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Sorensen DO, Avcu E, Lynch S, Ahlfors SP, Gow DW. Neural representation of phonological wordform in temporal cortex. Psychon Bull Rev 2024:10.3758/s13423-024-02511-6. [PMID: 38689188 DOI: 10.3758/s13423-024-02511-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/08/2024] [Indexed: 05/02/2024]
Abstract
While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words activate a variety of representations (e.g., segmental, semantic, articulatory) in addition to form-based representations. We addressed these challenges through a novel integrated neural decoding and effective connectivity design using region of interest (ROI)-based, source-reconstructed magnetoencephalography/electroencephalography (MEG/EEG) data collected during a lexical decision task. To identify wordform representations, we trained classifiers on words and nonwords from different phonological neighborhoods and then tested the classifiers' ability to discriminate between untrained target words that overlapped phonologically with the trained items. Training with word neighbors supported significantly better decoding than training with nonword neighbors in the period immediately following target presentation. Decoding regions included mostly right hemisphere regions in the posterior temporal lobe implicated in phonetic and lexical representation. Additionally, neighbors that aligned with target word beginnings (critical for word recognition) supported decoding, but equivalent phonological overlap with word codas did not, suggesting lexical mediation. Effective connectivity analyses showed a rich pattern of interaction between ROIs that support decoding based on training with lexical neighbors, especially driven by right posterior middle temporal gyrus. Collectively, these results evidence functional representation of wordforms in temporal lobes isolated from phonemic or semantic representations.
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Affiliation(s)
- David O Sorensen
- Division of Medical Sciences, Harvard Medical School, Cambridge, MA, USA
| | - Enes Avcu
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Skyla Lynch
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David W Gow
- Division of Medical Sciences, Harvard Medical School, Cambridge, MA, USA.
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
- Department of Psychology, Salem State University, Salem, MA, USA.
- Neurodynamics and Neural Decoding Group, Massachusetts General Hospital, 65 Landsdowne Street, rm 219, Cambridge, MA, 02139, USA.
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2
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Regev TI, Kim HS, Chen X, Affourtit J, Schipper AE, Bergen L, Mahowald K, Fedorenko E. High-level language brain regions process sublexical regularities. Cereb Cortex 2024; 34:bhae077. [PMID: 38494886 DOI: 10.1093/cercor/bhae077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 03/19/2024] Open
Abstract
A network of left frontal and temporal brain regions supports language processing. This "core" language network stores our knowledge of words and constructions as well as constraints on how those combine to form sentences. However, our linguistic knowledge additionally includes information about phonemes and how they combine to form phonemic clusters, syllables, and words. Are phoneme combinatorics also represented in these language regions? Across five functional magnetic resonance imaging experiments, we investigated the sensitivity of high-level language processing brain regions to sublexical linguistic regularities by examining responses to diverse nonwords-sequences of phonemes that do not constitute real words (e.g. punes, silory, flope). We establish robust responses in the language network to visually (experiment 1a, n = 605) and auditorily (experiments 1b, n = 12, and 1c, n = 13) presented nonwords. In experiment 2 (n = 16), we find stronger responses to nonwords that are more well-formed, i.e. obey the phoneme-combinatorial constraints of English. Finally, in experiment 3 (n = 14), we provide suggestive evidence that the responses in experiments 1 and 2 are not due to the activation of real words that share some phonology with the nonwords. The results suggest that sublexical regularities are stored and processed within the same fronto-temporal network that supports lexical and syntactic processes.
