The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.
Broad domain generality in focal regions of frontal and parietal cortex
Open accessAbstract
Significance: One of the oldest debates in cognitive neuroscience concerns the degree of functional specialization present in the human brain. Prior work has discovered several highly specialized components dedicated to particular mental functions, like face recognition or motion perception. However, our cognitive versatility suggests the additional existence of more general-purpose machinery. Building on prior neuroimaging evidence, along with neurophysiological evidence from non-human primates, we searched for such domain-general brain regions in humans. Seven diverse demanding cognitive tasks produced overlapping activation at the individual-subject level in a number of frontal and parietal brain regions. Thus, human cognition arises from hardware that includes not only specialized components, but also very general-purpose ones that plausibly enable us to solve novel problems.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The FPN and CON are functionally separable brain networks that enable flexible adaptive control and sustained task-set maintenance [142]; together, they form the MD network [143], a set of brain regions that is active during a range of tasks that require goal-directed behavior [139].”
From The role of prefrontal cortex in cognitive control and executive function (2022) · cites this paper as [139]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Conjunction maps of activation during different tasks (e.g., during inhibiting, updating, and shifting tasks), either with data estimated within one study [135, 138, 139] or with meta-analytic techniques [137, 140, 141], suggest that both children and adults recruit a common set of regions within the FPN and CON during diverse EF tasks.”
From The role of prefrontal cortex in cognitive control and executive function (2022) · cites this paper as [139]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Our findings show that brain regions that are engaged in a verbal WM task, which are associated with the operation of the MD network (Fedorenko et al., 2013;Duncan, 2010), are also engaged during spatial and imitative conflict resolution.”
From Functional Specificity and Sex Differences in the Neural Circuits Supporting the Inhibition of Automatic Imitation (2018) · cites this paper as Fedorenko et al., 2013
The cited source says what the claim attributes to it.
In the citing paper
“The hard > easy contrast has been found to robustly activate regions of the MD network (Fedorenko et al., 2011(Fedorenko et al., , 2013)).”
From Functional Specificity and Sex Differences in the Neural Circuits Supporting the Inhibition of Automatic Imitation (2018) · cites this paper as Fedorenko et al., 2013
In the citing paper
“In addition to the connectional anatomy, it has been noted that these same domain-independent regions are activated during a variety of different cognitive and motor control tasks [70, 71].”
From Neurocomputational mechanisms underlying subjective valuation of effort costs (2017) · cites this paper as [71]
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
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
An Integrative Theory of Prefrontal Cortex Function
Miller, E. K., & Cohen, J. D. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.167 · Cited by 12,803
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
Conflict monitoring and cognitive control
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001) · Psychological Review · doi:10.1037/0033-295x.108.3.624 · Cited by 7,351
Functional Network Organization of the Human Brain
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.006 · Cited by 4,124
Distributed and overlapping representations of faces and objects in ventral temporal cortex
Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001) · Science · doi:10.1126/science.1063736 · Cited by 3,940
The reorienting system of the human brain: from environment to theory of mind
Corbetta, M., Patel, G., & Shulman, G. L. (2008) · Neuron · doi:10.1016/j.neuron.2008.04.017 · Cited by 3,889
