The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Not Lost in Translation: Neural Responses Shared Across Languages
Open accessAbstract
How similar are the brains of listeners who hear the same content expressed in different languages? We directly compared the fMRI response time courses of English speakers and Russian speakers who listened to a real-life Russian narrative and its English translation. In the translation, we tried to preserve the content of the narrative while reducing the structural similarities across languages. The story evoked similar brain responses, invariant to the structural changes across languages, beginning just outside early auditory areas and extending through temporal, parietal, and frontal cerebral cortices. The similarity of responses across languages was nearly equal to the similarity of responses within each language group. The present results demonstrate that the human brain processes real-life information in a manner that is largely insensitive to the language in which that information is conveyed. The methods introduced here can potentially be used to quantify the transmission of meaning across cultural and linguistic boundaries.
Overview
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
Verification
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?
In the citing paper
“Accordingly, movie-viewing to spoken-recall pattern correlations were not found in low-level sensory areas, but instead were located in high-level DMN areas, which have been previously found to encode amodal abstract information (Binder et al. 2009; Honey et al. 2012; Regev et al. 2013).”
From How We Transmit Memories to Other Brains: Constructing Shared Neural Representations Via Communication (2017) · cites this paper as Honey et al. 2012
In the citing paper
“For example, the same narrative presented in different modalities (Regev et al., 2013; Baldassano et al., 2017; Zadbood et al., 2017) or languages (Honey et al., 2012) elicits similar time-courses of neural activity throughout the DMN despite major differences in low-level physical properties.”
From Shared understanding of narratives is correlated with shared neural responses (2019) · cites this paper as Honey et al., 2012
In the citing paper
“Thus, in order to time-lock the two stimuli, the Movie animation was segmented into 76 short events or actions (e.g. child bounces balls, parent kisses child goodnight, child and friend make a plan). The raw Audio story was edited to match the onset of each event in the animation, following Regev et al. (2013) and Honey et al. (2012) (Fig. 1).”
From Shared understanding of narratives is correlated with shared neural responses (2019) · cites this paper as Honey et al. (2012)
In the citing paper
“Following Honey et al. (2012), for between-condition analyses, we thus projected out the audio envelope from each subject’s neural response.”
From Shared understanding of narratives is correlated with shared neural responses (2019) · cites this paper as Honey et al. (2012)
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
The cortical organization of speech processing
Hickok, G., & Poeppel, D. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2113 · Cited by 5,495
Frith, C., & Frith, U. (2005) · Current Biology · doi:10.1016/j.cub.2005.08.041 · Cited by 3,561
Language, Thought, and Reality: Selected Writings of Benjamin Lee Whorf
Miller, G. A., & Carroll, J. B. (1957) · The American Journal of Psychology · doi:10.2307/1419256 · Cited by 2,748
Toward a mechanistic psychology of dialogue.
Pickering, M. J., & Garrod, S. (2004) · Behavioral and Brain Sciences · doi:10.1017/s0140525x04000056 · Cited by 2,678
Invariant visual representation by single neurons in the human brain
Quiroga, R. Q., Reddy, L., Kreiman, G., Koch, C., & Fried, I. (2005) · Nature · doi:10.1038/nature03687 · Cited by 1,988
Intersubject synchronization of cortical activity during natural vision
Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., & Malach, R. (2004) · Science · doi:10.1126/science.1089506 · Cited by 1,839
Self-citationOther minds in the brain: a functional imaging study of “theory of mind” in story comprehension.
