, S., et al. (2014) · Journal of Comparative Neurology · doi:10.1002/cne.23458 · Cited by 759
Corticocortical connections in the visual system: structure and function
Salin, P. A., & Bullier, J. (1995) · Physiological Reviews · doi:10.1152/physrev.1995.75.1.107 · Cited by 636
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Carruthers, P. (2024) · doi:10.1093/oso/9780198906131.001.0001 · Cited by 22
Scaling up visual attention and visual working memory to the real world
Brady, T. F., Störmer, V. S., Shafer-Skelton, A., Williams, J. R., Chapman, A. F., & Schill, H. M. (2019) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/bs.plm.2019.03.001 · Cited by 22
Shirzadi, S., Einalou, Z., & Dadgostar, M. (2020) · Optik · doi:10.1016/j.ijleo.2020.165347 · Cited by 20
Decoding category and familiarity information during visual imagery
Ragni, F., Lingnau, A., & Turella, L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118428 · Cited by 20
Libertus, M. E., Odic, D., Feigenson, L., & Halberda, J. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02085 · Cited by 20
Cellular psychology: relating cognition to context-sensitive pyramidal cells
Phillips, W. A., Bachmann, T., Spratling, M. W., Muckli, L., Petro, L. S., & Zolnik, T. (2025) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.09.002 · Cited by 18
Self-citationNeuroplasticity and crossmodal connectivity in the normal, healthy brain.
Karim, A. K. M. R., Proulx, M. J., de Sousa, A. A., & Likova, L. T. (2021) · Psychology & Neuroscience · doi:10.1037/pne0000258 · Cited by 20
A common neural code for representing imagined and inferred tastes
Avery, J. A., Carrington, M., & Martin, A. D. (2022) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2023.102423 · Cited by 19
Shiohama, T., McDavid, J., Levman, J. E. D., & Takahashi, E. (2019) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2019.05.009 · Cited by 18
The cognitive penetrability of perception: A blocked debate and a tentative solution
Cermeño-Aínsa, S. (2019) · Consciousness and Cognition · doi:10.1016/j.concog.2019.102838 · Cited by 21
Schindler, A., & Bartels, A. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw136 · Cited by 18
Melodic sound enhances visual awareness of congruent musical notes, but only if you can read music
Lee, M., Blake, R., Kim, S., & Kim, C.-Y. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509529112 · Cited by 18
de Borst, A. W., Valente, G., Jääskeläinen, I. P., & Tikka, P. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.043 · Cited by 17
de Borst, A. W., & de Gelder, B. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy151 · Cited by 18
Jung, Y., & Walther, D. B. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2816-20.2021 · Cited by 16
V1 as an egocentric cognitive map
Linton, P. (2021) · Neuroscience of Consciousness · doi:10.1093/nc/niab017 · Cited by 18
Auditory and Semantic Cues Facilitate Decoding of Visual Object Category in MEG
Brandman, T., Avancini, C., Leticevscaia, O., & Peelen, M. V. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz110 · Cited by 15
Testing the generalization of neural representations
Sandhaeger, F., & Siegel, M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120258 · Cited by 13
Chebat, D., Heimler, B., Hofsetter, S., & Amedi, A. (2018) · Contemporary clinical neuroscience · doi:10.1007/978-3-319-78926-2_13 · Cited by 15
A possible key role of vision in the development of schizophrenia
Császár, N., Kapócs, G., & Bókkon, I. (2018) · Reviews in the Neurosciences · doi:10.1515/revneuro-2018-0022 · Cited by 18
Wang, M., Hou, Y., Magrou, L., Autio, J. A., Misery, P., Coalson, T., Reid, E., Xu, Y., Lamy, C., Falchier, A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.27.489651 · Cited by 18
Calibrating vision: Concepts and questions
Bosten, J. M., Coen-Cagli, R., Franklin, A., Solomon, S. G., & Webster, M. A. (2022) · Vision Research · doi:10.1016/j.visres.2022.108131 · Cited by 13
Gu, J., Liu, B., Li, X., Wang, P., & Wang, B. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00135-2 · Cited by 13
Minimal theory of 3D vision: New approach to visual scale and visual shape.
