Every normally developing human infant solves the difficult problem of mapping their native-language phonology, but the neural mechanisms underpinning this behavior remain poorly understood. Here, motor constellation theory, an integrative neurophonological model, is presented, with the goal of explicating this issue. It is assumed that infants’ motor-auditory phonological mapping takes place through infants’ orosensory “reaching” for phonological elements observed in the language-specific ambient phonology, via reference to kinesthetic feedback from motor systems, and auditory feedback from resulting speech and speech-like sounds. (...) Attempts are regulated by basal ganglion–cerebellar speech neural circuitry, and successful attempts at reproduction are enforced through dopaminergic signaling. Early in life, the pace of anatomical development constrains mapping such that complete language-specific phonological mapping is prohibited by infants’ undeveloped supralaryngeal vocal tract and undescended larynx; constraints gradually dissolve with age, enabling adult phonology. Where appropriate, reference is made to findings from animal and clinical models. Some implications for future modeling and simulation efforts, as well as clinical settings, are also discussed. (shrink)

Although the neural systems that underlie spoken language are well-known, how they adapt to evolving social cues during natural conversations remains an unanswered question. In this work we investigate the neural correlates of face-to-face conversations between two individuals using functional near infrared spectroscopy and acoustical analyses of concurrent audio recordings. Nineteen pairs of healthy adults engaged in live discussions on two controversial topics where their opinions were either in agreement or disagreement. Participants were matched according to their a priori opinions (...) on these topics as assessed by questionnaire. Acoustic measures of the recorded speech including the fundamental frequency range, median fundamental frequency, syllable rate, and acoustic energy were elevated during disagreement relative to agreement. Consistent with both the a priori opinion ratings and the acoustic findings, neural activity associated with long-range functional networks, rather than the canonical language areas, was also differentiated by the two conditions. Specifically, the frontoparietal system including bilateral dorsolateral prefrontal cortex, left supramarginal gyrus, angular gyrus, and superior temporal gyrus showed increased activity while talking during disagreement. In contrast, talking during agreement was characterized by increased activity in a social and attention network including right supramarginal gyrus, bilateral frontal eye-fields, and left frontopolar regions. Further, these social and visual attention networks were more synchronous across brains during agreement than disagreement. Rather than localized modulation of the canonical language system, these findings are most consistent with a model of distributed and adaptive language-related processes including cross-brain neural coupling that serves dynamic verbal exchanges. (shrink)

A model of gestural sequencing in speech is proposed that aspires to producing biologically plausible fluent and efficient movement in generating an utterance. We have previously proposed a modification of the well-known task dynamic implementation of articulatory phonology such that any given articulatory movement can be associated with a quantification of effort (Simko & Cummins, 2010). To this we add a quantitative cost that decreases as speech gestures become more precise, and hence intelligible, and a third cost component that places (...) a premium on the duration of an utterance. Together, these three cost elements allow us to derive algorithmically optimal sequences of gestures and dynamical parameters for generating articulator movement. We show that the optimized movement displays many timing characteristics that are representative of real speech movement, capturing subtle details of relative timing between gestures. Optimal movement sequences also display invariances in timing that suggest syllable-level coordination for CV sequences. We explore the behavior of the model as prosodic context is manipulated in two dimensions: clarity of articulation and speech rate. Smooth, fluid, and efficient movements result. (shrink)

PurposeThe ability to hear ourselves speak has been shown to play an important role in the development and maintenance of fluent and coherent speech. Despite this, little is known about the developing speech motor control system throughout childhood, in particular if and how vocal and articulatory control may differ throughout development. A scoping review was undertaken to identify and describe the full range of studies investigating responses to frequency altered auditory feedback in pediatric populations and their contributions to our understanding (...) of the development of auditory feedback control and sensorimotor learning in childhood and adolescence.MethodRelevant studies were identified through a comprehensive search strategy of six academic databases for studies that included real-time perturbation of frequency in auditory input, an analysis of immediate effects on speech, and participants aged 18 years or younger.ResultsTwenty-three articles met inclusion criteria. Across studies, there was a wide variety of designs, outcomes and measures used. Manipulations included fundamental frequency, formant frequency, frequency centroid of fricatives, and both fundamental and formant frequencies. Study designs included contrasts across childhood, between children and adults, and between typical, pediatric clinical and adult populations. Measures primarily explored acoustic properties of speech responses. Some studies additionally examined the association of these acoustic responses with clinical measures, and neural measures using electrophysiology and magnetic resonance imaging.ConclusionFindings indicated that children above 4 years generally compensated in the opposite direction of the manipulation, however, in several cases not as effectively as adults. Overall, results varied greatly due to the broad range of manipulations and designs used, making generalization challenging. Differences found between age groups in the features of the compensatory vocal responses, latency of responses, vocal variability and perceptual abilities, suggest that maturational changes may be occurring in the speech motor control system, affecting the extent to which auditory feedback is used to modify internal sensorimotor representations. Varied findings suggest vocal control develops prior to articulatory control. Future studies with multiple outcome measures, manipulations, and more expansive age ranges are needed to elucidate findings. (shrink)