Fletcher, P. (1995) · Cognition · doi:10.1016/0010-0277(95)00692-r · Cited by 1,522
Human Brain Language Areas Identified by Functional Magnetic Resonance Imaging
Binder, J. R., Frost, J. A., Hammeke, T. A., Cox, R. W., Rao, S. M., & Prieto, T. (1997) · The Journal of Neuroscience · doi:10.1523/jneurosci.17-01-00353.1997 · Cited by 1,424
Deconvolution of Impulse Response in Event-Related BOLD fMRI1
Glover, G. H. (1999) · NeuroImage · doi:10.1006/nimg.1998.0419 · Cited by 1,411
Cited by
Sorted by citations
The default mode network: where the idiosyncratic self meets the shared social world
Yeshurun, Y., Nguyen, M., & Hasson, U. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-00420-w · Cited by 682
Self-citationShared memories reveal shared structure in neural activity across individuals
Chen, J., Leong, Y. C., Honey, C. J., Yong, C. H., Norman, K. A., & Hasson, U. (2017) · Nature Neuroscience · doi:10.1038/nn.4450 · Cited by 645
Self-citationMeasuring shared responses across subjects using intersubject correlation
Nastase, S. A., Gazzola, V., Hasson, U., & Keysers, C. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz037 · Cited by 419
Self-citationCoupled neural systems underlie the production and comprehension of naturalistic narrative speech
Silbert, L. J., Honey, C. J., Simony, E., Poeppel, D., & Hasson, U. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323812111 · Cited by 352
Self-citationMirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions
Hasson, U., & Frith, C. D. (2016) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2015.0366 · Cited by 371
Self-citationShared understanding of narratives is correlated with shared neural responses
Nguyen, M., Vanderwal, T., & Hasson, U. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.09.010 · Cited by 304
Self-citationSame Story, Different Story: The Neural Representation of Interpretive Frameworks
Yeshurun, Y., Swanson, S., Simony, E., Chen, J., Lazaridi, C., Honey, C. J., & Hasson, U. (2017) · Psychological Science · doi:10.1177/0956797616682029 · Cited by 300
Self-citationSherman, L. E., Rudie, J. D., Pfeifer, J. H., Masten, C. L., McNealy, K., & Dapretto, M. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.08.002 · Cited by 356
The revolution will not be controlled: natural stimuli in speech neuroscience
Hamilton, L. S., & Huth, A. G. (2018) · Language Cognition and Neuroscience · doi:10.1080/23273798.2018.1499946 · Cited by 322
Zadbood, A., Chen, J., Leong, Y. C., Norman, K. A., & Hasson, U. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx202 · Cited by 281
Self-citationZadbood, A., Chen, J., Leong, Y. C., Norman, K. A., & Hasson, U. (2016) · doi:10.1101/081208 · Cited by 281
Self-citationAre We Ready for Real-world Neuroscience?
Matusz, P. J., Dikker, S., Huth, A. G., & Perrodin, C. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_e_01276 · Cited by 220
Selective and invariant neural responses to spoken and written narratives
Regev, M., Honey, C. J., Simony, E., & Hasson, U. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1580-13.2013 · Cited by 215
Self-citationInfant and Adult Brains Are Coupled to the Dynamics of Natural Communication
Piazza, E. A., Hasenfratz, L., Hasson, U., & Lew‐Williams, C. (2019) · Psychological Science · doi:10.1177/0956797619878698 · Cited by 221
Self-citationHasson, U., Egidi, G., Marelli, M., & Willems, R. M. (2018) · Cognition · doi:10.1016/j.cognition.2018.06.018 · Cited by 157
Self-citationChen, J., Honey, C. J., Simony, E., Arcaro, M. J., Norman, K. A., & Hasson, U. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhv155 · Cited by 135
Self-citationEngaged listeners: shared neural processing of powerful political speeches
Schmälzle, R., Häcker, F. E. K., Honey, C. J., & Hasson, U. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsu168 · Cited by 135
Self-citationInterbrain synchrony: on wavy ground
Holroyd, C. B. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.02.002 · Cited by 138
Dialogues: The Science and Power of Storytelling
SUZUKI, W. A., Feliú-Mójer, M. I., Hasson, U., Yehuda, R., & Zarate, J. M. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1942-18.2018 · Cited by 130
Self-citationSharing the social world via intersubject neural synchronisation
Nummenmaa, L., Lahnakoski, J. M., & Glerean, E. (2018) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.02.021 · Cited by 124
