Cited by 393Neurobiology of Language and BilingualismPhonetics and Phonology ResearchLanguage Development and Disorders

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Neural Representations and Mechanisms for the Performance of Simple Speech Sequences

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Bohland, Jason W., Bullock, Daniel, Guenther, Frank H.·2010·Journal of Cognitive Neuroscience

DOI 10.1162/jocn.2009.21306PMC PMC2937837

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Abstract

Speakers plan the phonological content of their utterances before their release as speech motor acts. Using a finite alphabet of learned phonemes and a relatively small number of syllable structures, speakers are able to rapidly plan and produce arbitrary syllable sequences that fall within the rules of their language. The class of computational models of sequence planning and performance termed competitive queuing models have followed K. S. Lashley [The problem of serial order in behavior. In L. A. Jeffress (Ed.), Cerebral mechanisms in behavior (pp. 112-136). New York: Wiley, 1951] in assuming that inherently parallel neural representations underlie serial action, and this idea is increasingly supported by experimental evidence. In this article, we developed a neural model that extends the existing DIVA model of speech production in two complementary ways. The new model includes paired structure and content subsystems [cf. MacNeilage, P. F. The frame/content theory of evolution of speech production. Behavioral and Brain Sciences, 21, 499-511, 1998 ] that provide parallel representations of a forthcoming speech plan as well as mechanisms for interfacing these phonological planning representations with learned sensorimotor programs to enable stepping through multisyllabic speech plans. On the basis of previous reports, the model's components are hypothesized to be localized to specific cortical and subcortical structures, including the left inferior frontal sulcus, the medial premotor cortex, the basal ganglia, and the thalamus. The new model, called gradient order DIVA, thus fills a void in current speech research by providing formal mechanistic hypotheses about both phonological and phonetic processes that are grounded by neuroanatomy and physiology. This framework also generates predictions that can be tested in future neuroimaging and clinical case studies.