Linton, P. (2023) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0455 · Cited by 13
The Cooperative Neuron: Cellular Foundations of Mental Life
Phillips, W. A. (2023) · doi:10.1093/oso/9780198876984.001.0001 · Cited by 13
Császár, N., Scholkmann, F., Salari, V., Szőke, H., & Bókkon, I. (2015) · Reviews in the Neurosciences · doi:10.1515/revneuro-2015-0039 · Cited by 14
Neuroimaging results suggest the role of prediction in cross-domain priming
Amado, C., Kovács, P., Mayer, R., Ambrus, G. G., Trapp, S., & Kovács, G. (2018) · Scientific Reports · doi:10.1038/s41598-018-28696-0 · Cited by 17
Multisensory representations of space and time in sensory cortices
Gori, M., Bertonati, G., Campus, C., & Amadeo, M. B. (2022) · Human Brain Mapping · doi:10.1002/hbm.26090 · Cited by 12
Top-down specific preparatory activations for selective attention and perceptual expectations
Peñalver, J. M. G., López-García, D., González‐García, C., Aguado-López, B., Górriz, J. M., & Ruz, M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119960 · Cited by 15
Decoding dynamic visual scenes across the brain hierarchy
Chen, Y., Beech, P., Yin, Z., Jia, S., Zhang, J., Yu, Z., & Liu, J. K. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012297 · Cited by 17
Audiovisual associations alter the perception of low-level visual motion
Kafalıgönül, H., & Oluk, C. (2015) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2015.00026 · Cited by 12
Murphy, C., Rueschemeyer, S., Smallwood, J., & Jefferies, E. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01330 · Cited by 12
Musz, E., Loiotile, R. E., Chen, J., Cusack, R., & Bedny, M. (2021) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2022.108277 · Cited by 10
Experience transforms crossmodal object representations in the anterior temporal lobes
Li, A. Y., Ladyka‐Wojcik, N., Qazilbash, H., Golestani, A., Walther, D. B., Martin, C. B., & Barense, M. D. (2024) · eLife · doi:10.7554/elife.83382 · Cited by 12
Kóbor, A., Janacsek, K., Hermann, P., Zavecz, Z., Varga, V., Csépe, V., Vidnyánszky, Z., Kovács, G., & Németh, D. (2024) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02173 · Cited by 12
Distributed neural signatures of natural audiovisual speech and music in the human auditory cortex
Salmi, J., Koistinen, O.-P., Glerean, E., Jylänki, P., Vehtari, A., Jääskeläinen, I. P., Mäkelä, S., Nummenmaa, L., Nummi-Kuisma, K., Nummi, I., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.005 · Cited by 13
Electrocorticography Evidence of Tactile Responses in Visual Cortices
Gaglianese, A., Branco, M. P., Groen, I. I. A., Benson, N. C., Vansteensel, M. J., Murray, M. M., Petridou, N., & Ramsey, N. F. (2020) · Brain Topography · doi:10.1007/s10548-020-00783-4 · Cited by 12
Classic psychedelics: the special role of the visual system
Császár-Nagy, N., Kapócs, G., & Bókkon, I. (2019) · Reviews in the Neurosciences · doi:10.1515/revneuro-2018-0092 · Cited by 12
An investigation of the neural association between auditory imagery and perception of complex sounds
Gu, J., Zhang, H., Liu, B., Li, X., Wang, P., & Wang, B. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01948-z · Cited by 11
Pia, L., Garbarini, F., Burin, D., Fossataro, C., & Berti, A. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00287 · Cited by 11
Greening, S., Lee, T.-H., Burleigh, L., Grégoire, L., Robinson, T. D., Jiang, X.-R., Mather, M., & Kaplan, J. T. (2021) · bioRxiv · doi:10.1101/2021.02.04.429795 · Cited by 5
Beyond sense-specific processing: decoding texture in the brain from touch and sonified movement
Landelle, C., Caron‐Guyon, J., Nazarian, B., Anton, J., Sein, J., Pruvost, L., Amberg, M., Giraud, F., Félician, O., Danna, J., et al. (2023) · iScience · doi:10.1016/j.isci.2023.107965 · Cited by 12
Evaluating cognitive penetrability of perception across the senses
Vetter, P., Badde, S., Ferrè, E. R., Seubert, J., & Shinn‐Cunningham, B. G. (2024) · Nature Reviews Psychology · doi:10.1038/s44159-024-00382-1 · Cited by 14
