Brain, Vol. 123, No. 10, 1985-2004,
October 2000
© 2000 Oxford University Press
Brain correlates of stuttering and syllable production
A PET performance-correlation analysis
1 The Research Imaging Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas and 2 The Department of Speech and Hearing Sciences, University of California, Santa Barbara, California, USA
Correspondence to:
Dr Peter Fox, Research Imaging Center, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive MSC: 6240, San Antonio, TX 78229-3900, USA E-mail: fox{at}uthscsa.edu
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Abstract |
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To distinguish the neural systems of normal speech from those of stuttering, PET images of brain blood flow were probed (correlated voxel-wise) with per-trial speech-behaviour scores obtained during PET imaging. Two cohorts were studied: 10 right-handed men who stuttered and 10 right-handed, age- and sex-matched non-stuttering controls. Ninety PET blood flow images were obtained in each cohort (nine per subject as three trials of each of three conditions) from which r-value statistical parametric images (SPI{r}) were computed. Brain correlates of stutter rate and syllable rate showed striking differences in both laterality and sign (i.e. positive or negative correlations). Stutter-rate correlates, both positive and negative, were strongly lateralized to the right cerebral and left cerebellar hemispheres. Syllable correlates in both cohorts were bilateral, with a bias towards the left cerebral and right cerebellar hemispheres, in keeping with the left-cerebral dominance for language and motor skills typical of right-handed subjects. For both stutters and syllables, the brain regions that were correlated positively were those of speech production: the mouth representation in the primary motor cortex; the supplementary motor area; the inferior lateral premotor cortex (Broca's area); the anterior insula; and the cerebellum. The principal difference between syllable-rate and stutter-rate positive correlates was hemispheric laterality. A notable exception to this rule was that cerebellar positive correlates for syllable rate were far more extensive in the stuttering cohort than in the control cohort, which suggests a specific role for the cerebellum in enabling fluent utterances in persons who stutter. Stutters were negatively correlated with right-cerebral regions (superior and middle temporal gyrus) associated with auditory perception and processing, regions which were positively correlated with syllables in both the stuttering and control cohorts. These findings support long-held theories that the brain correlates of stuttering are the speech-motor regions of the non-dominant (right) cerebral hemisphere, and extend this theory to include the non-dominant (left) cerebellar hemisphere. The present findings also indicate a specific role of the cerebellum in the fluent utterances of persons who stutter. Support is also offered for theories that implicate auditory processing problems in stuttering.
stuttering; speech; oral reading; PET; performance-correlation analysis
BA = Brodmann area; SMA = supplementary motor area; ILPrM = inferior lateral premotor cortex; FEF = frontal eye fields; M1 = primary motor cortex; fMRI = functional MRI; SPI{r} = statistical parametric image of r-values
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Introduction |
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Converging research has led to the view that developmental stuttering is most likely a product of CNS dysfunction, possibly with genetic origins (McClean, 1990
; Boberg, 1993; Bloodstein, 1995). Incomplete left lateralization of speech and other motor skills is a much theorized source of the disorder (Travis, 1978; Moore, 1993). This possible aetiology was originally inferred from dichotic word listening (preferred ear) and word viewing (preferred field), from abnormally slow finger-tapping rates and from EEG studies (Webster, 1993; Ingham, 1998). More recently, functional brain imaging studies have proven consistent with this theory, showing incomplete left-lateralization of speech-motor systems and overactivity of premotor areas in stuttering (Wood et al., 1980; Wu et al., 1995; Fox et al., 1996; Braun et al., 1997). In addition, less-than-normal activations and even inhibitions (decreases in brain blood flow relative to control) of extraprimary auditory areas have been observed (Fox et al., 1996; Braun et al., 1997), consistent with theories of stuttering which emphasize failure of auditory processing and speech self-monitoring (Stromsta, 1986).
The spatial precision and statistical power with which specific brain regions have been implicated in stuttering by neuroimaging has advanced in parallel with advances in imaging and image-processing technologies. Early studies imaged single behavioural states and performed statistical contrasts between cohorts (i.e. stuttering versus non-stuttering) or between hemispheres within a cohort (Wood et al., 1980; Wu et al., 1995). More recent studies have imaged each subject in multiple behavioural states and applied within-subject conditional contrasts. Of greatest relevance, speech conditions with prominent stuttering have been contrasted with those with little or no stuttering (Fox et al., 1996; Braun et al., 1997). Conditional contrasts of stuttered and non-stuttered speech were achieved using fluency induction, whereby patients were trained before the imaging session in a behavioural modification procedure which remediated stuttering, and then imaged while speaking with and without induced fluency. Fluency induction procedures used in neuroimaging have included choral reading (Wu et al., 1995; Fox et al., 1996), rhythmic speech and rehearsed speech (Braun et al., 1997).
Within-subject conditional contrasts, despite being powerful and widely used, are not always an entirely adequate experimental strategy. Conditional contrasts rely on the assumption that behavioural/cognitive task components present in both conditions will be subserved by activation of the same brain areas and to the same degree in both states, thus cancelling (subtracting) in the conditional contrast. Further, conditional contrasts assume the investigator's ability to isolate the phenomenon of interest (e.g. stuttering) to one condition. While the symptoms of many neurological and psychiatric disorders can be modulated iatrogenically, they can be entirely isolated only rarely. Thus, an experimental strategy applicable when the behaviour of interest is not entirely under the experimenter's control is sorely needed.
Silbersweig and colleagues introduced just such a strategy, here termed performance-correlation analysis, and applied it to map the brain locations underlying auditory hallucinations in schizophrenic subjects (Silbersweig et al., 1995). Performance-correlation analysis used the principle that the intensity of brain activations is highly correlated with the frequency with which the neural elements are used during the imaging epoch. This rate principle has been demonstrated in many functional systems, including vision (Fox and Raichle, 1984, 1985; Kwong et al., 1992; Schneider et al., 1994), audition (Wise et al., 1991; Price et al., 1992; Binder et al., 1994) and movement (Sabatini et al., 1993; Rao et al., 1996). It has been confirmed both for PET (e.g. Fox and Raichle, 1985, 1994; Wise et al., 1991; Price et al., 1992) and for functional MRI (fMRI) (e.g. Kwong et al., 1992; Schneider et al., 1994).
Silbersweig applied this principle by using a behavioural measure (hallucination frequency) as a pattern vector with which to probe the image data, seeking brain regions in which blood flow covaried with the pattern vector. Braun and colleagues first applied the performance-correlation strategy in stuttering, using a `weighted dysfluency score' to compute voxel-wise correlations (Braun et al., 1997). In that study, the dysfluency score was positively correlated with several left-hemisphere motor regions and negatively correlated with auditory association areas bilaterally. A complementary analysis using a measure of fluent speech, such as syllable production rate, was not performed. Thus, the degree of regional dissociation between stuttering and speech was not assessed. The present study extends this line of analysis by performing a performance correlation analysis using both a stuttering-rate score and a speech-rate score both in persons who stutter and in non-stuttering controls. The image data used for this analysis were analysed previously by conditional contrast and have been reported briefly (Fox et al., 1996).
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Methods |
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Subjects
Ten right-handed, otherwise healthy men with developmental stuttering formed the stuttering cohort (mean age 32 years). Stuttering severity ranged from mild to severe. All stuttering men were pretested to ascertain their responsivity to choral reading. Only persons in whom stuttering could be eliminated reliably during choral reading were invited to participate in the imaging study. Ten right-handed, healthy, normally fluent men formed the control cohort (mean age 32 years). Informed consent was obtained from all subjects in accordance with the Declaration of Helsinki and under the auspices of the Institutional Review Boards of the University of Texas Health Science Center at San Antonio and the University of California, Santa Barbara.
