A control model of human tongue movements in speech

Analysis of Tongue Muscle Strain During Speech From Multimodal Magnetic Resonance Imaging

PURPOSE

Muscle groups within the tongue in healthy and diseased populations show different behaviors during speech. Visualizing and quantifying strain patterns of these muscle groups during tongue motion can provide insights into tongue motor control and adaptive behaviors of a patient.

METHOD

We present a pipeline to estimate the strain along the muscle fiber directions in the deforming tongue during speech production. A deep convolutional network estimates the crossing muscle fiber directions in the tongue using diffusion-weighted magnetic resonance imaging (MRI) data acquired at rest. A phase-based registration algorithm is used to estimate motion of the tongue muscles from tagged MRI acquired during speech. After transforming both muscle fiber directions and motion fields into a common atlas space, strain tensors are computed and projected onto the muscle fiber directions, forming so-called strains in the line of actions (SLAs) throughout the tongue. SLAs are then averaged over individual muscles that have been manually labeled in the atlas space using high-resolution T2-weighted MRI. Data were acquired, and this pipeline was run on a cohort of eight healthy controls and two glossectomy patients.

RESULTS

The crossing muscle fibers reconstructed by the deep network show orthogonal patterns. The strain analysis results demonstrate consistency of muscle behaviors among some healthy controls during speech production. The patients show irregular muscle patterns, and their tongue muscles tend to show more extension than the healthy controls.

CONCLUSIONS

The study showed visual evidence of correlation between two muscle groups during speech production. Patients tend to have different strain patterns compared to the controls. Analysis of variations in muscle strains can potentially help develop treatment strategies in oral diseases.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21957011.

Developmental Changes in Coarticulation Degree Relate to Differences in Articulatory Patterns: An Empirically Grounded Modeling Approach

PURPOSE

Coarticulatory effects in speech vary across development, but the sources of this variation remain unclear. This study investigated whether developmental differences in intrasyllabic coarticulation degree could be explained by differences in children's articulatory patterns compared to adults.

METHOD

To address this question, we first compared the tongue configurations of 3- to 7-year-old German children to those of adults. The observed developmental differences were then examined through simulations with Task Dynamics Application, a Task Dynamics simulation system, to establish which articulatory modifications could best reproduce the empirical results. To generate syllables simulating the lack of tongue gesture differentiation, we tested three simulation scenarios.

RESULTS

We found that younger speakers use less differentiated articulatory patterns to achieve alveolar constrictions than adults. The simulations corresponding to undifferentiated control of tongue tip and tongue body resulted in (a) tongue shapes similar to those observed in natural speech and (b) higher degrees of intrasyllabic coarticulation in children when compared to adults.

CONCLUSIONS

Results provide evidence that differences in articulatory patterns contribute to developmental differences in coarticulation degree. This study further shows that empirically informed modeling can advance our understanding of changes in coarticulatory patterns across age.

Developmental Functional Modules in Infant Vocalizations

Purpose Developmental functional modules (DFMs) are biological modules that are defined by their structural (morphological), functional, or developmental elements, and, in some cases, all three of these. This review article considers the hypothesis that vocal development in the first year of life can be understood in large part with respect to DFMs that characterize the speech production system. Method Literature is reviewed on relevant embryology, orofacial reflexes, craniofacial muscle properties, stages of vocal development, and related topics to identity candidates for DFMs. Results The following DFMs are identified and described: laryngeal, pharyngo-laryngeal, mandibular, velopharyngeal, labial complex, and lingual complex. These DFMs and their submodules, considered along with phenomena such as rhythmic movements, account for several well-documented features of vocal development in the first year of life. The proposed DFMs, rooted in embryologic, histologic, and kinematic properties, serve as low-dimensional control variables for the developing vocal tract. Each DFM is semi-autonomous but interacts with other DFMs to produce patterns of vocal behavior. Discussion Considered in relation to contemporary profiles and models of vocal development in the first year of life, DFMs have interpretive and explanatory value. DFMs complement other approaches in the study of infant vocalizations and are grounded in biology.

A Neuromotor to Acoustical Jaw-Tongue Projection Model With Application in Parkinson's Disease Hypokinetic Dysarthria

Aim

The present work proposes the study of the neuromotor activity of the masseter-jaw-tongue articulation during diadochokinetic exercising to establish functional statistical relationships between surface Electromyography (sEMG), 3D Accelerometry (3DAcc), and acoustic features extracted from the speech signal, with the aim of characterizing Hypokinetic Dysarthria (HD). A database of multi-trait signals of recordings from an age-matched control and PD participants are used in the experimental study.

Hypothesis:

The main assumption is that information between sEMG and 3D acceleration, and acoustic features may be quantified using linear regression methods.

Methods

Recordings from a cohort of eight age-matched control participants (4 males, 4 females) and eight PD participants (4 males, 4 females) were collected during the utterance of a diadochokinetic exercise (the fast repetition of diphthong [aI]). The dynamic and acoustic absolute kinematic velocities produced during the exercises were estimated by acoustic filter inversion and numerical integration and differentiation of the speech signal. The amplitude distributions of the absolute kinematic and acoustic velocities (AKV and AFV) are estimated to allow comparisons in terms of Mutual Information.

