Characterization of central manifestations in patients with Niemann-Pick disease type C.

PURPOSE: Niemann-Pick disease type C (NPC) is a rare lysosomal storage disease characterized by progressive neurodegeneration and neuropsychiatric symptoms. This study investigated pathophysiological mechanisms underlying motor deficits, particularly speech production, and cognitive impairment. METHODS: We prospectively phenotyped 8 adults with NPC and age-sex-matched healthy controls using a comprehensive assessment battery, encompassing clinical presentation, plasma biomarkers, hand-motor skills, speech production, cognitive tasks, and (micro-)structural and functional central nervous system properties through magnetic resonance imaging. RESULTS: Patients with NPC demonstrated deficits in fine-motor skills, speech production timing and coordination, and cognitive performance. Magnetic resonance imaging revealed reduced cortical thickness and volume in cerebellar subdivisions (lobule VI and crus I), cortical (frontal, temporal, and cingulate gyri) and subcortical (thalamus and basal ganglia) regions, and increased choroid plexus volumes in NPC. White matter fractional anisotropy was reduced in specific pathways (intracerebellar input and Purkinje tracts), whereas diffusion tensor imaging graph theory analysis identified altered structural connectivity. Patients with NPC exhibited altered activity in sensorimotor and cognitive processing hubs during resting-state and speech production. Canonical component analysis highlighted the role of cerebellar-cerebral circuitry in NPC and its integration with behavioral performance and disease severity. CONCLUSION: This deep phenotyping approach offers a comprehensive systems neuroscience understanding of NPC motor and cognitive impairments, identifying potential central nervous system biomarkers.

Anomalous morphology in left hemisphere motor and premotor cortex of children who stutter.

Stuttering is a neurodevelopmental disorder that affects the smooth flow of speech production. Stuttering onset occurs during a dynamic period of development when children first start learning to formulate sentences. Although most children grow out of stuttering naturally, ∼1% of all children develop persistent stuttering that can lead to significant psychosocial consequences throughout one's life. To date, few studies have examined neural bases of stuttering in children who stutter, and even fewer have examined the basis for natural recovery versus persistence of stuttering. Here we report the first study to conduct surface-based analysis of the brain morphometric measures in children who stutter. We used FreeSurfer to extract cortical size and shape measures from structural MRI scans collected from the initial year of a longitudinal study involving 70 children (36 stuttering, 34 controls) in the 3-10-year range. The stuttering group was further divided into two groups: persistent and recovered, based on their later longitudinal visits that allowed determination of their eventual clinical outcome. A region of interest analysis that focused on the left hemisphere speech network and a whole-brain exploratory analysis were conducted to examine group differences and group × age interaction effects. We found that the persistent group could be differentiated from the control and recovered groups by reduced cortical thickness in left motor and lateral premotor cortical regions. The recovered group showed an age-related decrease in local gyrification in the left medial premotor cortex (supplementary motor area and and pre-supplementary motor area). These results provide strong evidence of a primary deficit in the left hemisphere speech network, specifically involving lateral premotor cortex and primary motor cortex, in persistent developmental stuttering. Results further point to a possible compensatory mechanism involving left medial premotor cortex in those who recover from childhood stuttering.

The neural correlates of speech motor sequence learning.

Speech is perhaps the most sophisticated example of a species-wide movement capability in the animal kingdom, requiring split-second sequencing of approximately 100 muscles in the respiratory, laryngeal, and oral movement systems. Despite the unique role speech plays in human interaction and the debilitating impact of its disruption, little is known about the neural mechanisms underlying speech motor learning. Here, we studied the behavioral and neural correlates of learning new speech motor sequences. Participants repeatedly produced novel, meaningless syllables comprising illegal consonant clusters (e.g., GVAZF) over 2 days of practice. Following practice, participants produced the sequences with fewer errors and shorter durations, indicative of motor learning. Using fMRI, we compared brain activity during production of the learned illegal sequences and novel illegal sequences. Greater activity was noted during production of novel sequences in brain regions linked to non-speech motor sequence learning, including the BG and pre-SMA. Activity during novel sequence production was also greater in brain regions associated with learning and maintaining speech motor programs, including lateral premotor cortex, frontal operculum, and posterior superior temporal cortex. Measures of learning success correlated positively with activity in left frontal operculum and white matter integrity under left posterior superior temporal sulcus. These findings indicate speech motor sequence learning relies not only on brain areas involved generally in motor sequencing learning but also those associated with feedback-based speech motor learning. Furthermore, learning success is modulated by the integrity of structural connectivity between these motor and sensory brain regions.

