The DOI matches its Crossref record; 153 of the 158 references it cites were found in a registry or an index.
Neural Representations and Mechanisms for the Performance of Simple Speech Sequences
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
In the citing paper
“Finally, the left putamen and thalamus were incorporated into a motor loop that passes activity from the SMA via the putamen to the thalamus and into the motor cortex (Bohland et al., 2010).”
From A review and synthesis of the first 20years of PET and fMRI studies of heard speech, spoken language and reading (2012) · cites this paper as Bohland et al., 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Hodgkin, A. L., & Huxley, A. F. (1952) · The Journal of Physiology · doi:10.1113/jphysiol.1952.sp004764 · Cited by 23,191 · cited 1×
“Such multiplicative or shunting terms (Grossberg, 1973) are motivated by empirically observed cell membrane properties (e.g., Hodgkin & Huxley, 1952).”
Elman, J. L. (1990) · Cognitive Science · doi:10.1207/s15516709cog1402_1 · Cited by 11,212 · cited 2×
“More recent neural network models (Beiser & Houk, 1998; Elman, 1990; Lewandowsky & Murdock, 1989; Jordan, 1986) proposed revisions that rely”
Parallel organization of functionally segregated circuits linking basal ganglia and cortex
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.09.030186.002041 · Cited by 8,527 · cited 3×
“The organization of BG circuits into largely parallel loops (Alexander & Crutcher, 1990; Alexander et al., 1986) offers one possible substrate for the cascaded processing stages that enable linguistic selections from competing alternatives; these selections (cf. choice layer activations) can then…”
The magical number 4 in short-term memory: A reconsideration of mental storage capacity
Cowan, N. (2001) · Behavioral and Brain Sciences · doi:10.1017/s0140525x01003922 · Cited by 6,779 · cited 1×
“These properties help explain why there is a low limit (see Cowan, 2000) to the number of items that can be planned in working memory and recalled in the correct order.”
A theory of lexical access in speech production
Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999) · Behavioral and Brain Sciences · doi:10.1017/s0140525x99001776 · Cited by 5,295 · cited 3×
“SSM representations are functionally similar to a mental syllabary (Levelt & Wheeldon, 1994; Crompton, 1982), suggested by Levelt et al. (1999) to consist of a “repository of gestural scores for the frequently used syllables of the language” (p. 5).”
Speaking: from intention to articulation
(1989) · Choice Reviews Online · doi:10.5860/choice.27-1947 · Cited by 5,017 · cited 2×
“Such models generally follow the theoretical work of Levelt ( 1989 ), Garrett ( 1975 ), and others.”
Speaking: From Intention to Articulation
Levelt, W. J. M. (1989) · doi:10.7551/mitpress/6393.001.0001 · Cited by 4,804
Functional architecture of basal ganglia circuits: neural substrates of parallel processing
Alexander, G. E., & Crutcher, M. D. (1990) · Trends in Neurosciences · doi:10.1016/0166-2236(90)90107-l · Cited by 4,131 · cited 3×
“Interactions between the cortex and the BG are organized into multiple loop circuits (Middleton & Strick, 2000; Alexander & Crutcher, 1990; Alexander, DeLong, & Strick, 1986).”
Speaking. From Intention to Articulation
Caplan, D. N. (1990) · Trends in Neurosciences · doi:10.1016/0166-2236(90)90151-y · Cited by 4,036
The Handbook of brain theory and neural networks
(1996) · Choice Reviews Online · doi:10.5860/choice.33-4484 · Cited by 3,913
Research works printed but not linked: 7
- Baayen, 1995, The CELEX lexical database (release 2) [CD-ROM].