Results

The regression results show the relationships between sEMG and dynamic and acoustic estimates. The projection methodology may help in understanding the basic neuromotor muscle activity regarding neurodegenerative speech in remote monitoring neuromotor and neurocognitive diseases using speech as the vehicular tool, and in the study of other speech-related disorders. The study also showed strong and significant cross-correlations between articulation kinematics, both for the control and the PD cohorts. The absolute kinematic variables presents an observable difference for the PD participants compared to the control group.

Conclusion

Kinematic distributions derived from acoustic analysis may be useful biomarkers toward characterizing HD in neuromotor disorders providing new insights into PD.

Analysis of fiber strain in the human tongue during speech

This study investigates mechanical cooperation among tongue muscles. Five volunteers were imaged using tagged magnetic resonance imaging to quantify spatiotemporal kinematics while speaking. Waveforms of strain in the line of action of fibers (SLAF) were estimated by projecting strain tensors onto a model of fiber directionality. SLAF waveforms were temporally aligned to determine consistency across subjects and correlation across muscles. The cohort exhibited consistent patterns of SLAF, and muscular extension-contraction was correlated. Volume-preserving tongue movement in speech generation can be achieved through multiple paths, but the study reveals similarities in motion patterns and muscular action-despite anatomical (and other) dissimilarities.

Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants

Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson’s Disease.

Vowel Articulation Dynamic Stability Related to Parkinson's Disease Rating Features: Male Dataset

Neurodegenerative pathologies as Parkinson's Disease (PD) show important distortions in speech, affecting fluency, prosody, articulation and phonation. Classically, measurements based on articulation gestures altering formant positions, as the Vocal Space Area (VSA) or the Formant Centralization Ratio (FCR) have been proposed to measure speech distortion, but these markers are based mainly on static positions of sustained vowels. The present study introduces a measurement based on the mutual information distance among probability density functions of kinematic correlates derived from formant dynamics. An absolute kinematic velocity associated to the position of the jaw and tongue articulation gestures is estimated and modeled statistically. The distribution of this feature may differentiate PD patients from normative speakers during sustained vowel emission. The study is based on a limited database of 53 male PD patients, contrasted to a very selected and stable set of eight normative speakers. In this sense, distances based on Kullback-Leibler divergence seem to be sensitive to PD articulation instability. Correlation studies show statistically relevant relationship between information contents based on articulation instability to certain motor and nonmotor clinical scores, such as freezing of gait, or sleep disorders. Remarkably, one of the statistically relevant correlations point out to the time interval passed since the first diagnostic. These results stress the need of defining scoring scales specifically designed for speech disability estimation and monitoring methodologies in degenerative diseases of neuromotor origin.

Laplace-based modeling of fiber orientation in the tongue

Mechanical modeling of tongue deformation plays a significant role in the study of breathing, swallowing, and speech production. In the absence of internal joints, fiber orientations determine the direction of sarcomeric contraction and have great influence over real and simulated tissue motion. However, subject-specific experimental observations of fiber distribution are difficult to obtain; thus, models of fiber distribution are generally used in mechanical simulations. This paper describes modeling of fiber distribution using solutions of Laplace equations and compares the effectiveness of this approach against tractography from diffusion tensor magnetic resonance imaging. The experiments included qualitative comparison of streamlines from the fiber model against experimental tractography, as well as quantitative differences between biomechanical simulations focusing in the region near the genioglossus. The model showed good overall agreement in terms of fiber directionality and muscle positioning when compared to subject-specific imaging results and the literature. The angle between the fiber distribution model against tractography in the genioglossus and geniohyoid muscles averaged [Formula: see text] likely due to experimental noise. However, kinematic responses were similar between simulations with modeled fibers versus experimentally obtained fibers; average discrepancy in surface displacement ranged from 1 to 7 mm, and average strain residual magnitude ranged from [Formula: see text] to 0.2. The results suggest that, for simulation purposes, the modeled fibers can act as a reasonable approximation for the tongue's fiber distribution. Also, given its agreement with the global tongue anatomy, the approach may be used in model-based reconstruction of displacement tracking and diffusion results.

Inverse Biomechanical Modeling of the Tongue via Machine Learning and Synthetic Training Data

The tongue's deformation during speech can be measured using tagged magnetic resonance imaging, but there is no current method to directly measure the pattern of muscles that activate to produce a given motion. In this paper, the activation pattern of the tongue's muscles is estimated by solving an inverse problem using a random forest. Examples describing different activation patterns and the resulting deformations are generated using a finite-element model of the tongue. These examples form training data for a random forest comprising 30 decision trees to estimate contractions in 262 contractile elements. The method was evaluated on data from tagged magnetic resonance data from actual speech and on simulated data mimicking flaps that might have resulted from glossectomy surgery. The estimation accuracy was modest (5.6% error), but it surpassed a semi-manual approach (8.1% error). The results suggest that a machine learning approach to contraction pattern estimation in the tongue is feasible, even in the presence of flaps.