Evidence for planning and motor subtypes of stuttering based on resting state functional connectivity.

We tested the hypothesis, generated from the Gradient Order Directions Into Velocities of Articulators (GODIVA) model, that adults who stutter (AWS) may comprise subtypes based on differing connectivity within the cortico-basal ganglia planning or motor loop. Resting state functional connectivity from 91 AWS and 79 controls was measured for all GODIVA model connections. Based on a principal components analysis, two connections accounted for most of the connectivity variability in AWS: left thalamus - left posterior inferior frontal sulcus (planning loop component) and left supplementary motor area - left ventral premotor cortex (motor loop component). A k-means clustering algorithm using the two connections revealed three clusters of AWS. Cluster 1 was significantly different from controls in both connections; Cluster 2 was significantly different in only the planning loop; and Cluster 3 was significantly different in only the motor loop. These findings suggest the presence of planning and motor subtypes of stuttering.

Lateralization and Time-Course of Cortical Phonological Representations during Syllable Production.

Spoken language contains information at a broad range of timescales, from phonetic distinctions on the order of milliseconds to semantic contexts which shift over seconds to minutes. It is not well understood how the brain's speech production systems combine features at these timescales into a coherent vocal output. We investigated the spatial and temporal representations in cerebral cortex of three phonological units with different durations: consonants, vowels, and syllables. Electrocorticography (ECoG) recordings were obtained from five participants while speaking single syllables. We developed a novel clustering and Kalman filter-based trend analysis procedure to sort electrodes into temporal response profiles. A linear discriminant classifier was used to determine how strongly each electrode's response encoded phonological features. We found distinct time-courses of encoding phonological units depending on their duration: consonants were represented more during speech preparation, vowels were represented evenly throughout trials, and syllables during production. Locations of strongly speech-encoding electrodes (the top 30% of electrodes) likewise depended on phonological element duration, with consonant-encoding electrodes left-lateralized, vowel-encoding hemispherically balanced, and syllable-encoding right-lateralized. The lateralization of speech-encoding electrodes depended on onset time, with electrodes active before or after speech production favoring left hemisphere and those active during speech favoring the right. Single-electrode speech classification revealed cortical areas with preferential encoding of particular phonemic elements, including consonant encoding in the left precentral and postcentral gyri and syllable encoding in the right middle frontal gyrus. Our findings support neurolinguistic theories of left hemisphere specialization for processing short-timescale linguistic units and right hemisphere processing of longer-duration units.

A comparison of structural morphometry in children and adults with persistent developmental stuttering.

This cross-sectional study aimed to differentiate earlier occurring neuroanatomical differences that may reflect core deficits in stuttering versus changes associated with a longer duration of stuttering by analysing structural morphometry in a large sample of children and adults who stutter and age-matched controls. Whole-brain T1-weighted structural scans were obtained from 166 individuals who stutter (74 children, 92 adults; ages 3-58) and 191 controls (92 children, 99 adults; ages 3-53) from eight prior studies in our laboratories. Mean size and gyrification measures were extracted using FreeSurfer software for each cortical region of interest. FreeSurfer software was also used to generate subcortical volumes for regions in the automatic subcortical segmentation. For cortical analyses, separate ANOVA analyses of size (surface area, cortical thickness) and gyrification (local gyrification index) measures were conducted to test for a main effect of diagnosis (stuttering, control) and the interaction of diagnosis-group with age-group (children, adults) across cortical regions. Cortical analyses were first conducted across a set of regions that comprise the speech network and then in a second whole-brain analysis. Next, separate ANOVA analyses of volume were conducted across subcortical regions in each hemisphere. False discovery rate corrections were applied for all analyses. Additionally, we tested for correlations between structural morphometry and stuttering severity. Analyses revealed thinner cortex in children who stutter compared with controls in several key speech-planning regions, with significant correlations between cortical thickness and stuttering severity. These differences in cortical size were not present in adults who stutter, who instead showed reduced gyrification in the right inferior frontal gyrus. Findings suggest that early cortical anomalies in key speech planning regions may be associated with stuttering onset. Persistent stuttering into adulthood may result from network-level dysfunction instead of focal differences in cortical morphometry. Adults who stutter may also have a more heterogeneous neural presentation than children who stutter due to their unique lived experiences.

Increased Intra-Subject Variability of Neural Activity During Speech Production in People with Autism Spectrum Disorder.