PET imaging tasks
Each subject had nine PET scans: there were three trials of each of three conditions in a counterbalanced order. The imaged states were oral paragraph reading of a text passage (Solo); oral paragraph reading while accompanied by an audio recording of the text passage being read by a fluent speaker (Chorus); and eyes-closed rest (Rest). Choral reading is a well-described and highly reproducible procedure for the induction of fluency (Ingham and Packman, 1979). The passage for reading (Abbey, 1978) was presented on a video monitor suspended above the subject, ~14 inches from the eyes. For the Chorus condition, the recorded passage was presented via an earphone inserted in the subject's left ear. To counter adaptation effects (Van Riper and Hull, 1956), the 10 min interval between scans was occupied with casual conversation. For each task, reading was started at the moment of tracer injection, continued while the tracer circulated to the brain (~10 s), and was stopped after a 40 s image acquisition triggered by the arrival of the tracer bolus in the brain (see Image acquisition).
Speech measurements
Speech performance data were scored from audiotape recordings obtained during the 40 s PET scanning periods. Recordings were scored independently by two judges blinded to task conditions and cohorts. Stuttering rate was computed as the number of 4 s intervals judged to contain stuttering, with a maximum score of 10 in a 40 s scanning epoch. Syllable production rate was computed as the total number of syllables spoken in 40 s, counting each repeated syllable in a stutter in order to reflect speech-motor behaviour fully (Ingham et al., 1993). Speech naturalness was rated on a nine-point scale (Martin et al., 1984). An independent judge's interval-by-interval agreement for the presence or absence of stuttering ranged from 85.0 to 100% across subjects (mean 92.5), with 100% agreement that there was no stuttering during choral reading. Total agreement for syllable production ranged from 97.9 to 99.7% (mean 98.5%). There was no evidence of order or adaptation effects. Agreement for speech naturalness rating for two independent judges was within ±1 scale score for 20/20 samples (one sample from each of the 20 subjects).
Image acquisition
PET imaging was performed with a General Electric (Milwaukee, Wis., USA) 4096 camera. Brain blood flow was measured with H215O (half-life 123 s), administered as an intravenous bolus of 8–10 ml of saline containing 60 mCi (Herscovitch et al., 1983; Raichle et al., 1983). A 40 s scan was triggered as the tracer bolus entered the field of view (the brain), by the rise in the coincidence counting rate. A 10 min interscan interval was sufficient for isotope decay (five half-lives).
An anatomical MRI was acquired for each subject and used to optimize spatial normalization. MRI was performed with a 1.9 Tesla Elscint Prestige (Haifa, Israel) using a high-resolution 3D GRASS sequence: TR = 33 ms; TE = 12 ms; flip angle = 60°; voxel size = 1 mm3; matrix size =256 x 192 x 192; acquisition time = 15 min.
Image analysis
Three r-value statistical parametric images (SPI{r}) were computed as voxel-wise correlations with a measure of speech performance: (i) correlation with stuttering rate in the stuttering cohort; (ii) correlation with syllable production rate in the stuttering cohort; and (iii) correlation with syllable production rate in the non-stuttering cohort. For each SPI[r] (syllable-rate correlates and stutter-rate correlates), PET images from all three test conditions (Rest, Solo, Chorus) were included. In addition, 40 SPI{r} (20 per subject cohort) were generated using random-number lists but the same PET images, to characterize the null distribution for r in SPI{r} of the present sample size (90 PET images per cohort) and using present imaging equipment and image-processing tools. All SPI{r} were created with the MIPSTM software package (RIC, UTHSCSA, San Antonio, Tex., USA). Before the computation of SPI{r}, input blood flow images were spatially normalized relative to the atlas of Talairach and Tournoux (Talairach and Tournoux, 1988), using the algorithm of Lancaster and colleagues (Lancaster et al., 1995) as implemented in the SN software package (RIC). Locations were expressed as millimetre coordinates referenced to the anterior commissure as origin, the right, superior and anterior directions being positive.
SPI{r} were analysed for speech performance effects first by an omnibus (whole-brain) test and, if omnibus significance was proven, then a post hoc (regional) test was done, in a manner analogous to that described previously for conditional contrasts (Fox et al., 1988; Fox and Mintun, 1989). Local extrema (both positive and negative) were identified within each of the 43 SPI{r} (three assessing speech performance effects, 40 assessing the null distribution) using a 3D search algorithm described previously (Mintun et al., 1989). Each set of local extrema data was plotted as a frequency histogram (for visual inspection) and tested for skew (gamma-1 statistic) and kurtosis (gamma-2 statistic) as omnibus statistics (D'Agostino et al., 1990). Critical values for gamma statistics were chosen for P < 0.0033, i.e. 0.01 ÷ 3, to correct for the three independent comparisons (three speech performance SPI{r}). The SPI{r} were converted to SPI{z} by dividing each image voxel by the average standard deviation of the null distribution SPI{r}. P values were assigned from the Z distribution. Only Z values greater than 1.96 (P < 0.01) and forming contiguous clusters of >15 voxels (120 mm3) are reported. The critical value threshold for regional effects (Z > 1.96; P < 0.01) was not raised to correct for multiple comparisons (e.g. the number of image resolution elements) because omnibus significance was established before post hoc analysis, and because extrema data were also thresholded by cluster size (large clusters having a very low probability of occurrence in Gaussian random fields) (Poline et al., 1993; Roland et al., 1993; Xiong et al., 1995). Anatomical labels and Brodmann area (BA) designations were applied automatically, using a 3D electronic brain atlas (the Talairach Daemon, Research Imaging Center, San Antonio, Tex., USA) (Lancaster et al., 1997). Figures 4, 8 and 10 were created using the BrainMap database (Research Imaging Center) (Fox and Lancaster, 1996). These strategies and software are the same as those used by Denton and colleagues to detect regional correlations with serum Na+ concentration (Denton et al., 1999).
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Results |
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Speech performance
Choral reading proved a highly effective way of inducing fluency in this patient sample, entirely eliminating stuttering in all trials (three per subject) of all members of the stuttering cohort. In addition, choral reading increased the mean syllable production rate in the stuttering cohort without affecting the speech rate of the control cohort. Speech naturalness ratings during the Chorus condition were not significantly different between the two groups and were within the range expected for normally fluent speakers (Ingham, 1988
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In the Solo condition, the number of stuttered intervals in the stuttering cohort averaged 6.2 (range 1–10, SD 2.98) and the number of syllables 113.0 (range 82–154, SD 19.90) per 40-s scan (Fig. 1). In the Chorus condition, no stuttering was judged to occur in the stuttering cohort; the mean number of syllables spoken was 143.7 (range 121–173, SD 11.54). For the stuttering cohort, the difference in mean stuttering rate between the Solo and Chorus conditions was highly significant (t = 11.3; P < 0.0001, paired t-test); the difference in mean syllable rate was also highly significant (t = 8.4; P < 0.0001, paired t-test). Stuttering rate and syllable rate were inversely correlated to a moderate degree in the Solo condition alone (r = –0.51; P < 0.005).
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Control subjects did not stutter in either condition and spoke an average of 146.8 (range 129–173, SD 16.14) syllables in the Solo condition and 145.6 (range 121–181, SD 12.26) syllables in the Chorus condition. The difference in mean syllable rate between the Solo and Chorus conditions was not statistically significantly different for the control cohort (t = 0.39; P > 0.7, paired t-test).
Syllable-rate correlations
Positive correlations: control cohort
In the control cohort, positive correlations with syllable rate were observed in the speech-motor system, the auditory system and the visual system (Fig. 2). Speech-motor positive correlations (Table 2 and Figs 3 and 4
) were in regions reported by prior conditional contrast studies of speech, including the conditional contrast analysis of these same data (Fox et al., 1996), as follows. The primary motor cortex (M1)-mouth representation was very well defined, with a single response focus in each hemisphere. Laterality was as expected for a right-handed population, being stronger (r =0.62 versus 0.29) and more extensive (2.30 versus 0.82 cm3) on the left than on the right. A supplementary motor area (SMA)-mouth response was observed, with its local maximum on the right. The inferior lateral premotor cortex (ILPrM), or Broca's area (BA 44/6), was detected bilaterally, the right-side response being slightly stronger (r = 0.62 versus 0.51) and more extensive (4.90 versus 1.71 cm3) than the left. The insula was detected only on the left, as two discrete but relatively weak anterior foci. The anterior superior cerebellum was activated chiefly on the right side (right 5.54 cm3, left 0.98 cm3), in keeping with the left-dominant pattern of the cerebral motor responses. For all speech-motor responses, the locations were quite typical for a normal population (see Discussion).