Parkinson Disease Detection from Speech Articulation Neuromechanics

Aim: The research described is intended to give a description of articulation dynamics as a correlate of the kinematic behavior of the jaw-tongue biomechanical system, encoded as a probability distribution of an absolute joint velocity. This distribution may be used in detecting and grading speech from patients affected by neurodegenerative illnesses, as Parkinson Disease.

Hypothesis: The work hypothesis is that the probability density function of the absolute joint velocity includes information on the stability of phonation when applied to sustained vowels, as well as on fluency if applied to connected speech.

Methods: A dataset of sustained vowels recorded from Parkinson Disease patients is contrasted with similar recordings from normative subjects. The probability distribution of the absolute kinematic velocity of the jaw-tongue system is extracted from each utterance. A Random Least Squares Feed-Forward Network (RLSFN) has been used as a binary classifier working on the pathological and normative datasets in a leave-one-out strategy. Monte Carlo simulations have been conducted to estimate the influence of the stochastic nature of the classifier. Two datasets for each gender were tested (males and females) including 26 normative and 53 pathological subjects in the male set, and 25 normative and 38 pathological in the female set.

Results: Male and female data subsets were tested in single runs, yielding equal error rates under 0.6% (Accuracy over 99.4%). Due to the stochastic nature of each experiment, Monte Carlo runs were conducted to test the reliability of the methodology. The average detection results after 200 Montecarlo runs of a 200 hyperplane hidden layer RLSFN are given in terms of Sensitivity (males: 0.9946, females: 0.9942), Specificity (males: 0.9944, females: 0.9941) and Accuracy (males: 0.9945, females: 0.9942). The area under the ROC curve is 0.9947 (males) and 0.9945 (females). The equal error rate is 0.0054 (males) and 0.0057 (females).

Conclusions: The proposed methodology avails that the use of highly normalized descriptors as the probability distribution of kinematic variables of vowel articulation stability, which has some interesting properties in terms of information theory, boosts the potential of simple yet powerful classifiers in producing quite acceptable detection results in Parkinson Disease.

Test Suite for Image-Based Motion Estimation of the Brain and Tongue

Noninvasive analysis of motion has important uses as qualitative markers for organ function and to validate biomechanical computer simulations relative to experimental observations. Tagged MRI is considered the gold standard for noninvasive tissue motion estimation in the heart, and this has inspired multiple studies focusing on other organs, including the brain under mild acceleration and the tongue during speech. As with other motion estimation approaches, using tagged MRI to measure 3D motion includes several preprocessing steps that affect the quality and accuracy of estimation. Benchmarks, or test suites, are datasets of known geometries and displacements that act as tools to tune tracking parameters or to compare different motion estimation approaches. Because motion estimation was originally developed to study the heart, existing test suites focus on cardiac motion. However, many fundamental differences exist between the heart and other organs, such that parameter tuning (or other optimization) with respect to a cardiac database may not be appropriate. Therefore, the objective of this research was to design and construct motion benchmarks by adopting an "image synthesis" test suite to study brain deformation due to mild rotational accelerations, and a benchmark to model motion of the tongue during speech. To obtain a realistic representation of mechanical behavior, kinematics were obtained from finite-element (FE) models. These results were combined with an approximation of the acquisition process of tagged MRI (including tag generation, slice thickness, and inconsistent motion repetition). To demonstrate an application of the presented methodology, the effect of motion inconsistency on synthetic measurements of head-brain rotation and deformation was evaluated. The results indicated that acquisition inconsistency is roughly proportional to head rotation estimation error. Furthermore, when evaluating non-rigid deformation, the results suggest that inconsistent motion can yield "ghost" shear strains, which are a function of slice acquisition viability as opposed to a true physical deformation.

Assessing the multiscale architecture of muscular tissue with Q-space magnetic resonance imaging: Review

Contraction of muscular tissue requires the synchronized shortening of myofibers arrayed in complex geometrical patterns. Imaging such myofiber patterns with diffusion-weighted MRI reveals architectural ensembles that underlie force generation at the organ scale. Restricted proton diffusion is a stochastic process resulting from random translational motion that may be used to probe the directionality of myofibers in whole tissue. During diffusion-weighted MRI, magnetic field gradients are applied to determine the directional dependence of proton diffusion through the analysis of a diffusional probability distribution function (PDF). The directions of principal (maximal) diffusion within the PDF are associated with similarly aligned diffusion maxima in adjacent voxels to derive multivoxel tracts. Diffusion-weighted MRI with tractography thus constitutes a multiscale method for depicting patterns of cellular organization within biological tissues. We provide in this review, details of the method by which generalized Q-space imaging is used to interrogate multidimensional diffusion space, and thereby to infer the organization of muscular tissue. Q-space imaging derives the lowest possible angular separation of diffusion maxima by optimizing the conditions by which magnetic field gradients are applied to a given tissue. To illustrate, we present the methods and applications associated with Q-space imaging of the multiscale myoarchitecture associated with the human and rodent tongues. These representations emphasize the intricate and continuous nature of muscle fiber organization and suggest a method to depict structural "blueprints" for skeletal and cardiac muscle tissue.