Conflict monitoring and anterior cingulate cortex: an update
Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.10.003 · Cited by 3,623
Imaging Cognition II: An Empirical Review of 275 PET and fMRI Studies
Cabeza, R., & Nyberg, L. (2000) · Journal of Cognitive Neuroscience · doi:10.1162/08989290051137585 · Cited by 3,598
Cited by
Sorted by citations
Items 101–200 of 953
Beaty, R. E., Chen, Q., Christensen, A. P., Kenett, Y. N., Silvia, P. J., Benedek, M., & Schacter, D. L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116499 · Cited by 108
Wang, X., Margulies, D. S., Smallwood, J., & Jefferies, E. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117074 · Cited by 100
Multiple dimensions underlying the functional organization of the language network
Hodgson, V. J., Ralph, M. A. L., & Jackson, R. L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118444 · Cited by 104
Woolgar, A., Jackson, J. B., & Duncan, J. (2016) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00981 · Cited by 105
Self-citationKoyama, M. S., O’Connor, D. A., Shehzad, Z. E., & Milham, M. P. (2017) · Scientific Reports · doi:10.1038/s41598-017-17702-6 · Cited by 103
Wen, T., Mitchell, D. J., & Duncan, J. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa166 · Cited by 101
Self-citationMajerus, S., Cowan, N., Peters, F., Calster, L. V., Phillips, C. L. M., & Schrouff, J. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu189 · Cited by 87
Mineroff, Z., Blank, I., Mahowald, K., & Fedorenko, E. G. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.09.011 · Cited by 91
Self-citationHumphreys, G. F., & Ralph, M. A. L. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx107 · Cited by 95
Rodríguez-Nieto, G., Seer, C., Sidlauskaite, J., Vleugels, L., Van Roy, A., Hardwick, R., & Swinnen, S. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119665 · Cited by 89
Convergence of cortical types and functional motifs in the human mesiotemporal lobe
Paquola, C., Benkarim, O. M., DeKraker, J., Larivière, S., Frässle, S., Royer, J., Tavakol, S., Valk, S. L., Bernasconi, A., Bernasconi, N., et al. (2020) · eLife · doi:10.7554/elife.60673 · Cited by 85
Kiran, S., Meier, E. L., Kapse, K. J., & Glynn, P. A. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00316 · Cited by 89
Allostasis as a core feature of hierarchical gradients in the human brain
Katsumi, Y., Theriault, J. E., Quigley, K. S., & Barrett, L. F. (2022) · Network Neuroscience · doi:10.1162/netn_a_00240 · Cited by 88
Functional Characterization of the Human Speech Articulation Network
Basilakos, A., Smith, K. G., Fillmore, P., Fridriksson, J., & Fedorenko, E. G. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx100 · Cited by 94
Self-citationDomain-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
Self-citationEEG microstate features according to performance on a mental arithmetic task
Kim, K., Duc, N. T., Choi, M., & Lee, B. (2021) · Scientific Reports · doi:10.1038/s41598-020-79423-7 · Cited by 88
Fedorenko, E. G. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2021.02.023 · Cited by 84
Self-citationThe Dual Mechanisms of Cognitive Control Project
Braver, T. S., Kizhner, A., Tang, R., Freund, M. C., & Etzel, J. A. (2021) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01768 · Cited by 103
Less is more: neural mechanisms underlying anomia treatment in chronic aphasic patients
Nardo, D., Holland, R., Leff, A. P., Price, C. J., & Crinion, J. T. (2017) · Brain · doi:10.1093/brain/awx234 · Cited by 80
Assem, M., Blank, I., Mineroff, Z., Ademoğlu, A., & Fedorenko, E. G. (2020) · Cortex · doi:10.1016/j.cortex.2020.06.013 · Cited by 92
Self-citationClinical Concepts Emerging from fMRI Functional Connectomics
Matthews, P. M., & Hampshire, A. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.031 · Cited by 83
Persistent neuronal activity in human prefrontal cortex links perception and action
Haller, M., Case, J., Crone, N. E., Chang, E. F., King‐Stephens, D., Laxer, K. D., Weber, P. B., Parvizi, J., Knight, R. T., & Shestyuk, A. Y. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0267-2 · Cited by 83