- Bullock, 2003, Competitive queuing for serial planning and performance., 241
- Jonas, 1987, The supplementary motor region and speech., 241
- Rogers, 2001, Spoken word production without assembly: Is it possible?, Aphasiology, 15, 68
- Shattuck-Hufnagel, 1979, Speech errors as evidence for a serial order mechanism in sentence production., 295
- Van der Merwe, 1997, A theoretical framework for the characterization of pathological speech sensorimotor control., 1
- Werker, 1992, Infant speech perception and phonological acquisition., 285
Cited by
Sorted by citations
Items 201–300 of 392
Morphology and The Mental Lexicon
Embick, D., Creemers, A., & Davies, A. J. G. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.17 · Cited by 7
Involvement of the cortico-basal ganglia-thalamo-cortical loop in developmental stuttering.Preprint
Chang, S., & Guenther, F. H. (2019) · doi:10.31234/osf.io/2qhtp · Cited by 8
Miller, H. E., Garnett, E. O., Murray, E. S. H., Nieto-Castañón, A., Tourville, J. A., Chang, S., & Guenther, F. H. (2023) · Brain Communications · doi:10.1093/braincomms/fcad301 · Cited by 8
“53,55,56 These included the following regions: caudate, cerebellum (cortex), pallidum, putamen and thalamus proper.”
BackgroundResultFumel, J., Bahuaud, D., Weed, E., Fusaroli, R., & Basirat, A. (2024) · Journal of Speech Language and Hearing Research · doi:10.1044/2024_jslhr-23-00588 · Cited by 7
Computer-Implemented Articulatory Models for Speech Production: A Review
Kröger, B. J. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.796739 · Cited by 7
“A blueprint for the organization of neural control in speech production is given by the DIVA model (Directions Into Velocities of Articulators, see Guenther 2006, Bohland et al., 2010, and Guenther and Vladusich 2012).”
BackgroundMethodHybbinette, H., Östberg, P., Schalling, E., Deboussard, C. N., Plantin, J., Borg, J., & Lindberg, P. G. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.1013652 · Cited by 7
“The importance of the premotor cortex in speech production has also been highlighted in neurocomputational models of speech production, such as the Directions Into Velocities of Articulators (DIVA) model (20) and its expanded version, the Gradient Order DIVA (GODIVA) model (21, 22).”
BackgroundLinn, W., Barrios‐Martinez, J., Fernandes-Cabral, D. T., Jacquesson, T., Nunez, M. A., Gómez, R. J., Anania, Y., Fernandez-Miranda, J. C., & Yeh, F.-C. F. (2024) · Human Brain Mapping · doi:10.1002/hbm.26630 · Cited by 7
Subthalamic nucleus neurons encode syllable sequence and phonetic characteristics during speech
Lipski, W. J., Bush, A., Chrabaszcz, A. V., Crammond, D. J., Fiez, J. A., Turner, R. S., & Richardson, R. M. (2024) · Journal of Neurophysiology · doi:10.1152/jn.00471.2023 · Cited by 9
“The GODIVA model of the neural mechanisms of speech production postulates that a cortical-basal ganglia loop circuit controls the release of planned speech sounds to the execution system so that a new motor program is initiated only upon completion of the previous program (22).”
Chrabaszcz, A. V., Wang, D., Lipski, W. J., Bush, A., Crammond, D. J., Shaiman, S., Dickey, M. W., Holt, L. L., Turner, R. S., Fiez, J. A., et al. (2021) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2021.101019 · Cited by 7
“…an important node in the language network, emphasizing their role in initiation, planning, monitoring, selection and coordination processes (e.g., Bohland, Bullock, & Guenther, 2010; Crosson, Zawacki, Brinson, Lu, & Sadek, 1997; Eisinger, Urdaneta, Foote, Okun, & Gunduz, 2018; Guenther, Ghosh, &…”
Geva, S., Schneider, L. M., Roberts, S. M., Khan, S., Gajardo‐Vidal, A., Lorca‐Puls, D. L., PLORAS team, Hope, T. M. H., Green, D. W., & Price, C. J. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102820 · Cited by 7
“38 shown to receive preparatory signals on the order of information from pre-SMA and to send driving signals to the motor regions that execute motor commands (Bohland et al., 2010).”