A comprehensive assessment of genioglossus electromyographic activity in healthy adults

The genioglossus (GG) is an extrinsic muscle of the human tongue that plays a critical role in preserving airway patency. In the last quarter century, >50 studies have reported on respiratory-related GG electromyographic (EMG) activity in human subjects. Remarkably, of the studies performed, none have duplicated subject body position, electrode recording locations, and/or breathing task(s), making interpretation and integration of the results across studies extremely challenging. In addition, more recent research assessing lingual anatomy and muscle contractile properties has identified regional differences in muscle fiber type and myosin heavy chain expression, giving rise to the possibility that the anterior and posterior regions of the muscle fulfill distinct functions. Here, we assessed EMG activity in anterior and posterior regions of the GG, across upright and supine, in rest breathing and in volitionally modulated breathing tasks. We tested the hypotheses that GG EMG is greater in the posterior region and in supine, except when breathing is subject to volitional modulation. Our results show differences in the magnitude of EMG (%regional maximum) between anterior and posterior muscle regions (7.95 ± 0.57 vs. 11.10 ± 0.99, respectively; P < 0.001), and between upright and supine (8.63 ± 0.73 vs. 10.42 ± 0.90, respectively; P = 0.008). Although the nature of a task affects the magnitude of EMG (P < 0.001), the effect is similar for anterior and posterior muscle regions and across upright and supine (P > 0.2).

The distributed lambda (λ) model (DLM): a 3-D, finite-element muscle model based on Feldman's λ model; assessment of orofacial gestures

PURPOSE

The authors aimed to design a distributed lambda model (DLM), which is well adapted to implement three-dimensional (3-D), finite-element descriptions of muscles.

METHOD

A muscle element model was designed. Its stress-strain relationships included the active force-length characteristics of the λ model along the muscle fibers, together with the passive properties of muscle tissues in the 3-D space. The muscle element was first assessed using simple geometrical representations of muscles in the form of rectangular bars. It was then included in a 3-D face model, and its impact on lip protrusion was compared with the impact of a Hill-type muscle model.

RESULTS

The force-length characteristic associated with the muscle elements matched well with the invariant characteristics of the λ model. The impact of the passive properties was assessed. Isometric force variation and isotonic displacements were modeled. The comparison with a Hill-type model revealed strong similarities in terms of global stress and strain.

CONCLUSION

The DLM accounted for the characteristics of the λ model. Biomechanically, no clear differences were found between the DLM and a Hill-type model. Accurate evaluations of the λ model, based on the comparison between data and simulations, are now possible with 3-D biomechanical descriptions of the speech articulators because of the DLM.

Electrocorticographic correlates of overt articulation of 44 English phonemes: intracranial recording in children with focal epilepsy

OBJECTIVE

We determined the temporal-spatial patterns of electrocorticography (ECoG) signal modulation during overt articulation of 44 American English phonemes.

METHODS

We studied two children with focal epilepsy who underwent extraoperative ECoG recording. Using animation movies, we delineated 'when' and 'where' gamma- (70-110 Hz) and low-frequency-band activities (10-30 Hz) were modulated during self-paced articulation.

RESULTS

Regardless of the classes of phoneme articulated, gamma-augmentation initially involved a common site within the left inferior Rolandic area. Subsequently, gamma-augmentation and/or attenuation involved distinct sites within the left oral-sensorimotor area with a timing variable across phonemes. Finally, gamma-augmentation in a larynx-sensorimotor area took place uniformly at the onset of sound generation, and effectively distinguished voiced and voiceless phonemes. Gamma-attenuation involved the left inferior-frontal and superior-temporal regions simultaneously during articulation. Low-frequency band attenuation involved widespread regions including the frontal, temporal, and parietal regions.

CONCLUSIONS

Our preliminary results support the notion that articulation of distinct phonemes recruits specific sensorimotor activation and deactivation. Gamma attenuation in the left inferior-frontal and superior-temporal regions may reflect transient functional suppression in these cortical regions during automatic, self-paced vocalization of phonemes containing no semantic or syntactic information.

SIGNIFICANCE

Further studies are warranted to determine if measurement of event-related modulations of gamma-band activity, compared to that of the low-frequency-band, is more useful for decoding the underlying articulatory functions.

Speech production as state feedback control

Spoken language exists because of a remarkable neural process. Inside a speaker's brain, an intended message gives rise to neural signals activating the muscles of the vocal tract. The process is remarkable because these muscles are activated in just the right way that the vocal tract produces sounds a listener understands as the intended message. What is the best approach to understanding the neural substrate of this crucial motor control process? One of the key recent modeling developments in neuroscience has been the use of state feedback control (SFC) theory to explain the role of the CNS in motor control. SFC postulates that the CNS controls motor output by (1) estimating the current dynamic state of the thing (e.g., arm) being controlled, and (2) generating controls based on this estimated state. SFC has successfully predicted a great range of non-speech motor phenomena, but as yet has not received attention in the speech motor control community. Here, we review some of the key characteristics of speech motor control and what they say about the role of the CNS in the process. We then discuss prior efforts to model the role of CNS in speech motor control, and argue that these models have inherent limitations – limitations that are overcome by an SFC model of speech motor control which we describe. We conclude by discussing a plausible neural substrate of our model.