Bogulski, C., Bice, K., & Kroll, J. (2018) · Bilingualism: Language and Cognition · doi:10.1017/s1366728918000858 · Cited by 56
Anderson, A. J., Binder, J. R., Fernandino, L., Humphries, C., Conant, L. L., Aguilar, M., Wang, X., Doko, D., & Raizada, R. D. S. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw240 · Cited by 111
Information flow across the cortical timescale hierarchy during narrative construction
Chang, C. H. C., Nastase, S. A., & Hasson, U. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2209307119 · Cited by 92
Self-citationAmplification of local changes along the timescale processing hierarchy
Yeshurun, Y., Nguyen, M., & Hasson, U. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1701652114 · Cited by 94
Self-citationStudying the dynamics of autonomic activity during emotional experience
Golland, Y., Keissar, K., & Levit‐Binnun, N. (2014) · Psychophysiology · doi:10.1111/psyp.12261 · Cited by 103
Chen, G., Shin, Y., Taylor, P. A., Glen, D., Reynolds, R. C., Israel, R. B., & Cox, R. W. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.023 · Cited by 92
Conservative and liberal attitudes drive polarized neural responses to political content
Leong, Y. C., Chen, J., Willer, R., & Zaki, J. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2008530117 · Cited by 94
Domain-General Brain Regions Do Not Track Linguistic Input as Closely as Language-Selective Regions
Blank, I., & Fedorenko, E. G. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3642-16.2017 · Cited by 93
Meshulam, M., Hasenfratz, L., Hillman, H., Liu, Y., Nguyen, M., Norman, K. A., & Hasson, U. (2021) · Nature Communications · doi:10.1038/s41467-021-22202-3 · Cited by 86
Self-citationDecoding the neural representation of story meanings across languages
Dehghani, M., Boghrati, R., Man, K., Hoover, J., Gimbel, S. I., Vaswani, A., Zevin, J. D., Immordino‐Yang, M. H., Gordon, A. S., Damásio, A. R., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23814 · Cited by 83
Mapping between fMRI responses to movies and their natural language annotations
Vodrahalli, K., Chen, P.-H., Liang, Y., Baldassano, C. A., Chen, J., Yong, E., Honey, C. J., Hasson, U., Ramadge, P. J., Norman, K. A., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.042 · Cited by 79
Self-citationContextual Alignment of Cognitive and Neural Dynamics
Ames, D. L., Honey, C. J., Chow, M. A., Todorov, A., & Hasson, U. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00728 · Cited by 74
Self-citationDynamic intersubject neural synchronization reflects affective responses to sad music
Sachs, M. E., Habibi, A., Damásio, A. R., & Kaplan, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116512 · Cited by 74
The Embodied-Enactive-Interactive Brain: Bridging Neuroscience and Creative Arts Therapies
Vaisvaser, S. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.634079 · Cited by 85
Regev, M., Simony, E., Lee, K. J., Tan, K. M., Chen, J., & Hasson, U. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy282 · Cited by 74
Self-citationAnderson, A. J., Kiela, D., Binder, J. R., Fernandino, L., Humphries, C. J., Conant, L. L., Raizada, R. D. S., Grimm, S., & Lalor, E. C. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.1152-20.2021 · Cited by 70
Anderson, D. R., & Davidson, M. C. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.05.008 · Cited by 74
No evidence for differences among language regions in their temporal receptive windows
Blank, I., & Fedorenko, E. G. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116925 · Cited by 74
Driving and suppressing the human language network using large language models
Tuckute, G., Sathe, A., Srikant, S., Taliaferro, M., Wang, M., Schrimpf, M., Kay, K., & Fedorenko, E. G. (2024) · Nature Human Behaviour · doi:10.1038/s41562-023-01783-7 · Cited by 106
Teacher–student neural coupling during teaching and learning
Nguyen, M., Chang, A. E., Micciche, E. T., Meshulam, M., Nastase, S. A., & Hasson, U. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab103 · Cited by 83
Self-citationNeurocomputational Models of Language Processing
Hale, J., Campanelli, L., Li, J., Bhattasali, S., Pallier, C., & Brennan, J. (2021) · Annual Review of Linguistics · doi:10.1146/annurev-linguistics-051421-020803 · Cited by 68
How Does the “Default Mode” Network Contribute to Semantic Cognition?