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Affiliation(s)
- Tamar I Regev
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Hee So Kim
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Xuanyi Chen
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- Department of Cognitive Sciences, Rice University, Houston, TX 77005, United States
| | - Josef Affourtit
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Abigail E Schipper
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
| | - Leon Bergen
- Department of Linguistics, University of California San Diego, San Diego CA 92093, United States
| | - Kyle Mahowald
- Department of Linguistics, University of Texas at Austin, Austin, TX 78712, United States
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- The Harvard Program in Speech and Hearing Bioscience and Technology, Boston, MA 02115, United States
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3
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Magnuson JS, Crinnion AM, Luthra S, Gaston P, Grubb S. Contra assertions, feedback improves word recognition: How feedback and lateral inhibition sharpen signals over noise. Cognition 2024; 242:105661. [PMID: 37944313 PMCID: PMC11238470 DOI: 10.1016/j.cognition.2023.105661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 10/17/2023] [Accepted: 11/02/2023] [Indexed: 11/12/2023]
Abstract
Whether top-down feedback modulates perception has deep implications for cognitive theories. Debate has been vigorous in the domain of spoken word recognition, where competing computational models and agreement on at least one diagnostic experimental paradigm suggest that the debate may eventually be resolvable. Norris and Cutler (2021) revisit arguments against lexical feedback in spoken word recognition models. They also incorrectly claim that recent computational demonstrations that feedback promotes accuracy and speed under noise (Magnuson et al., 2018) were due to the use of the Luce choice rule rather than adding noise to inputs (noise was in fact added directly to inputs). They also claim that feedback cannot improve word recognition because feedback cannot distinguish signal from noise. We have two goals in this paper. First, we correct the record about the simulations of Magnuson et al. (2018). Second, we explain how interactive activation models selectively sharpen signals via joint effects of feedback and lateral inhibition that boost lexically-coherent sublexical patterns over noise. We also review a growing body of behavioral and neural results consistent with feedback and inconsistent with autonomous (non-feedback) architectures, and conclude that parsimony supports feedback. We close by discussing the potential for synergy between autonomous and interactive approaches.
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Affiliation(s)
- James S Magnuson
- University of Connecticut. Storrs, CT, USA; BCBL. Basque Center on Cognition Brain and Language, Donostia-San Sebastián, Spain; Ikerbasque. Basque Foundation for Science, Bilbao, Spain.
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4
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Sorensen DO, Avcu E, Lynch S, Ahlfors SP, Gow DW. Neural representation of phonological wordform in bilateral posterior temporal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549751. [PMID: 37503242 PMCID: PMC10370090 DOI: 10.1101/2023.07.19.549751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words evoke activation of a variety of representations (e.g., segmental, semantic, articulatory) in addition to form-based representations. We addressed these challenges through a novel integrated neural decoding and effective connectivity design using region of interest (ROI)-based, source reconstructed magnetoencephalography/electroencephalography (MEG/EEG) data collected during a lexical decision task. To localize wordform representations, we trained classifiers on words and nonwords from different phonological neighborhoods and then tested the classifiers' ability to discriminate between untrained target words that overlapped phonologically with the trained items. Training with either word or nonword neighbors supported decoding in many brain regions during an early analysis window (100-400 ms) reflecting primarily incremental phonological processing. Training with word neighbors, but not nonword neighbors, supported decoding in a bilateral set of temporal lobe ROIs, in a later time window (400-600 ms) reflecting activation related to word recognition. These ROIs included bilateral posterior temporal regions implicated in wordform representation. Effective connectivity analyses among regions within this subset indicated that word-evoked activity influenced the decoding accuracy more than nonword-evoked activity did. Taken together, these results evidence functional representation of wordforms in bilateral temporal lobes isolated from phonemic or semantic representations.
