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Fedorenko, Evelina (13)
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McGovern Institute for Brain Research at MIT (4)
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2021 (19)
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Simple Search
Hits 1 – 19 of 19
1
An ERP index of real-time error correction within a noisy-channel framework of human communication.
Ryskin, Rachel
;
Stearns, Laura
;
Bergen, Leon
. - : eScholarship, University of California, 2021
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2
Syntactic dependencies correspond to word pairs with high mutual information
Futrell, Richard
;
Qian, Peng
;
Gibson, Edward A
...
In: Association for Computational Linguistics (2021)
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3
The Language Network is Recruited but Not Required for Nonverbal Event Semantics
Ivanova, Anna A
;
Mineroff, Zachary
;
Zimmerer, Vitor
...
In: MIT Press (2021)
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4
Breakdowns in Informativeness of Naturalistic Speech Production in Primary Progressive Aphasia
Gallée, Jeanne
;
Cordella, Claire
;
Fedorenko, Evelina G
...
In: MDPI (2021)
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5
Lack of selectivity for syntax relative to word meanings throughout the language network
Blank, Idan Asher
;
Siegelman, Matthew
;
Mineroff, Zachary A
...
In: PMC (2021)
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6
Neural encoding and production of functional morphemes in the posterior temporal lobe
Lee, Daniel K
;
Fedorenko, Evelina
;
Simon, Mirela V
...
In: Nature (2021)
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7
Syntactic dependencies correspond to word pairs with high mutual information
Futrell, Richard
;
Qian, Peng
;
Gibson, Edward
...
In: Association for Computational Linguistics (2021)
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8
Breakdowns in Informativeness of Naturalistic Speech Production in Primary Progressive Aphasia
Gallée, Jeanne
;
Cordella, Claire
;
Fedorenko, Evelina
...
In: Multidisciplinary Digital Publishing Institute (2021)
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9
An ERP index of real-time error correction within a noisy-channel framework of human communication
Ryskin, Rachel
;
Stearns, Laura
;
Bergen, Leon
;
Eddy, Marianna
;
Fedorenko, Evelina
;
Gibson, Edward
In: bioRxiv (2021)
Abstract:
Recent evidence suggests that language processing is well-adapted to noise in the input (e.g., spelling or speech errors, misreading or mishearing) and that comprehenders readily correct the input via rational inference over possible intended sentences given probable noise corruptions. In the current study, we probed the processing of noisy linguistic input, asking whether well-studied ERP components may serve as useful indices of this inferential process. In particular, we examined sentences where semantic violations could be attributed to noise-for example, in "The storyteller could turn any incident into an amusing antidote", where the implausible word "antidote" is orthographically and phonologically close to the intended "anecdote". We found that the processing of such sentences-where the probability that the message was corrupted by noise exceeds the probability that it was produced intentionally and perceived accurately-was associated with a reduced (less negative) N400 effect and an increased P600 effect, compared to semantic violations which are unlikely to be attributed to noise ("The storyteller could turn any incident into an amusing hearse"). Further, the magnitudes of these ERP effects were correlated with the probability that the comprehender retrieved a plausible alternative. This work thus adds to the growing body of literature that suggests that many aspects of language processing are optimized for dealing with noise in the input, and opens the door to electrophysiologic investigations of the computations that support the processing of imperfect input.
URL:
https://hdl.handle.net/1721.1/138212
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10
Do domain-general executive resources play a role in linguistic prediction? Re-evaluation of the evidence and a path forward
Ryskin, Rachel
;
Levy, Roger P
;
Fedorenko, Evelina
In: Prof. Fedorenko (2021)
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11
No evidence for differences among language regions in their temporal receptive windows
Blank, Idan Asher
;
Fedorenko, Evelina G
In: Elsevier (2021)
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12
No evidence for differences among language regions in their temporal receptive windows
Blank, Idan A
;
Fedorenko, Evelina
In: Elsevier (2021)
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13
Comprehension of computer code relies primarily on domain-general executive brain regions
Ivanova, Anna A
;
Srikant, Shashank
;
Sueoka, Yotaro
...
In: eLife (2021)
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14
Functional Network Dynamics of the Language System
Chai, Lucy R
;
Mattar, Marcelo G
;
Blank, Idan Asher
...
In: Oxford University Press (2021)
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15
The Small and Efficient Language Network of Polyglots and Hyper-polyglots
Jouravlev, Olessia
;
Mineroff, Zachary A
;
Blank, Idan Asher
...
In: bioRxiv (2021)
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16
The domain-general multiple demand (MD) network does not support core aspects of language comprehension: a large-scale fMRI investigation
Diachek, Evgeniia
;
Blank, Idan
;
Siegelman, Matthew
...
In: Journal of Neuroscience (2021)
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17
The language system in the human brain ...
AIxIA 2021
;
Fedorenko, Evelina
. - : Underline Science Inc., 2021
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18
Similarity of computations across domains does not imply shared implementation: The case of language comprehension
Fedorenko, Evelina
;
Shain, Cory
In: Curr Dir Psychol Sci (2021)
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19
Incremental Language Comprehension Difficulty Predicts Activity in the Language Network but Not the Multiple Demand Network
Wehbe, Leila
;
Blank, Idan Asher
;
Shain, Cory
...
In: Cereb Cortex (2021)
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