The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index; none of the 39 sources its claims cite is checked for support yet.
Functional specificity for high-level linguistic processing in the human brain
Open accessAbstract
Neuroscientists have debated for centuries whether some regions of the human brain are selectively engaged in specific high-level mental functions or whether, instead, cognition is implemented in multifunctional brain regions. For the critical case of language, conflicting answers arise from the neuropsychological literature, which features striking dissociations between deficits in linguistic and nonlinguistic abilities, vs. the neuroimaging literature, which has argued for overlap between activations for linguistic and nonlinguistic processes, including arithmetic, domain general abilities like cognitive control, and music. Here, we use functional MRI to define classic language regions functionally in each subject individually and then examine the response of these regions to the nonlinguistic functions most commonly argued to engage these regions: arithmetic, working memory, cognitive control, and music. We find little or no response in language regions to these nonlinguistic functions. These data support a clear distinction between language and other cognitive processes, resolving the prior conflict between the neuropsychological and neuroimaging literatures.
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Written from the paper’s full text.
TL;DR
Using fMRI, the authors functionally defined language regions in each subject and tested whether those regions respond to arithmetic, working memory, cognitive control, or music. They found little or no response to these nonlinguistic functions, supporting a clear distinction between language and other cognitive processes.
Key findings
- Across seven nonlinguistic tasks, language-sensitive ROIs showed little or no response; no other ROIs showed reliable responses to any nonlinguistic task after correction, except one left middle frontal gyrus (LMFG) ROI that responded significantly to verbal working memory.
- The music contrast produced some response in several language ROIs, but effects were weak overall and none survived correction for multiple comparisons.
- Whole-brain overlap analyses at the ROI-analysis threshold found no spatially systematic regions where language activations overlapped with any of the seven nonlinguistic tasks; with liberal thresholding, three overlap regions emerged, including posterior left inferior frontal gyrus (LIFG) overlap with verbal working memory in 85% of subjects and a similar region with Stroop in 71%.
- The authors conclude that most key cortical regions for high-level linguistic processing are not engaged by mental arithmetic, general working memory, cognitive control, or musical processing, with the LMFG as the main exception.
Methods
- Forty-eight right-handed native English speakers (31 females, ages 18–40) participated; each was run on a language localizer and one or more nonlinguistic tasks. Task-specific samples were: math n = 11, spatial WM n = 12, verbal WM n = 13, MSIT n = 15, vMSIT n = 12, Stroop n = 14, and music n = 12, with overlapping subjects across tasks.
- The language localizer contrasted reading sentences vs. pronounceable nonwords with a memory probe; nonlinguistic experiments contrasted harder vs. easier conditions for arithmetic, spatial WM, verbal WM, MSIT, vMSIT, and Stroop, and intact vs. scrambled music.
- fMRI data were collected on a 3-T Siemens Trio, analyzed with SPM5 and custom MATLAB scripts; language ROIs were defined per subject by intersecting group-level parcels with individual localizer maps thresholded at P < 0.001 uncorrected, and responses were estimated using cross-validation across runs.
Limitations
- The paper states that the investigated regions are not the only ones engaged in or necessary for language: language also requires auditory/visual and motor cortex, and domain-general frontal/parietal regions may be necessary for many linguistic functions.
- The paper states that the computations in the posterior LIFG overlap region remain an open question and that higher spatial resolution might reveal the apparent overlap to be artifactual due to proximity of language-sensitive and demanding-task regions.
- The paper notes that the localizer targets high-level linguistic processing and does not address other aspects of language such as sound-level processes; evident from the text, the whole-brain overlap findings required liberal thresholding, and per-task samples were small (11–15 participants) with overlapping subjects across experiments.
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Claims the paper makes
21 Own result · 14 Not checked yet · 12 Own interpretation · 4 Own method · 4 No basis given
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 response to intact music is barely above the fixation baseline (and lower than the response to the language localizer control task)”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“At the threshold used for the ROI analyses, no spatially systematic regions were detected in which language activations overlapped with any of the seven nonlinguistic tasks, confirming the overall picture of language specificity found in the ROI analyses.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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 response to intact music is barely above the fixation baseline (and lower than the response to the language localizer control task)”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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 current results show that most of the key cortical regions engaged in high-level linguistic processing are not engaged by mental arithmetic, general working memory, cognitive control, or musical processing, indicating a high degree of functional specificity in the brain regions that support language.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“[This threshold is not too stringent to discover true overlap when it exists; at the same threshold, we discovered robust overlap regions in the frontal and parietal lobes between Stroop and the multisource interference task (MSIT) cognitive control task in a subset of the subjects run on both tasks.]”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“One frontal language ROI left middle frontal gyrus (LMFG) showed a significant response to verbal working memory after correcting for the number of ROIs; this region is, thus, not specialized for sentence understanding.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
In the paper
“we find no hint of activation for either of the other two cognitive control tasks [the MSIT task (39) and its variant, verbal MSIT (vMSIT)]”
What the sources say
- Not checked yetcites [39] Bush G, Shin LM. The Multi-Source Interference Task: An fMRI task that reliably activates the cingulo-frontal-parietal cognitive/attention network. Nat Protoc. 2006;1:308–313. doi: 10.1038/nprot.2006.48. [DOI] [PubMed] [Google Scholar] source
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Furthermore, although this region does respond more strongly to intact than scrambled musical stimuli (consistent with some previous claims) (21), the response to intact music is barely above the fixation baseline (and lower than the response to the language localizer control task)”
What the sources say
- Not checked yetcites [21] Maess B, Koelsch S, Gunter TC, Friederici AD. Musical syntax is processed in Broca's area: An MEG study. Nat Neurosci. 2001;4:540–545. doi: 10.1038/87502. [DOI] [PubMed] [Google Scholar] source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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 third region, present in 85% of the subjects, emerged in the posterior part of our left inferior frontal gyrus (LIFG) language ROI and responded to both language and verbal WM”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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 music contrast did produce some response in several language ROIs (SI Text), suggesting possibly overlapping circuits; however, these effects were weak overall, and none survived correction for multiple comparisons.”