BackgroundMoving in time: Simulating how neural circuits enable rhythmic enactment of planned sequences
Zeid, O., & Bullock, D. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.08.006 · Cited by 7
Chesters, J., Möttönen, R., & Watkins, K. E. (2021) · doi:10.31219/osf.io/8st3j · Cited by 7
Human Precentral Gyrus Neurons Link Speech Sequences from Listening to SpeakingPreprint
Xu, D., Chung, J. E., Silva, A. B., Metzger, S. L., Greicius, Q., Zhang, Y., Leonard, M. K., Aghi, M. K., Hervey‐Jumper, S. L., & Chang, E. F. (2024) · SSRN Electronic Journal · doi:10.1101/2024.12.27.630563 · Cited by 9
Nozari, N. (2025) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2025.101247 · Cited by 7
Vissani, M., Bush, A., Lipski, W. J., Bullock, L., Fischer, P., Neudorfer, C., Holt, L. L., Fiez, J. A., Turner, R., & Richardson, R. M. (2025) · Nature Communications · doi:10.1038/s41467-025-58781-8 · Cited by 10
“We brie fl y address the gradient order DIVA (GODIVA) model here because it concerns speech planning mechanisms 96,98 , which is informative for the θ – α SPC differences we observed >1 s before speech onset in accurate versus error trials.”
Kinematic Analysis of Speech Sound Sequencing Errors Induced by Delayed Auditory Feedback
Cler, G. J., Lee, J. C., Mittelman, T., Stepp, C. E., & Bohland, J. W. (2017) · Journal of Speech Language and Hearing Research · doi:10.1044/2017_jslhr-s-16-0234 · Cited by 6
“Under this view, coordinated neural mechanisms must sequentially select the appropriate phonological units from a planning buffer, while concurrently activating lower-level sensory-motor programs that drive the production of individual syllables (Bohland et al., 2010).”
BackgroundNeural Network Models of Human Executive Function and Decision Making
Levine, D. S. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-803676-1.00005-2 · Cited by 9
Evidence for Speech Sound Disorder (SSD) Assessment
Wertzner, H. F., Francisco, D. T., Barrozo, T. F., & Pagan-Neves, L. D. O. (2017) · InTech eBooks · doi:10.5772/intechopen.70036 · Cited by 6
Vascular syndromes: Revisiting classification of poststroke aphasia
Bunker, L. D., & Hillis, A. E. (2022) · Handbook of clinical neurology · doi:10.1016/b978-0-12-823384-9.00002-5 · Cited by 6
Swann, Z., Daliri, A., & Honeycutt, C. F. (2022) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-21-00486 · Cited by 6
Etter, N. M., Dressler, E. V. M., & Andreatta, R. D. (2015) · International Journal of Speech-Language Pathology · doi:10.3109/17549507.2015.1060527 · Cited by 6
3. The Interactional Challenge: L2 Learning and Use in the Third Age
Green, D. W. (2017) · Multilingual Matters eBooks · doi:10.21832/9781783099412-005 · Cited by 6
Jackendoff, R. S. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.3 · Cited by 6
Language control in the context of L3 acquisition
Green, D. W. (2017) · Bilingual processing and acquisition · doi:10.1075/bpa.5.02gre · Cited by 5
“Subcortical signals also enable plan execution (Bohland et al. 2009).”
BackgroundSpencer, C. E., Davison, K. E., Boucher, A. R., & Zuk, J. (2022) · Language Speech and Hearing Services in Schools · doi:10.1044/2022_lshss-21-00170 · Cited by 5
Höbler, F., Bitan, T., Tremblay, L., & Nil, L. D. (2023) · Journal of Fluency Disorders · doi:10.1016/j.jfludis.2023.105959 · Cited by 5
Dynamic Approaches to Phonological Processing
Hatfield, H. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009258661 · Cited by 5
DOPAMINE EXCESS MAY DELAY SELECTION OF SYLLABIC MOTOR PROGRAMS: A MODELING STUDY OF STUTTERING
Civier, O., Bullock, D. H., Max, L., & Guenther, F. H. (2011) · ICPhS · Cited by 5
Mailend, M., Maas, E., & Story, B. H. (2021) · Cognitive Neuropsychology · doi:10.1080/02643294.2021.2009790 · Cited by 5
“We used the DIVA/GODIVA model(4) (Bohland et al., 2010; Guenther, 2016; Guenther et al., 2006), a well-supported detailed model of speech motor planning and control, because it meets these criteria.”
