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1	Imagined speech can be decoded from low- and cross-frequency intracranial EEG features
	Martin, Stéphanie; Doyle, Werner K.; Poeppel, David...
	In: ISSN: 2041-1723 ; Nature communications, Vol. 13, No 1 (2022) P. 48 (2022)
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2	Musical Sophistication and Speech Auditory-Motor Coupling: Easy Tests for Quick Answers
	Rimmele, Johanna M.; Kern, Pius; Lubinus, Christina...
	In: Front Neurosci (2022)
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3	Imagined speech can be decoded from low- and cross-frequency intracranial EEG features
	Proix, Timothée; Delgado Saa, Jaime; Christen, Andy; Martin, Stephanie; Pasley, Brian N.; Knight, Robert T.; Tian, Xing; Poeppel, David; Doyle, Werner K.; Devinsky, Orrin; Arnal, Luc H.; Mégevand, Pierre; Giraud, Anne-Lise
	In: Nat Commun (2022)
	Abstract: Reconstructing intended speech from neural activity using brain-computer interfaces holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech has met limited success, mainly because the associated neural signals are weak and variable compared to overt speech, hence difficult to decode by learning algorithms. We obtained three electrocorticography datasets from 13 patients, with electrodes implanted for epilepsy evaluation, who performed overt and imagined speech production tasks. Based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future brain computer interfaces, and assessed their performance to discriminate speech items in articulatory, phonetic, and vocalic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings show that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding.
	Keyword: Article
	URL: https://doi.org/10.1038/s41467-021-27725-3 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748882/ http://www.ncbi.nlm.nih.gov/pubmed/35013268
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4	The cognitive neurosciences
	Poeppel, David; Mangun, George R.; Gazzaniga, Michael S.. - : MIT Press, 2020
	MPI für Psycholinguistik
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5	Neural dynamics of phoneme sequencing in real speech jointly encode order and invariant content
	Gwilliams, Laura; King, Jean-Rémi; Marantz, Alec...
	In: https://hal.archives-ouvertes.fr/hal-03089733 ; 2020 (2020)
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6	On Multi-Scale Processing in The Auditory System
	Teng, Xiangbin; Poeppel, David
	In: Forum Acusticum ; https://hal.archives-ouvertes.fr/hal-03235920 ; Forum Acusticum, Dec 2020, Lyon, France. pp.1407-1408, ⟨10.48465/fa.2020.0640⟩ (2020)
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7	Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy
	Giroud, Jérémy; Trébuchon, Agnès; Schön, Daniele...
	In: ISSN: 1544-9173 ; EISSN: 1545-7885 ; PLoS Biology ; https://hal.archives-ouvertes.fr/hal-02496552 ; PLoS Biology, Public Library of Science, 2020, 18 (3), pp.e3000207. ⟨10.1371/journal.pbio.3000207⟩ (2020)
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8	NyU-BU contextually controlled stories Corpus: NUBUC ...
	Lewis, Gwyneth; van Rijn, Pol; Gwilliams, Laura. - : Zenodo, 2020
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9	NyU-BU contextually controlled stories Corpus: NUBUC ...
	Lewis, Gwyneth; van Rijn, Pol; Gwilliams, Laura. - : Zenodo, 2020
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10	Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy
	Giroud, Jérémy; Trébuchon, Agnès; Schön, Daniele. - : Public Library of Science, 2020
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11	Working Memory and syntactic complexity in Brazilian Portuguese and English
	Gouvea, Ana C.; Poeppel, David
	In: North East Linguistics Society (2020)
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12	Spectrotemporal modulation provides a unifying framework for auditory cortical asymmetries
	Flinker, Adeen; Doyle, Werner K.; Mehta, Ashesh D.. - 2019
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13	Spontaneous synchronization to speech reveals neural mechanisms facilitating language learning
	Assaneo, M. Florencia; Ripolles, Pablo; Orpella, Joan. - 2019
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14	In Spoken Word Recognition, the Future Predicts the Past
	Gwilliams, Laura; Linzen, Tal; Poeppel, David. - : Society for Neuroscience, 2018
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15	Cortical tracking of linguistic structures: the role of covert prosody ...
	Glushko, Anastasia; Poeppel, David; Wolpert, Max. - : Unpublished, 2017
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16	Phonological (un)certainty weights lexical activation ...
	Gwilliams, Laura; Poeppel, David; Marantz, Alec. - : arXiv, 2017
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17	The processing of biologically plausible and implausible forms in American Sign Language: evidence for perceptual tuning ...
	Almeida, Diogo; Poeppel, David; Corina, David. - : Figshare, 2016
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18	The processing of biologically plausible and implausible forms in American Sign Language: evidence for perceptual tuning ...
	Almeida, Diogo; Poeppel, David; Corina, David. - : Figshare, 2016
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19	The processing of biologically plausible and implausible forms in American Sign Language: evidence for perceptual tuning ...
	Almeida, Diogo; Poeppel, David; Corina, David. - : Taylor & Francis, 2016
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20	The processing of biologically plausible and implausible forms in American Sign Language: evidence for perceptual tuning ...
	Almeida, Diogo; Poeppel, David; Corina, David. - : Taylor & Francis, 2016
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