Background: Communication difficulties are a core deficit in many people with autism spectrum disorder (ASD). The current study evaluated neural activation in participants with ASD and neurotypical (NT) controls during a speech production task. Methods: Neural activities of participants with ASD (N = 15, M = 16.7 years, language abilities ranged from low verbal abilities to verbally fluent) and NT controls (N = 12, M = 17.1 years) was examined using functional magnetic resonance imaging with a sparse-sampling paradigm. Results: There were no differences between the ASD and NT groups in average speech activation or inter-subject run-to-run variability in speech activation. Intra-subject run-to-run neural variability was greater in the ASD group and was positively correlated with autism severity in cortical areas associated with speech. Conclusions: These findings highlight the importance of understanding intra-subject neural variability in participants with ASD.

fMRI investigation of unexpected somatosensory feedback perturbation during speech.

Somatosensory feedback plays a critical role in the coordination of articulator movements for speech production. In response to unexpected resistance to lip or jaw movements during speech, fluent speakers can use the difference between the somatosensory expectations of a speech sound and the actual somatosensory feedback to adjust the trajectories of functionally relevant but unimpeded articulators. In an effort to investigate the neural substrates underlying the somatosensory feedback control of speech, we used an event-related sparse sampling functional magnetic resonance imaging paradigm and a novel pneumatic device that unpredictably blocked subjects' jaw movements. In comparison to speech, perturbed speech, in which jaw perturbation prompted the generation of compensatory speech motor commands, demonstrated increased effects in bilateral ventral motor cortex, right-lateralized anterior supramarginal gyrus, inferior frontal gyrus pars triangularis and ventral premotor cortex, and bilateral inferior posterior cerebellum (lobule VIII). Structural equation modeling revealed a significant increased influence from left anterior supramarginal gyrus to right anterior supramarginal gyrus and from left anterior supramarginal gyrus to right ventral premotor cortex as well as a significant increased reciprocal influence between right ventral premotor cortex and right ventral motor cortex and right anterior supramarginal gyrus and right inferior frontal gyrus pars triangularis for perturbed speech relative to speech. These results suggest that bilateral anterior supramarginal gyrus, right inferior frontal gyrus pars triangularis, right ventral premotor and motor cortices are functionally coupled and influence speech motor output when somatosensory feedback is unexpectedly perturbed during speech production.

Representation of semantic typicality in brain activation in healthy adults and individuals with aphasia: A multi-voxel pattern analysis.

This study aimed to investigate brain regions that show different activation patterns between semantically typical and atypical items in both healthy adults and individuals with aphasia (PWA). Eighteen neurologically healthy adults and twenty-one PWA participated in an fMRI semantic feature verification task that included typical and atypical stimuli from five different semantic categories. A whole-brain searchlight multi-voxel pattern analysis (MVPA) was conducted to classify brain activation patterns between typical and atypical conditions in each participant group separately. Behavioral responses were faster and more accurate for typical vs. atypical items across both groups. The searchlight MVPA identified two significant clusters in healthy adults: left middle occipital gyrus and right calcarine cortex, but no significant clusters were found in PWA. A follow-up analysis in PWA revealed a significant association between neural classification of semantic typicality in the left middle occipital gyrus and reaction times in the fMRI task. When the typicality effect was examined for each semantic category at the univariate level, significance was identified in the visual cortex for fruits in both groups of participants. These findings suggest that semantic typicality was modulated in the visual cortex in healthy individuals, but to a lesser extent in the same region in PWA.

Reliability of single-subject neural activation patterns in speech production tasks.

Speech neuroimaging research targeting individual speakers could help elucidate differences that may be crucial to understanding speech disorders. However, this research necessitates reliable brain activation across multiple speech production sessions. In the present study, we evaluated the reliability of speech-related brain activity measured by functional magnetic resonance imaging data from twenty neuro-typical subjects who participated in two experiments involving reading aloud simple speech stimuli. Using traditional methods like the Dice and intraclass correlation coefficients, we found that most individuals displayed moderate to high reliability. We also found that a novel machine-learning subject classifier could identify these individuals by their speech activation patterns with 97% accuracy from among a dataset of seventy-five subjects. These results suggest that single-subject speech research would yield valid results and that investigations into the reliability of speech activation in people with speech disorders are warranted.

Behavioral and neural correlates of speech motor sequence learning in stuttering and neurotypical speakers: an fMRI investigation.

