Longitudinal cerebral blood flow changes during speech in hereditary ataxia

ClearSpeechTogether: a Rater Blinded, Single, Controlled Feasibility Study of Speech Intervention for People with Progressive Ataxia

BACKGROUND

Progressive ataxias frequently lead to speech disorders and consequently impact on communication participation and psychosocial wellbeing. Whilst recent studies demonstrate the potential for improvements in these areas, these treatments generally require intensive input which can reduce acceptability of the approach. A new model of care-ClearSpeechTogether-is proposed which maximises treatment intensity whilst minimising demands on clinician. This study aimed to establish feasibility and accessibility of this approach and at the same time determine the potential benefits and adverse effects on people with progressive ataxias.

METHOD

This feasibility study targeted people with progressive ataxia and mild-moderate speech and gross motor impairment. ClearSpeechTogether consisted of four individual sessions over 2 weeks followed by 20 patient-led group sessions over 4 weeks. All sessions were provided online. Quantitative and qualitative data were collected for evaluation.

RESULTS

Nine participants completed treatment. Feasibility and acceptability were high and no adverse effects were reported. Statistical tests found significantly reduced vocal strain, improved reading intelligibility and increased participation and confidence. Participant interviews highlighted the value of group support internalisation of speech strategies and psycho-social wellbeing.

DISCUSSION

ClearSpeechTogether presented a feasible, acceptable intervention for a small cohort of people with progressive ataxia. It matched or exceeded the outcomes previously reported following individual therapy. Particularly notable was the fact that this could be achieved through patient led practice without the presence of a clinician. Pending confirmation of our results by larger, controlled trials, ClearSpeechTogether could represent an effective approach to manage speech problems in ataxia.

Altered cerebral blood flow in patients with spinocerebellar degeneration

Objectives

Spinocerebellar degeneration (SCD) comprises a multitude of disorders with sporadic and hereditary forms, including spinocerebellar ataxia (SCA). Except for progressive cerebellar ataxia and structural atrophy, hemodynamic changes have also been observed in SCD. This study aimed to explore the whole-brain patterns of altered cerebral blood flow (CBF) and its correlations with disease severity and psychological abnormalities in SCD via arterial spin labeling (ASL).

Methods

Thirty SCD patients and 30 age- and sex-matched healthy controls (HC) were prospectively recruited and underwent ASL examination on a 3.0T MR scanner. The Scale for Assessment and Rating of Ataxia (SARA) and the International Cooperative Ataxia Rating Scale (ICARS) scores were used to evaluate the disease severity in SCD patients. Additionally, the status of anxiety, depression and sleep among all patients were, respectively, evaluated by the Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS) and Self-Rating Scale of Sleep (SRSS). We compared the whole-brain CBF value between SCD group and HC group at the voxel level. Then, the correlation analyses between CBF and disease severity, and psychological abnormalities were performed on SCD group.

Results

Compared with HC, SCD patients demonstrated decreased CBF value in two clusters (FWE corrected P < 0.05), covering bilateral dentate and fastigial nuclei, bilateral cerebellar lobules I-IV, V and IX, left lobule VI, right lobule VIIIb, lobules IX and X of the vermis in the cerebellar Cluster 1 and the dorsal part of raphe nucleus in the midbrain Cluster 2. The CBF of cerebellar Cluster 1 was negatively correlated with SARA scores (Spearman’s rho = –0.374, P = 0.042) and SDS standard scores (Spearman’s rho = –0.388, P = 0.034), respectively. And, the CBF of midbrain Cluster 2 also had negative correlations with SARA scores (Spearman’s rho = –0.370, P = 0.044) and ICARS scores (Pearson r = –0.464, P = 0.010).

Conclusion

The SCD-related whole-brain CBF changes mainly involved in the cerebellum and the midbrain of brainstem, which are partially overlapped with the related function cerebellar areas of hand, foot and tongue movement. Decreased CBF was related to disease severity and depression status in SCD. Therefore, CBF may be a promising neuroimaging biomarker to reflect the severity of SCD and suggest mental changes.

Genotypic Differences in Networks Supporting Regional Predictors of Speech Rate in Spinocerebellar Ataxia: Preliminary Observations

Background: Disordered speech production, dysarthria, is a common characteristic of the spinocerebellar ataxias (SCAs). Although dysarthric features differ across SCAs, a previous analysis revealed that a combination of regional cerebral blood flow (rCBF) in the left inferior frontal region and the right caudate predicted syllable rate, a pattern reported in normal speakers. This study examined the relationships between primary predictor brain regions and other areas of the brain in three SCA groups. The regions associated with the primary predictors are considered as elements of secondary networks since they are associated with regional speech predictors rather than directly with speech performance.