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 10
- Probably not a substantial claim. 8
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 music contrast did produce some response in several language ROIs (SI Text), suggesting possibly overlapping circuits; however, these effects were weak overall, and none survived correction for multiple comparisons.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
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
“Nevertheless, a complementary analysis shows that a portion of the LIFG language ROI is selective for high-level linguistic processing and not engaged in either verbal WM or Stroop (Fig. 4).”
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
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
“Because the activation patterns were similar across the two tasks, we collapsed the data from these two groups of participants for the current analyses.”
plainn = 4- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. 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
“Note that the brain regions investigated here are surely not the only ones engaged in or necessary for language processing.”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The order of conditions was counterbalanced; each condition was equally likely to appear in the earlier vs. later parts of each run and was as likely to follow every other condition as it was to precede it.”
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The resulting piece had component sounds similar to the intact music but lacked musical structure.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably 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
“These data support a clear distinction between language and other cognitive processes, resolving the prior conflict between the neuropsychological and neuroimaging literatures.”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, ROI analyses can obscure functional heterogeneity within an ROI or miss important overlapping regions outside the borders of the ROI.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“Of course, the question of the relationship between linguistic and nonlinguistic processes extends to other aspects of language (e.g., sound-level processes), which we are not targeting with the current language localizer task.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The responses to the sentences and nonwords conditions were estimated using cross-validation across the functional runs, and therefore, the data used to estimate the effects were always independent of the data used for ROI definition (46).”
What the sources say
- Not checked yetcites [46] Vul E, Kanwisher N. Begging the question: The non-independence error in fMRI data analysis. In: Hanson S, Bunzl M, editors. Foundational issues for human brain mapping. Cambridge, MA: MIT Press; 2010. pp. 71–91. [Google Scholar] source
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
In the paper
“and to be robust to changes in stimulus modality (visual/auditory) (see also ref. 32), specific stimuli, and task (passive reading vs. reading with a probe task, which is used here).”
What the sources say
- Not checked yetcites [32] Braze D, et al. Unification of sentence processing via ear and eye: An fMRI study. Cortex. 2011;47:416–431. doi: 10.1016/j.cortex.2009.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar] source
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“However, the neuroimaging claims are based largely on observations of activation for a nonlanguage task in or near a general brain region previously implicated in language (e.g., Broca's area), without a direct demonstration of overlap of linguistic and nonlinguistic activations in the same subjects.”
What the sources say
- Not checked yetcites [7] Dehaene S, Spelke E, Pinel P, Stanescu R, Tsivkin S. Sources of mathematical thinking: Behavioral and brain-imaging evidence. Science. 1999;284:970–974. doi: 10.1126/science.284.5416.970. [DOI] [PubMed] [Google Scholar] source
- Not checked yetcites [8] Novick JM, Trueswell JC, Thompson-Schill SL. Cognitive control and parsing: Reexamining the role of Broca's area in sentence comprehension. Cogn Affect Behav Neurosci. 2005;5:263–281. doi: 10.3758/cabn.5.3.263. [DOI] [PubMed] [Google Scholar] source
- Not checked yetcites [9] Levitin DJ, Menon V. Musical structure is processed in “language” areas of the brain: A possible role for Brodmann Area 47 in temporal coherence. Neuroimage. 2003;20:2142–2152. doi: 10.1016/j.neuroimage.2003.08.016. [DOI] [PubMed] [Google Scholar] source
- Not checked yetcites [10] Awh E, et al. Dissociation of storage and rehearsal in verbal working memory: Evidence from positron emission tomography. Psych Science. 1996;7:25–31. [Google Scholar] source
- Not checked yetcites [11] Badre D, Poldrack RA, Paré-Blagoev EJ, Insler RZ, Wagner AD. Dissociable controlled retrieval and generalized selection mechanisms in ventrolateral prefrontal cortex. Neuron. 2005;47:907–918. doi: 10.1016/j.neuron.2005.07.023. [DOI] [PubMed] [Google Scholar] source
- Not checked yetcites [12] Blumstein S. Reflections on the cognitive neuroscience of language. In: Gazzaniga M, editor. The Cognitive Neurosciences. Cambridge, MA: MIT Press; 2009. pp. 1235–1240. [Google Scholar]
- Not checked yetcites [13] Braver TS, et al. A parametric study of prefrontal cortex involvement in human working memory. Neuroimage. 1997;5:49–62. doi: 10.1006/nimg.1996.0247. [DOI] [PubMed] [Google Scholar] source
- Not checked yetcites [14] Bunge SA, Klingberg T, Jacobsen RB, Gabrieli JDE. A resource model of the neural basis of executive working memory. Proc Natl Acad Sci USA. 2000;97:3573–3578. doi: 10.1073/pnas.050583797. [DOI] [PMC free article] [PubMed] [Google Scholar] source
- Not checked yetcites [15] Cohen JD, et al. Activation of the prefrontal cortex in a nonspatial working memory task with functional MRI. Hum Brain Mapp. 1994;1:293–304. doi: 10.1002/hbm.460010407. [DOI] [PubMed] [Google Scholar] source
- Not checked yetcites [16] Fadiga L, Craighero L, D'Ausilio A. Broca's area in language, action, and music. Ann N Y Acad Sci. 2009;1169:448–458. doi: 10.1111/j.1749-6632.2009.04582.x. [DOI] [PubMed] [Google Scholar] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“ROI-based analyses afford great statistical power and reduce the blurring of functional activations inevitable in group analyses.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“(here and throughout the study, responses were estimated using data from left-out runs not used for defining the ROIs).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper relies on this without support.