Derivation of a finite-element model of lingual deformation during swallowing from the mechanics of mesoscale myofiber tracts obtained by MRI

To demonstrate the relationship between lingual myoarchitecture and mechanics during swallowing, we performed a finite-element (FE) simulation of lingual deformation employing mesh aligned with the vector coordinates of myofiber tracts obtained by diffusion tensor imaging with tractography in humans. Material properties of individual elements were depicted in terms of Hill's three-component phenomenological model, assuming that the FE mesh was composed of anisotropic muscle and isotropic connective tissue. Moreover, the mechanical model accounted for elastic constraints by passive and active elements from the superior and inferior directions and the effect of out-of-plane muscles and connective tissue. Passive bolus effects were negligible. Myofiber tract activation was simulated over 500 ms in 1-ms steps following lingual tip association with the hard palate and incorporated specifically the accommodative and propulsive phases of the swallow. Examining the displacement field, active and passive muscle stress, elemental stretch, and strain rate relative to changes of global shape, we demonstrate that lingual reconfiguration during these swallow phases is characterized by (in sequence) the following: 1) lingual tip elevation and shortening in the anterior-posterior direction; 2) inferior displacement related to hyoglossus contraction at its inferior-most position; and 3) dominant clockwise rotation related to regional contraction of the genioglossus and contraction of the hyoglossus following anterior displacement. These simulations demonstrate that lingual deformation during the indicated phases of swallowing requires temporally patterned activation of intrinsic and extrinsic muscles and delineate a method to ascertain the mechanics of normal and pathological swallowing.

Kinematic linkage of the tongue, jaw, and hyoid during eating and speech

OBJECTIVE

Tongue movement is temporo-spatially coordinated with jaw and hyoid movements during eating and speech. As such, we evaluated: (1) the correlation between the tongue with jaw and hyoid movements during eating and speech and (2) the relative influence of the jaw and hyoid on determining tongue movement.

DESIGN

Lateral projection videofluorography was recorded while 16 healthy subjects ate solid foods or read a standard passage. The position of anterior and posterior tongue markers (ATM and PTM, respectively), the jaw, and the hyoid relative to the upper occlusal plane was quantified with the upper canine as the origin (0,0) point for Cartesian coordinates. For vertical and horizontal dimensions, separate multiple linear regression analyses were performed with ATM or PTM position as a function of jaw and hyoid positions.

RESULTS

Vertically, both ATM and PTM positions were highly correlated with the jaw and hyoid during eating (median r=0.87). The relative influence was higher for the jaw than the hyoid for ATM position (P<0.001), but lower for PTM position (P=0.04). Horizontally, tongue marker positions had moderate correlation with the jaw and hyoid during eating (r=0.47), due more to hyoid position than to jaw position. Overall, correlations were lower during speech than eating.

CONCLUSION

This study demonstrated distinct kinematic linkages between the movements of the jaw, the hyoid and the anterior and posterior tongue markers, as well as differing impact of the jaw and the hyoid in determining tongue movement during eating and speech.

Tongue movements during water swallowing in healthy young and older adults

PURPOSE

The purpose of this study was to explore the nature and extent of variability in tongue movement during healthy swallowing as a function of aging and gender. In addition, changes were quantified in healthy tongue movements in response to specific differences in the nature of the swallowing task (discrete vs. sequential swallows).

METHOD

Electromagnetic midsagittal articulography (EMMA) was used to study the swallowing-related movements of markers located in midline on the anterior (blade), middle (body), and posterior (dorsum) tongue in a sample of 34 healthy adults in 2 age groups (under vs. over 50 years of age). Participants performed a series of reiterated water swallows, in either a discrete or a sequential manner.

RESULTS

This study shows that age-related changes in tongue movements during swallowing are restricted to the domain of movement duration. The authors confirm that different tongue regions can be selectively modulated during swallowing tasks and that both functional and anatomical constraints influence the manner in which tongue movement modulation occurs. Sequential swallowing, in comparison to discrete swallowing, elicits simplification or down-scaling of several kinematic parameters.

CONCLUSION

The data illustrate task-specific stereotyped patterns of tongue movement in swallowing, which are robust to the effects of healthy aging in all aspects other than movement duration.