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Avcu E, Newman O, Ahlfors SP, Gow DW. Neural evidence suggests phonological acceptability judgments reflect similarity, not constraint evaluation. Cognition 2023; 230:105322. [PMID: 36370613 PMCID: PMC9712273 DOI: 10.1016/j.cognition.2022.105322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 10/24/2022] [Accepted: 11/01/2022] [Indexed: 11/11/2022]
Abstract
Acceptability judgments are a primary source of evidence in formal linguistic research. Within the generative linguistic tradition, these judgments are attributed to evaluation of novel forms based on implicit knowledge of rules or constraints governing well-formedness. In the domain of phonological acceptability judgments, other factors including ease of articulation and similarity to known forms have been hypothesized to influence evaluation. We used data-driven neural techniques to identify the relative contributions of these factors. Granger causality analysis of magnetic resonance imaging (MRI)-constrained magnetoencephalography (MEG) and electroencephalography (EEG) data revealed patterns of interaction between brain regions that support explicit judgments of the phonological acceptability of spoken nonwords. Comparisons of data obtained with nonwords that varied in terms of onset consonant cluster attestation and acceptability revealed different cortical regions and effective connectivity patterns associated with phonological acceptability judgments. Attested forms produced stronger influences of brain regions implicated in lexical representation and sensorimotor simulation on acoustic-phonetic regions, whereas unattested forms produced stronger influence of phonological control mechanisms on acoustic-phonetic processing. Unacceptable forms produced widespread patterns of interaction consistent with attempted search or repair. Together, these results suggest that speakers' phonological acceptability judgments reflect lexical and sensorimotor factors.
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Affiliation(s)
- Enes Avcu
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America.
| | - Olivia Newman
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America
| | - Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States of America; Department of Radiology, Harvard Medical School, Boston, MA, United States of America
| | - David W Gow
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States of America; Department of Psychology, Salem State University, Salem, MA, United States of America; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA 02139, United States of America
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6
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Gow DW, Avcu E, Schoenhaut A, Sorensen DO, Ahlfors SP. Abstract representations in temporal cortex support generative linguistic processing. LANGUAGE, COGNITION AND NEUROSCIENCE 2022; 38:765-778. [PMID: 37332658 PMCID: PMC10270390 DOI: 10.1080/23273798.2022.2157029] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 11/21/2022] [Indexed: 06/20/2023]
Abstract
Generativity, the ability to create and evaluate novel constructions, is a fundamental property of human language and cognition. The productivity of generative processes is determined by the scope of the representations they engage. Here we examine the neural representation of reduplication, a productive phonological process that can create novel forms through patterned syllable copying (e.g. ba-mih → ba-ba-mih, ba-mih-mih, or ba-mih-ba). Using MRI-constrained source estimates of combined MEG/EEG data collected during an auditory artificial grammar task, we identified localized cortical activity associated with syllable reduplication pattern contrasts in novel trisyllabic nonwords. Neural decoding analyses identified a set of predominantly right hemisphere temporal lobe regions whose activity reliably discriminated reduplication patterns evoked by untrained, novel stimuli. Effective connectivity analyses suggested that sensitivity to abstracted reduplication patterns was propagated between these temporal regions. These results suggest that localized temporal lobe activity patterns function as abstract representations that support linguistic generativity.
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Affiliation(s)
- David W. Gow
- Department of Neurology Massachusetts General Hospital and Harvard Medical School; Boston, MA, 02114
- Department of Psychology, Salem State University; Salem, MA, 01970
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Charlestown, MA, 02129
- Program in Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard Medical School; Boston, MA 02115
| | - Enes Avcu
- Department of Neurology Massachusetts General Hospital and Harvard Medical School; Boston, MA, 02114
| | - Adriana Schoenhaut
- Department of Neurology Massachusetts General Hospital and Harvard Medical School; Boston, MA, 02114
| | - David O. Sorensen
- Program in Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard Medical School; Boston, MA 02115
| | - Seppo P. Ahlfors
- Program in Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard Medical School; Boston, MA 02115
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School; Boston, MA, 02114
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7
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DIANA, a Process-Oriented Model of Human Auditory Word Recognition. Brain Sci 2022; 12:brainsci12050681. [PMID: 35625067 PMCID: PMC9140177 DOI: 10.3390/brainsci12050681] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/05/2022] [Accepted: 05/10/2022] [Indexed: 02/04/2023] Open
Abstract
This article presents DIANA, a new, process-oriented model of human auditory word recognition, which takes as its input the acoustic signal and can produce as its output word identifications and lexicality decisions, as well as reaction times. This makes it possible to compare its output with human listeners’ behavior in psycholinguistic experiments. DIANA differs from existing models in that it takes more available neuro-physiological evidence on speech processing into account. For instance, DIANA accounts for the effect of ambiguity in the acoustic signal on reaction times following the Hick–Hyman law and it interprets the acoustic signal in the form of spectro-temporal receptive fields, which are attested in the human superior temporal gyrus, instead of in the form of abstract phonological units. The model consists of three components: activation, decision and execution. The activation and decision components are described in detail, both at the conceptual level (in the running text) and at the computational level (in the Appendices). While the activation component is independent of the listener’s task, the functioning of the decision component depends on this task. The article also describes how DIANA could be improved in the future in order to even better resemble the behavior of human listeners.