Methods: Speech and rCBF data from 9 SCA1, 8 SCA5, and 5 SCA6 individuals were analyzed. Partial correlations were used to identify brain regions associated with the primary predictors.

Results: Secondary networks differed across SCA genotypes. SCA1 and SCA6 demonstrated both positive and negative associations between primary and secondary areas, whereas the associations in the SCA5 genotype were only positive. The SCA5 associations were also largely bilaterally symmetrical. Both SCA1 and SCA5 demonstrated secondary associations with the right caudate, whereas the SCA6 group had no such associations.

Conclusions: These results demonstrate that although primary aspects of a brain network may remain functional, pathophysiological processes associated with different SCA genotypes may express themselves in alterations of broader, secondary brain networks. These secondary networks may reflect generic functional associations with the primary predictor regions, compensatory activity in the presence of an SCA, SCA pathology, or some combination of these factors.

Stimulation of the Subthalamic Nucleus Changes Cortical-Subcortical Blood Flow Patterns During Speech: A Positron Emission Tomography Study

Background: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment for Parkinson's disease (PD) but can have an adverse effect on speech. In normal speakers and in those with spinocerebellar ataxia, an inverse relationship between regional cerebral blood flow (rCBF) in the left inferior frontal (IFG) region and the right caudate (CAU) is associated with speech rate. This pattern was examined to determine if it was present in PD, and if so, whether it was altered by STN-DBS.

Methods: Positron Emission Tomography (PET) measured rCBF during speech in individuals with PD not treated with STN-DBS (n = 7), and those treated with bilateral STN-DBS (n = 7). Previously reported results from non-PD control subjects (n = 16) were reported for comparison. The possible relationships between speech rate during scanning and data from the left and right IFG and CAU head regions were investigated using a step-wise multiple linear regression to identify brain regions that interacted to predict speech rate.

Results: The multiple linear regression analysis replicated previously reported predictive coefficients for speech rate involving the left IFG and right CAU regions. However, the relationships between these predictive coefficients and speech rates were abnormal in both PD groups. In PD who had not received STN-DBS, the right CAU coefficient decreased normally with increasing speech rate but the left IFG coefficient abnormally decreased. With STN-DBS, this pattern was partially normalized with the addition of a left IFG coefficient that increased with speech rate, as in normal controls, but the abnormal left IFG decreasing coefficient observed in PD remained. The magnitudes of both cortical predictive coefficients but not the CAU coefficient were exaggerated with STN-DBS.

Conclusions: STN-DBS partially corrects the abnormal relationships between rCBF and speech rate found in PD by introducing a left IFG subregion that increases with speech rate, but the conflicting left IFG subregion response remained. Conflicting IFG responses may account for some of the speech problems observed after STN-DBS. Cortical and subcortical regions may be differentially affected by STN-DBS.

Performance and Function Meet Structure: A White Matter Connection Tuned for Vocal Production

Contemporary imaging techniques have increased the potential for establishing how brain regions interact during spoken language. Some imaging methods report bilateral changes in brain activity during speech, whereas another approach finds that the relationship between individual variability in speech measures and individual variability in brain activity more closely resembles clinical observations. This approach has repeatedly demonstrated that speaking rate for phonological and lexical items can be predicted by an inverse relationship between cerebral blood flow in the left inferior frontal region and the right caudate nucleus. To determine whether morphology contributes to this relationship, we examined ipsilateral and contralateral white matter connections between these structures using diffusion tensor imaging, and we further assessed possible relationships between morphology and selected acoustic measures of participants' vocal productions. The ipsilateral connections between the inferior frontal regions and the caudate nuclei had higher average fractional anisotropy and mean diffusivity values than the contralateral connections. Neither contralateral connection between inferior frontal and caudate regions showed a significant advantage on any of the average morphology measures. However, individual differences in white matter morphology were significantly correlated with individual differences in vocal amplitude and frequency stability in the left frontal–right caudate connection. This cortical–striatal connection may be “tuned” for a role in the coordination of cortical and subcortical activity during speech. The structure–function relationship in this cortical-subcortical pathway supports the previous observation of a predictive pattern of cerebral blood flow during speech and may reflect a mechanism that ensures left-hemisphere control of the vocal expression of propositional language.