MethodMcCall, J. D., DeMarco, A. T., Mandal, A. S., Fama, M. E., van der Stelt, C. M., Lacey, E. H., Laks, A. B., Snider, S. F., Friedman, R. B., & Turkeltaub, P. E. (2023) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02000 · Cited by 6
Eichler, K., Hampel, S., Alejandro-García, A., Calle-Schuler, S. A., Santana-Cruz, A., Kmecova, L., Blagburn, J. M., Hoopfer, E. D., & Seeds, A. M. (2024) · eLife · doi:10.7554/elife.87602.3 · Cited by 5
“This model proposes that the premotor elements of different movements to be executed in sequence are activated (or readied) in parallel and then selected sequentially through a mechanism where movements occurring earlier in the sequence suppress later ones (Bohland et al., 2010; Bullock, 2004; Houghton and Hartley, 19…”
BackgroundThe role of anticipation and an adaptive monitoring system in stuttering
Arenas, R. M., Gupta, P., Tomblin, B., Moon, J., Duff, M., & Zebrowski, P. M. (2012) · doi:10.17077/etd.i4okjr74 · Cited by 6
Contributions of pragmatics to word learning and interpretation
Grigoroglou, M., & Anna Papafragou, A. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.21 · Cited by 6
The neural organisation of language production: Evidence from neuroimaging and neuromodulationPreprint
de Zubicaray, G. I. (2022) · doi:10.31234/osf.io/pf5sk · Cited by 5
Eichler, K., Hampel, S., Alejandro-García, A., Calle-Schuler, S. A., Santana-Cruz, A., Kmecova, L., Blagburn, J. M., Hoopfer, E. D., & Seeds, A. M. (2023) · doi:10.1101/2023.02.11.528119 · Cited by 4
“This model proposes that the premotor elements of different movements to be executed in sequence are activated (or readied) in parallel and then selected sequentially through a mechanism where movements occurring earlier in the sequence suppress later ones (Bohland et al., 2010; Bullock, 2004; Houghton and Hartley, 19…”
BackgroundLevy, D. F., Greicius, Q., Wang, C., Ko, E., Xu, D., Andrews, J. P., & Chang, E. F. (2025) · Neurobiology of Language · doi:10.1162/nol_a_00166 · Cited by 4
“While the pre-SMA is often included in models of the neural bases of speech (i.e., the motor planning and execution aspects of language production; Bohland et al., 2010; Dick et al., 2019; Price, 2010), it is absent from many of the dominant models of the broader language network (e.g., Dell et…”
InfluentialCalle-Schuler, S. A., Santana-Cruz, A., Kmecová, L., Hampel, S., & Seeds, A. M. (2026) · eLife · doi:10.7554/elife.108044.3 · Cited by 4
Factors Affecting Nonnative Consonant Cluster Learning
Buchwald, A. B., & Cheng, H.-S. (2023) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-22-00322 · Cited by 4
The Effects of Deep Brain Stimulation on Speech Motor Control in People With Parkinson's Disease
Nip, I. S. B., Burke, M. M., & Kim, Y. (2023) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-22-00443 · Cited by 4
The Advancement of Neuroimaging Research Investigating Developmental Stuttering
Beal, D. S. (2011) · Perspectives on Fluency and Fluency Disorders · doi:10.1044/ffd21.3.88 · Cited by 4
Language control in bimodal bilinguals: multimodality and serial order
Green, D. W. (2015) · Bilingualism Language and Cognition · doi:10.1017/s1366728915000383 · Cited by 4
Deriving the onset and offset times of planning units from acoustic and articulatory measurements
Rodd, J., Bosker, H. R., ten Bosch, L., & Ernestus, M. (2019) · The Journal of the Acoustical Society of America · doi:10.1121/1.5089456 · Cited by 4
“145 (2), February 2019 Rodd et al. lexical access and multi-word processes of speech production (e.g., Bohland et al., 2010; Dell and O’Seaghdha, 1992; Levelt et al., 1999).”