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8
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Gow DW, Schoenhaut A, Avcu E, Ahlfors SP. Behavioral and Neurodynamic Effects of Word Learning on Phonotactic Repair. Front Psychol 2021; 12:590155. [PMID: 33776832 PMCID: PMC7987836 DOI: 10.3389/fpsyg.2021.590155] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 02/04/2021] [Indexed: 11/22/2022] Open
Abstract
Processes governing the creation, perception and production of spoken words are sensitive to the patterns of speech sounds in the language user's lexicon. Generative linguistic theory suggests that listeners infer constraints on possible sound patterning from the lexicon and apply these constraints to all aspects of word use. In contrast, emergentist accounts suggest that these phonotactic constraints are a product of interactive associative mapping with items in the lexicon. To determine the degree to which phonotactic constraints are lexically mediated, we observed the effects of learning new words that violate English phonotactic constraints (e.g., srigin) on phonotactic perceptual repair processes in nonword consonant-consonant-vowel (CCV) stimuli (e.g., /sre/). Subjects who learned such words were less likely to "repair" illegal onset clusters (/sr/) and report them as legal ones (/∫r/). Effective connectivity analyses of MRI-constrained reconstructions of simultaneously collected magnetoencephalography (MEG) and EEG data showed that these behavioral shifts were accompanied by changes in the strength of influences of lexical areas on acoustic-phonetic areas. These results strengthen the interpretation of previous results suggesting that phonotactic constraints on perception are produced by top-down lexical influences on speech processing.
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Affiliation(s)
- David W. Gow
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
- Department of Psychology, Salem State University, Salem, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States
| | - Adriana Schoenhaut
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Enes Avcu
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Seppo P. Ahlfors
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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9
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Bermúdez-Margaretto B, Beltrán D, Shtyrov Y, Dominguez A, Cuetos F. Neurophysiological Correlates of Top-Down Phonological and Semantic Influence during the Orthographic Processing of Novel Visual Word-Forms. Brain Sci 2020; 10:E717. [PMID: 33050157 PMCID: PMC7601445 DOI: 10.3390/brainsci10100717] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 09/25/2020] [Accepted: 10/06/2020] [Indexed: 11/17/2022] Open
Abstract
The acquisition of new vocabulary is usually mediated by previous experience with language. In the visual domain, the representation of orthographically unfamiliar words at the phonological or conceptual levels may facilitate their orthographic learning. The neural correlates of this advantage were investigated by recording EEG activity during reading novel and familiar words across three different experiments (n = 22 each), manipulating the availability of previous knowledge on the novel written words. A different pattern of event-related potential (ERP) responses was found depending on the previous training, resembling cross-level top-down interactive effects during vocabulary acquisition. Thus, whereas previous phonological experience caused a modulation at the post-lexical stages of the visual recognition of novel written words (~520 ms), additional semantic training influenced their processing at a lexico-semantic stage (~320 ms). Moreover, early lexical differences (~180 ms) elicited in the absence of previous training did not emerge after both phonological and semantic training, reflecting similar orthographic processing and word-form access.
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Affiliation(s)
- Beatriz Bermúdez-Margaretto
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, 101000 Moscow, Russia
| | - David Beltrán
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, 38071 Tenerife, Spain; (D.B.); (A.D.)