Cortical-subcortical production of formulaic language: A review of linguistic, brain disorder, and functional imaging studies leading to a production model

Formulaic language forms about one-fourth of everyday talk. Formulaic (fixed expressions) and novel (grammatical language) differ in important characteristics. The features of idioms, slang, expletives, proverbs, aphorisms, conversational speech formulas, and other fixed expressions include ranges of length, flexible cohesion, memory storage, nonliteral and situation meaning, and affective content. Neurolinguistic observations in persons with focal brain damage or progressive neurological disease suggest that producing formulaic expressions can be achieved by interactions between the right hemisphere and subcortical structures. The known functional characteristics of these structures form a compatible substrate for production of formulaic expressions. Functional imaging using a performance-based analysis supported a right hemisphere involvement in producing conversational speech formulas, while indicating that the pause fillers, uh and um, engage the left hemisphere and function like lexical items. Together these findings support a dual-process model of language, whereby formulaic and grammatical language are modulated by different cerebral structures.

The Affective Nature of Formulaic Language: A Right-Hemisphere Subcortical Process

Formulaic expressions naturally convey affective content. The unique formal and functional characteristics of idioms, slang, expletives, proverbs, conversational speech formulas, and the many other conventional expressions in this repertory have been well-described: these include unitary form, conventionalized and non-literal meanings, and reliance on social context. Less highlighted, but potent, is the intrinsic presence of affective meaning. Expletives, for example, signal strong emotion. Idioms, too, inherently communicate emotional connotations, and conversational speech formulas allow for empathetic bonding and humor. The built-in affective content of formulaic expressions, in combination with their other unique characteristics, is compatible with the proposal that brain structures other than those representing grammatical language are in play in producing formulaic expressions. Evidence is presented for a dual process model of language, whereby a right hemisphere-subcortical system modulates formulaic language.

Switching Language Modes: Complementary Brain Patterns for Formulaic and Propositional Language

Language has been modeled as a rule governed behavior for generating an unlimited number of novel utterances using phonological, syntactic, and lexical processes. This view of language as essentially propositional is expanding as a contributory role of formulaic expressions (e.g., you know, have a nice day, how are you?) is increasingly recognized. The basic features of the functional anatomy of this language system have been described by studies of brain damage: left lateralization for propositional language and greater right lateralization and basal ganglia involvement for formulaic expressions. Positron emission tomography (PET) studies of cerebral blood flow (CBF) have established a cortical-subcortical pattern of brain activity predictive of syllable rate during phonological/lexical repetition. The same analytic approach was applied to analyzing brain images obtained during spontaneous monologues. Sixteen normal, right-handed, native English speakers underwent PET scanning during several language tasks. Speech rate for the repetition of phonological/lexical items was predicted by increased CBF in the left inferior frontal region and decreased CBF in the head of the right caudate nucleus, replicating previous results. A complementary cortical-subcortical pattern (CBF increased in the right inferior frontal region and decreased in the left caudate) was predictive of the use of speech formulas during monologue speech. The use of propositional language during the monologues was associated with strong left lateralization (increased CBF at the left inferior frontal region and decreased CBF at the right inferior frontal region). Normal communication involves the integration of two language modes, formulaic and novel, that have different neural substrates.

Functional connectivity associated with acoustic stability during vowel production: implications for vocal-motor control

Vowels provide the acoustic foundation of communication through speech and song, but little is known about how the brain orchestrates their production. Positron emission tomography was used to study regional cerebral blood flow (rCBF) during sustained production of the vowel /a/. Acoustic and blood flow data from 13, normal, right-handed, native speakers of American English were analyzed to identify CBF patterns that predicted the stability of the first and second formants of this vowel. Formants are bands of resonance frequencies that provide vowel identity and contribute to voice quality. The results indicated that formant stability was directly associated with blood flow increases and decreases in both left- and right-sided brain regions. Secondary brain regions (those associated with the regions predicting formant stability) were more likely to have an indirect negative relationship with first formant variability, but an indirect positive relationship with second formant variability. These results are not definitive maps of vowel production, but they do suggest that the level of motor control necessary to produce stable vowels is reflected in the complexity of an underlying neural system. These results also extend a systems approach to functional image analysis, previously applied to normal and ataxic speech rate that is solely based on identifying patterns of brain activity associated with specific performance measures. Understanding the complex relationships between multiple brain regions and the acoustic characteristics of vocal stability may provide insight into the pathophysiology of the dysarthrias, vocal disorders, and other speech changes in neurological and psychiatric disorders.