The individual-subject overlap analysis strategy has almost never been applied in neuroimaging investigations of high-level linguistic processing.
“a data analysis strategy that has almost never been applied in neuroimaging investigations of high-level linguistic processing”
The paper relies on this without support.
Most claims about the overlap between linguistic and nonlinguistic processes have concerned syntactic processing.
“However, most claims about the overlap between linguistic and nonlinguistic processes have concerned (i) syntactic processing, which is included in our functional contrast, and (ii) brain regions, which are robustly activated by our localizer (e.g., Broca's area).”
The paper relies on this without support.
Most claims about the overlap between linguistic and nonlinguistic processes have concerned brain regions robustly activated by the language localizer.
“However, most claims about the overlap between linguistic and nonlinguistic processes have concerned (i) syntactic processing, which is included in our functional contrast, and (ii) brain regions, which are robustly activated by our localizer (e.g., Broca's area).”
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 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., 2011
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
“Neuroimaging studies have consistently shown that the language network -a set of brain regions responsible for language comprehension and production -remains largely inactive during various reasoning tasks”
From Training Large Language Models to Reason in a Continuous Latent Space (2024) · cites this paper as Fedorenko et al., 2011
Experimental — accuracy not yet measuredIn the citing paper
“There is little doubt that perisylvian regions are more involved in processing language inputs than some other brain systems (see, e.g., Blank & Fedorenko, 2017), and may be particularly involved in language tasks (e.g., Fedorenko, Behr, & Kanwisher, 2011).”
From Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension (2018) · cites this paper as Fedorenko, Behr, & Kanwisher, 2011
In the citing paper
“it responds reliably when people listen to, read, or generate sentences, but not when they perform arithmetic tasks, engage in logical reasoning, understand computer programs, listen to music, categorize objects or events, reason about people’s mental states, or process non-verbal communicative information like facial expressions or gestures [37, 41, 42, 43, 44, 45, 46, 47, 48].”
From Dissociating language and thought in large language models (2024) · cites this paper as [37]
In the citing paper
“is sensitive to linguistic regularities at multiple levels: from phonological/sub-lexical [36] to phrase/sentence level [37, 38]”
From Dissociating language and thought in large language models (2024) · cites this paper as [37]
Citations
Cites
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
Common regions of the human frontal lobe recruited by diverse cognitive demands
Duncan, J., & Owen, A. M. (2000) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01633-7 · Cited by 2,498
Towards a neural basis of auditory sentence processing
Friederici, A. D. (2002) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01839-8 · Cited by 2,231
Hickok, G., & Poeppel, D. (2004) · Cognition · doi:10.1016/j.cognition.2003.10.011 · Cited by 2,212
The Architecture of Cognitive Control in the Human Prefrontal Cortex
Koechlin, É., Ody, C., & Kouneiher, F. (2003) · Science · doi:10.1126/science.1088545 · Cited by 1,939
Contributions of memory circuits to language: the declarative/procedural model
Ullman, M. T. (2004) · Cognition · doi:10.1016/j.cognition.2003.10.008 · Cited by 1,893
The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour
Duncan, J. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.004 · Cited by 1,846
Sources of Mathematical Thinking: Behavioral and Brain-Imaging Evidence
Dehaene, S., Spelke, E., Pinel, P., Stanescu, R., & Tsivkin, S. (1999) · Science · doi:10.1126/science.284.5416.970 · Cited by 1,739
A Parametric Study of Prefrontal Cortex Involvement in Human Working Memory
Braver, T. S., Cohen, J. D., Nystrom, L. E., Jonides, J., Smith, E. E., & Noll, D. C. (1997) · NeuroImage · doi:10.1006/nimg.1996.0247 · Cited by 1,694
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
Research works printed but not linked: 1
- P Broca, [Notes on the seat of the faculty of articulate language, followed by an observation of aphemia. Bull Soc Anat Paris 6, 330–357, French. (1861).
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Self-citationHosseini, E. A., Schrimpf, M., Zhang, Y., Bowman, S., Zaslavsky, N., & Fedorenko, E. (2024) · Neurobiology of Language · doi:10.1162/nol_a_00137 · Cited by 63
“…selected the checkpoint with the best perplexity on the validation set and tested how well the model representations capture human neural (fMRI) responses to sentences in the language-selective network (Fedorenko et al., 2011) and human behavioral responses in a self-paced reading task (Figure 1D).”
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“We also examined the specificity of this relationship by considering another network important for high-level cognition – the fronto-temporal language-selective network (Fedorenko et al., 2011).”
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LIEBERMAN, P. H. (2012) · Journal of Phonetics · doi:10.1016/j.wocn.2012.04.001 · Cited by 68
Language and music: sound, structure, and meaning
Slevc, L. R. (2012) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1186 · Cited by 76
“Still, so far only two fMRI studies have directly compared neural activation to language and music in the same participants, and both have found little evidence for overlap.(81,82) This lack of overlap has been taken to support largely independent neural networks for linguistic and musical syntactic processing, howeve…”
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“Each trial lasted 8 s (see Fedorenko et al., 2011, for details).”
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Lane, C., Kanjlia, S., Richardson, H., Fulton, A., Omaki, A., & Bedny, M. (2017) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01045 · Cited by 58
The Neurobiology of Agrammatic Sentence Comprehension: A Lesion Study
Rogalsky, C., LaCroix, A. N., Chen, K., Anderson, S. W., Damásio, H., Love, T. E., & Hickok, G. S. (2017) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01200 · Cited by 68
“…Broca’s area in sentence processing have included a memory task (Blank, Balewski, Mahowald & Fedorenko, 2016; Fedorenko, Hsieh, Nieto-Castanon, Whitfield-Gabrieli & Kanwisher, 2010; Fedorenko et al. 2011, Fedorenko, Duncan & Kanwisher, 2012a; Fedorenko, Nieto-Castanon & Kanwisher, 2012b, 2012c).”