- Facultad de Psicología, Universidad de La Laguna, 38071 Tenerife, Spain
| | - Yury Shtyrov
- Institute for Clinical Medicine—Center for Functionally Integrative Neuroscience (CFIN), Aarhus University, 8000 Aarhus, Denmark;
| | - Alberto Dominguez
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, 38071 Tenerife, Spain; (D.B.); (A.D.)
- Facultad de Psicología, Universidad de La Laguna, 38071 Tenerife, Spain
| | - Fernando Cuetos
- Facultad de Psicología, Universidad de Oviedo, 33001 Oviedo, Spain;
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Getz LM, Toscano JC. The time-course of speech perception revealed by temporally-sensitive neural measures. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2020; 12:e1541. [PMID: 32767836 DOI: 10.1002/wcs.1541] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 05/28/2020] [Accepted: 06/26/2020] [Indexed: 11/07/2022]
Abstract
Recent advances in cognitive neuroscience have provided a detailed picture of the early time-course of speech perception. In this review, we highlight this work, placing it within the broader context of research on the neurobiology of speech processing, and discuss how these data point us toward new models of speech perception and spoken language comprehension. We focus, in particular, on temporally-sensitive measures that allow us to directly measure early perceptual processes. Overall, the data provide support for two key principles: (a) speech perception is based on gradient representations of speech sounds and (b) speech perception is interactive and receives input from higher-level linguistic context at the earliest stages of cortical processing. Implications for models of speech processing and the neurobiology of language more broadly are discussed. This article is categorized under: Psychology > Language Psychology > Perception and Psychophysics Neuroscience > Cognition.
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Affiliation(s)
- Laura M Getz
- Department of Psychological Sciences, University of San Diego, San Diego, California, USA
| | - Joseph C Toscano
- Department of Psychological and Brain Sciences, Villanova University, Villanova, Pennsylvania, USA
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11
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Early lexical influences on sublexical processing in speech perception: Evidence from electrophysiology. Cognition 2020; 197:104162. [DOI: 10.1016/j.cognition.2019.104162] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 12/11/2019] [Accepted: 12/16/2019] [Indexed: 11/17/2022]
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Silva S, Vigário M, Fernandez BL, Jerónimo R, Alter K, Frota S. The Sense of Sounds: Brain Responses to Phonotactic Frequency, Phonological Grammar and Lexical Meaning. Front Psychol 2019; 10:681. [PMID: 30984081 PMCID: PMC6447827 DOI: 10.3389/fpsyg.2019.00681] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 03/11/2019] [Indexed: 11/13/2022] Open
Abstract
Two outstanding questions in spoken-language comprehension concern (1) the interplay of phonological grammar (legal vs. illegal sound sequences), phonotactic frequency (high- vs. low-frequency sound sequences) and lexicality (words vs. other sound sequences) in a meaningful context, and (2) how the properties of phonological sequences determine their inclusion or exclusion from lexical-semantic processing. In the present study, we used a picture-sound priming paradigm to examine the ERP responses of adult listeners to grammatically illegal sound sequences, to grammatically legal sound sequences (pseudowords) with low- vs. high-frequency, and to real words that were either congruent or incongruent to the picture context. Results showed less negative N1-P2 responses for illegal sequences and low-frequency pseudowords (with differences in topography), but not high-frequency ones. Low-frequency pseudowords also showed an increased P3 component. However, just like illegal sequences, neither low- nor high-frequency pseudowords differed from congruent words in the N400. Thus, phonotactic frequency had an impact before, but not during lexical-semantic processing. Our results also suggest that phonological grammar, phonotactic frequency and lexicality may follow each other in this order during word processing.