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+0.3 and size
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In the auditory system, positive correlations with syllable rate were distributed widely across the superior temporal gyrus (Fig. 5
, top panel), but were minimal or absent in other gyri. These effects were somewhat right-lateralized (4.38 cm3 on the left, 5.61 cm3 on the right), which probably resulted from unilateral, left-ear auditory input during choral reading.
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In the visual system, positive correlation foci formed two relatively discrete clusters: one superior and one inferior (Fig. 6
). Superior effects were chiefly in the cuneus and were right-lateralized (left 8.12 cm3, right 13.18 cm3). Inferior effects were chiefly in the lingual gyrus and were left-lateralized (left 10.94 cm3, right 5.75 cm3).
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Positive correlations: stuttering cohort
As in the control cohort, the stuttering cohort showed positive correlations with syllable rate in the speech-motor system, the auditory system and the visual system (Fig. 2
). Differences from the control, however, were limited to the speech-motor system.
In the stuttering cohort, speech-motor positive correlations (Table 3) were more numerous, more extensive, more right-lateralized in the cerebrum (Figs 3 and 4) and left-lateralized in the cerebellum (Figs 7 and 8), and less stereotypically localized than in the control cohort. The SMA-mouth response was located normally and right-lateralized, as in the control cohort, but was more extensive (1.90 cm3) than in the controls (1.43 cm3). Unlike in the control cohort, in the stuttering cohort the M1-mouth responses were not readily differentiated from the ILPrM (BA 44/6, or Broca's area) responses. Rather, three foci were distributed along each precentral gyrus. The most superior of these were at z-axis locations typical of M1-mouth (Table 3; see also Discussion), while the other two were at z-axis levels more typical of ILPrM. Cerebellar responses were more extensive in the stuttering cohort (8.92 cm3) than in the control cohort (5.54 cm3); cerebellar responses were strongly left-lateralized (left 8.22 cm3, right 1.87 cm3) rather than right-lateralized as in the controls.
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Auditory system positive correlations with syllable rate were quite similar to those of the control cohort (Fig. 5
, top). Syllable rate correlations were extensive in the superior temporal gyrus but minimal in other gyri. These superior temporal effects, however, were mildly left-lateralized (left 4.73 cm3, right 4.06 cm3), which differed from the control cohort.
Visual system positive correlations with syllable rate were also quite similar to the those for the control cohort (Fig. 6). The right-lateralized cuneus effects were similar in magnitude and laterality to those of the control cohort. Similarly, the left-lateralized lingual effects were quite similar to those seen in the control cohort.
Negative correlations: both cohorts
Negative correlations with syllable rate (regions less active during speech than during rest) were extensive for both groups (Table 5 and Figs 5, 9 and 10). In general, negative correlations were removed from speech-related areas, forming large clusters in the superior lateral prefrontal cortex (superior and middle frontal gyri), in the medial (precuneus) and lateral (inferior parietal lobule) parietal cortex, in the middle temporal gyrus, and in the limbic cortex (anterior and posterior cingulate and parahippocampal gyri). Neither cohort had any inhibitions in the cerebellum or occipital lobe. For the control cohort, the negative correlations with syllable rate tended to be left-lateralized. In the stuttering cohort, negative correlations with syllable rate tended to be more right-lateralized.
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Stutter-rate correlations
Positive correlations with stutter rate reached significance only in the frontal lobe (speech-motor areas), the cerebellum and the occipital lobe (Fig. 2
). The temporal, parietal and limbic lobes showed no significant positive correlations with stuttering. Negative correlations with stutter rate were most marked in the temporal lobe (Fig. 5). No negative correlations with stutter rate were seen in the occipital lobe or cerebellum.
In the cerebrum, stutter-rate correlations (both positive and negative) were strongly right-lateralized. In the cerebellum, they were strongly left-lateralized. For the most part, correlations with stutter rate were less extensive than correlations with syllable rate, in keeping with the lower frequency per scan (Table 1) and their presence in one state (Solo) rather than two. The sole exception was that negative correlations in the temporal lobe were more extensive for stutter rate than for syllable rate in either cohort.
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Positive correlations
In cerebral speech-motor regions, positive correlations with stutter rate were strongly right-lateralized (Figs 2–4
and Table 4). Medial frontal (SMA-mouth) foci were bilateral and more extensive (2.16 cm3) than syllable correlations in both the stuttering cohort (1.90 cm3) and the control cohort (1.43 cm3). Lateral frontal responses were in the precentral gyrus, entirely on the right side. These responses were distributed in the z-axis from +33 to +22 mm, not allowing a clear differentiation between M1-mouth and inferior premotor responses. The right anterior insula (lying beneath the frontal operculum) was positively correlated with stutter rate. Cerebellar responses were extensive and strongly left-lateralized (left 4.42, right 2.13) (Figs 7 and 8; Table 4).
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Occipital lobe positive correlations with stutter rate, like the positive correlations with syllable rate, were most extensive in the cuneate and lingual gyri (Fig. 6
). In the cuneus, the laterality (left 1.62 cm3, right 4.19 cm3) resembled that of syllable-rate positive correlations in both cohorts. In the lingual gyrus, stutter-rate positive correlations were right-lateralized (left 1.67, right 3.41), unlike syllable correlations in either cohort.
Negative correlations
Negative correlations were present in the frontal, temporal, limbic and parietal lobes (Table 5 and Figs 5, 9 and 10). No statistically significant negative correlations were observed in the occipital lobe or cerebellum. Negative correlations with stutter rate generally followed the distribution of the syllable-rate negative correlations (see Negative correlations: both cohorts), but were much less spatially extensive (6–20% of the total volume observed for syllable rate). The one exception to this generalization was the temporal lobe (Fig. 5, bottom), where the total volume (all gyri) of stutter-rate negative correlations were more extensive (6.87 cm3) than syllable-rate correlations in the control cohort (6.28 cm3) and nearly as extensive as syllable-rate correlations in the stuttering cohort (9.36 cm3). Further, negative correlations with stutter rate were much more prominent in the superior temporal gyrus (primary and periprimary auditory cortex) than were negative correlations with syllable rate in either cohort. That is, stuttering-rate negative correlations fell in the same regions as syllable-rate positive correlations (Figs 10 and 11).