A Tri-network Model of Human Semantic Processing
Xu, Y., Yong He, A., & Bi, Y. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.01538 · Cited by 79
For a cognitive neuroscience of concepts: Moving beyond the grounding issue
Leshinskaya, A., & Caramazza, A. (2016) · Psychonomic Bulletin & Review · doi:10.3758/s13423-015-0870-z · Cited by 86
Shain, C., Blank, I., Fedorenko, E. G., Gibson, E. A. F., & Schuler, W. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1894-21.2022 · Cited by 78
Self-citationShashidhara, S., Mitchell, D. J., Erez, Y., & Duncan, J. (2019) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01440 · Cited by 81
Self-citationErez, Y., & Duncan, J. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.1134-15.2015 · Cited by 85
Self-citationJiang, X., Li, X., Lv, J., Zhang, T., Zhang, S., Guo, L., & Liu, T. (2015) · Human Brain Mapping · doi:10.1002/hbm.23013 · Cited by 76
Jackson, J. B., Rich, A. N., Williams, M., & Woolgar, A. (2016) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01039 · Cited by 83
Bhandari, A., Gagne, C., & Badre, D. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01291 · Cited by 79
Ryskin, R. A., Lévy, R., & Fedorenko, E. G. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.107258 · Cited by 79
Self-citationInnate connectivity patterns drive the development of the visual word form area
Li, J., Osher, D. E., Hansen, H. A., & Saygin, Z. M. (2020) · Scientific Reports · doi:10.1038/s41598-020-75015-7 · Cited by 74
Woolgar, A., Afshar, S., Williams, M., & Rich, A. N. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00827 · Cited by 81
Hu, J., Small, H., Kean, H., Takahashi, A., Zekelman, L., Kleinman, D., Ryan, E., Nieto-Castañón, A., Ferreira, V., & Fedorenko, E. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhac350 · Cited by 73
Self-citationWehbe, L., Blank, I. A., Shain, C., Futrell, R., Levy, R., von der Malsburg, T., Smith, N., Gibson, E., & Fedorenko, E. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab065 · Cited by 72
Self-citationNo 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
Self-citationNeuroplasticity in Aphasia: A Proposed Framework of Language Recovery
Kiran, S., Meier, E. L., & Johnson, J. P. (2019) · Journal of Speech Language and Hearing Research · doi:10.1044/2019_jslhr-l-rsnp-19-0054 · Cited by 69
Cogdell-Brooke, L. S., Sowden, P. T., Violante, I. R., & Thompson, H. E. (2020) · Human Brain Mapping · doi:10.1002/hbm.25170 · Cited by 73
Diveica, V., Koldewyn, K., & Binney, R. J. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118702 · Cited by 71
Hallam, G., Whitney, C., Hymers, M., Gouws, A. D., & Jefferies, E. (2016) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2016.09.012 · Cited by 77
Wu, T., Chen, C., Spagna, A., Wu, X., Mackie, M., Russell‐Giller, S., Xu, P., Luo, Y., Liu, X., Hof, P. R., et al. (2019) · The Journal of Comparative Neurology · doi:10.1002/cne.24804 · Cited by 74
Brain Modularity Mediates the Relation between Task Complexity and Performance
Yue, Q., Martin, R. C., Fischer‐Baum, S., Ramos-Nuñez, A. I., Ye, F., & Deem, M. W. (2017) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01142 · Cited by 69
Liu, Y.-F., Kim, J., Wilson, C., & Bedny, M. (2020) · eLife · doi:10.7554/elife.59340 · Cited by 64
The Role of the Parietal Cortex in the Representation of Task-Reward Associations
Wisniewski, D., Reverberi, C., Momennejad, I., Kahnt, T., & Haynes, J.-D. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4882-14.2015 · Cited by 67
Sensory-Biased and Multiple-Demand Processing in Human Lateral Frontal Cortex
Noyce, A. L., Cestero, N., Michalka, S., Shinn‐Cunningham, B. G., & Somers, D. C. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0660-17.2017 · Cited by 67
Stimulating Multiple-Demand Cortex Enhances Vocabulary Learning
Sliwinska, M. W., Violante, I. R., Wise, R. G., Leech, R., Devlin, J. T., Geranmayeh, F., & Hampshire, A. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3857-16.2017 · Cited by 62
From Believing to Belief: A General Theoretical Model
Seitz, R. J., Paloutzian, R. F., & Angel, H. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01292 · Cited by 65