Fernandino, L., & Binder, J. R. (2024) · Brain and Language · doi:10.1016/j.bandl.2024.105405 · Cited by 70
Learning Naturalistic Temporal Structure in the Posterior Medial Network
Aly, M., Chen, J., Turk‐Browne, N. B., & Hasson, U. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01308 · Cited by 55
Self-citationChang, C. H. C., Lazaridi, C., Yeshurun, Y., Norman, K. A., & Hasson, U. (2021) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01707 · Cited by 52
Self-citationNeural Correlates of Risk Perception during Real-Life Risk Communication
Schmälzle, R., Hacker, F., Renner, B., Honey, C. J., & Schupp, H. T. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.5323-12.2013 · Cited by 54
Self-citationNeural synchrony predicts children's learning of novel words
Piazza, E. A., Cohen, A., Trach, J. E., & Lew‐Williams, C. (2021) · Cognition · doi:10.1016/j.cognition.2021.104752 · Cited by 51
Zinszer, B. D., Anderson, A., Kang, O., Wheatley, T., & Raizada, R. D. S. (2016) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01000 · Cited by 33
Studying the visual brain in its natural rhythm
Leopold, D. A., & Park, S. H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116790 · Cited by 47
Grall, C., Tamborini, R., Weber, R., & Schmälzle, R. (2021) · Journal of Communications · doi:10.1093/joc/jqab004 · Cited by 37
Self-regulation via neural simulation
Gilead, M., Boccagno, C., Silverman, M., Hassin, R. R., Weber, J., & Ochsner, K. N. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1600159113 · Cited by 42
Concepts in the Brain: The View From Cross-linguistic Diversity
Kemmerer, D. (2019) · doi:10.1093/oso/9780190682620.001.0001 · Cited by 42
Goldstein, A., Wang, H., Niekerken, L., Schain, M., Zada, Z., Aubrey, B., Sheffer, T., Nastase, S. A., Gazula, H., Singh, A., et al. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02105-9 · Cited by 57
Self-citationMapping Specific Mental Content during Musical Imagery
Regev, M., Halpern, A. R., Owen, A. M., Patel, A. D., & Zatorre, R. J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab036 · Cited by 44
Paunov, A. M., Blank, I., Jouravlev, O., Mineroff, Z., Gallée, J., & Fedorenko, E. G. (2022) · Neurobiology of Language · doi:10.1162/nol_a_00071 · Cited by 39
Anderson, A. J., Lalor, E. C., Lin, F. V., Binder, J. R., Fernandino, L., Humphries, C., Conant, L. L., Raizada, R. D. S., Grimm, S., & Wang, X. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy110 · Cited by 39
The Coupled Brains of Captivated Audiences
Schmälzle, R., & Grall, C. (2020) · Journal of Media Psychology Theories Methods and Applications · doi:10.1027/1864-1105/a000271 · Cited by 40
Integrating media content analysis, reception analysis, and media effects studies
Schmälzle, R., & Huskey, R. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1155750 · Cited by 39
Gamma‐band neural coupling during conceptual alignment
Chen, D., Zhang, R., Liu, J., Wang, P., Bei, L., Liu, C. J., & Li, X. (2022) · Human Brain Mapping · doi:10.1002/hbm.25831 · Cited by 33
Interpersonal educational neuroscience: A scoping review of the literature
Zhang, Y., Hu, Y., Ma, F., Cui, H., Cheng, X., & Pan, Y. (2024) · Educational Research Review · doi:10.1016/j.edurev.2024.100593 · Cited by 44
Narrative comprehension beyond language: Common brain networks activated by a movie and its script
Tikka, P., Kauttonen, J., & Hlushchuk, Y. (2018) · PLoS ONE · doi:10.1371/journal.pone.0200134 · Cited by 30
Rowland, S. C., Hartley, D. E. H., & Wiggins, I. M. (2018) · Trends in Hearing · doi:10.1177/2331216518804116 · Cited by 36
Neurodynamics of Relational Aesthetic Engagement in Creative Arts Therapies
Vaisvaser, S., King, J. L., Orkibi, H., & Aleem, H. (2024) · Review of General Psychology · doi:10.1177/10892680241260840 · Cited by 38
Arnulf, J. K., Larsen, K. R. T., Martinsen, Ø. L., & Egeland, T. (2018) · Behavior Research Methods · doi:10.3758/s13428-017-0999-y · Cited by 32