Intelligible speakers achieve specific vocal tract constrictions in rapid sequence. These constrictions are associated in theory with speech motor goals. Adult-focused models of speech production assume that discrete phonological representations, sequenced into word-length plans for output, define these goals. This assumption introduces a serial order problem for speech. It is also at odds with children's speech. In particular, child phonology and timing control suggest holistic speech plans, and so the hypothesis of whole word production. This hypothesis solves the serial order (...) problem by avoiding it. When the same solution is applied to adult speech the problem becomes how to explain the development of highly intelligible speech. This is the problem addressed here. A modeling approach is used to demonstrate how perceptual-motor units of production emerge over developmental time with the perceptual-motor integration of holistic speech plans that are also phonological representations; the specific argument is that perceptual-motor units are a product of trajectories (nearly) crossing in motor space. The model, which focuses on the integration process, defines the perceptual-motor map as a set of linked pairs of experienced perceptual and motor trajectories. The trajectories are time-based excursions through speaker-defined perceptual and motor spaces. By hypothesis, junctures appear where motor trajectories near or overlap one another in motor space when the shared (or extremely similar) articulatory configurations in these regions are exploited to combine perceptually-linked motor paths along different trajectories. Junctures form in clusters in motor space. These clusters, along with their corresponding (linked) perceptual points, represent perceptual-motor units of production, albeit at the level of speech motor control only. The units serve as pivots in motor space during speaking; they are points of transition from one motor trajectory to another along perceptually-linked paths that are selected to produce best approximations of whole word targets. (shrink)

Experimental studies of speech production involving compensations for auditory and somatosensory perturbations and adaptation after training suggest that both types of sensory information are considered to plan and monitor speech production. Interestingly, individual sensory preferences have been observed in this context: subjects who compensate less for somatosensory perturbations compensate more for auditory perturbations, and \textit{vice versa}. We propose to integrate this sensory preference phenomenon in a model of speech motor planning using a probabilistic model in which speech units are characterized (...) both in auditory and somatosensory terms. Sensory preference is implemented in the model according to two approaches. In the first approach, which is often used in motor control models accounting for sensory integration, sensory preference is attributed to the relative precision (i.e., inverse of the variance) of the sensory characterization of the speech motor goals associated with phonological units (which are phonemes in the context of this paper). In the second, ``more original’’ variant, sensory preference is implemented by modulating the sensitivity of the comparison between the predicted sensory consequences of motor commands and the sensory characterizations of the phonemes. We present simulation results using these two variants, in the context of the adaptation to an auditory perturbation, implemented in a 2-dimensional biomechanical model of the tongue. Simulation results show that both variants lead to qualitatively similar results. Distinguishing them experimentally would require precise analyses of partial compensation patterns. However, the second proposed variant implements sensory preference without changing the sensory characterizations of the phonemes. This dissociates sensory preference and sensory characterizations of the phonemes, and makes the account of sensory preference more flexible. Indeed, in the second variant the sensory characterizations of the phonemes can remain stable, when sensory preference varies as a response to cognitive or attentional control. This opens new perspectives for capturing speech production variability associated with aging, disorders and speaking conditions. (shrink)

Neuroethological investigations of mammalian and avian auditory systems have documented species-specific specializations for processing complex acoustic signals that could, if viewed in abstract terms, have an intriguing and striking relevance for human speech sound categorization and representation. Each species forms biologically relevant categories based on combinatorial analysis of information-bearing parameters within the complex input signal. This target article uses known neural models from the mustached bat and barn owl to develop, by analogy, a conceptualization of human processing of consonant plus (...) vowel sequences that offers a partial solution to the noninvariance dilemma the locus equations orderly output constraint”) is hypothesized based on the notion of an evolutionarily conserved auditory-processing strategy. High correlation and linearity between critical parameters in the speech signal that help to cue place of articulation categories might have evolved to satisfy a preadaptation by mammalian auditory systems for representing tightly correlated, linearly related components of acoustic signals. (shrink)

The proposed model consists of 1) a Phonological Planning Component to plan the symbolic and relational goals for an utterance, 2) a Phonetic Planning Component to plan the quantitative details of the acoustic goals and how they will be achieved articulatorily, and 3) a Motor-Sensory Implementation Component to ensure that the goals are achieved on time. The temporal characteristics specified in the Phonetic Planning Component include durations between acoustic landmarks, as well as parameters of Lee’s TauG-Guidance equation, which determine how (...) a movement evolves over time. Movement coordination is assumed to be based on movement endpoints (rather than onsets) and accomplished via Tau-coupling (Lee 1998). Both the Phonetic Planning and Motor-Sensory Implementation components are assumed to make use of general-purpose, phonology-extrinsic, timekeeping mechanisms to represent, specify, and track time. Supporting evidence includes greater timing precision at movement endpoints compared to other parts of movements, suggesting the separate control of the timing of movement endpoints compared to other parts of movement. This evidence challenges models in which all parts of a movement trajectory are controlled by the same equation of motion, but supports models in which a) each abstract, symbolic phonological representation maps onto spatial and temporal characteristics of the part(s) of movement most closely related to the goal of producing a planned set of acoustic cues to signal the phonological contrast (often the endpoint), b) movements are coordinated primarily based on the goal-related part of movement, and c) speakers give priority to the accurate implementation of the part(s) of movement most closely related to the phonological goals. Further support for phonology-extrinsic timing comes from three types of evidence suggesting that surface durations are represented during speech production. Finally, phonology-extrinsic timing is supported by greater timing variability for repetitions of longer intervals, assumed to be due to noise in a general-purpose (and phonology-extrinsic) timekeeping process. The evidence appears to be incompatible with models that have a unified Phonology/Phonetics Component, with models which do not represent the surface timing of phonetic events, nor with models in which timing in speech production is not represented, specified and tracked by a general-purpose timekeeping mechanisms. (shrink)