Distinct and common neural coding of semantic and non-semantic control demands
Gao, Z., Zheng, L. J., Chiou, R. Y.-C., Gouws, A. D., Krieger‐Redwood, K., Wang, X., Varga, D., Ralph, M. A. L., Smallwood, J., & Jefferies, E. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118230 · Cited by 65
Voxelwise Encoding Models Show That Cerebellar Language Representations Are Highly Conceptual
LeBel, A., Jain, S., & Huth, A. G. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0118-21.2021 · Cited by 68
Dynamic network coding of working-memory domains and working-memory processes
Soreq, E., Leech, R., & Hampshire, A. (2019) · Nature Communications · doi:10.1038/s41467-019-08840-8 · Cited by 64
Jouravlev, O., Kell, A. J. E., Mineroff, Z., Haskins, A. J., Ayyash, D., Kanwisher, N., & Fedorenko, E. G. (2020) · Autism Research · doi:10.1002/aur.2393 · Cited by 66
Self-citationChen, X., Affourtit, J., Ryskin, R., Regev, T. I., Norman-Haignere, S., Jouravlev, O., Malik-Moraleda, S., Kean, H., Varley, R., & Fedorenko, E. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad087 · Cited by 57
Self-citationThe tenacious brain: How the anterior mid-cingulate contributes to achieving goals
Touroutoglou, A., Andreano, J. M., Dickerson, B. C., & Barrett, L. F. (2019) · Cortex · doi:10.1016/j.cortex.2019.09.011 · Cited by 70
Neural Coding for Instruction-Based Task Sets in Human Frontoparietal and Visual Cortex
Muhle-Karbe, P. S., Duncan, J., Baene, W. D., Mitchell, D. J., & Braß, M. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw032 · Cited by 68
Self-citationSeydell-Greenwald, A., Ferrara, K., Chambers, C. E., Newport, E., & Landau, B. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.10.005 · Cited by 58
Both Default and Multiple-Demand Regions Represent Semantic Goal Information
Wang, X., Gao, Z., Smallwood, J., & Jefferies, E. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1782-20.2021 · Cited by 63
Stefaniak, J. D., Alyahya, R. S. W., & Ralph, M. A. L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117960 · Cited by 64
Muhle-Karbe, P. S., Derrfuß, J., Lynn, M. T., Neubert, F. X., Fox, P. T., Braß, M., & Eickhoff, S. B. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv073 · Cited by 62
Polspoel, B., Peters, L., Vandermosten, M., & Smedt, B. D. (2017) · Human Brain Mapping · doi:10.1002/hbm.23691 · Cited by 61
Woolgar, A., Williams, M., & Rich, A. N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.083 · Cited by 65
Neural systems of cognitive demand avoidance
Sayalı, C., & Badre, D. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.06.016 · Cited by 60
Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization
Lorenz, R., Violante, I. R., Monti, R. P., Montana, G., Hampshire, A., & Leech, R. (2018) · Nature Communications · doi:10.1038/s41467-018-03657-3 · Cited by 58
Jung, J., Bungert, A., Bowtell, R. W., & Jackson, S. R. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00031 · Cited by 61
Alam, T. R. G., Mckeown, B., Gao, Z., Bernhardt, B. C., de Wael, R. V., Margulies, D. S., Smallwood, J., & Jefferies, E. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02374-w · Cited by 61
Two common and distinct forms of variation in human functional brain networks
Dworetsky, A., Seitzman, B. A., Adeyemo, B., Nielsen, A. N., Hatoum, A. S., Smith, D. M., Nichols, T. E., Neta, M., Petersen, S. E., & Gratton, C. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01618-2 · Cited by 70
Mondok, C., & Wiener, M. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.1000995 · Cited by 58
Bedini, M., & Baldauf, D. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15393 · Cited by 60
Jackson, J. B., Feredoes, E. A., Rich, A. N., Lindner, M., & Woolgar, A. (2021) · Communications Biology · doi:10.1038/s42003-021-02109-x · Cited by 56
Variable disruption of a syntactic processing network in primary progressive aphasia
Wilson, S. M., DeMarco, A. T., Henry, M. L., Gesierich, B. G., Babiak, M. C., Miller, B. L., & Gorno‐Tempini, M. L. (2016) · Brain · doi:10.1093/brain/aww218 · Cited by 58
Meditation and cognitive ageing: the role of mindfulness meditation in building cognitive reserve.