Anatomical basis of lingual hydrostatic deformation

The mammalian tongue is believed to fall into a class of organs known as muscular hydrostats, organs for which muscle contraction both generates and provides the skeletal support for motion. We propose that the myoarchitecture of the tongue, consisting of intricate arrays of muscular fibers, forms the structural basis for hydrostatic deformation. Owing to the fact that maximal diffusion of the ubiquitous water molecule occurs orthogonal to the short axis of most fiber-type cells, diffusion-weighted magnetic resonance imaging (MRI)measurements can be used to derive information regarding 3-D fiber orientation in situ. Image data obtained in this manner suggest that the tongue consists of a complex juxtaposition of muscle fibers oriented in orthogonal arrays, which provide the basis for multidirectional contraction and isovolemic deformation. From a mechanical perspective, the lingual tissue may be considered as set of continuous coupled units of compression and expansion from which 3-D strain maps may be derived. Such functional data demonstrate that during physiological movements, such as protrusion, bending and swallowing, hydrostatic deformation occurs via synergistic contractions of orthogonally aligned intrinsic and extrinsic fibers. Lingual deformation can thus be represented in terms of models demonstrating that synergistic contraction of fibers at orthogonal or near-orthogonal directions to each other is a necessary condition for volume-conserving deformation. Evidence is provided in support of the supposition that hydrostatic deformation is based on the contraction of orthogonally aligned intramural fibers functioning as a mechanical continuum.

The dynamics of lingual-mandibular coordination during liquid swallowing

Previous literature on tongue-jaw relationships during swallowing has focused on behaviors observed with chewable solid foods. The present investigation was undertaken to evaluate both the nature and stability of coordinative relationships between the jaw and three points located along the midsagittal groove of the tongue--anterior (blade), middle (body), and posterior (dorsum)--during swallowing of thin and honey-thick liquids. A reiterative swallowing paradigm was used, with two task conditions (discrete and sequential), to explore the stability of tongue-jaw coordination across different frequencies of swallowing. Eight healthy participants in two age groups (young, older) performed sets of repeated swallows. Tongue and jaw movements were measured using electromagnetic midsagittal articulography. The data were analyzed in terms of variability in the spatiotemporal movement pattern for each fleshpoint of interest, and the temporal coupling (frequency entrainment) and relative phasing of movement for each tongue segment compared to the mandible. The results illustrate a stereotypical but not invariant sequence of movement phasing in the tongue-jaw complex during liquid swallowing and task-related reductions in variability at higher frequencies of swallowing in tongue dorsum movements. This evidence supports the idea that different segments of the tongue couple with the jaw as a synergy for swallowing, but can modify their coupling relationship to accommodate task demands.

Coordination of thumb joints during opposition

Thumb opposition plays a vital role in hand function. Kinematically, thumb opposition results from composite movements from multiple joints moving in multiple directions. The purpose of this study was to examine the coordination of thumb joints during opposition tasks. A total of 15 female subjects with asymptomatic hands were studied. Three-dimensional angular kinematics of the carpometacarpal (CMC), metacarpophalangeal (MCP) and interphalangeal (IP) joints were obtained by a marker-based motion analysis system. Thumb opposition revealed coordination among joints in a specific direction (inter-joint coordination) and among different directions within a joint (intra-joint coordination). In particular, linear couplings existed between the flexion and pronation at the CMC joint, and between the flexion of the CMC joint and flexion of the MCP joint. Principal component analysis showed that only two principal components adequately represented the thumb opposition data of seven movement directions. A term functional degrees of freedom by virtue of principal component analysis was proposed to uncover the extent of movement coordination in functional tasks.

Neuromuscular organization of the superior longitudinalis muscle in the human tongue. 1. Motor endplate morphology and muscle fiber architecture

Proper tongue function is essential for respiration and mastication, yet we lack basic information on the anatomical organization underlying human tongue movement. Here we use microdissection, acetylcholinesterase histochemistry, silver staining of nerves, alpha bungarotoxin binding and immunohistochemistry to describe muscle fiber architecture and motor endplate (MEP) distribution of the human superior longitudinalis muscle (SL). The human SL extends from tongue base to tongue tip and is composed of fiber bundles that range from 2.8 to 15.7 mm in length. Individual muscle fibers of the SL range from 1.2 to 17.3 mm in length (1.3-18.2% of muscle length). Seventy-one percent of SL fibers have blunt-blunt terminations; the remainder have blunt-taper terminations. Multiple MEPs are present along SL length and dual MEPs are present on some muscle fibers. These data demonstrate that the human SL is a muscle of "in-series" design. We suggest that SL motor units are organized to innervate specific regions of the tongue body and that activation of SL motor units according to anteroposterior location is one strategy employed by the nervous system to control tongue shape and tongue movement.

Computational simulation of human upper airway collapse using a pressure-/state-dependent model of genioglossal muscle contraction under laminar flow conditions

A three-element, pressure- and state (sleep and wake) -dependent contraction model of the genioglossal muscle was developed based on the microstructure of skeletal muscle and the cross-bridge theory. This model establishes a direct connection between the contractile forces generated in muscle fibers and the measured electromyogram signals during various upper airway conditions. This effectively avoids the difficulty of determining muscle shortening velocity during complex pharyngeal conditions when modeling the muscle's contractile behaviors. The activation of the genioglossal muscle under different conditions was then simulated. A sensitivity analysis was performed to determine the effects of varying each modeled parameter on the muscle's contractile behaviors. This muscle contraction model was then incorporated into our anatomically correct, two-dimensional computational model of the pharyngeal airway to perform a finite-element analysis of air flow, tissue deformation, and airway collapse. The model-predicted muscle deformations are consistent with previous observations regarding upper airway behavior in normal subjects.