Berglund-Barraza, A., Carey, S., Hart, J., Vanneste, S., & Evans, J. L. (2023) · Journal of Speech Language and Hearing Research · doi:10.1044/2023_jslhr-21-00098 · Cited by 4
Masapollo, M., Zezas, E., Shamsi, A., Wayland, R. P., Smith, D. J., & Guenther, F. H. (2023) · Journal of Psycholinguistic Research · doi:10.1007/s10936-023-09998-5 · Cited by 4
“…production of complex or extended sequences of articulatory movements involves the use of well-learned subsequences, often referred to as “ chunks ” (Bohland et al., 2010; Cholin et al., 2006; Christiansen & Chater, 2016; Guenther, 2016; Lashley, 1951; Levelt & Wheel-don, 1994; Levelt et al.,…”
BackgroundInfluentialEtter, N. M., McKeon, P. O., Dressler, E. V. M., & Andreatta, R. D. (2017) · International Journal of Speech-Language Pathology · doi:10.1080/17549507.2017.1318303 · Cited by 4
Natural Language Processing in Large-Scale Neural Models for Medical Screenings
Stille, C. M., Bekolay, T., Blouw, P., & Kröger, B. J. (2019) · Frontiers in Robotics and AI · doi:10.3389/frobt.2019.00062 · Cited by 4
“Further, GODIVA provides an extension for speech production at a suprasegmental level (Bohland et al., 2010).”
BackgroundAltered Functional Connectivity and Brain Network Property in Pregnant Women With Cleft Fetuses
Li, Z., Li, C., Liang, Y., Wang, K., Zhang, W., Chen, R., Wu, Q., & Zhang, X. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02235 · Cited by 4
“On the other hand, pronunciation is a process of continuous learning and imitation, while speech imitation is a complex process that requires the interaction of both sensory and motor systems, such that acoustic inputs can be processed, transformed to target motor outputs, and articulated as speech (Guenther, 2006; Bo…”
BackgroundSpeech Production in Motor Speech Disorders
Weismer, G. G., & Green, J. R. (2015) · Wiley eBooks · doi:10.1002/9781118584156.ch14 · Cited by 4
Infants’ Learning of Speech Sounds and Word-Forms
Swingley, D. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.6 · Cited by 4
Landau, B. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.5 · Cited by 4
Speech movement variability in people who stutter: A vocal tract MRI studyPreprint
Wiltshire, C. E. E., Chiew, M., Chesters, J., Healy, M. P., & Watkins, K. E. (2020) · doi:10.31234/osf.io/bhe57 · Cited by 4
Dyslin, S. M., DeMarco, A. T., Staples, R., Dickens, J. V., Snider, S. F., Friedman, R. B., & Turkeltaub, P. E. (2025) · Neurobiology of Language · doi:10.1162/nol.a.216 · Cited by 3
https://jpcp.uswr.ac.ir/article-1-747-en.html
Aval, N. M. (2021) · Practice in Clinical Psychology · doi:10.32598/jpcp.9.3.761.1 · Cited by 4
Neural activity flows through cortical subnetworks during speech production
Castellucci, G. A., MacKay, M., Kovach, C. K., Tabasi, F., Greenlee, J. D. W., & Long, M. A. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116783 · Cited by 3
“…implicated in planning using the CI task 35,39 —such as the inferior frontal gyrus (IFG), 9,10,60 MFG, 61-63 anterior PrCG, 5,64 and anterior STG 6,10,65,66 —in addition to planning-linked structures within the left superior frontal, 5,11,67,68 fusiform, 69,70 and middle 6,46 temporal gyri.”
Liu, F., Zhang, Y., Shi, Y., Chen, Z., & Feng, X. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.10.221 · Cited by 3
Understanding how the human brain tracks emitted speech sounds to execute fluent speech production
Callan, A. M., & Callan, D. E. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001533 · Cited by 3
Gerwin, K. L., Walsh, B. M., & Christ, S. L. (2022) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-21-00654 · Cited by 3
Singing and Speaking Ability in Parkinson's Disease and Spinocerebellar Ataxia
Kim, Y., Sidtis, D. V. L., & Sidtis, J. J. (2023) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-22-00274 · Cited by 4
“As an alternative explanation has been advanced that externally cued tasks require less cognitive–linguistic demands than spontaneous speech (Bohland et al., 2010; Feenaughty et al., 2013; Huber & Darling, 2011; Tourville & Guenther, 2011; Weir-Mayta et al., 2017).”