Malinowski, P., & Shalamanova, L. (2017) · Journal of Cognitive Enhancement · doi:10.1007/s41465-017-0022-7 · Cited by 50
Closing the mechanistic gap: the value of microarchitecture in understanding cognitive networks
Paquola, C., Amunts, K., Evans, A. C., Smallwood, J., & Bernhardt, B. C. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.07.001 · Cited by 52
Tschentscher, N., Mitchell, D. J., & Duncan, J. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.2478-16.2017 · Cited by 52
Self-citationFunctional brain activation associated with working memory training and transfer
Clark, C. M., Lawlor‐Savage, L., & Goghari, V. M. (2017) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.07.030 · Cited by 57
Noy, N., Bickel, S., Golumbic, E. Z., Harel, M., Golan, T., Davidesco, I., Schevon, C. A., McKhann, G. M., Goodman, R. R., Schroeder, C. E., et al. (2015) · Consciousness and Cognition · doi:10.1016/j.concog.2015.03.006 · Cited by 63
Sims, J. A., Kapse, K. J., Glynn, P. A., Sandberg, C., Tripodis, Y., & Kiran, S. (2016) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2015.10.019 · Cited by 51
Similar coding of freely chosen and externally cued intentions in a fronto-parietal network
Wisniewski, D., Goschke, T., & Haynes, J. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.044 · Cited by 55
Thompson, H. E., Almaghyuli, A., Noonan, K. A., Barak, O., Ralph, M. A. L., & Jefferies, E. (2018) · Journal of Neuropsychology · doi:10.1111/jnp.12142 · Cited by 57
Goal-seeking compresses neural codes for space in the human hippocampus and orbitofrontal cortex
Muhle-Karbe, P. S., Sheahan, H., Pezzulo, G., Spiers, H. J., Chien, S., Schuck, N. W., & Summerfield, C. (2023) · Neuron · doi:10.1016/j.neuron.2023.08.021 · Cited by 54
Chiou, R. Y.-C., Jefferies, E., Duncan, J., Humphreys, G. F., & Ralph, M. A. L. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac358 · Cited by 54
Self-citationRethinking Remapping: Circuit Mechanisms of Recovery after Stroke
Campos, B., Choi, H., DeMarco, A. T., Seydell‐Greenwald, A., Hussain, S. J., Joy, M. T., Turkeltaub, P. E., & Zeiger, W. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1425-23.2023 · Cited by 51
Synthetic consciousness: the distributed adaptive control perspective
Verschure, P. F. M. J. (2016) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2015.0448 · Cited by 54
Tobyne, S. M., Somers, D. C., Brissenden, J. A., Michalka, S., Noyce, A. L., & Osher, D. E. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.007 · Cited by 50
Heckner, M. K., Cieslik, E. C., Eickhoff, S. B., Camilleri, J. A., Hoffstaedter, F., & Langner, R. (2020) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01616 · Cited by 53
Kim, H., Chey, J., & Lee, S. (2017) · Neuroscience Research · doi:10.1016/j.neures.2017.05.004 · Cited by 53
Jacoby, N., & Fedorenko, E. G. (2018) · Language Cognition and Neuroscience · doi:10.1080/23273798.2018.1525494 · Cited by 55
Self-citationIntonation guides sentence processing in the left inferior frontal gyrus
van der Burght, C. L., Goucha, T., Friederici, A. D., Kreitewolf, J., & Hartwigsen, G. (2019) · Cortex · doi:10.1016/j.cortex.2019.02.011 · Cited by 47
Direct impact of cognitive control on sentence processing and comprehension
Hsu, N. S., Kuchinsky, S. E., & Novick, J. M. (2020) · Language Cognition and Neuroscience · doi:10.1080/23273798.2020.1836379 · Cited by 57
Yin, D., Liu, W., Zeljic, K., Wang, Z., Lv, Q., Fan, M., Cheng, W., & Wang, Z. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.1476-16.2016 · Cited by 43
A synergistic workspace for human consciousness revealed by Integrated Information Decomposition
Luppi, A. I., Mediano, P. A. M., Rosas, F. E., Allanson, J. E., Pickard, J. D., Carhart-Harris, R. L., Williams, G. B., Craig, M. M., Finoia, P., Owen, A. M., et al. (2023) · eLife · doi:10.7554/elife.88173 · Cited by 120
Distinct Stages of Moment-to-Moment Processing in the Cinguloopercular and Frontoparietal Networks
Gratton, C., Neta, M., Sun, H., Ploran, E. J., Schlaggar, B. L., Wheeler, M. E., Petersen, S. E., & Nelson, S. M. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw092 · Cited by 48
Cieslik, E. C., Seidler, I., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.05.012 · Cited by 47
Dreßing, A., Nitschke, K., Kümmerer, D., Bormann, T., Beume, L.-A., Schmidt, C. S. M., Ludwig, V. M., Mader, I., Willmes, K., Rijntjes, M., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw383 · Cited by 51
Mandonnet, E., Cerliani, L., Siuda-Krzywicka, K., Poisson, I., Zhi, N., Volle, E., & de Schotten, M. T. (2017) · Neurochirurgie · doi:10.1016/j.neuchi.2017.03.003 · Cited by 50
What are reaction time indices of automatic imitation measuring?