Construction and control of a physiological articulatory model

A physiological articulatory model has been constructed using a fast computation method, which replicates midsagittal regions of the speech organs to simulate articulatory movements during speech. This study aims to improve the accuracy of modeling by using the displacement-based finite-element method and to develop a new approach for controlling the model. A "semicontinuum" tongue tissue model was realized by a discrete truss structure with continuum viscoelastic cylinders. Contractile effects of the muscles were systemically examined based on model simulations. The results indicated that each muscle drives the tongue toward an equilibrium position (EP) corresponding to the magnitude of the activation forces. The EPs shifted monotonically as the activation force increased. The monotonic shift revealed a unique and invariant mapping, referred to as an EP map, between a spatial position of the articulators and the muscle forces. This study proposes a control method for the articulatory model based on the EP maps, in which co-contractions of agonist and antagonist muscles are taken into account. By utilizing the co-contraction, the tongue tip and tongue dorsum can be controlled to reach their targets independently. Model simulation showed that the co-contraction of agonist and antagonist muscles could increase the stability of a system in dynamic control.

Tongue movements in feeding and speech

The position of the tongue relative to the upper and lower jaws is regulated in part by the position of the hyoid bone, which, with the anterior and posterior suprahyoid muscles, controls the angulation and length of the floor of the mouth on which the tongue body 'rides'. The instantaneous shape of the tongue is controlled by the 'extrinsic muscles' acting in concert with the 'intrinsic' muscles. Recent anatomical research in non-human mammals has shown that the intrinsic muscles can best be regarded as a 'laminated segmental system' with tightly packed layers of the 'transverse', 'longitudinal', and 'vertical' muscle fibers. Each segment receives separate innervation from branches of the hypoglosssal nerve. These new anatomical findings are contributing to the development of functional models of the tongue, many based on increasingly refined finite element modeling techniques. They also begin to explain the observed behavior of the jaw-hyoid-tongue complex, or the hyomandibular 'kinetic chain', in feeding and consecutive speech. Similarly, major efforts, involving many imaging techniques (cinefluorography, ultrasound, electro-palatography, NMRI, and others), have examined the spatial and temporal relationships of the tongue surface in sound production. The feeding literature shows localized tongue-surface change as the process progresses. The speech literature shows extensive change in tongue shape between classes of vowels and consonants. Although there is a fundamental dichotomy between the referential framework and the methodological approach to studies of the orofacial complex in feeding and speech, it is clear that many of the shapes adopted by the tongue in speaking are seen in feeding. It is suggested that the range of shapes used in feeding is the matrix for both behaviors.

Influences of tongue biomechanics on speech movements during the production of velar stop consonants: a modeling study

This study explores the following hypothesis: forward looping movements of the tongue that are observed in VCV sequences are due partly to the anatomical arrangement of the tongue muscles, how they are used to produce a velar closure, and how the tongue interacts with the palate during consonantal closure. The study uses an anatomically based two-dimensional biomechanical tongue model. Tissue elastic properties are accounted for in finite-element modeling, and movement is controlled by constant-rate control parameter shifts. Tongue raising and lowering movements are produced by the model mainly with the combined actions of the genioglossus, styloglossus, and hyoglossus. Simulations of V1CV2 movements were made, where C is a velar consonant and V is [a], [i], or [u]. Both vowels and consonants are specified in terms of targets, but for the consonant the target is virtual, and cannot be reached because it is beyond the surface of the palate. If V1 is the vowel [a] or [u], the resulting trajectory describes a movement that begins to loop forward before consonant closure and continues to slide along the palate during the closure. This pattern is very stable when moderate changes are made to the specification of the target consonant location and agrees with data published in the literature. If V1 is the vowel [i], looping patterns are also observed, but their orientation was quite sensitive to small changes in the location of the consonant target. These findings also agree with patterns of variability observed in measurements from human speakers, but they contradict data published by Houde [Ph.D. dissertation (1967)]. These observations support the idea that the biomechanical properties of the tongue could be the main factor responsible for the forward loops when V1 is a back vowel, regardless of whether V2 is a back vowel or a front vowel. In the [i] context it seems that additional factors have to be taken into consideration in order to explain the observations made on some speakers.

Tongue-surface movement patterns during speech and swallowing

The tongue has been frequently characterized as being composed of several functionally independent articulators. The question of functional regionality within the tongue was examined by quantifying the strength of coupling among four different tongue locations across a large number of consonantal contexts and participants. Tongue behavior during swallowing was also described. Vertical displacements of pellets affixed to the tongue were extracted from the x-ray microbeam database. Forty-six participants recited 20 vowel-consonant-vowel (VCV) combinations and swallowed 10 ccs of water. Tongue-surface movement patterns were quantitatively described by computing the covariance between the vertical time-histories of all possible pellet pairs. Phonemic differentiation in vertical tongue motions was observed as coupling varied predictably across pellet pairs with place of articulation. Moreover, tongue displacements for speech and swallowing clustered into distinct groups based on their coupling profiles. Functional independence of anterior tongue regions was evidenced by a wide range of movement coupling relations between anterior tongue pellets. The strengths and weaknesses of the covariance-based analysis for characterizing tongue movement are considered.