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Discussion |
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The brain correlates of stutters and syllables were tested using a parametric, performance correlation analysis of PET brain blood-flow images acquired during oral paragraph reading. Stutter-rate was varied both spontaneously and by fluency induction using choral reading. Normal volunteers performed the same tasks as the stuttering cohort. Brain correlates of stutter rate and syllable rate showed striking differences in both laterality and sign (i.e. there were positive or negative correlations). Stutter-rate correlates, both positive and negative, were strongly lateralized to the right cerebral and left cerebellar hemispheres. Syllable correlates in both cohorts were bilateral, with a bias towards the left cerebral and right cerebellar hemispheres, in keeping with the left-cerebral dominance for language and motor skills typical of right-handed subjects. For both stutters and syllables, the brain regions that were correlated positively were those of speech production (M1-mouth, SMA, ILPrM, insula and cerebellum), the principal difference being in hemispheric laterality. A notable exception to this rule was that cerebellar syllable correlates in the stuttering cohort were far more extensive than in the control cohort, which suggests a specific role for the cerebellum in enabling fluent utterances in persons who stutter. Stuttering was negatively correlated with right-cerebral regions (superior and middle temporal gyrus) associated with auditory perception and processing, regions which were positively correlated with syllables in both the stuttering and the control cohort. These findings support long-held theories that the brain correlates of stuttering are located in speech-motor regions (Ingham, 1998
), especially of the non-dominant (right) cerebral hemisphere (Travis, 1978), and extend this theory to include the non-dominant (left) cerebellar hemisphere. The present findings also indicate a specific role of the cerebellum in the fluent utterances of persons who stutter. Support is also offered for theories that implicate auditory processing problems in stuttering (Stromsta, 1986). Regional effects (regional speech performance correlations) can be classified as belonging to one of four logical categories, each of which has a physiological interpretation. The four categories are: (i) normal effects of visual–oral reading; (ii) state effects of stuttering; (iii) trait effects of stuttering; and (iv) compensatory effects. In the control cohort, all effects were considered normal effects by definition. In the stuttering cohort, effects which resembled syllable-rate correlates of the control cohort were considered normal for either speech performance measure. In the visual system, for example, correlates of both syllable rate and stutter rate were similar in pattern to the normal syllable-rate correlates. Thus, these correlates were considered normal effects of viewing printed words for the purpose of reading them aloud, irrespective of whether the resulting utterances were stuttered or not. At the other extreme, stutter-rate correlates which differed substantially from the syllable correlates in the control cohort were considered `state' effects of stuttering. In the cerebellum, for example, the normal correlates of syllable rate were strongly right-lateralized; stutter-rate correlates were strongly left-lateralized. They were therefore considered normal and state effects, respectively. Syllable-rate effects in the stuttering cohort were classified as (i) normal, (ii) trait or (iii) compensatory. Trait effects were those which were intermediate in distribution between state effects and normal effects. That is, even when speech was made fluent (by choral reading), a distribution trend towards the state effect (of stuttering) was seen. Frontal syllable-rate correlates offer a good example of trait effects, being intermediate between the left laterality of normal effects and the right-laterality of state effects. Compensatory effects were those whose pattern was specific to the production of non-stuttered syllables by the stuttering cohort, i.e. responses present only insofar as the stuttering group spoke syllables fluently. The clearest example of a compensatory effect was the cerebellum, in which the correlated volume for syllable rate in the stuttering cohort was much greater than for normal or state effects. The purpose of this categorization was to provide physiological interpretations of specific regional effects and, thereby, to generate predictions for testing through further analyses and experiments. For this reason, the remainder of the discussion is organized by brain region.
Cerebral speech-motor effects
Speech-motor regions of the frontal lobes showed marked state effects of stuttering, which differed strikingly from the distribution of normal effects. For the most part, stutter-rate correlates were found in regions previously implicated by conditional contrast analysis, including ILPrM (Broca's area, BA 44/6), SMA (medial BA 6) and the anterior insula. Overall, effects in the present analysis were more regionally specific and more right-lateralized than in the categorical analysis (Fox et al., 1996). Some regions that were implicated previously were less implicated or not implicated by the present analysis, notably the right superior lateral premotor cortex (lateral BA 6) and M1-mouth (BA 4). Other regions, however, were more clearly implicated than previously, most notably ILPrM. Despite such differences in the details, the major conclusion of both analyses was the same: stuttering was associated with overactivity of the right cerebral regions involved in speech planning and execution. Collectively, speech-motor correlates of stuttering were therefore more refined in the present analysis than in the prior analysis, but were largely concordant.
Precentral gyrus
The inferior portion of the precentral gyrus had strong state effects for stuttering, all of which were right-hemispheric. State effects consisted of three foci confined to a relatively small inferior–posterior (z-axis) distribution, with z-coordinates ranging from +24 to +28. The mean location (Talairach coordinates +49, –10, +27) is quite typical of (albeit contralateral to) the Broca's area (BA 44/6) activations reported during overt-speech tasks (Petersen et al., 1988; Paus et al., 1993; Petrides et al., 1993; Bookheimer et al., 1995; Braun et al., 1997; Fiez and Petersen, 1998). Thus, stuttering was associated with overactivation of the right-sided homologue of Broca's area.
Trait effects of stuttering were also noted in the precentral gyrus. Three syllable-rate correlation foci (stuttering cohort) were distributed along each precentral gyrus (left and right), ranging in the z-axis from +16 to +36 (Table 3). In the left hemisphere, the most superior response was at a z-coordinate of +32, which is quite inferior for M1-mouth, which has an average z-axis coordinate in the left hemisphere of +40 (Fox et al., 1999, 2000). In the right hemisphere, the most superior response was at +36, a location which is quite typical of the right-hemisphere location of M1-mouth (Fox et al., 1999, 2000). The additional response in each hemisphere blurred the distinction between M1 and ILPrM, which was clear-cut in the two-focus pattern of the control cohort. Further, the syllable correlates along the precentral gyrus were nearly equally extensive on the left (4.82 cm3) and right (4.37 cm3). While this is normal for ILPrM, it is atypical for M1-mouth, which should be left-lateralized. Collectively, trait effects were observed which can be interpreted as showing (i) a right-hemisphere bias to precentral gyrus activations; (ii) that they were due chiefly to a right-sided predominance of the M1-mouth response; and (iii) the lack of clear distinction between M1-mouth and ILPrM.
SMA
The SMA showed both state and trait effects of stuttering. State effects (stutter-rate correlates) were bilateral and extensive (2.16 cm3), more so than the syllable-rate correlates in either cohort. Syllable-rate correlates in the stuttering cohort had a greater volume (1.90 cm3) than in the control cohort (1.43 cm3), although the laterality and location of the SMA responses were virtually identical and normal. Thus, there was a mild trait effect in addition to the state effect. Categorical analysis of the present data showed a similar effect.
Anterior insula
The anterior insula has been implicated in motor programming by several studies, including studies of speech production (Paulesu et al., 1993; Parsons et al., 1994; Raichle et al., 1994; Dronkers, 1996; Fox et al., 1996; Fiez and Petersen, 1998). In the present analysis, the right insula showed state effects of stuttering, and possible trait effects, as follows. In the control cohort, speech-rate correlates included the left insula, as expected. Stutter-rate correlates in the insula, however, were entirely right-lateralized, two foci lying deep and anterior to the right-sided ILPrM effects described above. No significant speech-rate correlates were observed in the insula for the stuttering cohort, which may be interpreted as an intermediate distribution (i.e. a trait effect) lying midway between the state pattern and the normal pattern of effects. Alternatively, the absence of insular effects during fluency induction could be attributed to the novelty of the task, whereby the cerebellum (repeatedly implicated in motor learning, see Cerebellar speech-motor effects) assumed control in lieu of the insula, which has been hypothesized as participating chiefly in automatic, overlearned motor behaviours rather than novel, newly learned behaviours (Raichle et al., 1994). By this interpretation, the absence of anterior insular correlates of syllable production (stuttering cohort) could be a counterpart of compensatory cerebellar effects (see Cerebellar speech-motor effects).
Superior lateral premotor area
Previous categorical analysis of the present data has implicated the right superior lateral premotor cortex in stuttering. In the left hemisphere, this region has been reported as being active during speech (Petersen et al., 1988). The present parametric analysis, however, failed to show any effects (state, trait or normal) in this region.
Cerebellar speech-motor effects
The cerebellum showed prominent normal, state and compensatory effects (but not trait effects), all in the posterior lobe, in lateral, vermal and paravermal regions. Stutter-rate correlates were considered state effects, as their laterality was the reverse of the normal effects of syllable production in the controls. Specifically, stutter-rate correlates were strongly left-lateralized, whereas syllable-rate correlates in controls were strongly right-lateralized. These lateralizations were concordant with cerebral speech-motor effects—both stuttering state effects and normal effects. In fact, the laterality of the normal effects was more striking in the cerebellum than in the cerebral speech-motor regions.