Stuttering is a neurodevelopmental disorder characterized by impaired production of coordinated articulatory movements needed for fluent speech. It is currently unknown whether these abnormal production characteristics reflect disruptions to brain mechanisms underlying the acquisition and/or execution of speech motor sequences. To dissociate learning and control processes, we used a motor sequence learning paradigm to examine the behavioral and neural correlates of learning to produce novel phoneme sequences in adults who stutter (AWS) and neurotypical controls. Participants intensively practiced producing pseudowords containing non-native consonant clusters (e.g., "gvasf") over two days. The behavioral results indicated that although the two experimental groups showed comparable learning trajectories, AWS performed significantly worse on the task prior to and after speech motor practice. Using functional magnetic resonance imaging (fMRI), the authors compared brain activity during articulation of the practiced words and a set of novel pseudowords (matched in phonetic complexity). FMRI analyses revealed no differences between AWS and controls in cortical or subcortical regions; both groups showed comparable increases in activation in left-lateralized brain areas implicated in phonological working memory and speech motor planning during production of the novel sequences compared to the practiced sequences. Moreover, activation in left-lateralized basal ganglia sites was negatively correlated with in-scanner mean disfluency in AWS. Collectively, these findings demonstrate that AWS exhibit no deficit in constructing new speech motor sequences but do show impaired execution of these sequences before and after they have been acquired and consolidated.

The Neural Circuitry Underlying the "Rhythm Effect" in Stuttering.

Purpose Stuttering is characterized by intermittent speech disfluencies, which are dramatically reduced when speakers synchronize their speech with a steady beat. The goal of this study was to characterize the neural underpinnings of this phenomenon using functional magnetic resonance imaging. Method Data were collected from 16 adults who stutter and 17 adults who do not stutter while they read sentences aloud either in a normal, self-paced fashion or paced by the beat of a series of isochronous tones ("rhythmic"). Task activation and task-based functional connectivity analyses were carried out to compare neural responses between speaking conditions and groups after controlling for speaking rate. Results Adults who stutter produced fewer disfluent trials in the rhythmic condition than in the normal condition. Adults who stutter did not have any significant changes in activation between the rhythmic condition and the normal condition, but when groups were collapsed, participants had greater activation in the rhythmic condition in regions associated with speech sequencing, sensory feedback control, and timing perception. Adults who stutter also demonstrated increased functional connectivity among cerebellar regions during rhythmic speech as compared to normal speech and decreased connectivity between the left inferior cerebellum and the left prefrontal cortex. Conclusions Modulation of connectivity in the cerebellum and prefrontal cortex during rhythmic speech suggests that this fluency-inducing technique activates a compensatory timing system in the cerebellum and potentially modulates top-down motor control and attentional systems. These findings corroborate previous work associating the cerebellum with fluency in adults who stutter and indicate that the cerebellum may be targeted to enhance future therapeutic interventions. Supplemental Material https://doi.org/10.23641/asha.14417681.

Neural substrates of verbal repetition deficits in primary progressive aphasia.

In this cross-sectional study, we examined the relationship between cortical thickness and performance on several verbal repetition tasks in a cohort of patients with primary progressive aphasia in order to test predictions generated by theoretical accounts of phonological working memory that predict phonological content buffers in left posterior inferior frontal sulcus and supramarginal gyrus. Cortical surfaces were reconstructed from magnetic resonance imaging scans from 42 participants diagnosed with primary progressive aphasia. Cortical thickness was measured in a set of anatomical regions spanning the entire cerebral cortex. Correlation analyses were performed between cortical thickness and average score across three phonological working memory-related tasks: the Repetition sub-test from the Western Aphasia Battery, a forward digit span task, and a backward digit span task. Significant correlations were found between average working memory score across tasks and cortical thickness in left supramarginal gyrus and left posterior inferior frontal sulcus, in support of prior theoretical accounts of phonological working memory. Exploratory whole-brain correlation analyses performed for each of the three behavioural tasks individually revealed a distinct set of positively correlated regions for each task. Comparison of cortical thickness measures from different primary progressive aphasia sub-types to cortical thickness in age-matched controls further revealed unique patterns of atrophy in the different subtypes.

Distinct representations of phonemes, syllables, and supra-syllabic sequences in the speech production network.