Speech motor deficits in cerebellar infarctions

Functional imaging studies demonstrated cerebellar activation during speech movements in the rostral cerebellar region. Ischemic lesions of this area, which is supplied by the superior cerebellar artery, induce dysarthria.

Speech in spinocerebellar ataxia

Spinocerebellar ataxias (SCAs) are a heterogeneous group of autosomal dominant cerebellar ataxias clinically characterized by progressive ataxia, dysarthria and a range of other concomitant neurological symptoms. Only a few studies include detailed characterization of speech symptoms in SCA. Speech symptoms in SCA resemble ataxic dysarthria but symptoms related to phonation may be more prominent. One study to date has shown an association between differences in speech and voice symptoms related to genotype. More studies of speech and voice phenotypes are motivated, to possibly aid in clinical diagnosis. In addition, instrumental speech analysis has been demonstrated to be a reliable measure that may be used to monitor disease progression or therapy outcomes in possible future pharmacological treatments. Intervention by speech and language pathologists should go beyond assessment. Clinical guidelines for management of speech, communication and swallowing need to be developed for individuals with progressive cerebellar ataxia.

Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data

We present an extension of the Linear Mixed Effects (LME) modeling approach to be applied to the mass-univariate analysis of longitudinal neuroimaging (LNI) data. The proposed method, called spatiotemporal LME or ST-LME, builds on the flexible LME framework and exploits the spatial structure in image data. We instantiated ST-LME for the analysis of cortical surface measurements (e.g. thickness) computed by FreeSurfer, a widely-used brain Magnetic Resonance Image (MRI) analysis software package. We validate the proposed ST-LME method and provide a quantitative and objective empirical comparison with two popular alternative methods, using two brain MRI datasets obtained from the Alzheimer's disease neuroimaging initiative (ADNI) and Open Access Series of Imaging Studies (OASIS). Our experiments revealed that ST-LME offers a dramatic gain in statistical power and repeatability of findings, while providing good control of the false positive rate.

Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models

Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer - a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences.

Performance-based connectivity analysis: a path to convergence with clinical studies

Connectivity analyses have become increasingly important in functional imaging. When used to describe the functional anatomy of a specific behavior, these analyses are generally applied to a subset of the data that demonstrate significant differences when experimental conditions are contrasted. Such data reduction is sub-optimal for a systems approach as it assumes that all data that survive the statistical contrast filter are related to the behavior and that none of the filtered data has a significant function. When such data filtering is applied to speech and language tasks, the resulting functional anatomy rarely reflects the brain lateralization established in over a century and a half of clinical studies. A two-step performance-based connectivity analysis is described in which the first step uses multiple linear regression to establish a direct relationship between regional brain activity and a measure of performance. The second step uses partial correlations to examine the functional relationships between the predictor regions and other brain regions. When applied to regional cerebral blood flow data obtained with positron emission tomography during a speech production task, the results demonstrate left lateralization of motor control areas, thalamic involvement in repetition rate, and auditory cortical suppression, all consistent with clinical observations. The integration of performance measures into the earliest stages of image analysis without reliance on data filtering based on decomposition may provide a path toward convergence with traditional descriptions of functional anatomy based on clinical studies.

Speech characteristics associated with three genotypes of ataxia

PURPOSE

Advances in neurobiology are providing new opportunities to investigate the neurological systems underlying motor speech control. This study explores the perceptual characteristics of the speech of three genotypes of spino-cerebellar ataxia (SCA) as manifest in four different speech tasks.

METHODS

Speech samples from 26 speakers with SCA were perceptually rated by experienced listeners. The genotypes were: SCA1, SCA5, or SCA6. The speech tasks were: diadochokinesis, word repetition, sentence reading, and picture description. The speech samples were rated using two sets of dimensions characterized as primary (e.g., articulation, rate, and rhythm) or secondary (e.g., imprecise consonants, excess and equal stress, and harsh voice).

RESULTS

On primary dimensions, SCA6 was the most impaired generally. Articulation was the most severely affected dimension and the diadochokinesis task was most effective in revealing speech impairments. On secondary dimensions, picture description was the task most likely to produce abnormal speech. The SCA groups shared articulatory problems but differed with respect to abnormal voice features.

CONCLUSIONS

These results support previous characterizations of ataxic dysarthria, and provide further information about the speech characteristics of genetic subtypes. Task demands affect perceptual ratings. Voice characteristics may be key to differentiating ataxic subtypes. As the genetic disorders that affect speech become better understood, more detailed characterizations of motor control systems should emerge.