Syllable-rate correlates in the stuttering cohort were judged to be compensatory, rather than trait, by virtue of their extent. Syllable-rate effects were far more extensive in the stuttering cohort than in the control cohort and also much more extensive than the stutter-rate (state) effects (Fig. 2). That is, the cerebellar response to non-stuttered syllables in the stuttering cohort was marked overactivity relative to each of the two reference effects (normal and state). One interpretation of this effect is that the cerebellum plays a pivotal role in the fluent utterances of persons who stutter. This interpretation would be in keeping with the long-held theories that the cerebellum is responsible for the coordination and timing of complex movements (Ito, 1984; Thach et al., 1992). It would also be in keeping with emerging theories of cerebellar processing of complex sensory information (Gao et al., 1996; Parsons et al., 2000a), including auditory information (Parsons et al., 2000b). An alternative interpretation is that the cerebellar overactivity occurs because the subjects were using/learning a novel motor skill, i.e. fluency induction by choral reading. This interpretation would be in keeping with the hypothesized role of the cerebellum in sensorimotor learning (Bloedel, 1992; Grafton et al., 1992; Jenkins et al., 1994; Doyon 1997). Studies assessing cerebellar adaptation (or lack of it) to the chronic use of fluency induction could disentangle these two possibilities. That is, if the excessive cerebellar syllable correlates in the stuttering cohort diminished over time to the same level as in the control cohort (probably with a concordant increase in insular activity), the effects could be attributed to motor skill learning. If the cerebellar effects (and absence of insular effects) persisted, they would be confirmed as compensatory.
Temporal and other negative effects
Statistically significant negative effects (blood flow going down as performance rate rose) were observed in many brain areas (Table 5 and Figs 5, 9 and 10). Because the resting state was included in the analysis, negative correlations would suggest that regional inhibition in an absolute sense (i.e. blood flow during task performance being below blood flow at rest) was present. This was tested by a subtractive comparison of the Solo reading condition with the Rest condition, which confirmed that blood flow was decreased below resting-state levels in many areas, including temporal lobe regions showing negative correlations with stutter rate. For most areas, the patterns of negative correlations were similar for all three types of correlates, i.e. all effects were normal effects. The most likely physiological explanation for these normal effects is that these areas were more active during the resting state than during either task state in either cohort. That is, these areas were engaged in mental activity (random thoughts) during the resting state that ceased when attention was turned to the performance of the speech tasks (Shulman et al., 1997). For the temporal lobe, however, the patterns of negative correlates were clearly different by cohort and by speech index and bear detailed interpretation, as follows (Fig. 5).
Temporal lobe effects
In both cohorts, positive correlates to syllable rate were observed in the superior temporal gyrus bilaterally, i.e. in the primary and periprimary auditory cortex (Figs 5 and 11). That these effects were symmetrical and even mildly left-lateralized in the stuttering cohort indicates that they were not solely due to the left-ear input of the choral recording. Left monaural stimulation would be expected to give a balance of activation of approximately 2/3 : 1/3 (right : left) (Woldorff et al., 1999). Thus, the self-stimulation of speech production or the interhemispheric transfer of linguistic material to the language-dominant hemisphere or both have come into play. It is notable that, unlike in the frontal lobe, there were no positive correlates of stuttering in the temporal lobe.
Negative correlates of both stuttering and speech were prominent in the superior and middle temporal gyri. In the superior temporal gyrus, the negative correlates were chiefly state and trait effects of stuttering. During stuttering, there were extensive inhibitions, chiefly on the right. For syllable rate correlations in the stuttering cohort, right-sided inhibitions were less extensive than during stuttering, but more marked than during normal fluency. Thus, these fit the pattern of state (stuttering) and trait (induced fluency) effects. We interpret these as indicating that stuttering entails a diminished capacity for auditory monitoring during stuttering that persists during fluent speech. This interpretation fits with prior reports of diminished auditory processing in persons who stutter (Stromsta, 1972; Rosenfield and Jerger, 1984; Salmelin et al., 1998).
In the middle temporal gyrus there was evidence of compensatory effects as well as state effects, in a pattern similar to that observed in the cerebellum. Left-lateralized middle temporal gyrus inhibitions were prominent in the control cohort (normal effect). Stuttering correlations (state effects) were similar in volume and intensity but were strongly right-lateralized. Syllable rate correlations for the stuttering cohort, rather than being intermediate between the normal and state effects, were bilateral and of larger volume than either state or normal effects. Thus, these fit the pattern of compensatory effects. This suggests that inhibition of higher-order auditory processing in the middle temporal gyrus may be an important component of the mechanism through which fluency is induced, at least by choral reading. Perhaps this is the reason even white noise can alleviate stuttering (Maraist and Hutton, 1957). This also suggests that the cerebellum and the temporal lobe may be working in concert to achieve induced fluency, a postulate that can be further tested by an effective-connectivity analysis (Friston et al., 1993; Friston, 1996; Liu et al., 1999).
Non-temporal negative effects
In both cohorts, negative correlates with syllable and stutter rates were also present in the frontal, limbic and parietal lobes (Fig. 9). Notably, none was present in the occipital lobe or cerebellum. In each of the areas in which they occurred, response volumes for syllable rate were similar for each cohort and considerably greater than the response volume for stutter rate. The negative correlates (blood flow decreasing during task performance) were spatially distant from the speech-task-associated positive correlates and from primary sensory or motor areas. Specifically, they were in association areas probably involved in the higher-order, interoceptive and introspective mental processes present in the resting state but not during speech performance, when subjects were engaged in a task (Shulman et al., 1997).
Occipital effects
Occipital effects, which were entirely positive, fell into two major groupings: superior and inferior. In both regions, the patterns of response were largely similar for all three speech-performance measures.
Inferior occipital effects
Inferior effects were chiefly in the lingual gyrus (Fig. 6). Syllable correlates for both groups were strongly left-lateralized and were similar in intensity and volume. Stutter-rate correlates were much smaller in volume and were chiefly right-sided. The left lingual gyrus has been implicated repeatedly in visual word-form processing (Petersen et al., 1988, 1990; Raichle et al., 1994; Fiez and Petersen, 1998), and was expected in the present tasks in which the subjects read paragraphs presented visually. The correlation of the right lingual gyrus with stutter rate may be indicative of repeated visual scanning of a word or phrase whose utterance has been delayed by a stutter, a phenomenon that is well described (Brutten and Janssen, 1979; Bakker et al., 1991). The right-laterality of this effect is somewhat puzzling. It may indicate that the word-form processing is already complete and not repeated during repetitive scanning. Alternatively, it might indicate that the anomalous dominance of stuttering, so evident in the frontal lobe, temporal lobe and cerebellum, extends even to visual word-form processing.
Superior occipital effects
Superior occipital effects were chiefly in the superior, anterior cuneate gyrus (Fig. 6). All effects were judged to be normal effects, as all three correlation patterns were similar. Notably, all response patterns were moderately right-lateralized. We interpret these responses as probably being due to spatially directed attention, which is supported by right-lateralized systems which include the parieto-occipital junction (Pardo et al., 1991; Mesulam, 1999), and to oculomotor control during paragraph reading (Law et al., 1998; Gitelman et al., 1999). Superior occipital effects have not been reported during single-word reading (Fiez and Petersen, 1998), during which the eyes remain stationary. When considering the eye movements generated during paragraph reading, it is surprising that the frontal eye fields (FEF) were not identified in any conditions, although the FEF have been identified repeatedly during voluntary saccades by PET and fMRI (for review, see Paus, 1996). In both tasks (solo and choral reading), subjects scanned many lines of text (reading 82–173 words per image acquisition) (Table 1). A possible explanation for the absence of a FEF response is that saccades during paragraph reading are of small amplitude, albeit frequent. That is, the small excursion of reading-induced saccades may have induced blood-flow changes of insufficient intensity to be detected. FEF activation was also absent in the prior categorical analysis.
Methodological considerations
The present study applied several novel or uncommon strategies for experimental design, data analysis and data interpretation. For this reason, key aspects of the methods are addressed here.