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Background
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BackgroundMethodInfluential
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Background
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Background
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Background
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Testing hypotheses about the underlying deficit of apraxia of speech through computational neural modelling with the DIVA model
Terband, H., Rodd, J., & Maas, E. (2019) · International Journal of Speech-Language Pathology · doi:10.1080/17549507.2019.1669711 · Cited by 14
“SSM cells represent speech sounds (the size of phonemes, syllables, or frequent words and phrases) and are activated by higher-level input from the phonological encoding stage (Bohland, Bullock, & Guenther, 2010; Guenther et al., 2006).”
Background
Speech perception, production, and the sensorimotor mu rhythm
Jenson, D. E., Thornton, D. M., Saltuklaroglu, T., & Harkrider, A. W. (2014) · Biomedical Sciences and Engineering Conference (BSEC) · doi:10.1109/bsec.2014.6867736 · Cited by 17
“In speech production, the dorsal stream enables feedforward and feedback loops necessary for fluent production at normal speech rates with online dynamic error correction [1] [2] [3] [4] [5] ([20]).”
Background
On The Dynamics of Lexical Access In Two or More Languages
Kroll, J. F., Bice, K., Botezatu, M. R., & Zirnstein, M. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.26 · Cited by 13
Supplementary motor area in speech initiation: A large-scale intracranial EEG evaluation of stereotyped word articulation
Bullock, L., Forseth, K. J., Woolnough, O., Rollo, P. S., & Tandon, N. (2024) · iScience · doi:10.1016/j.isci.2024.111531 · Cited by 17
Structural disconnection of the posterior medial frontal cortex reduces speech error monitoring
McCall, J. D., Dickens, J. V., Mandal, A. S., DeMarco, A. T., Fama, M. E., Lacey, E. H., Kelkar, A. S., Medaglia, J. D., & Turkeltaub, P. E. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102934 · Cited by 12
“perception regions proceeds directly between speech production regions in the inferior frontal gyrus and ventral premotor cortex to auditory cortical areas in the temporal lobe (Bohland et al., 2010; Guenther & Vladusich, 2012).”
Speech sequencing in the human precentral gyrus
Liu, J. R., Zhao, L., Hullett, P. W., & Chang, E. F. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02250-1 · Cited by 15
“19–23).”
Influential
Relationship between the Sequencing and Timing of Vocal Motor Elements in Birdsong
Matheson, A. M. M., & Sakata, J. T. (2015) · PLoS ONE · doi:10.1371/journal.pone.0143203 · Cited by 12
Examining speech motor planning difficulties in apraxia of speech and aphasia via the sequential production of phonetically similar words
Mailend, M., Maas, E., Beeson, P. M., Story, B. H., & Forster, K. I. (2020) · Cognitive Neuropsychology · doi:10.1080/02643294.2020.1847059 · Cited by 13
“The current study focuses on two empirically supported hypotheses about the underlying mechanism in AOS: the Reduced Buffer Capacity Hypothesis (Rogers & Storkel, 1999) and the Program Retrieval Deficit Hypothesis (Bohland et al., 2010; Mailend & Maas, 2013; McNeil et al., 2004).”
Method
Speech Production
Guenther, F. H., Tourville, J. A., & Bohland, J. W. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00265-7 · Cited by 12
Involvement of the Central Cognitive Mechanism in Word Production in Adults Who Stutter
Tsai, P.-T., & Ratner, N. B. (2016) · Journal of Speech Language and Hearing Research · doi:10.1044/2016_jslhr-s-14-0224 · Cited by 13
Evidence for planning and motor subtypes of stuttering based on resting state functional connectivity
Rowe, H. P., Tourville, J. A., Nieto-Castañón, A., Garnett, E. O., Chow, H. M., Chang, S., & Guenther, F. H. (2024) · Brain and Language · doi:10.1016/j.bandl.2024.105417 · Cited by 11
Reinvestigating the Neural Bases Involved in Speech Production of Stutterers: An ALE Meta-Analysis
Zhang, N., Yin, Y., Jiang, Y., & Huang, C. (2022) · Brain Sciences · doi:10.3390/brainsci12081030 · Cited by 11
“A neurocomputational model—directions into velocities of articulators (DIVA)— specified the relationship between the behavioral and neural underpinnings of stuttering [35,36].”
Method
Proton Chemical Shift Imaging of the Brain in Pediatric and Adult Developmental Stuttering
O’Neill, J., Dong, Z., Bansal, R., Ivanov, I., Hao, X., Desai, J. D., Pozzi, E., & Peterson, B. S. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2016.3199 · Cited by 11
Microstructural white matter changes underlying speech deficits in Parkinson’s disease
Mollaei, F., & Chinoor, M. A. B. (2024) · Brain and Language · doi:10.1016/j.bandl.2024.105378 · Cited by 10
“As proposed by the GODIVA framework (Bohland et al., 2010), this motor circuit monitors the initiation and production of speech.”
A historical perspective on the neurobiology of speech and language: from the 19th century to the present
Tremblay, P., & Brambati, S. M. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1420133 · Cited by 10
“The more recent Goal-oriented dynamics of articulators (GODIVA) model (Bohland et al., 2010) extends DIVA by incorporating dynamic aspects of articulatory movements, temporal dynamics, and improved error correction.”
Background
Revisiting the concreteness effect: Non-arbitrary mappings between form and concreteness of English words influence lexical processing
Kearney, E., McMahon, K. L., Guenther, F. H., Arciuli, J., & de Zubicaray, G. I. (2024) · Cognition · doi:10.1016/j.cognition.2024.105972 · Cited by 10
“To date, models of speech production have implemented rule-based mechanisms to assemble sequences of phonemes according to the pho-notactic constraints of a given language (e.g., Bohland et al., 2010; Dell et al., 2000; Levelt et al., 1999).”
Method
Functional anatomy and topographical organization of the frontotemporal arcuate fasciculus
Basile, G. A., Nozais, V., Quartarone, A., Giustiniani, A., Ielo, A., Cerasa, A., Milardi, D., Abdallah, M., de Schotten, M. T., Forkel, S. J., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-07274-3 · Cited by 10
On the Emergence of Phonological Knowledge and on Motor Planning and Motor Programming in a Developmental Model of Speech Production
Kröger, B. J., Bekolay, T., & Cao, M. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.844529 · Cited by 13
“, 1999) or mainly concentrate on modeling the sensorimotor aspects of speech production (e.g., Guenther, 2006; Bohland et al., 2010) it is the goal of our model sketch to give the complete view on speech production, i.”
BackgroundResultInfluential
Impaired Categorical Perception of Speech Sounds Under the Backward Masking Condition in Adults Who Stutter
Shao, J., Bakhtiar, M., & Zhang, C. (2022) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-21-00276 · Cited by 10
Differences in implicit motor learning between adults who do and do not stutter
Höbler, F., Bitan, T., Tremblay, L., & Nil, L. D. (2022) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2022.108342 · Cited by 13
“The pars opercularis and basal ganglia also play an essential role during speech development, supporting the sequential articulation of phonemic gestures to form well-learnt and automatized speech motor programs (Bohland et al., 2010; Dick et al., 2019).”