Self-citationSciortino, P., & Kayser, C. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120093 · Cited by 14
Auditory cortex conveys non-topographic sound localization signals to visual cortex
Mazo, C., Baeta, M., & Petreanu, L. (2024) · Nature Communications · doi:10.1038/s41467-024-47546-4 · Cited by 14
Semantic Grounding of Novel Spoken Words in the Primary Visual Cortex
Garagnani, M., Kirilina, E. P., & Friedemann Pulvermüller, A. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.581847 · Cited by 12
Visual imagery of faces and cars in face-selective visual areas
Sunday, M. A., McGugin, R. W., Tamber-Rosenau, B. J., & Gauthier, L. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205041 · Cited by 10
Neural network topologies supporting individual variations in vividness of visual imagery
Kvamme, T. L., Lumaca, M., Bajada, C. J., Gregersen, S. D., Hobot, J., Paunović, D., Wierzchoń, M., Zana, B., Silvanto, J., & Sandberg, K. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121520 · Cited by 11
Skirzewski, M., Molotchnikoff, S., Hernandez, L. F., & Maya‐Vetencourt, J. F. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.806376 · Cited by 9
Cortical and white matter substrates supporting visuospatial working memory
Ueda, R., Sakakura, K., Mitsuhashi, T., Sonoda, M., Firestone, E., Kuroda, N., Kitazawa, Y., Uda, H., Luat, A. F., Johnson, E. L., et al. (2024) · Clinical Neurophysiology · doi:10.1016/j.clinph.2024.03.008 · Cited by 9
Park, S., & Serences, J. T. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00300.2021 · Cited by 11
Visual cortex responds to sound onset and offset during passive listening
Brang, D., Plass, J., Sherman, A., Stacey, W. C., Wasade, V. S., Grabowecky, M., Ahn, E., Towle, V. L., Tao, J. X., Wu, S., et al. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00164.2021 · Cited by 11
Winne, J. D., Devos, P., Leman, M., & Botteldooren, D. B. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.894366 · Cited by 10
Phillips, I. B. (2025) · Noûs · doi:10.1111/nous.12551 · Cited by 9
Recurrent cortical networks encode natural sensory statistics via sequence filtering
Deveau, C. E., Zhou, Z., LaFosse, P. K., Deng, Y., Mirbagheri, S., Steinmetz, N. A., & Histed, M. H. (2026) · Neuron · doi:10.1016/j.neuron.2025.12.024 · Cited by 10
Barker, R. M., St‐Laurent, M., & Buchsbaum, B. R. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119205 · Cited by 9
Cutting Through the Noise: Auditory Scenes and Their Effects on Visual Object Processing
Williams, J. R., & Störmer, V. S. (2024) · Psychological Science · doi:10.1177/09567976241237737 · Cited by 10
Neural processing of naturalistic audiovisual events in space and time
Hu, Y., & Mohsenzadeh, Y. (2025) · Communications Biology · doi:10.1038/s42003-024-07434-5 · Cited by 9
Cortical feedback to V1 and V2 contains unique information about high-level scene structure
Morgan, A., Petro, L. S., & Muckli, L. F. (2016) · Journal of Vision · doi:10.1167/16.12.529 · Cited by 8
Self-citationDecoding Spatial Versus Non-spatial Processing in Auditory Working Memory
Erhart, M., Czoschke, S., Fischer, C., Bledowski, C., & Kaiser, J. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.637877 · Cited by 8
Heimler, B., & Amedi, A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-812492-5.00015-2 · Cited by 8
Imageless imagery in aphantasia: decoding non-sensory imagery in aphantasia
Meng, M., Chang, S., Zhang, X., & Pearson, J. (2023) · doi:10.21203/rs.3.rs-3162223/v1 · Cited by 8
Liu, S., You, B., Zhang, X., Shaw, A., Chen, H., & Jackson, T. (2023) · Clinical Journal of Pain · doi:10.1097/ajp.0000000000001103 · Cited by 7
Audition as a Trigger of Head Movements
Cohen-Lhyver, B., Argentieri, S., & Gas, B. (2020) · Modern acoustics and signal processing · doi:10.1007/978-3-030-00386-9_23 · Cited by 7
Effects of expectation on face perception and its association with expertise