BackgroundJanse, E., Shen, C., & de Kerf, E. (2023) · Journal of Speech Language and Hearing Research · doi:10.1044/2023_jslhr-23-00076 · Cited by 3
Cortical Tracking of Speech Is Reduced in Adults Who Stutter When Listening for Speaking
Gastaldon, S., Busan, P., Molinaro, N., & Lizarazu, M. (2024) · Journal of Speech Language and Hearing Research · doi:10.1044/2024_jslhr-24-00227 · Cited by 4
Stern, M. C., & Shaw, J. A. (2025) · Journal of Phonetics · doi:10.1016/j.wocn.2025.101427 · Cited by 3
“We discovered that the ratio of instantaneous displacement, −𝑥 + 𝑥 " , to instantaneous velocity, 𝑥̇ , decays ‘Is it the case that Leifeng Pagoda must be rebuilt or (just) that it can be rebuilt?’”
A Novel Investigation of Generalized Motor Program Theory: Syllable Stress as a Motor-Class Variable
Meigh, K. M. (2017) · Journal of Speech Language and Hearing Research · doi:10.1044/2017_jslhr-s-16-0247 · Cited by 3
“The complexity of speech production would intuitively suggest that multiple GMPs are encoded and retrieved from memory during speech production (e.g., phonemes and syllable levels; Bohland et al., 2010; Roelofs & Meyer, 1998); therefore, the results of this study should not be surprising.”
Johnson, R., Matthews, J., Diawara, N., & Carroll, R. M. (2020) · Frontiers in Applied Mathematics and Statistics · doi:10.3389/fams.2020.00032 · Cited by 3
“Advancements in functional neuroimaging and computational modeling have resulted in two widely recognized models for speech motor control, Directions into Velocities of Articulators (DIVA), and speech sequencing, Gradient Order DIVA (GODIVA) [10, 11].”
BackgroundCai, S. (2011) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 3
Phonological variation and lexical form
Purse, R., Tamminga, M., & White, Y. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.15 · Cited by 3
Schwarz, F., & Zehr, J. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.18 · Cited by 3
Efficient Communication and The Organization of The Lexicon
Mahowald, K., Dautriche, I., Braginsky, M., & Gibson, T. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.19 · Cited by 7
Eichler, K., Hampel, S., Alejandro-García, A., Calle-Schuler, S. A., Santana-Cruz, A., Kmecova, L., Blagburn, J. M., Hoopfer, E. D., & Seeds, A. M. (2024) · doi:10.7554/elife.87602.2 · Cited by 2
Bullock, L., Forseth, K. J., Woolnough, O., Rollo, P. S., & Tandon, N. (2023) · doi:10.1101/2023.04.04.535557 · Cited by 2
Brain Dynamics of Speech Modes Encoding: Loud and Whispered Speech Versus Standard Speech
Sanders, B., Lancheros, M., Bourqui, M., & Laganaro, M. (2025) · Brain Topography · doi:10.1007/s10548-025-01108-z · Cited by 3
“Despite decades of investigation, a clear account of the interaction between the neural processes underlying speech production and their dynamics is still needed (Bohland et al. 2010; Laga-naro 2019; Miller & Guenther 2021; Verwoert et al. 2022).”
Rowe, H. P., Miller, H. E., Belisle, R. M., Perrachione, T. K., & Guenther, F. H. (2025) · Neurobiology of Language · doi:10.1162/nol.a.18 · Cited by 2
“Both LpIFS and RCbm are thought to be involved in the learning of speech sequences, such as the sequences of phonemes making up the phonotactically illegal syllables used here (Bohland et al., 2010; Bohland & Guenther, 2006; Guenther, 2016).”
Kröger, B. J. (2023) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2205124 · Cited by 2
“The sensorimotor neural production models DIVA [4] and GODIVA [5] represent further components of the production pathway from the phonological form via activation of motor programs down to motor execution and include auditory and somatosensory feedback to allow motor corrections.”
MethodInfluentialLateralization and Time-Course of Cortical Phonological Representations during Syllable Production
Meier, A. M., Kuzdeba, S., Jackson, L., Daliri, A., Tourville, J. A., Guenther, F. H., & Greenlee, J. D. W. (2023) · eNeuro · doi:10.1523/eneuro.0474-22.2023 · Cited by 3
Kröger, B. J. (2023) · Frontiers in Language Sciences · doi:10.3389/flang.2023.1100774 · Cited by 2
Cummine, J., Ngo, T., & Nisbet, K. (2023) · Brain Sciences · doi:10.3390/brainsci13121622 · Cited by 2
“In the speech production literature, the caudate is implicated in speech planning [2] and has been noted for playing a role in rhythm.”