Neural Correlates of Subliminal Language Processing
Axelrod, V., Bar, M., Rees, G. E., & Yovel, G. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu022 · Cited by 53
“Schematic fl ow of one block with meaningful sentence in CFS invisible experiment.”
No evidence of theory of mind reasoning in the human language network
Shain, C., Paunov, A., Chen, X., et al. (2022) · bioRxiv · doi:10.1101/2022.07.18.500516 · Cited by 56
“This task is described in detail in Fedorenko et al. (2010) and subsequent studies from the Fedorenko lab (e.g. Fedorenko et al. 2011, 2020; Blank et al. 2014; Blank, Balewski, et al. 2016a; Blank, Duff, et al. 2016b ; Pritchett et al. 2018; Paunov et al. 2019; Shain et al. 2020, among others;…”
Self-citationBoth Default and Multiple-Demand Regions Represent Semantic Goal Information
Wang, X.-Y., Gao, Z., Smallwood, J., et al. (2020) · Journal of Neuroscience · doi:10.1101/2020.07.09.196048 · Cited by 54
“In the second session, participants completed easy and hard spatial working memory and arithmetic tasks (from Blank, Kanwisher, & Fedorenko, 2014; Fedorenko et al., 2011, 2013) designed to localise MDN and DMN.”
MethodBhandari, A., Gagne, C., & Badre, D. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01291 · Cited by 79
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
“Language comprehension involves an interplay between regions that are specifically important for linguistic processing, and multiple demand regions (Fedorenko et al., 2011, 2012, 2013; Fedorenko, 2014; Fedorenko and Thompson-Schill, 2014).”
BackgroundWiener, M., Lee, Y. S., Lohoff, F. W., & Coslett, H. B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.019 · Cited by 56
“A shortcoming of group averaging of fMRI performance is that individual differences in activation patternswill not be detected (Fedorenko et al., 2011).”
BackgroundHigh-level language processing regions are not engaged in action observation or imitation
Pritchett, B., Hoeflin, C., Koldewyn, K., Dechter, E., & Fedorenko, E. G. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00222.2018 · Cited by 46
Self-citationDistributed Sensitivity to Syntax and Semantics throughout the Language Network
Shain, C., Kean, H., Casto, C., Lipkin, B., Affourtit, J., Siegelman, M., Mollica, F., & Fedorenko, E. G. (2024) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02164 · Cited by 69
“However, the exact locations, shapes, and sizes of language areas vary between individuals (Lipkin et al., 2022; Fedorenko et al., 2010, 2011).”
BackgroundResultInfluentialSelf-citationProsodic Structure as a Parallel to Musical Structure
Heffner, C. C., & Slevc, L. R. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01962 · Cited by 50
Neural Encoding and Decoding With Distributed Sentence Representations
Sun, J., Wang, S., Zhang, J., & Zong, C. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3027595 · Cited by 44
“Following [20], we pick four brain networks: language networks [39], visual networks [36], default mode network (DMN) [38], and multiple demand (MD) network.”
BackgroundJacoby, N., & Fedorenko, E. G. (2018) · Language Cognition and Neuroscience · doi:10.1080/23273798.2018.1525494 · Cited by 55
“Subjects had to keep track of four (Easy condition) or eight (Hard condition) locations in a 3 × 4 grid (Fedorenko et al., 2011).”
BackgroundMethodSelf-citationStimulating 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
“Domain-specific networks encompass brain regions that are highly specialized for particular types of demand, for example, motor or language processes (Varley et al., 2005; Fedorenko et al., 2011; Monti et al., 2012).”
BackgroundComprehension of computer code relies primarily on domain-general executive resourcesPreprint
Ivanova, A. A., Srikant, S., Sueoka, Y., Kean, H., Dhamala, R., O’Reilly, U.-M., Bers, M. U., & Fedorenko, E. G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.17605/osf.io/9jfn5 · Cited by 5
“The lack of the language system engagement during code comprehension adds to the body of work that demonstrates high input selectivity of these regions (Fedorenko et al., 2011; Jouravlev et al., 2019; Monti et al., 2009, 2012; Pritchett et al., 2018).”
BackgroundMethodInfluentialSelf-citationStefaniak, J. D., Alyahya, R. S. W., & Ralph, M. A. L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117960 · Cited by 64
Evidence for Shared Cognitive Processing of Pitch in Music and Language
Perrachione, T. K., Fedorenko, E. G., Vinke, L. N., Gibson, E. A. F., & Dilley, L. C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073372 · Cited by 50
Self-citationRyskin, R. A., Lévy, R., & Fedorenko, E. G. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.107258 · Cited by 79
Self-citationChen, L., Goucha, T., Männel, C., Friederici, A. D., & Zaccarella, E. (2021) · Human Brain Mapping · doi:10.1002/hbm.25432 · Cited by 39
“Given that Broca's area contains BA 44 and BA 45, and these are reported to have functional (e.g., Fedorenko et al., 2011; Friederici, 2011, 2017; Goucha & Friederici, 2015; Grodzinsky & Friederici, 2006; Hagoort, 2005; Hagoort & Indefrey, 2014; Matchin et al., 2017; Pallier et al., 2011; Tyler et…”
BackgroundThe evolution of language and thought.