Mares, I., Smith, F. W., Goddard, E., Keighery, L., Papasavva, M., Ewing, L., & Smith, M. L. (2024) · Scientific Reports · doi:10.1038/s41598-024-59284-0 · Cited by 10
Self-citationNánay, B. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198809500.003.0013 · Cited by 7
Decoding across sensory modalities reveals common supramodal signatures of conscious perceptionPreprint
Sanchez, G., Hartmann, T., Fuscà, M., Demarchi, G., & Weisz, N. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/115535 · Cited by 7
Auditory features modelling reveals sound envelope representation in striate cortexPreprint
Martinelli, A., Handjaras, G., Betta, M., Leo, A., Cecchetti, L., Pietrini, P., Ricciardi, E., & Bottari, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.15.043174 · Cited by 9
Early visual cortex tracks speech envelope in the absence of visual inputPreprint
Bednaya, E., Mirkovic, B., Berto, M., Ricciardi, E., Martinelli, A., Federici, A., Debener, S., & Bottari, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.28.497713 · Cited by 7
Dissonant music engages early visual processing
Bravo, F., Glogowski, J., Stamatakis, E. A., & Herfert, K. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2320378121 · Cited by 7
Decoding Reach Direction in Early “Visual” Cortex of Congenitally Blind Individuals
Bola, Ł., Vetter, P., Wenger, M., & Amedi, A. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0376-23.2023 · Cited by 8
Self-citationHuman visual perceptual organization beats thinking on speed
van der Helm, P. A. (2017) · Attention Perception & Psychophysics · doi:10.3758/s13414-017-1281-1 · Cited by 6
Decoding sound categories based on whole-brain functional connectivity patterns
Zhang, J., Zhang, G., Li, X., Wang, P., Wang, B., & Liu, B. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-018-9976-z · Cited by 6
van den Boom, M., Vansteensel, M. J., Koppeschaar, M. I., Raemaekers, M. A. H. L. L., & Ramsey, N. F. (2019) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ab302c · Cited by 6
Amadeo, M. B., Störmer, V. S., Campus, C., & Gori, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-48079-3 · Cited by 6
Feature-Specific Denoising of Neural Activity for Natural Image Identification
Wu, H., Zheng, N., & Chen, B. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3062067 · Cited by 6
Line drawings reveal the structure of internal visual models conveyed by cortical feedback.Preprint
Morgan, A., Petro, L. S., & Muckli, L. F. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/041186 · Cited by 6
Self-citationMethodologies for Identifying the Neural Correlates of Consciousness
Rees, G. E., & Frith, C. (2017) · Wiley eBooks · doi:10.1002/9781119132363.ch42 · Cited by 6
Auditory guidance of eye movements toward threat-related images in the absence of visual awareness
Hu, J., Badde, S., & Vetter, P. (2024) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2024.1441915 · Cited by 6
Self-citationDecoding semantic sound categories in early visual cortex
Pollicina, G., Müller, S. A., Dalton, P., & Vetter, P. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf208 · Cited by 5
Self-citationGalus, W. L. (2026) · Integrative Psychological and Behavioral Science · doi:10.1007/s12124-026-09984-1 · Cited by 8
Proactive selective attention across competition contexts
Aguado-López, B., Palenciano, A. F., Peñalver, J. M. G., Díaz-Gutiérrez, P., López-García, D., Avancini, C., Ciria, L. F., & Ruz, M. (2024) · Cortex · doi:10.1016/j.cortex.2024.04.009 · Cited by 5
Aphantasia and the unconscious imagery hypothesis
Mckilliam, A., & Kirberg, M. (2025) · Consciousness and Cognition · doi:10.1016/j.concog.2025.103924 · Cited by 6
Almeida, J., Kristensen, S., Tal, Z., & Fracasso, A. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121514 · Cited by 5
Абсатова, К. А., Kurgansky, А. V., & Machinskaya, R. I. (2016) · Psychology & Neuroscience · doi:10.1037/pne0000063 · Cited by 5