Background
Altered Engagement of the Speech Motor Network is Associated with Reduced Phonological Working Memory in Autism
O’Brien, A. M., Perrachione, T. K., Weil, L. W., Araujo, Y. S., Halverson, K. K., Harris, A., Ostrovskaya, I., Kjelgaard, M., Wexler, K. N., Tager-Flusberg, H. B., et al. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103299 · Cited by 13
“According to the GODIVA neurocomputational model of speech processing (Bohland et al., 2010), IFG and SMA/pre-SMA subserve parallel phonological buffers, with the former encoding phonemic sequences and the latter representing abstract syllable frames and/or premotor sequencing of speech (Tremblay &…”
An Informatics Approach to Integrating Genetic and Neurological Data in Speech and Language Neuroscience
Bohland, J. W., Myers, E. M., & Kim, E. (2013) · Neuroinformatics · doi:10.1007/s12021-013-9201-6 · Cited by 11
“While there are a number of models of speech production (e.g., Guenther et al. 2006; Bohland et al. 2010b; Hickok et al. 2011), speech perception and processing (e.g., Hickok and Poeppel 2004, 2007; Rauschecker and Scott 2009), and theoretical accounts for language processing (e.g., Friederici…”
BackgroundInfluential
Emergence of an Action Repository as Part of a Biologically Inspired Model of Speech Processing: The Role of Somatosensory Information in Learning Phonetic-Phonological Sound Features
Kröger, B. J., Bafna, T., & Cao, M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01462 · Cited by 10
Frequency-tagged visual evoked responses track syllable effects in visual word recognition
Montani, V., Chanoine, V., Jonathan Grainger, B., & Ziegler, J. C. (2019) · Cortex · doi:10.1016/j.cortex.2019.08.014 · Cited by 11
Language Control and Attention during Conversation
Green, D. W. (2019) · Wiley eBooks · doi:10.1002/9781119387725.ch21 · Cited by 10
Meta-analysis of structural integrity of white matter and functional connectivity in developmental stuttering
Matsuhashi, K., Itahashi, T., Aoki, R., & Hashimoto, R. (2023) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2023.110827 · Cited by 10
“In an influential computational model of speech production, the Gradient Order DIVA model (Bohland et al., 2010), the connection constitutes an input to the motor loop, and the information flow from SMA to putamen is proposed to control the initiation of motor programs for speech production.”
Method
How to cut the pie is no piece of cake: Toward a process‐oriented approach to assessment and diagnosis of speech sound disorders
Littlejohn, M., & Maas, E. (2023) · International Journal of Language & Communication Disorders · doi:10.1111/1460-6984.12934 · Cited by 9
Functional brain outcomes of L2 speech learning emerge during sensorimotor transformation
Carey, D., Miquel, M. E., Evans, B. G., Adank, P., & McGettigan, C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.053 · Cited by 9
“…and executing appropriate speech articulatory plans, and relaying auditory and somatosensory feedback in order to correct speech errors online (Hickok, 2012; see also Guenther, 2006; Bohland et al., 2010; Simmonds et al., 2014a; Cogan et al., 2014; Parker-Jones et al., 2013; Chang et al., 2013).”
Motor learning guided treatment for acquired apraxia of speech
Johnson, R. K. (2017) · Speech Language and Hearing · doi:10.1080/2050571x.2017.1379721 · Cited by 7
Nuclear vowel priming and anticipatory oral postures: evidence for parallel phonological planning?
Krause, P. A., & Kawamoto, A. H. (2019) · Language Cognition and Neuroscience · doi:10.1080/23273798.2019.1636104 · Cited by 9
“…UK Limited, trading as Taylor & Francis Group CONTACT Peter A. Krause peakraus@ucsc.edu their associated phonemes incrementally from left to right, according to GODIVA word-level representations excite all the elements of their phonological planning gradient co-temporally (Bohland et al., 2010).”
BackgroundMethod
Spoken word recognition
Magnuson, J. S., & Crinnion, A. M. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.23 · Cited by 10
Oxford Handbooks in Linguistics
(2022) · Oxford University Press eBooks · doi:10.1093/9780191954481.003.0108 · Cited by 9
Treatment for preschool age children who stutter: Protocol of a randomised, non-inferiority parallel group pragmatic trial with Mini-KIDS, social cognitive behaviour treatment and the Lidcombe Program—TreatPaCS
Leclercq, A., Waelkens, V., Roelant, E., Allegaert, M., Verhaegen, I., Claes, K., Dauvister, E., Snijders, S., Eggers, K., Moyse, A., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0304212 · Cited by 8
The Role of Basal Ganglia and Its Neuronal Connections in the Development of Stuttering: A Review Article
Deepa, G., Shrikrishna, B. H., Gajbe, U., Singh, B. R., Sawal, A., & Balwir, T. (2022) · Cureus · doi:10.7759/cureus.28653 · Cited by 8
“The GODIVA model replicates brain cell activity and explains how the brain can store random utterances that follow a speaker's grammar [34].”
Background
DIVA Meets EEG: Model Validation Using Formant-Shift Reflex
Cuadros, J., Rivera, L. Z., Castro, C., Whitaker, G., Otero, M., Weinstein, A., Martínez-Montes, E., Prado, P., & Zañartu, M. (2023) · Applied Sciences · doi:10.3390/app13137512 · Cited by 8
“The DIVA environment, which also comprises the gradient order DIVA (GODIVA) for the analysis of speech sequencing [66], is now enriched with a new neuroimaging modality (EEG).”
Background
Perceptuomotor compatibility effects in vowels: Beyond phonemic identity
Mokari, P. G., Gafos, A. I., & Williams, D. (2020) · Attention Perception & Psychophysics · doi:10.3758/s13414-020-02014-1 · Cited by 11
Delayed Auditory Feedback Elicits Specific Patterns of Serial Order Errors in a Paced Syllable Sequence Production Task
Malloy, J. R., Nistal, D. A., Heyne, M., Tardif, M. C., & Bohland, J. W. (2022) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-21-00427 · Cited by 9
Speech serial control in healthy speakers and speakers with hypokinetic or ataxic dysarthria: effects of sequence length and practice
Reilly, K. J., & Spencer, K. A. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00665 · Cited by 8
Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics
Arbib, M. A., Bonaiuto, J. J., Bornkessel‐Schlesewsky, I., Kemmerer, D. L., MacWhinney, B., Nielsen, F. Å., & Öztop, E. (2013) · Neuroinformatics · doi:10.1007/s12021-013-9210-5 · Cited by 8
“Linking between items in the databases may not be straightforward as they can have " fuzzy " relationships, e.g., as shown in the Online Brain Atlas Reconciliation Tool (OBART) (Bohland et al. 2009a) where corresponding brain regions in different atlases often do not overlap completely.”
Influential
The Effect of Transcranial Direct Current Stimulation on Jaw Motor Function Is Task Dependent: Speech, Syllable Repetition and Chewing
Simione, M., Fregni, F., & Green, J. R. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00033 · Cited by 8
“…complex behaviors, such as spoken word production, this entails that stimulation of the motor cortex is likely to affect the many concurrent processes (i.e., linguistic, cognitive, attention) engaged during speech production (Bohland et al., 2010) and level of skill required for the specific task.”
Background
Exploring the role of subcortical structures in developmental reading impairments
Cheema, K., Lantz, N., & Cummine, J. (2017) · Neuroreport · doi:10.1097/wnr.0000000000000938 · Cited by 8