LIEBERMAN, P. H. (2016) · PubMed · doi:10.4436/jass.94029 · Cited by 51
Deen, B., Saxe, R. R., & Bedny, M. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00807 · Cited by 49
Left Ventrolateral Prefrontal Cortex in Processing of Words and Sentences
Nozari, N., & Thompson‐Schill, S. L. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-407794-2.00046-8 · Cited by 78
A syntax–lexicon trade-off in language production
Rezaii, N., Mahowald, K., Ryskin, R. A., Dickerson, B. C., & Gibson, E. A. F. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2120203119 · Cited by 41
“a similar mechanism of selection and competitor inhibition, it is plausible that cognitive control—possibly language-specific (94)—plays a role in syntactic selection as well.”
BackgroundThe LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant UnitsPreprint
AlKhamissi, B., Tuckute, G., Bosselut, A., & Schrimpf, M. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2411.02280
“Consistent with human neuroscience (Fedorenko et al., 2011; Amal-ric and Dehaene, 2019; Ivanova et al., 2020), LLM language units are particularly selective for nat-ural language compared to arithmetic equations, C++ code, or random sequences of characters (all matching the number of tokens and…”
Cross-domain correlation in pitch perception, the influence of native language
Chen, A., Liu, L., & Kager, R. (2016) · Language Cognition and Neuroscience · doi:10.1080/23273798.2016.1156715 · Cited by 52
Bidirectional Syntactic Priming across Cognitive Domains: From Arithmetic to Language and Back
Scheepers, C., & Sturt, P. (2014) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2013.873815 · Cited by 45
“In a functional magnetic resonance imaging (fMRI) study, Fedorenko, Behr, and Kanwisher (2011) found little or no response by functionally localized language regions to sequential mathematical tasks such as summing four consecutive numbers.”
BackgroundThe role of the left prefrontal cortex in sentence-level semantic integration
Zhu, Z., Feng, G., Zhang, J. X., Li, G., Li, H., & Wang, S. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.060 · Cited by 42
“Similar to the present study, Fedorenko et al. (2011) also found language specific activation in LIFG during sentence comprehension, when compared with tasks engaging cognitive control and working memory load.”
Hauptman, M., Blank, I., & Fedorenko, E. (2022) · bioRxiv · doi:10.1101/2022.03.08.481056 · Cited by 42
“literal conditions across diverse phenomena with respect to three candidate networks: the language-selective network (Fedorenko et al., 2011), which supports language processing, the Theory of Mind (ToM) network (Saxe &”
BackgroundSelf-citationPerceived communicative intent in gesture and language modulates the superior temporal sulcus
Redcay, E., Velnoskey, K. R., & Rowe, M. L. (2016) · Human Brain Mapping · doi:10.1002/hbm.23251 · Cited by 49
“We also chose this task as it has been used previously as a language localizer to address similar questions of neural overlap [see Fedorenko et al., 2011].”
BackgroundMethodInfluentialLaCroix, A. N., Diaz, A. F., & Rogalsky, C. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01138 · Cited by 65
“…been used in this literature, including discrimination, anomaly/error detection, (Koelsch et al., 2005; Carrus et al., 2013), grammatical acceptability (Patel et al., 1998a; Patel, 2008), final-word lexical decision (Hoch et al., 2011), and memory/comprehension tasks (Fedorenko et al., 2009, 2011).”
BackgroundMethodDynamic Functional Organization of Language
Blumstein, S. E., & Amso, D. (2013) · Perspectives on Psychological Science · doi:10.1177/1745691612469021 · Cited by 40
“In a recent study, Federenko, Behr, and Kanwisher (2011) used a language localizer to map out language regions on an individual subject basis.”
BackgroundDirect 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
How the brain makes sense beyond the processing of single words – An MEG study
Hultén, A., Schoffelen, J., Uddén, J., Lam, N. H. L., & Peter Hagoort, A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.035 · Cited by 45
“To date, the sentences and word list paradigm with written words has mainly been used in hemodynamic studies (Fedorenko et al., 2011; Friederici et al., 2000; Humphries et al., 2005, 2006; Jobard et al., 2007; Snijders et al., 2009; Stowe et al., 1998; Vandenberghe et al., 2002; Xu et al., 2005).”
The shared neural basis of music and language
Yu, M., Xu, M., Li, X., Chen, Z., Song, Y., & Jia Liu, B. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.06.003 · Cited by 47
Jaffe‐Dax, S., Kimel, E., & Ahissar, M. (2018) · eLife · doi:10.7554/elife.30018 · Cited by 40
“The superior temporal cortex is known to be involved in a broad range of auditory tasks, including simple tone discrimination (Daikhin and Ahissar, 2015), language (Fedorenko et al., 2010) and music (Fedorenko et al., 2011), and even social tasks (e.g. Deen et al., 2015).”
BackgroundSpeech-accompanying gestures are not processed by the language-processing mechanisms
Jouravlev, O., Zheng, D., Balewski, Z., Le Arnz Pongos, A., Levan, Z., Goldin-Meadow, S., & Fedorenko, E. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.107132 · Cited by 39
“We leveraged our knowledge about the core language network – a set of frontal and temporal brain areas that selectively support high-level language processing (Fedorenko et al., 2011), including lexico-semantic and combinatorial processing (Fedorenko et al.”
Self-citationFedorenko, E. G., & Shain, C. (2021) · Current Directions in Psychological Science · doi:10.1177/09637214211046955 · Cited by 48
“The language network robustly bears out this prediction (e.g., Fedorenko et al., 2011).”
BackgroundSelf-citationLow-frequency neural activity reflects rule-based chunking during speech listening
Jin, P., Lu, Y., & Ding, N. (2020) · eLife · doi:10.7554/elife.55613 · Cited by 44
“There are also studies, however, arguing for domain-specific sequence processing mechanisms, especially for the processing of language (Fedorenko et al., 2011).”