BackgroundInfluentialDesjardins, M., Jomphe, V., Lagadec-Gaulin, L., Cohen, M. L., & Abbott, K. V. (2024) · Journal of Speech Language and Hearing Research · doi:10.1044/2024_jslhr-23-00673 · Cited by 2
Distinct neural processes link speech planning and execution
Duraivel, S., Rahimpour, S., Barth, K. J., Chiang, C., Wang, C., Harward, S. C., Lad, S. P., Sexton, D., Friedman, A. H., Sinha, S. R., et al. (2026) · Nature Human Behaviour · doi:10.1038/s41562-026-02546-w · Cited by 3
“Based on neuro-anatomical studies that investigated speech articulation 4,16,20,65,68 , we divided these ROIs into three distinct networks based on previous literature: planning (IFG, rMFG, and cMFG), articulation (PrCG & PoCG, and IPC), and monitoring (aSTG, pSTG, STS, and PAC).”
InfluentialTerband, H., Rodd, J., & Maas, E. (2015) · MPG.PuRe (Max Planck Society) · Cited by 2
Phoneme and Stress Programming Interact During Nonword Repetition Learning
Meigh, K. M., Cobun, E. R., & Yunusova, Y. (2020) · Journal of Speech Language and Hearing Research · doi:10.1044/2020_jslhr-19-00262 · Cited by 2
Ahmadi, Z. Z., DiBacco, M. L., & Pearl, P. L. (2021) · Journal of Child Neurology · doi:10.1177/08830738211001210 · Cited by 2
“Concerning the connectivity of subcortical areas and SMA, it is mostly cited that the anterior regions of the SMA are strongly connected to the caudate,(35) which is involved in cognitive processes(36,37) and phonological segmentation.(38) In contrast, the posterior regions of SMA are strongly connected to the thalamu…”
BackgroundJackson, E. S. (2015) · CUNY Academic Works (City University of New York) · Cited by 2
Children’s Use of Syntax In Word Learning
Lidz, J. L. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.10 · Cited by 2
Phonological Abstraction in The Mental Lexicon
Bakovic, E. J., Heinz, J. N., & Rawski, J. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198845003.013.14 · Cited by 2
Nozari, N., & Pinet, S. (2019) · doi:10.31234/osf.io/x9wq7 · Cited by 2
Defining brain pathways for human spoken language and vocal learningPreprint
Theofanopoulou, C., & Jarvis, E. D. (2023) · doi:10.31234/osf.io/pa5fq · Cited by 2
Manes, J. L., & Guenther, F. H. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-820480-1.00120-0 · Cited by 2
Some properties of mental speech preparation as revealed by self-monitoring
Quené, H., & Nooteboom, S. G. (2024) · Speech Communication · doi:10.1016/j.specom.2024.103043 · Cited by 1
Speaking demands: concurrent visuomotor rotor pursuit tracking measures cognitive load for speech
Kriegel, Z., & Whitfield, J. A. (2024) · Speech Language and Hearing · doi:10.1080/2050571x.2024.2317027 · Cited by 2
“However, it was expected that sentence repetition and counting forward by one might slightly degrade percent time on target in the visuomotor rotor pursuit tracking task because of a more complex sequence of intended phonemes translated into speech motor commands (Bohland et al., 2010).”
InfluentialProduction training and contextual similarity hurt the comprehension of new vocabulary
Waller, M., Yurovsky, D., & Nozari, N. (2024) · Language Cognition and Neuroscience · doi:10.1080/23273798.2024.2429127 · Cited by 1
“This link is critical for both learning and monitoring language production (e.g. Bohland et al., 2010; Hickok, 2012; Levelt et al., 1999; Nozari, 2020).”