Authors: Bohland, J. W., Bullock, D., & Guenther, F. H.
Affiliations: Cold Spring Harbor Laboratory (US)
Boston University (US)
ORCID: Bohland, Jason W.
Bullock, Daniel
Guenther, Frank H.
Venue: Journal of Cognitive Neuroscience
Publisher: MIT Press
Published: 2010-07-01
Volume: 22
Issue: 7
Pages: 1504-1529
ISSN: 0898-929X (ISSN-L)
1530-8898
DOI: 10.1162/jocn.2009.21306
PMC: PMC2937837
OpenAlex: W2114774561
Cited by: 393
References: 158
Citations by year: 2026: 21 · 2025: 26 · 2024: 29 · 2023: 33 · 2022: 64 · 2021: 15 · 2020: 22 · 2019: 40 · 2018: 18 · 2017: 26 · 2016: 19 · 2015: 23 · 2014: 16 · 2013: 18 · 2012: 10
FWCI: 3.72
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Journal of Cognitive Neuroscience (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion)
Funders: National Science Foundation (0354378)
National Institutes of Health (NIH-R01, DC002852)
National Institute on Deafness and Other Communication Disorders (R01DC002852, R01DC007683)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
Keywords: speech production, phonological planning, sequence planning, DIVA model, serial order, basal ganglia, thalamus
MeSH terms: Basal Ganglia, Computer Simulation, Frontal Lobe, Models, Neurological, Neural Pathways, Phonetics, Psychomotor Performance, Speech, Thalamus

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Neural Representations and Mechanisms for the Performance of Simple Speech Sequences

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