BackgroundQi, Z., Han, M., Wang, Y., Angeles, C. D. L., Liu, Q., Garel, K.-L. A., Chen, E. S., Whitfield, S., Gabrieli, J. D. E., & Perrachione, T. K. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.008 · Cited by 52
“It is possible that as the phonological analysis becomes necessary for higher-level language processing, the acoustic analysis of speech sounds supported by the right hemisphere might no longer be optimal (Blumstein et al., 2005; Hickok and Poeppel, 2007; Fedorenko et al., 2011; Friederici, 2011; Myers, 2014).”
BackgroundBemis, D. K., & Liina Pylkkänen, A. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00583 · Cited by 42
“All three of these regions have been implicated in combinatorial linguistic processing by a substantial number of studies (Bottini et al., 1994; Humphries et al., 2001; Vandenberghe et al., 2002; Mar, 2004; Lau et al., 2008; Fedorenko et al., 2011; Pallier et al., 2011), and thus these results provide a basis against…”
BackgroundResultInfluentialAn approach to separating the levels of hierarchical structure building in language and mathematics
Makuuchi, M., Bahlmann, J., & Friederici, A. D. (2012) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0095 · Cited by 35
Hauptman, M., Blank, I., & Fedorenko, E. (2023) · Cortex · doi:10.1016/j.cortex.2023.01.013 · Cited by 44
Self-citationPronouns reactivate conceptual representations in human hippocampal neurons
Dijksterhuis, D. E., Self, M. W., Possel, J. K., Peters, J. C., van Straaten, E. C. W., Idema, S., Baayen, J. C., van der Salm, S. M. A., Aarnoutse, E. J., van Klink, N. E. C., et al. (2024) · Science · doi:10.1126/science.adr2813 · Cited by 36
Assem, M., Blank, I., Mineroff, Z., Ademoglu, A., & Fedorenko, E. G. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/110270 · Cited by 3
“To test whether the brain-behavior relationship we observed is selective to the MD network, we considered another large-scale neural network: the fronto-temporal languageselective network in the left hemisphere (Fedorenko et al., 2011) (Figure 5A).”
InfluentialSelf-citationBourguignon, N. J. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.09.008 · Cited by 47
Word-to-text integration: Message level and lexical level influences in ERPs
Stafura, J. Z., & Perfetti, C. A. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.09.012 · Cited by 38
From Language to Cognition: How LLMs Outgrow the Human Language Network
AlKhamissi, B., Tuckute, G., Tang, Y., et al. (2025) · Conference on Empirical Methods in Natural Language Processing · doi:10.48550/arxiv.2503.01830 · Cited by 37
“…compared to various non-linguistic inputs and tasks, such as music perception (Fedorenko et al., 2012; Chen et al., 2023) or arithmetic computation (Fedorenko et al., 2011; Monti et al., 2012) (for review, see (Fedorenko et al., 2024)) and the language network only shows weak responses when…”
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
Self-citationFrankland, S. M., & Greene, J. (2019) · Cerebral Cortex · doi:10.31234/osf.io/65tn7 · Cited by 35
Giavazzi, M., Daland, R., Palminteri, S., Peperkamp, S., Brugières, P., Jacquemot, C., Schramm, C., de Langavant, L. C., & Bachoud‐Lévi, A. (2018) · Cortex · doi:10.1016/j.cortex.2018.08.031 · Cited by 45
Prefrontal and Hippocampal Structure Predict Statistical Learning Ability in Early Childhood
Finn, A., Kharitonova, M., Holtby, N., & Sheridan, M. (2019) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01342 · Cited by 34
Disentangling neuroplasticity mechanisms in post-stroke language recovery
Billot, A., & Kiran, S. (2024) · Brain and Language · doi:10.1016/j.bandl.2024.105381 · Cited by 37
“While in healthy individuals cognitive control and language networks show dissociated patterns of activation during simple language tasks (Fedorenko et al., 2011), multiple studies have suggested that bilateral domain-general cognitive control networks are engaged alongside the language network in…”
Neural basis of the crossmodal correspondence between auditory pitch and visuospatial elevation
McCormick, K., Lacey, S., Stilla, R. F., Nygaard, L. C., & Sathian, K. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.02.029 · Cited by 38
“Thus, the semantic localizer essentially replicated the previously reported language network (Fedorenko et al., 2010, 2011).”
BackgroundMethodResultInfluentialSentence processing selectivity in Broca's area: evident for structure but not syntactic movement
Rogalsky, C., Almeida, D., Sprouse, J., & Hickok, G. S. (2015) · Language Cognition and Neuroscience · doi:10.1080/23273798.2015.1066831 · Cited by 35
Nozari, N., Trueswell, J., & Thompson-Schill, S. L. (2016) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1068-8 · Cited by 33
Neural populations in the language network differ in the size of their temporal receptive windows
Regev, T. I., Casto, C., Hosseini, E. A., Adamek, M., Ritaccio, A. L., Willie, J. T., Brunner, P., & Fedorenko, E. G. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01944-2 · Cited by 31
“In particular, clear separation exists between the language-processing system 7 and both (1) lower-level perceptual areas and (2) higher-level cognitive areas (see ref.”
BackgroundSelf-citationAnderson, E. D., & Barbey, A. K. (2022) · Human Brain Mapping · doi:10.1002/hbm.26164 · Cited by 42
“, 2020) generated from experimental data via a watershed method (Fedorenko et al., 2011).”
MethodPrefrontal cortex supports speech perception in listeners with cochlear implants
Sherafati, A., Dwyer, N. Y., Bajracharya, A., Hassanpour, M. S., Eggebrecht, A. T., Firszt, J. B., Culver, J. P., & Peelle, J. E. (2022) · eLife · doi:10.7554/elife.75323 · Cited by 42
Matchin, W., & Wood, E. A. (2020) · Cerebral Cortex Communications · doi:10.1093/texcom/tgaa029 · Cited by 37
The ventrolateral prefrontal cortex facilitates processing of sentential context to locate referents
Nozari, N., Mirman, D., & Thompson‐Schill, S. L. (2016) · Brain and Language · doi:10.1016/j.bandl.2016.04.006 · Cited by 69
Agrammatic output in non-fluent, including Broca’s, aphasia as a rational behavior
Fedorenko, E. G., Ryskin, R. A., & Gibson, E. A. F. (2022) · Aphasiology · doi:10.1080/02687038.2022.2143233 · Cited by 36
“, 2020)—in core linguistic processes like lexical access and semantic/syntactic composition, showing that such computations are instead carried out within the language-specific cortical areas (Fedorenko et al., 2011).”