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Affiliation(s)
- Susana Silva
- Neurocognition and Language Group, Center for Psychology at University of Porto, Porto, Portugal
| | - Marina Vigário
- Center of Linguistics, School of Arts and Humanities, University of Lisbon, Lisbon, Portugal
| | | | - Rita Jerónimo
- Instituto Universitário de Lisboa (ISCTE-IUL), CIS-IUL, Lisbon, Portugal
| | - Kai Alter
- Center of Linguistics, School of Arts and Humanities, University of Lisbon, Lisbon, Portugal
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sónia Frota
- Center of Linguistics, School of Arts and Humanities, University of Lisbon, Lisbon, Portugal
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Mahler NA, Chenery HJ. A Developmental Perspective on Processing Semantic Context: Preliminary Evidence from Sentential Auditory Word Repetition in School-Aged Children. JOURNAL OF PSYCHOLINGUISTIC RESEARCH 2019; 48:81-105. [PMID: 29992391 DOI: 10.1007/s10936-018-9591-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The current investigation examined the developmental changes involved in processing semantic context in auditorily presented sentences, as well as underlying attentional and suppression mechanisms. Thirty-nine typically developing school-aged children aged 6;0-14;0 years participated in the current cross-sectional sentential auditory word repetition study. Component processes involved in auditory word recognition were examined and their respective developmental trajectories systematically delineated. Experimental manipulations included semantic congruity (congruous, incongruous), sentence constraint (high, low), cloze probability (high, low), and processing mode. High sentence constraints elicited top-down pre-potency type effects, which resulted in active suppression of anticipated cloze words and longer naming latencies of perceived cloze words when violated with conflicting bottom-up information. In addition, developmental changes in component processes reflected underlying changes in attention, with evidence that suppression mechanisms remained relatively constant with age. Findings are interpreted in line with the Trace (McClelland and Elman in Cogn Psychol 18(1):1-86, 1986) model of auditory word recognition.
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Affiliation(s)
- N A Mahler
- School of Health and Rehabilitation Sciences, The University of Queensland, Saint Lucia, QLD, 4072, Australia.
- Speech Pathology, School of Allied Health Sciences, Gold Coast Campus, Griffith University, South Port, QLD, 4222, Australia.
| | - H J Chenery
- School of Health and Rehabilitation Sciences, The University of Queensland, Saint Lucia, QLD, 4072, Australia
- Faculty of Health Sciences and Medicine, Bond University, 14 University Drive, Robina, QLD, 4226, Australia
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14
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Hu B, Dong Q, Hao Y, Zhao Q, Shen J, Zheng F. Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects. J Neural Eng 2018; 14:046002. [PMID: 28397708 DOI: 10.1088/1741-2552/aa6c6f] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. APPROACH The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. MAIN RESULTS This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. SIGNIFICANCE These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.
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Affiliation(s)
- Bin Hu
- School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China
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15
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Magnuson JS, Mirman D, Luthra S, Strauss T, Harris HD. Interaction in Spoken Word Recognition Models: Feedback Helps. Front Psychol 2018; 9:369. [PMID: 29666593 PMCID: PMC5891609 DOI: 10.3389/fpsyg.2018.00369] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 03/06/2018] [Indexed: 11/13/2022] Open
Abstract
Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.
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Affiliation(s)
- James S. Magnuson
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, United States
| | - Daniel Mirman
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Sahil Luthra
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, United States
| | - Ted Strauss
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
| | - Harlan D. Harris
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, United States
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16
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Gow DW, Ahlfors SP. Tracking reorganization of large-scale effective connectivity in aphasia following right hemisphere stroke. BRAIN AND LANGUAGE 2017; 170:12-17. [PMID: 28364641 PMCID: PMC5472378 DOI: 10.1016/j.bandl.2017.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Revised: 12/22/2016] [Accepted: 03/15/2017] [Indexed: 06/07/2023]
Abstract
In this paper we demonstrate the application of new effective connectivity analyses to characterize changing patterns of task-related directed interaction in large (25-55 node) cortical networks following the onset of aphasia. The subject was a left-handed woman who became aphasic following a right-hemisphere stroke. She was tested on an auditory word-picture verification task administered one and seven months after the onset of aphasia. MEG/EEG and anatomical MRI data were used to create high spatiotemporal resolution estimates of task-related cortical activity. Effective connectivity analyses of those data showed a reduction of bilateral network influences on preserved right-hemisphere structures, and an increase in intra-hemispheric left-hemisphere influences. She developed a connectivity pattern that was more left lateralized than that of right-handed control subjects. Her emergent left hemisphere network showed a combination of increased functional subdivision of perisylvian language areas and recruitment of medial structures.