A biomechanical model of sagittal tongue bending

The human tongue is a structurally complex and extremely flexible organ. In order to better understand the mechanical basis for lingual deformations, we modeled a primitive movement of the tongue, sagittal tongue bending. We hypothesized that sagittal bending is a synergistic deformation derived from co-contraction of the longitudinalis and transversus muscles. Our model of tongue bending was based on classical bimetal strip theory, in which curvature is produced when one muscle layer contracts more so than another. Contraction was modulated via mismatched thermal expansion coefficients and temperature change (to simulate muscular contraction). Our results demonstrated that synergistic contraction produced curvature and strain results which were in better correspondence to empirical results derived from tagging MRI than were the results of contraction of the longitudinalis muscle alone. This fundamental reliance of tongue bending on the synergistic contraction of its intrinsic fibers supports the muscular hydrostat theory of tongue function.

Modeling tongue surface contours from Cine-MRI images

This study demonstrated that a simple mechanical model of global tongue movement in parallel sagittal planes could be used to quantify tongue motion during speech. The goal was to represent simply the differences in 2D tongue surface shapes and positions during speech movements and in subphonemic speech events such as coarticulation and left-to-right asymmetries. The study used tagged Magnetic Resonance Images to capture motion of the tongue during speech. Measurements were made in three sagittal planes (left, midline, right) during movement from consonants (/k/, /s/) to vowels (/i/, /a/, /u/). MR image-sequences were collected during the C-to-V movement. The image-sequence had seven time-phases (frames), each 56 ms in duration. A global model was used to represent the surface motion. The motions were decomposed into translation, rotation, homogeneous stretch, and in-plane shear. The largest C-to-V shape deformation was from /k/ to /a/. It was composed primarily of vertical compression, horizontal expansion, and downward translation. Coarticulatory effects included a trade-off in which tongue shape accommodation was used to reduce the distance traveled between the C and V. Left-to-right motion asymmetries may have increased rate of motion by reducing the amount of mass to be moved.

Coordinate-free sensorimotor processing: computing with population codes

The purpose of the study is to outline a computational architecture for the intelligent processing of sensorimotor patterns. The focus is on the nature of the internal representations of the outside world which are necessary for planning and other goal-oriented functions. A model of cortical map dynamics and self-organization is proposed that integrates a number of concepts and methods partly explored in the field. The novelty and the biological plausibility is related to the global architecture which allows one to deal with sensorimotor patterns in a coordinate-free way, using population codes as distributed internal representations of external variables and the coupled dynamics of cortical maps as a general tool of trajectory formation. The basic computational features of the model are demonstrated in the case of articulatory speech synthesis and some of the metric properties are evaluated by means of simple simulation studies.

Recent tests of the equilibrium-point hypothesis (lambda model)

The lambda model of the equilibrium-point hypothesis (Feldman & Levin, 1995) is an approach to motor control which, like physics, is based on a logical system coordinating empirical data. The model has gone through an interesting period. On one hand, several nontrivial predictions of the model have been successfully verified in recent studies. In addition, the explanatory and predictive capacity of the model has been enhanced by its extension to multimuscle and multijoint systems. On the other hand, claims have recently appeared suggesting that the model should be abandoned. The present paper focuses on these claims and concludes that they are unfounded. Much of the experimental data that have been used to reject the model are actually consistent with it.

A dynamic biomechanical model for neural control of speech production

A model of the midsagittal plane motion of the tongue, jaw, hyoid bone, and larynx is presented, based on the lambda version of equilibrium point hypothesis. The model includes muscle properties and realistic geometrical arrangement of muscles, modeled neural inputs and reflexes, and dynamics of soft tissue and bony structures. The focus is on the organization of control signals underlying vocal tract motions and on the dynamic behavior of articulators. A number of muscle synergies or "basic motions" of the system are identified. In particular, it is shown that systematic sources of variation in an x-ray data base of midsagittal vocal tract motions can be accounted for, at the muscle level, with six independent commands, each corresponding to a direction of articulator motion. There are two commands for the jaw (corresponding to sagittal plane jaw rotation and jaw protrusion), one command controlling larynx height, and three commands for the tongue (corresponding to forward and backward motion of the tongue body, arching and flattening of the tongue dorsum, and motion of the tongue tip). It is suggested that all movements of the system can be approximated as linear combinations of such basic motions. In other words, individual movements and sequences of movements can be accounted for by a simple additive control model. The dynamics of individual commands are also assessed. It is shown that the dynamic effects are not neglectable in speechlike movements because of the different dynamic behaviors of soft and bony structures.