Interpretative logic: state, trait, compensation
The interpretative logic applied herein, i.e. segregating regional effects into categories of normal, state, trait and compensatory, appears robust despite its simplicity. In prior brain-imaging studies of stuttering, assignations of causality have been made tentatively, if at all, because of concerns that the regional effects observed during stuttering as likely reflect compensatory mechanisms as causal. The combination of task design and analysis provides a route around this logical obstacle. By having both stuttering (Solo) and induced fluency (Chorus) within the same experimental scenario, compensatory effects were specifically imaged (i.e. induced fluency) and segregated from state-specific effects by the performance correlation analysis (Table 6). The exuberant cerebellar effects associated with syllable production in the stuttering cohort appear to be an excellent candidate for a compensatory mechanism. On the other hand, it must be acknowledged that acute, ineffective compensations may be present within the category of state effects. For example, the inhibition of the right temporal lobe (negative correlation with stutter rate) is conceivably due to habitual avoidance of self-monitoring during stuttering that is neither causal nor an effective compensation. The finding of a state effect and a trait effect (i.e. an attenuated form of the state effect) in the same region seems to be particularly strong evidence that the region plays a causal role and that its provocation of stuttering is alleviated by the action of some other compensatory region(s). Effective connectivity analysis (Friston et al., 1993; Friston, 1996; Liu, 1999) seeking negative covariance between compensatory regions (e.g. cerebellum) and causal regions (e.g. SMA and right ILPrM) would strengthen this logic still further.
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Tasks
The tasks employed (solo reading and choral reading) for this study were selected only after due consideration of their strengths and weakness. Paragraph reading was used in preference to single-word reading because stutters occur at roughly the same frequency during paragraph reading as during spontaneous speech, while single-word reading is virtually stutter-free. [Thus, imaging studies of persons who stutter which have used single-word tasks (e.g. De Nil et al., 1998) actually failed to image the behaviour of interest (i.e. stuttering).] Reading was also used in preference to the recitation of memorized passages, to avoid the tendency to rhythmicity, which decreases stuttering. Choral reading was selected as the method of inducing fluency for three reasons: (i) it is remarkably efficacious; (ii) only minimal training is needed to achieve good fluency; (iii) the speech produced is judged to be normal by skilled listeners (Ingham and Packman, 1979
), as opposed to that induced by rhythmic speech, prolonged speech or other methods of inducing fluency commonly used as stuttering treatments (Runyan and Adams, 1978). The chief disadvantage of choral reading is its inapplicability as a treatment modality. Thus, choral reading is not a suitable task to ask whether the putatively compensatory cerebellar effects will persist after treatment. Prolonged speech, on the other hand, would be an excellent candidate for such a study, presuming that the cerebellar compensatory effects will be observed during this fluency induction. Another disadvantage of choral reading is the need for auditory input, the possible confounds of which are discussed above. The use of paragraph reading as a task for mapping speech-production systems is uncommon, not only for studies of stuttering (of which there are still few) but even for studies of normal speech. Prior studies in normal subjects of the functional activation patterns during reading have been limited almost entirely to single-word reading (for review, see Fiez and Petersen, 1999). The similarity of the control cohort activations reported here for paragraph reading to those reported previously for single-word is noteworthy.
Population
The present study reports only on right-handed men, probably the population with the most marked cerebral lateralization (Shaywitz et al., 1995). The population was limited in order to make it as homogeneous as possible. Nevertheless, it remains to be seen whether women or children who stutter will show similar effects. Having demonstrated that interpretable, stuttering-specific effects can be identified with these methods, a companion study of women performing solo reading and choral reading is now being undertaken by the authors.
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Acknowledgments |
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We wish to thank Lawrence Parsons for critiquing the manuscript and Barbara Rowe and Sarabeth Pridgen for assistance in formatting the manuscript. This work was supported by grants from the National Institutes of Health (1RO1MH60246-01; 1RO1DC036801-A1; PO1MH/DA52176) and the Charles A. Dana Foundation Clinical Hypothesis Program (to P.T.F).
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Abbey E. The monkey wrench gang. Edinburgh: Canongate Publishing; 1975. p. 3.
Bakker K, Brutten, GJ, Janssen P, van der Meulen S. An eyemarking study of anticipation and dysfluency among elementary school stutterers. J Fluency Disord 1991; 16: 25–33.
Binder JR, Rao SM, Hammeke TA, Frost JA, Bandettini PA, Hyde JS. Effects of stimulus rate on signal response during functional magnetic resonance imaging of auditory cortex. Brain Res Cogn Brain Res 1994; 2: 31–8.[Medline]
Bloedel JR. Functional heterogeneity with structural homogeneity: how does the cerebellum operate? Behav Brain Sci 1992; 15: 666–78.[Web of Science]
Bloodstein O. A handbook on stuttering. 5th ed. San Diego: Singular Publishing Group; 1995.
Boberg E. Neuropsychology of stuttering. Edmonton (AB): University of Alberta Press; 1993.
Bookheimer SY, Zeffiro TA, Blaxton T, Gaillard W, Theodore W. Regional cerebral blood flow during object naming and word reading. Hum Brain Mapp 1995; 3: 93–106.[Web of Science]
Braun AR, Varga M, Stager S, Schulz G, Selbie S, Maisog JM, et al. Altered patterns of cerebral activity during speech and language production in developmental stuttering. An H215O positron emission tomography study. Brain 1997; 120: 761–84.
Brutten GJ, Janssen P. An eye-marking investigation of anticipated and observed stuttering. J Speech Hear Res 1979; 22: 22–8.
D'Agostino RB, Belanger A, D'Agostino RJ Jr. A suggestion for using powerful and informative tests of normality. Am Statistician 1990; 44: 316–21.
De Nil LF, Kroll RM, House S. A positron emission tomography study of treatment-related changes in brain activation patterns following a three-week intensive intervention program for stuttering adults. Neuroimage 1998; 7 (4 Pt 2): S197.
Denton D, Shade R, Zamarippa F, Egan G, Blair-West J, McKinley M, et al. Correlation of regional cerebral blood flow and change of plasma sodium concentration during genesis and satiation of thirst. Proc Natl Acad Sci USA 1999; 96: 2532–7.
Doyon J. Skill learning. In: Schmahmann JD, editor. The cerebellum and cognition. San Diego: Academic Press; 1997. p. 273–94.
Dronkers NF. A new brain region for coordinating speech articulation. Nature 1996; 384: 159–61.[Medline]
Fiez JA, Petersen SE. Neuroimaging studies of word reading. [Review]. Proc Natl Acad Sci USA 1998; 95: 914–21.
Fox PT, Lancaster JL. Un atlas du cerveau sur internet. Recherche 1996; 289: 49–51.
Fox PT, Mintun MA. Noninvasive functional brain mapping by change-distribution analysis of averaged PET images of H215O tissue activity. J Nucl Med 1989; 30: 141–9.
Fox PT, Raichle ME. Stimulus rate dependence of regional cerebral blood flow in human striate cortex, demonstrated by positron emission tomography. J Neurophysiol 1984; 51: 1109–20.
Fox PT, Raichle ME. Stimulus rate determines regional brain blood flow in striate cortex. Ann Neurol 1985; 17: 303–5.[Web of Science][Medline]
Fox PT, Mintun MA, Reiman EM, Raichle ME. Enhanced detection of focal brain responses using inter-subject averaging and change-distribution analysis of subtracted PET images. J Cereb Blood Flow Metab 1988; 8: 642–53.[Web of Science][Medline]
Fox PT, Ingham RJ, Ingham JC, Hirsch TB, Downs JH, Martin C, et al. A PET study of the neural systems of stuttering. Nature 1996; 382: 158–61.[Medline]
Fox PT, Huang AY, Parsons LM, Xiong J-H, Rainey L, Lancaster JL. Functional volumes modeling: scaling for group size in averaged images. Hum Brain Mapp 1999; 8: 143–50.[Web of Science][Medline]
Fox PT, Huang AY, Parsons LM, Xiong J-H, Zamarripa F, Rainey L, et al. Location-probability profiles for the mouth region of human primary motor cortex: metanalysis and validation. Neuroimage. In press 2000.
Friston KJ. Statistical parametric mapping and other analyses of functional imaging data. In: Toga AW, Mazziotta JC, editors. Brain mapping: the methods. San Diego: Academic Press; 1996. p. 363–86.