BackgroundInfluentialSelf-citationParallel systems for social and spatial reasoning within the cortical apexPreprint
Deen, B., & Freiwald, W. A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.23.461550 · Cited by 35
The impact of spelling regularity on handwriting production: A coupled fMRI and kinematics study
Palmis, S., Velay, J.-L., Fabiani, E., Nazarian, B., Anton, J.-L., Habib, M., Kandel, S., & Longcamp, M. (2019) · Cortex · doi:10.1016/j.cortex.2018.11.024 · Cited by 40
Darda, K. M., Butler, E. E., & Ramsey, R. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01261 · Cited by 31
“The hard > easy contrast has been found to robustly activate regions of the MD network (Fedorenko et al., 2011, 2013).”
BackgroundMethodSmith, D. M., Perez, D. C., Porter, A., Dworetsky, A., & Gratton, C. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2020.12.004 · Cited by 31
The emergence of long-range language network structural covariance and language abilities
Qi, T., Schaadt, G., Cafiero, R., Bräuer, J., Skeide, M. A., & Friederici, A. D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.014 · Cited by 31
Semantic conflicts are resolved differently by adults with and without ADHD
Segal, D., Mashal, N., & Shalev, L. (2015) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2015.09.024 · Cited by 29
The human social cognitive network contains multiple regions within the amygdala
Edmonds, D., Salvo, J. J., Anderson, N. L., Lakshman, M., Yang, Q., Kay, K., Zelano, C., & Braga, R. M. (2024) · Science Advances · doi:10.1126/sciadv.adp0453 · Cited by 35
“For instance, it was noted that, even in group-averaged estimates, which blur over individual differences ( 50 – 53 ), there are hints of substructure within the canonical DN ( 43 , 54 – 61 ); ToM tasks tend to activate a more anterior region of the inferior parietal lobe at or near the…”
Functional dissociation of the language network and other cognition in early childhood
Hiersche, K. J., Schettini, E., Li, J., & Saygin, Z. M. (2024) · Human Brain Mapping · doi:10.1002/hbm.26757 · Cited by 26
“Language function is supported by a domain-specific, left-lateralized, frontotemporal language network (Fedorenko et al., 2010, 2011; Ojemann, 1991; Vigneau et al., 2006), that is selective for the semantic and syntactic properties of language (Fedorenko et al., 2010).”
BackgroundThe State of Cognitive Control in Language Processing
Ness, T., Langlois, V. J., Kim, A. E., & Novick, J. M. (2023) · Perspectives on Psychological Science · doi:10.1177/17456916231197122 · Cited by 40
“Although the LIFG has long been associated with syntactic function in particular (e.g., Fedorenko et al., 2011; Stromswold et al., 1996), several studies find that the LIFG is engaged by the presence of representational conflict, even when syntactic processing demands do not vary.”
Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language
Ellis, K. (2023) · neural information processing systems · doi:10.52202/075280-0577 · Cited by 4
Bansal, R., & Peterson, B. (2021) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2021.12.001 · Cited by 28
“Biologically valid MRI findings typically form clusters of voxels within the brain,[24] because the adjoining and interconnected cellular elements in tissues that support a given information processing function are considerably larger than a voxel[34, 35].”
BackgroundComplementary hemispheric lateralization of language and social processing in the human brain.
Rajimehr, R., Firoozi, A., Rafipoor, H., et al. (2021) · Cell Reports · doi:10.21203/rs.3.rs-808005/v1 · Cited by 28
“This cognitive process is mediated by a network of cortical areas in lateral temporal and lateral prefrontal cortices (Friederici, 2011), which are collectively involved in language comprehension (Fedorenko et al., 2011) and language production (Sahin et al., 2009).”
BackgroundSalvo, J. J., Holubecki, A. M., & Braga, R. M. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2021.05.003 · Cited by 30
Tuckute, G., Paunov, A., Kean, H. H., Small, H., Mineroff, Z., Blank, I., & Fedorenko, E. (2021) · bioRxiv · doi:10.1101/2021.05.28.446230 · Cited by 28
“In NT individuals, math and language draw on distinct networks (e.g., Varley et al., 2005; Fedorenko et al., 2011; Monti et al., 2012; Amalric & Dehaene, 2019) but i) math processing is generally left-lateralized (Monti et al.”
BackgroundSelf-citationSmith, D. M., Perez, D. C., Porter, A., Dworetsky, A., & Gratton, C. (2020) · Current Opinion in Behavioral Sciences · doi:10.31234/osf.io/9e28n · Cited by 1
Camerino, I., Sierpowska, J., Reid, A., Meyer, N. H., Tuladhar, A. M., Kessels, R. P. C., de Leeuw, F., & Piai, V. (2020) · Human Brain Mapping · doi:10.1002/hbm.25273 · Cited by 32
Meier, E. L., Johnson, J. P., Pan, Y., & Kiran, S. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101919 · Cited by 29
Hugdahl, K., Bereśniewicz, J., Kazimierczak, K., Kompus, K., Westerhausen, R., Ersland, L., Grüner, R., & Specht, K. (2019) · PLoS ONE · doi:10.1371/journal.pone.0218358 · Cited by 31
Measuring and Modeling Nonlinear Interactions Between Brain Regions with fMRI
Anzellotti, S., Fedorenko, E., Kell, A. J. E., et al. (2016) · bioRxiv · doi:10.1101/074856 · Cited by 27
Self-citation‘Syntactic Perturbation’ During Production Activates the Right IFG, but not Broca’s Area or the ATL
Matchin, W., & Hickok, G. S. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00241 · Cited by 26
“The sentence > list contrast in comprehension occasionally activates Broca’s area (Bedny et al., 2011; Fedorenko et al., 2011; Pallier et al., 2011), but these effects are much less consistent than for the ATL (Rogalsky and Hickok, 2011).”