Exploring Hierarchical Auditory Representation via a Neural Encoding Model
Wang, L., Liu, H., Zhang, X., Zhao, S., Guo, L., Han, J., & Hu, X. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.843988 · Cited by 5
The “Hidden Observer” as the Cognitive Unconscious During Hypnosis
Császár, N., Scholkmann, F., Kapócs, G., & Bókkon, I. (2016) · Activitas Nervosa Superior · doi:10.1007/bf03379735 · Cited by 4
Semantically Congruent Sounds Facilitate the Decoding of Degraded Images
Lu, L., Zhang, G., Xu, J., & Liu, B. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2018.01.051 · Cited by 5
Impulse responses reveal unimodal and bimodal access to visual and auditory working memoryPreprint
Wolff, M. J., Kandemir, G., Stokes, M. G., & Akyürek, E. G. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/623835 · Cited by 5
Divergent Perception: Framing Creative Cognition Through the Lens of Sensory Flexibility
Bellemare‐Pepin, A., & Jerbi, K. (2024) · The Journal of Creative Behavior · doi:10.1002/jocb.1525 · Cited by 7
Matuszewski, J., Bola, Ł., Collignon, O., & Marchewka, A. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1153-24.2024 · Cited by 5
Is Reduced Visual Processing the Price of Language?
Johansson, C., & Фолгеро, П. О. (2022) · Brain Sciences · doi:10.3390/brainsci12060771 · Cited by 4
Neuroimaging evidence for the direct role of auditory scene analysis in object perception
Gurariy, G., Randall, R., & Greenberg, A. S. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac501 · Cited by 4
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Comparing Bayesian models for simultaneity judgement with different causal assumptions
Satō, Y. (2021) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2021.102521 · Cited by 6
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Continuous Theta Burst to Supplementary Motor Area Modulates Groove
Spiech, C., Martínez, M. G., Lazzari, G., & Penhune, V. B. (2026) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.70186 · Cited by 3
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Metadata
- Authors
- Vetter, P., Smith, F. W., & Muckli, L.
- Affiliations
- University of Geneva (CH)
- University of Glasgow (GB)
- Corresponding author
- Vetter, Petra
- Muckli, Lars
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 24
- Issue
- 11
- Pages
- 1256-1262
- ISSN
- 0960-9822 (ISSN-L)
- PMC
- PMC4046224
- OpenAlex
- W2016034937
- Semantic Scholar
- e40eefc9d7e41953e2a24e0bfd9701be9b8752bd
- Cited by
- 323
- References
- 52
- Citations by year
- 2026: 12 · 2025: 23 · 2024: 38 · 2023: 75 · 2022: 20 · 2021: 21 · 2020: 21 · 2019: 25 · 2018: 18 · 2017: 19 · 2016: 20 · 2015: 25 · 2014: 6
- FWCI
- 32.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Current Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
- Archive ouverte UNIGE (University of Geneva) (acceptedVersion, other-oa)
- UEA Digital Repository (University of East Anglia) (submittedVersion, cc-by)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Funders
- College of Science and Engineering, University of Minnesota
- Biotechnology and Biological Sciences Research Council (BB/G005044/1)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Keywords
- early visual cortex, auditory imagery, auditory perception, top-down feedback, multisensory integration, predictive coding, abstract information, visuospatial processing, attention, working memory, blindfolded participants
- MeSH terms
- Acoustic Stimulation, Auditory Perception, Humans, Magnetic Resonance Imaging, Memory, Short-Term, Photic Stimulation, Visual Cortex, 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.
A language model drew the claims from the paper on 2026-10-10, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-10 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
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 ›
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