Friston KJ, Frith CD, Liddle PF, Frackowiak RS. Comparing functional (PET) images: the assessment of significant change. J Cereb Blood Flow Metab 1991; 11: 690–9.[Web of Science][Medline]
Friston KJ, Frith CD, Frackowiak RSJ. Time-dependent changes in effective connectivity measured with PET. Hum Brain Mapp 1993; 1: 69–79.
Gao J-H, Parsons LM, Bower JM, Xiong J, Li J, Fox PT. Cerebellum implicated in sensory acquisition and discrimination rather than motor control. Science 1996; 272: 545–7.[Abstract]
Gitelman DR, Nobre AC, Parrish TB, LaBar KS, Kim YH, Meyer JR, et al. A large-scale distributed network for covert spatial attention: further anatomical delineation based on stringent behavioural and cognitive controls. Brain 1999; 122: 1093–106.
Grafton ST, Mazziotta JC, Presty S, Friston KJ, Frackowiak RS, Phelps ME. Functional anatomy of human procedural learning determined with regional cerebral blood flow and PET. J Neurosci 1992; 12: 2542–8.[Abstract]
Herscovitch P, Markham J, Raichle ME. Brain blood flow measured with intravenous H215O: I. Theory and error analysis. J Nucl Med 1983; 14: 782–9.
Ingham RJ. Stuttering and behavior therapy: current status and experimental foundations. San Diego: College-Hill Press; 1984.
Ingham RJ. Speech naturalness and stuttering research: a review. In: Gerber SI, Mencher GT, editors. International perspectives on communication disorders. Washington (DC): Gallaudet University Press; 1988. p. 168–80.
Ingham RJ. On learning from speech-motor control research on stuttering. In: Cordes AK, Ingham RJ, editors. Treatment efficacy for stuttering: a search for empirical bases. San Diego: Singular Publishing Group; 1998. p. 67–101.
Ingham RJ, Packman A. A further evaluation of the speech of stutterers during chorus- and nonchorus-reading conditions. J Speech Hear Res 1979; 22: 784–93.
Ingham RJ, Cordes AK, Gow ML. Time-interval measurement of stuttering: modifying interjudge agreement. J Speech Hear Res 1993; 36: 503–15.
Ingham RJ, Fox PT, Ingham JC, Zamarripa F, Martin C, Jerabek P, et al. Functional-lesion investigation of developmental stuttering with positron emission tomography. J Speech Hear Res 1996; 39: 1208–27.
Ingham RJ, Fox PT, Ingham JC. An H232bO positron emission tomography (PET) study on adult stutterers: findings and implications. In: Hulstjin W, Peters HFM, van Lieshout PHHM, editors. Speech motor production: motor control, brain research and fluency disorders. Amsterdam: Elsevier; 1997. p. 293–306.
Ito M. The cerebellum and neural control. New York: Raven Press; 1984.
Jenkins IH, Brooks DJ, Nixon PD, Frackowiak RS, Passingham RE. Motor sequence learning: a study with positron emission tomography. J Neurosci 1994; 14: 3775–90.[Abstract]
Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, et al. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA 1992; 89: 5675–9.
Lancaster JL, Glass TG, Lankipalli BR, Downs H, Mayberg H, Fox PT, et al. A modality-independent approach to spatial normalization of tomographic images of the human brain. Hum Brain Mapp 1995; 3: 209–23.
Lancaster JL, Rainey LH, Summerlin JL, Frietas CS, Fox PT, Evans AC, et al. Automated labeling of the human brain: a preliminary report on the development and evaluation of a forward-transform method. Hum Brain Mapp 1997; 5: 238–42.[Web of Science]
Law I, Svarer C, Rostrup E, Paulson OB. Parieto-occipital cortex activation during self-generated eye movements in the dark. Brain 1998; 121: 2189–200.
Liu Y, Gao J-H, Liotti M, Pu Y, Fox PT. Temporal dissociation of parallel processing in the human subcortical outputs. Nature 1999; 400: 364–7.[Medline]
Maraist JA, Hutton C. Effect of auditory masking upon the speech of stutterers. J Speech Hear Disord 1957; 22: 385–9.
McClean MD. Neuromotor aspects of stuttering: levels of impairment and disability. ASHA Rep 1990; 18: 64–71.
Martin RR, Haroldson SK, Triden KA. Stuttering and speech naturalness. J Speech Hear Disord 1984; 49: 53–8.
Mesulam MM. Spatial attention and neglect: parietal, frontal and cingulate contributions to the mental representation and attentional targeting of salient extrapersonal events. [Review]. Philos Trans R Soc Lond B Biol Sci 1999; 354: 1325–46.
Mintun MA, Fox PT, Raichle ME. A highly accurate method of localizing regions of neuronal activation in the human brain with positron emission tomography. J Cereb Blood Flow Metab 1989; 9: 96–103.[Web of Science][Medline]
Moore WH Jr. Hemisphere processing research. In: Boberg E, editor. Neuropsychology of stuttering. Edmonton (AB): University of Alberta Press; 1993. p. 39–72.
Moore WH, Haynes WO. Alpha hemispheric asymmetry and stuttering: some support for segmentation dysfunction hypothesis. J Speech Hear Res 1980; 23: 229–47.
Pardo JV, Fox PT, Raichle ME. Localization of a human system for sustained attention by positron emission tomography. Nature 1991; 349: 61–4.[Medline]
Parsons LM, Fox PT, Downs JH, Glass T, Hirsch TB, Martin CC, et al. Use of implicit motor imagery for visual shape discrimination as revealed by PET. Nature 1995; 375: 54–8.[Medline]
Parsons LM, Denton D, Egan G, McKinley M, Shade R, Lancaster J, et al. Neuroimaging evidence implicating cerebellum in support of sensory/cognitive processes associated with thirst. Proc Natl Acad Sci USA. 2000a; 97: 2332–6.
Parsons LM, Schmahmann JD, Grill SE, Bower JM. Neurological evidence implicating the cerebellum in fine auditory discriminations. Soc Neurosci. Abstr 2000 p. 2905.
Paulesu E, Frith CD, Frackowiak RSJ. The neural correlates of the verbal component of working memory. Nature 1993; 372: 342–5.
Paus T. Location and function of the human frontal eye-field: a selective review. [Review]. Neuropsychologia 1996; 34: 475–83.[Web of Science][Medline]
Paus T, Petrides M, Evans AC, Meyer E. Role of the human anterior cingulate cortex in the control of oculomotor, manual, and speech responses: a positron emission tomography study. J Neurophysiol 1993; 70: 453–69.
Petersen SE, Fox PT, Posner MI, Mintun M, Raichle ME. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature 1988; 311: 585–9.
Petersen SE, Fox PT, Snyder AZ, Raichle ME. Activation of extrastriate and frontal cortical areas by visual words and word-like stimuli. Science 1990; 249: 1041–4.
Petrides M, Alivisatos B, Meyer E, Evans AC. Functional activation of the human frontal cortex during the performance of verbal working memory tasks. Proc Natl Acad Sci USA 1993; 90: 878–82.
Poline J-B, Mazoyer BM. Analysis of individual positron emission tomography activation maps by detection of high signal-to-noise-ratio pixel clusters. J Cereb Blood Flow Metab 1993; 13: 425–37.[Web of Science][Medline]
Pool KD, Devous MD Sr, Freeman FJ, Watson BC, Finitzo T. Regional cerebral blood flow in developmental stutterers. Arch Neurol 1991; 48: 509–12.
Price C, Wise R, Ramsay S, Friston K, Howard D, Patterson K, et al. Regional response differences within the human auditory cortex when listening to words. Neurosci Lett 1992; 146: 179–82.[Web of Science][Medline]
Raichle ME, Martin WR, Herscovitch P, Mintun MA, Markham J. Brain blood flow measured with intravenous H215O. II. Implementation and validation. J Nucl Med 1983; 24: 790–8.
Raichle ME, Fiez JA, Videen TO, MacLeod A-MK, Pardo JV, Fox PT, et al. Practice-related changes in human brain functional anatomy during nonmotor learning. Cereb Cortex 1994; 4: 8–26.