BackgroundMeyer, L., Obleser, J., Kiebel, S. J., & Friederici, A. D. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00523 · Cited by 24
“In general, this is in line with the previously suggested independence of prefrontal argument – order-related brain activity from working memory processes during sentence processing (Caplan et al., 2000; Fedorenko et al., 2011).”
BackgroundResultA sensitive period in the neural phenotype of language in blind individuals
Pant, R., Kanjlia, S., & Bedny, M. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100744 · Cited by 29
Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
Nakai, T., & Sakai, K. L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0111439 · Cited by 27
The small and efficient language network of polyglots and hyper-polyglots
Jouravlev, O., Mineroff, Z., Blank, I., et al. (2019) · bioRxiv · doi:10.1101/713057 · Cited by 24
“This result argues against ubiquitous between-group differences in information processing, and is in line with prior work that has suggested that the language network is functionally distinct from other high-level large-scale networks (e.g., Blank et al., 2014; Fedorenko et al., 2011; Fedorenko & Varley, 2016; Minerof…”
ResultSelf-citationMeier, E. L., Johnson, J. P., & Kiran, S. (2018) · Cortex · doi:10.1016/j.cortex.2018.08.006 · Cited by 33
Bulut, T. (2023) · Brain and Behavior · doi:10.1002/brb3.3046 · Cited by 26
“Specifically, superior-posterior parts of the left IFG were found to be shared between domain-specific (language) and domain-general (verbal working memory and cognitive control) functions (Fedorenko et al., 2011).”
BackgroundMethodInfluentialSpeech and music recruit frequency-specific distributed and overlapping cortical networksPreprint
Rietmolen, N. T., Mercier, M. R., Trébuchon, A., Morillon, B., & Schön, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.08.511398 · Cited by 4
“…claims for a clear distinction between brain regions exclusively dedicated to language versus other cognitive processes (Chen et al., 2023; Fedorenko et al., 2011; Fedorenko & Blank, 2020; Friederici, 2020) and for the existence of specific and separate neural populations for speech, music, and…”
BackgroundInfluentialQuantitative MRI reveals differences in striatal myelin in children with DLD
Krishnan, S., Cler, G. J., Smith, H. J., Willis, H. E., Asaridou, S. S., Healy, M. P., Papp, D., & Watkins, K. E. (2022) · eLife · doi:10.7554/elife.74242 · Cited by 42
“15 the speech and language network (Ayyash et al., 2021; Fedorenko et al., 2011; Hickok & Poeppel, 2007; Rauschecker & Scott, 2009), and ventral sensorimotor cortex and insula are regions that are clearly implicated in speech motor control (Bouchard et al.”
BackgroundMalik-Moraleda, S., Ayyash, D., Gallée, J., Affourtit, J., Hoffmann, M., Mineroff, Z., Jouravlev, O., & Fedorenko, E. G. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.28.454040 · Cited by 21
“Each trial lasted 8 s (see (Fedorenko et al., 2011) for the timing details).”
BackgroundMethodResultInfluentialSelf-citationSimilar neural networks respond to coherence during comprehension and production of discourse
Morales, M., Patel, T., Tamm, A., Pickering, M. J., & Hoffman, P. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab485 · Cited by 23
“This aligns with the general view that cognitive control at the higher levels of language processing draws on specific neural resources distinct from those engaged in other cognitive domains (Fedorenko et al. 2011; Mineroff et al. 2018).”
BackgroundGene Expression Correlates of the Cortical Network Underlying Sentence Processing
Kong, X., Tzourio‐Mazoyer, N., Joliot, M., Fedorenko, E. G., Liu, J., Fisher, S. E., & Francks, C. (2020) · Neurobiology of Language · doi:10.1162/nol_a_00004 · Cited by 24
Self-citationFaroqi‐Shah, Y., Sebastian, R., & Woude, A. V. (2018) · Human Brain Mapping · doi:10.1002/hbm.24334 · Cited by 29
Metadata
- Authors
- Fedorenko, E., Behr, M. K., & Kanwisher, N.
- Affiliations
- Massachusetts Institute of Technology (US)
- Brain and Cognitive Sciences Department and
- McGovern Institute for Brain Research (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-09
- Volume
- 108
- Issue
- 39
- Pages
- 16428-16433
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3182706
- OpenAlex
- W2096462008
- Semantic Scholar
- b62b60be4fe51188d90a27dd9fc695c924a55b0b
- Cited by
- 595
- References
- 0
- Citations by year
- 2026: 43 · 2025: 52 · 2024: 75 · 2023: 42 · 2022: 47 · 2021: 61 · 2020: 38 · 2019: 32 · 2018: 38 · 2017: 33 · 2016: 34 · 2015: 35 · 2014: 22 · 2013: 24 · 2012: 17
- FWCI
- 10.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- Massachusetts Institute of Technology
- National Institutes of Health (5k99hd057522-02)
- McGovern Institute for Brain Research, Massachusetts Institute of Technology
- 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 › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Keywords
- language lateralization, functional specificity, language regions, arithmetic, working memory, cognitive control, music processing, domain specificity
- MeSH terms
- Brain, Female, Humans, Linguistics, Magnetic Resonance Imaging, Male, Speech
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 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
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