Ramsey, R. (2018) · Consciousness and Cognition · doi:10.1016/j.concog.2018.08.006 · Cited by 51
Adaptive paradigms for mapping phonological regions in individual participants
Yen, M., DeMarco, A. T., & Wilson, S. M. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.040 · Cited by 47
Intrinsic functional connectivity is organized as three interdependent gradients
Zhang, J., Abiose, O., Katsumi, Y., Touroutoglou, A., Dickerson, B. C., & Barrett, L. F. (2019) · Scientific Reports · doi:10.1038/s41598-019-51793-7 · Cited by 47
Exploring distinct default mode and semantic networks using a systematic ICA approach
Jackson, R. L., Cloutman, L. L., & Ralph, M. A. L. (2019) · Cortex · doi:10.1016/j.cortex.2018.12.019 · Cited by 49
Barbieri, E., Mack, J. E., Chiappetta, B., Europa, E., & Thompson, C. K. (2019) · Cortex · doi:10.1016/j.cortex.2019.06.015 · Cited by 48
Branco, P., Seixas, D., & Castro, S. L. (2019) · Human Brain Mapping · doi:10.1002/hbm.24821 · Cited by 47
Age-Dependent Contribution of Domain-General Networks to Semantic Cognition
Martin, S., Saur, D., & Hartwigsen, G. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab252 · Cited by 46
Metadata
- Authors
- Fedorenko, E., Duncan, J., & Kanwisher, N.
- Affiliations
- McGovern Institute for Brain Research (US)
- MRC Cognition and Brain Sciences Unit (GB)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-09-23
- Volume
- 110
- Issue
- 41
- Pages
- 16616-16621
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3799302
- OpenAlex
- W2001896589
- Cited by
- 952
- References
- 99
- Citations by year
- 2026: 79 · 2025: 101 · 2024: 93 · 2023: 63 · 2022: 82 · 2021: 94 · 2020: 90 · 2019: 85 · 2018: 62 · 2017: 75 · 2016: 61 · 2015: 42 · 2014: 23 · 2013: 2
- FWCI
- 23.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- National Science Foundation (057522, 0904625)
- Ellison Medical Foundation
- Massachusetts Institute of Technology
- National Institutes of Health (5k99hd057522-02)
- McGovern Institute for Brain Research, Massachusetts Institute of Technology
- Medical Research Council
- National Eye Institute (R01EY013455)
- National Institute of Child Health and Human Development
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K99 HD-057522)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- domain generality, domain specificity, frontal cortex, parietal cortex, cognitive flexibility, arithmetic, working memory, cognitive inhibition, single-subject analysis, functional topography
- MeSH terms
- Adult, Brain Mapping, Cognition, Female, Frontal Lobe, Humans, Magnetic Resonance Imaging, Male, Massachusetts, Middle Aged, Neuropsychological Tests, Parietal Lobe
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