Functional neuroimaging studies have converged on a core network of brain regions that supports speech production, but the sublexical processing stages performed by the different parts of this network remain unclear. Using an fMRI adaptation paradigm and quantitative analysis of patterns of activation rather than contrast subtractions alone, we were able to identify a set of neural substrates predominantly engaged in phonemic, syllabic, and supra-syllabic levels of processing during speech. Phoneme-level processes were found in the left SMA, pallidum, posterior superior temporal gyrus, and superior lateral cerebellum. Syllable-level processes were found in the left ventral premotor cortex, and supra-syllabic processes related to phonological chunking were found in the right superior lateral cerebellum. Active regions that were not sensitive to sublexical manipulations included primary motor and auditory cortical areas, and medial cerebellum. These results offer a quantitative technique for localizing sublexical neural processes that are difficult to dissociate using non-invasive imaging techniques and provide the beginnings of a "brain map" for language output.

Auditory Feedback Control Mechanisms Do Not Contribute to Cortical Hyperactivity Within the Voice Production Network in Adductor Spasmodic Dysphonia.

Purpose Adductor spasmodic dysphonia (ADSD), the most common form of spasmodic dysphonia, is a debilitating voice disorder characterized by hyperactivity and muscle spasms in the vocal folds during speech. Prior neuroimaging studies have noted excessive brain activity during speech in participants with ADSD compared to controls. Speech involves an auditory feedback control mechanism that generates motor commands aimed at eliminating disparities between desired and actual auditory signals. Thus, excessive neural activity in ADSD during speech may reflect, at least in part, increased engagement of the auditory feedback control mechanism as it attempts to correct vocal production errors detected through audition. Method To test this possibility, functional magnetic resonance imaging was used to identify differences between participants with ADSD (n = 12) and age-matched controls (n = 12) in (a) brain activity when producing speech under different auditory feedback conditions and (b) resting-state functional connectivity within the cortical network responsible for vocalization. Results As seen in prior studies, the ADSD group had significantly higher activity than the control group during speech with normal auditory feedback (compared to a silent baseline task) in three left-hemisphere cortical regions: ventral Rolandic (sensorimotor) cortex, anterior planum temporale, and posterior superior temporal gyrus/planum temporale. Importantly, this same pattern of hyperactivity was also found when auditory feedback control of speech was eliminated through masking noise. Furthermore, the ADSD group had significantly higher resting-state functional connectivity between sensorimotor and auditory cortical regions within the left hemisphere as well as between the left and right hemispheres. Conclusions Together, our results indicate that hyperactivation in the cortical speech network of individuals with ADSD does not result from hyperactive auditory feedback control mechanisms and rather is likely related to impairments in somatosensory feedback control and/or feedforward control mechanisms.

Functional Parcellation of the Speech Production Cortex.

Neuroimaging has revealed a core network of cortical regions that contribute to speech production, but the functional organization of this network remains poorly understood. Purpose We describe efforts to identify reliable boundaries around functionally homogenous regions within the cortical speech motor control network in order to improve the sensitivity of functional magnetic resonance imaging (fMRI) analyses of speech production and thus improve our understanding of the functional organization of speech production in the brain. Method We used a bottom-up, data-driven approach by pooling data from 12 previously conducted fMRI studies of speech production involving the production of monosyllabic and bisyllabic words and pseudowords that ranged from single vowels and consonant-vowel pairs to short sentences (163 scanning sessions, 136 unique participants, 39 different speech conditions). After preprocessing all data through the same pipeline and registering individual contrast maps to a common surface space, hierarchical clustering was applied to contrast maps randomly sampled from the pooled data set in order to identify consistent functional boundaries across subjects and tasks. Boundary completion was achieved by applying adaptive smoothing and watershed segmentation to the thresholded population-level boundary map. Hierarchical clustering was applied to the mean within-functional region of interest (fROI) response to identify networks of fROIs that respond similarly during speech. Results We identified highly reliable functional boundaries across the cortical areas involved in speech production. Boundary completion resulted in 117 fROIs in the left hemisphere and 109 in the right hemisphere. Clustering of the mean within-fROI response revealed a core sensorimotor network flanked by a speech motor planning network. The majority of the left inferior frontal gyrus clustered with the visual word form area and brain regions (e.g., anterior insula, dorsal anterior cingulate) associated with detecting salient sensory inputs and choosing the appropriate action. Conclusion The fROIs provide insight into the organization of the speech production network and a valuable tool for studying speech production in the brain by improving within-group and between-groups comparisons of speech-related brain activity. Supplemental Material https://doi.org/10.23641/asha.9402674.

A neuroimaging study of premotor lateralization and cerebellar involvement in the production of phonemes and syllables.