Neural synchronization as a function of engagement with the narrative
Ohad, T., & Yeshurun, Y. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120215 · Cited by 32
Chen, G., Taylor, P. A., Qu, X., Molfese, P. J., Bandettini, P. A., Cox, R. W., & Finn, E. S. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116474 · Cited by 28
Strong health messages increase audience brain coupling
Imhof, M. A., Schmälzle, R., Renner, B., & Schupp, H. T. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116527 · Cited by 30
(2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374 · Cited by 30
Culture in Mind – An Enactivist Account
Hutto, D. D., Gallagher, S., Ilundáin‐Agurruza, J., & Hipólito, I. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.009 · Cited by 29
Neural dynamics underlying emotional transmissions between individuals
Golland, Y., Levit‐Binnun, N., Hendler, T., & Lerner, Y. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx049 · Cited by 30
Self-citationZhu, J., Chen, S., Guo, J., Li, W., Li, X., Huang, L., & Ye, M. (2024) · European Journal of Oncology Nursing · doi:10.1016/j.ejon.2024.102535 · Cited by 26
Katabi, N., Simon, H., Yakim, S., Ravreby, I., Ohad, T., & Yeshurun, Y. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0895-22.2022 · Cited by 27
Dieffenbach, M. C., Gillespie, G. S. R., Burns, S. M., McCulloh, I., Ames, D. L., Dagher, M. M., Falk, E. B., & Lieberman, M. D. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa115 · Cited by 29
Malik-Moraleda, S., Jouravlev, O., Taliaferro, M., Mineroff, Z., Cucu, T., Mahowald, K., Blank, I., & Fedorenko, E. G. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae049 · Cited by 32
Effects of acute psychosocial stress on interpersonal cooperation and competition in young women
Zhang, R., Zhou, X., Feng, D., Yuan, D., Li, S., Lu, C., & Li, X. (2021) · Brain and Cognition · doi:10.1016/j.bandc.2021.105738 · Cited by 23
Zhang, Q., Li, B., Jin, S., Liu, W., Liu, J., Xie, S., Zhang, L., Kang, Y., Ding, Y., Zhang, X., et al. (2022) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2022.111485 · Cited by 21
Häusler, C. O., Eickhoff, S. B., & Hanke, M. (2022) · Scientific Data · doi:10.1038/s41597-022-01250-4 · Cited by 21
Teacher-student neural coupling during teaching and learning
Nguyen, M., Chang, A., Micciche, E., Meshulam, M., Nastase, S. A., & Hasson, U. (2020) · doi:10.1101/2020.05.07.082958 · Cited by 67
Self-citationPuschmann, S., Regev, M., Baillet, S., & Zatorre, R. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0932-20.2020 · Cited by 20
Driving and suppressing the human language network using large language modelsPreprint
Tuckute, G., Sathe, A., Srikant, S., Taliaferro, M., Wang, M., Schrimpf, M., Kay, K., & Fedorenko, E. G. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.16.537080 · Cited by 20
Gendron, M., Mesquita, B., & Barrett, L. F. (2020) · Culture, Mind, and Brain · doi:10.1017/9781108695374.010 · Cited by 20
Scaling in Colloidal and Biological Networks
Nosonovsky, M., & Roy, P. (2020) · Entropy · doi:10.3390/e22060622 · Cited by 19
Schmälzle, R. (2022) · Communication Theory · doi:10.1093/ct/qtac009 · Cited by 18
Deep speech-to-text models capture the neural basis of spontaneous speech in everyday conversationsPreprint
Goldstein, A., Wang, H., Niekerken, L., Zada, Z., Aubrey, B., Sheffer, T., Nastase, S. A., Gazula, H., Schain, M., Singh, A., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.26.546557 · Cited by 19
Self-citationBerezutskaya, J., Baratin, C., Freudenburg, Z. V., & Ramsey, N. F. (2020) · Human Brain Mapping · doi:10.1002/hbm.25144 · Cited by 18
Culture, Mind, and Brain: Emerging Concepts, Models, and Applications
Kirmayer, L. J., Worthman, C. M., Kitayama, S., Lemelson, R., & Cummings, C. A. (2020) · Cited by 15