Right-Hemispheric White Matter Organization Is Associated With Speech Timing in Autistic Children
Davison, K. E., Liu, T., Belisle, R. M., Perrachione, T. K., Qi, Z., Gabrieli, J. D. E., Tager-Flusberg, H. B., & Zuk, J. (2025) · Journal of Speech Language and Hearing Research · doi:10.1044/2025_jslhr-24-00548 · Cited by 1
“…a region known to play a major role in auditory processing of spectrotemporal information important for speech perception (Hickok & Poeppel, 2007); and (c) the pre – supplementary motor area (preSMA), a speech motor region involved in the planning of articulatory movements (Bohland et al., 2010).”
Prem, P., Saggu, S., Boadu, A., Saju, S., Nisbet, K., & Cummine, J. (2025) · Neuroscience · doi:10.1016/j.neuroscience.2025.09.035 · Cited by 2
Höbler, F., Liu, Y., Beltz, A. M., Becker, H. C., Angstadt, M., Guenther, F. H., & Chang, S. (2025) · Neurobiology of Language · doi:10.1162/nol.a.26 · Cited by 1
“With most of the DIVA and GODIVA nodes implicated in developmental stuttering, moments of stuttering are hypothesized to arise from specific disruptions to the functioning of the basal ganglia proper (Alm, 2004, 2021; Civier et al., 2013), or in corticostriatal WM connectivity (Civier et al., 2013), thereby impacting…”
InfluentialLi, S., Chen, Z., Luo, X., Wang, J., Teng, P., Luan, G., Wang, Q., & Tian, X. (2025) · Communications Biology · doi:10.1038/s42003-025-08847-6 · Cited by 1
Testing theories of stuttering: cognitive heterogeneity but shared orosensory tactile weaknesses
Thorre, A. V., Patri, J.-F., & Vannuscorps, G. (2025) · Cognitive Neuropsychology · doi:10.1080/02643294.2025.2572357 · Cited by 1
“In the GODIVA model (Bohland et al., 2010), stut-tering arises from delays in the deactivation of the ongoing syllable (leading to prolongations) or in the activation of the subsequent syllable (leading to blocks).”
An Imaging‐Guided Neural Model Explains Lexical Stress Alteration in Acquired Apraxia of Speech
Civier, O., Ramage, A. E., Tourville, J. A., Robin, D. A., Guenther, F. H., & Ballard, K. J. (2025) · Human Brain Mapping · doi:10.1002/hbm.70412 · Cited by 1
“…explanation of the atypical neural dynamics that give rise to AOS, and to simulate them numerically using a neuro-computational model of speech production (i.e., a custom instantiation of the DIVA/ GODIVA family of speech production models, see Bohland et al. 2010; Guenther et al. 2006).”
InfluentialKasper, J., Kell, C. A., & Perrier, P. (2025) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2025.101298 · Cited by 1
The neural correlates of mid- and end-clause silent pauses in L1 and L2 speech
Révész, A., Jeong, H., Suzuki, S., Cui, H., Matsuura, S., Saito, K., & Sugiura, M. (2026) · Bilingualism Language and Cognition · doi:10.1017/s1366728926101011 · Cited by 2
Erasmus clinical model of the onset and development of stuttering 2.0
Franken, M.-C. J. P., Oonk, L. C., Bast, B. J. E. G., Bouwen, J., & Nil, L. D. (2024) · Journal of Fluency Disorders · doi:10.1016/j.jfludis.2024.106040 · Cited by 1
Inhibitory modulation of speech trajectories: Evidence from a vowel-modified Stroop task
Beach, S. D., & Niziolek, C. A. (2024) · Cognitive Neuropsychology · doi:10.1080/02643294.2024.2315831 · Cited by 1
“As speaking is perhaps the most complex human motor behaviour, lateral inhibition underlies many theoretical and computational accounts of speech motor planning and selection (Bohland et al., 2010; Meyer & Gordon, 1985; Schade & Berg, 1992; Tilsen, 2013; Yaniv et al., 1990).”
BackgroundCai, X. F., & Zhang, Q. (2025) · Brain Research · doi:10.1016/j.brainres.2025.150010 · Cited by 1
Metadata
- Authors
- Bohland, J. W., Bullock, D., & Guenther, F. H.
- Affiliations
- Cold Spring Harbor Laboratory (US)
- Boston University (US)
- 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
- 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
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