PURPOSE: This study investigated the network of brain regions involved in overt production of vowels, monosyllables, and bisyllables to test hypotheses derived from the Directions Into Velocities of Articulators (DIVA) model of speech production (Guenther, Ghosh, & Tourville, 2006). The DIVA model predicts left lateralized activity in inferior frontal cortex when producing a single syllable or phoneme and increased cerebellar activity for consonant-vowel syllables compared with steady-state vowels. METHOD: Sparse sampling functional magnetic resonance imaging (fMRI) was used to collect data from 10 right-handed speakers of American English while producing isolated monosyllables (e.g., "ba," "oo"). Data were analyzed using both voxel-based and participant-specific anatomical region-of-interest-based techniques. RESULTS: Overt production of single monosyllables activated a network of brain regions, including left ventral premotor cortex, left posterior inferior frontal gyrus, bilateral supplementary motor area, sensorimotor cortex, auditory cortex, thalamus, and cerebellum. Paravermal cerebellum showed greater activity for consonant-vowel syllables compared to vowels. CONCLUSIONS: The finding of left-lateralized premotor cortex activity supports the DIVA model prediction that this area contains cell populations representing syllable motor programs without regard for semantic content. Furthermore, the superior paravermal cerebellum is more active for consonant-vowel syllables compared with vowels, perhaps due to increased timing constraints for consonant production.

An Investigation of Compensation and Adaptation to Auditory Perturbations in Individuals With Acquired Apraxia of Speech.

Two auditory perturbation experiments were used to investigate the integrity of neural circuits responsible for speech sensorimotor adaptation in acquired apraxia of speech (AOS). This has implications for understanding the nature of AOS as well as normal speech motor control. Two experiments were conducted. In Experiment 1, compensatory responses to unpredictable fundamental frequency (F0) perturbations during vocalization were investigated in healthy older adults and adults with acquired AOS plus aphasia. F0 perturbation involved upward and downward 100-cent shifts versus no shift, in equal proportion, during 2 s vocalizations of the vowel /a/. In Experiment 2, adaptive responses to sustained first formant (F1) perturbations during speech were investigated in healthy older adults, adults with AOS and adults with aphasia only (APH). The F1 protocol involved production of the vowel /ε/ in four consonant-vowel words of Australian English (pear, bear, care, dare), and one control word with a different vowel (paw). An unperturbed Baseline phase was followed by a gradual Ramp to a 30% upward F1 shift stimulating a compensatory response, a Hold phase where the perturbation was repeatedly presented with alternating blocks of masking trials to probe adaptation, and an End phase with masking trials only to measure persistence of any adaptation. AOS participants showed normal compensation to unexpected F0 perturbations, indicating that auditory feedback control of low-level, non-segmental parameters is intact. Furthermore, individuals with AOS displayed an adaptive response to sustained F1 perturbations, but age-matched controls and APH participants did not. These findings suggest that older healthy adults may have less plastic motor programs that resist modification based on sensory feedback, whereas individuals with AOS have less well-established and more malleable motor programs due to damage from stroke.

Neural modeling and imaging of the cortical interactions underlying syllable production.

This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and somatosensory cortical areas. Computer simulations of the model verify its ability to account for compensation to lip and jaw perturbations during speech. Specific anatomical locations of the model's components are estimated, and these estimates are used to simulate fMRI experiments of simple syllable production.

Representation of sound categories in auditory cortical maps.

Functional magnetic resonance imaging (fMRI) was used to investigate the representation of sound categories in human auditory cortex. Experiment 1 investigated the representation of prototypical (good) and nonprototypical (bad) examples of a vowel sound. Listening to prototypical examples of a vowel resulted in less auditory cortical activation than did listening to nonprototypical examples. Experiments 2 and 3 investigated the effects of categorization training and discrimination training with novel nonspeech sounds on auditory cortical representations. The 2 training tasks were shown to have opposite effects on the auditory cortical representation of sounds experienced during training: Discrimination training led to an increase in the amount of activation caused by the training stimuli, whereas categorization training led to decreased activation. These results indicate that the brain efficiently shifts neural resources away from regions of acoustic space where discrimination between sounds is not behaviorally important (e.g., near the center of a sound category) and toward regions where accurate discrimination is needed. The results also provide a straightforward neural account of learned aspects of perceptual distortion near sound categories: Sounds from the center of a category are more difficult to discriminate from each other than sounds near category boundaries because they are represented by fewer cells in the auditory cortical areas.