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Affiliation(s)
- David W Gow
- Neuropsychology Laboratory, Massachusetts General Hospital, 175 Cambridge St., CPZ S340, Boston, MA 02114, United States; Department of Psychology, Salem State University, 352 Lafayette St., Salem, MA 01970, United States; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 Thirteenth St., S2301, Charlestown, MA 02129, United States; Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Ave., E25-519, Cambridge, MA 02139, United States.
| | - Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 Thirteenth St., S2301, Charlestown, MA 02129, United States
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17
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Hunter CR. Is the time course of lexical activation and competition in spoken word recognition affected by adult aging? An event-related potential (ERP) study. Neuropsychologia 2016; 91:451-464. [DOI: 10.1016/j.neuropsychologia.2016.09.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2016] [Revised: 09/05/2016] [Accepted: 09/07/2016] [Indexed: 10/21/2022]
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18
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Gow DW, Olson BB. Using effective connectivity analyses to understand processing architecture: Response to commentaries by Samuel, Spivey and McQueen, Eisner and Norris. LANGUAGE, COGNITION AND NEUROSCIENCE 2016; 31:869-875. [PMID: 28090547 PMCID: PMC5232413 DOI: 10.1080/23273798.2016.1192656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 05/10/2016] [Indexed: 06/06/2023]
Affiliation(s)
- David W. Gow
- Neuropsychology Laboratory, Massachusetts General Hospital, 100 Cambridge St., rm 2030, Boston, MA 02114
- Department of Psychology, Salem State University, 352 Lafayette St., Salem, MA 01970
- Athinoula A. Martinos Center for Biomedical Imaging. Massachusetts General Hospital, 149 Thirteenth St., S2301, Charlestown, MA.02129
- Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Ave., E25-519, Cambridge, MA 02139
| | - Bruna B. Olson
- University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655
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19
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Gow DW, Olson BB. Sentential influences on acoustic-phonetic processing: A Granger causality analysis of multimodal imaging data. LANGUAGE, COGNITION AND NEUROSCIENCE 2015; 31:841-855. [PMID: 27595118 PMCID: PMC5006748 DOI: 10.1080/23273798.2015.1029498] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2014] [Accepted: 03/05/2015] [Indexed: 05/14/2023]
Abstract
Sentential context influences the way that listeners identify phonetically ambiguous or perceptual degraded speech sounds. Unfortunately, inherent inferential limitations on the interpretation of behavioral or BOLD imaging results make it unclear whether context influences perceptual processing directly, or acts at a post-perceptual decision stage. In this paper, we use Kalman-filter enabled Granger causation analysis of MR-constrained MEG/EEG data to distinguish between these possibilities. Using a retrospective probe verification task, we found that sentential context strongly affected the interpretation of words with ambiguous initial voicing (e.g. DUSK-TUSK). This behavioral context effect coincided with increased influence by brain regions associated with lexical representation on regions associated with acoustic-phonetic processing. These results support an interactive view of sentence context effects on speech perception.
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Affiliation(s)
- David W. Gow
- Neuropsychology Laboratory, Massachusetts General Hospital, 175 Cambridge St., CPZ S340, Boston, MA 02114
- Department of Psychology, Salem State University, 352 Lafayette St., Salem, MA 01970
- Athinoula A. Martinos Center for Biomedical Imaging. Massachusetts General Hospital, 149 Thirteenth St., S2301, Charlestown, MA.02129
- Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Ave., E25-519, Cambridge, MA 02139
| | - Bruna B. Olson
- Neuropsychology Laboratory, Massachusetts General Hospital, 175 Cambridge St., CPZ S340, Boston, MA 02114
- Athinoula A. Martinos Center for Biomedical Imaging. Massachusetts General Hospital, 149 Thirteenth St., S2301, Charlestown, MA.02129
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