Evaluating the impact of short educational videos on the cortical networks for mathematics
Amalric, M., Roveyaz, P., & Dehaene, S. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2213430120 · Cited by 16
Chen, C. L., Gong, X. L., Tseng, C., Klein, D. L., Gallant, J. L., & Deniz, F. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2503721123 · Cited by 21
Puschmann, S., Regev, M., Fakhar, K., Zatorre, R. J., & Thiel, C. M. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.1157-23.2023 · Cited by 12
Olfaction Modulates Inter-Subject Correlation of Neural Responses
DeGuzman, P., Jain, A., Tabert, M. H., & Parra, L. C. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00702 · Cited by 12
Affective Typography: The Effect of AI-Driven Font Design on Empathetic Story Reading
Shen, J. J., Jin, K., Zhang, A., Breazeal, C., & Park, H. W. (2023) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3544549.3585625 · Cited by 10
Singer, N., Jacoby, N., Hendler, T., & Granot, R. (2023) · Journal of Cognition · doi:10.5334/joc.286 · Cited by 10
Lin, N., Zhang, X., Wang, X., & Wang, S. (2024) · Brain and Language · doi:10.1016/j.bandl.2024.105388 · Cited by 10
What do aesthetic affordances afford?
Sánchez, C. V. (2022) · Enrahonar An international journal of theoretical and practical reason · doi:10.5565/rev/enrahonar.1401 · Cited by 11
Nunes, A. S., Kozhemiako, N., Moiseev, A., Seymour, R. A., Cheung, T., Ribary, U., & Doesburg, S. M. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116414 · Cited by 10
Early signatures of and developmental change in brain regions for theory of mind
Richardson, H., & Saxe, R. R. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-814411-4.00021-4 · Cited by 13
Neural correlates of semantic number: A cross-linguistic investigation
Dunagan, D. G., Zhang, S., Li, J., Bhattasali, S., Pallier, C., Whitman, J. B., Yang, Y., & Hale, J. (2021) · Brain and Language · doi:10.1016/j.bandl.2022.105110 · Cited by 10
Manning, J. R. (2024) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190917982.013.38 · Cited by 10
A cross-modal investigation of the neural substrates for ongoing cognition
Wang, M., & He, B. J. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00945 · Cited by 10
The Perspective from Cognitive Neuroscience
Kemmerer, D. L. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190682620.003.0002 · Cited by 9
Decoding the Neural Representation of Story Meanings across LanguagesPreprint
Dehghani, M., Boghrati, R., Man, K., Hoover, J., Gimbel, S., Vaswani, A., Zevin, J. D., Immordino‐Yang, M. H., Gordon, A., Damásio, A. R., et al. (2017) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/qrpp3 · Cited by 13
Metadata
- Authors
- Honey, C. J., Thompson, C. R., Lerner, Y., & Hasson, U.
- Affiliations
- Princeton University (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2012-10-31
- Volume
- 32
- Issue
- 44
- Pages
- 15277-15283
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC3525075
- OpenAlex
- W2035023916
- Cited by
- 192
- References
- 36
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 14 · 2023: 18 · 2022: 17 · 2021: 20 · 2020: 45 · 2019: 18 · 2018: 14 · 2017: 12 · 2016: 8 · 2015: 2 · 2014: 5 · 2013: 2 · 2012: 1
- FWCI
- 1.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (R01MH094480)
- National Institute on Drug Abuse (R21DA024423)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- language invariance, narrative comprehension, English-Russian translation, language processing, auditory cortex, temporal lobe, parietal cortex, frontal cortex
- MeSH terms
- Acoustic Stimulation, Adult, Algorithms, Brain, Brain Mapping, Cerebral Cortex, Female, Humans, Image Processing, Computer-Assisted, Language, Magnetic Resonance Imaging, Male, Memory, Oxygen, Psycholinguistics, Cluster Analysis, Multilingualism, Comprehension, Young Adult
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