Rao SM, Bandettini PA, Binder JR, Bobholz JA, Hammeke TA, Stein EA, et al. Relationship between finger movement rate and functional magnetic resonance signal change in human primary motor cortex. J Cereb Blood Flow Metab 1996; 16: 1250–4.[Web of Science][Medline]
Roland PE, Levin B, Kawashima R, Akerman S. Three-dimensional analysis of clustered voxels in 15O-butanol brain activation images. Hum Brain Mapp 1993; 1: 3–9.
Rosenfield DB, Jerger J. Stuttering and auditory function. In: Curlee RF, Perkins WH, editors. Nature and treatment of stuttering: new directions. San Diego: College-Hill Press; 1984. p. 73–87.
Runyan CM, Adams MR. Perceptual study of the speech of `successfully therapeutized' stutterers. J Fluency Dis 1978; 3: 25–39.
Sabatini U, Chollet F, Rascol O, Celsis P, Rascol A, Lenzi GL, et al. Effect of side and rate of stimulation on cerebral blood flow changes in motor areas during finger movements in humans. J Cereb Blood Flow Metab 1993; 13: 639–45.[Web of Science][Medline]
Salmelin R, Schnitzler A, Schmitz F, Jäncke L, Witte OW, Freund HJ. Functional organization of the auditory cortex is different in stutterers and fluent speakers. Neuroreport 1998; 9: 2225–9.[Web of Science][Medline]
Schmahmann JD, Doyon J, McDonald D, Holmes C, Lavoie K, Hurwitz AS et al. Three-dimensional MRI atlas of the human cerebellum in proportional stereotaxic space. Neuroimage 1999; 10: 233–60.[Web of Science][Medline]
Schneider W, Casey BJ, Noll D. Functional MRI mapping of stimulus rate effects across visual processing stages. Hum Brain Mapp 1994; 1: 117–33.
Shaywitz BA, Shaywitz SE, Pugh KR, Constable RT, Skudlarski P, Fulbright RK, et al. Sex differences in the functional organization of the brain for language. Nature 1995; 373: 607–9.[Medline]
Shulman GL, Fiez JA, Corbetta M, Buckner RL, Miezin FM, Raichle ME et al. Common blood flow changes. J Cogn Neurosci 1997; 9: 648–63.[Web of Science]
Silbersweig DA, Stern E, Frith CD, Cahill C, Holmes A, Grootebank S, et al. A functional neuroanatomy of hallucinations in schizophrenia. Nature 1995; 378: 176–9.[Medline]
Stromsta C. Interaural phase disparity of stutterers and nonstutterers. J Speech Hear Res 1972; 15: 771–80.
Stromsta C. Elements of stuttering. Oshtemo (MI): Atsmorts; 1986.
Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain. Stuttgart; Thieme; 1988.
Thach WT, Goodkin HP, Keating JG. The cerebellum and the adaptive coordination of movement. Annu Rev Neurosci 1992; 15: 403–42.[Web of Science][Medline]
Travis LE. Speech pathology. New York: Appleton-Century; 1931.
Travis LE. The cerebral dominance theory of stuttering: 1931–1978. J Speech Hear Disord 1978; 43: 278–81.
Van Riper C, Hull CJ. The quantitative effect of certain situations on stuttering. In: Johnson W, Leutenegger RR, editors. Stuttering in children and adults. Minneapolis: University of Minnesota Press; 1956. p. 199–206.
Webster WG. Hurried hands and tangled tongues. In: Boberg E, editor. Neuropsychology of stuttering. Edmonton (AB): University of Alberta Press; 1993. p. 73–127.
Wise R, Chollet F, Hadar U, Friston K, Hoffner E, Frackowiak R. Distribution of cortical neural networks involved in word comprehension and word retrieval. Brain 1991; 114: 1803–17.
Woldorff MG, Tempelmann C, Fell J, Tegeler C, Gaschler-Markefski B, Hinrichs H, et al. Lateralized auditory spatial perception and the contralaterality of cortical processing as studied with functional magnetic resonance imaging and magnetoencephalography. Hum Brain Mapp 1999; 7: 49–66.[Web of Science][Medline]
Wood F, Stump D, McKeehan A, Sheldon S, Proctor J. Patterns of regional cerebral blood flow during attempted reading aloud by stutterers both on and off haloperidol medication: evidence for inadequate left frontal activation during stuttering. Brain Lang 1980; 9: 141–4.[Web of Science][Medline]
Wu JC, Maguire G, Riley G, Fallon J, La Casse L, Chin S, et al. A positron emission tomography [18F]deoxyglucose study of developmental stuttering. Neuroreport 1995; 6: 501–5.[Web of Science][Medline]
Xiong J, Gao J-H, Lancaster JL, Fox PT. Clustered pixels analysis for functional MRI activation studies in the human brain. Hum Brain Mapp 1995; 3: 287–301.
Received January 6, 2000. Revised April 25, 2000. Accepted June 15, 2000.
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 B E Shapiro and M R Natowicz Late-onset Tay-Sachs disease presenting as a childhood stutter J. Neurol. Neurosurg. Psychiatry, January 1, 2009; 80(1): 94 - 95. [Full Text] [PDF]
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C. Weber-Fox and A. Hampton Stuttering and Natural Speech Processing of Semantic and Syntactic Constraints on Verbs J Speech Lang Hear Res, October 1, 2008; 51(5): 1058 - 1071. [Abstract] [Full Text] [PDF]
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 J. G. Millichap Etiology and Treatment of Developmental Stuttering AAP Grand Rounds, April 1, 2008; 19(4): 42 - 42. [Full Text] [PDF]
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 M. D. Cykowski, P. V. Kochunov, R. J. Ingham, J. C. Ingham, J.-F. Mangin, D. Riviere, J. L. Lancaster, and P. T. Fox Perisylvian Sulcal Morphology and Cerebral Asymmetry Patterns in Adults Who Stutter Cereb Cortex, March 1, 2008; 18(3): 571 - 583. [Abstract] [Full Text] [PDF]
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K. E. Watkins, S. M. Smith, S. Davis, and P. Howell Structural and functional abnormalities of the motor system in developmental stuttering Brain, January 1, 2008; 131(1): 50 - 59. [Abstract] [Full Text] [PDF]
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 D. Ward The aetiology and treatment of developmental stammering in childhood Arch. Dis. Child., January 1, 2008; 93(1): 68 - 71. [Full Text] [PDF]
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 J. F. Huber, K. Bradley, B. Spiegler, and M. Dennis Long-Term Neuromotor Speech Deficits in Survivors of Childhood Posterior Fossa Tumors: Effects of Tumor Type, Radiation, Age at Diagnosis, and Survival Years J Child Neurol, July 1, 2007; 22(7): 848 - 854. [Abstract] [PDF]
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T. Godinho, R. J. Ingham, J. Davidow, and J. Cotton The distribution of phonated intervals in the speech of individuals who stutter. J Speech Lang Hear Res, February 1, 2006; 49(1): 161 - 171. [Abstract] [Full Text] [PDF]
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S. Tutuncuoglu, G. Serdaroglu, and B. Kadoglu Landau-Kleffner Syndrome Beginning With Stuttering: Case Report J Child Neurol, October 1, 2002; 17(10): 785 - 788. [Abstract] [PDF]
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S. C. Blank, S. K. Scott, K. Murphy, E. Warburton, and R. J. S. Wise Speech production: Wernicke, Broca and beyond Brain, August 1, 2002; 125(8): 1829 - 1838. [Abstract] [Full Text] [PDF]
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 Brain Correlates of Stuttering: Cause or Consequence? Journal Watch Neurology, June 8, 2001; 2001(608): 6 - 6. [Full Text]
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 The Neuroscientist Comments Neuroscientist, April 1, 2001; 7(2): 89 - 90. [PDF]
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C. L. Ludlow Stuttering: dysfunction in a complex and dynamic system Brain, October 1, 2000; 123(10): 1983 - 1984. [Full Text] [PDF]
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