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Kenyon KH, Boonstra F, Noffs G, Morgan AT, Vogel AP, Kolbe S, Van Der Walt A. The characteristics and reproducibility of motor speech functional neuroimaging in healthy controls. Front Hum Neurosci 2024; 18:1382102. [PMID: 39171097 PMCID: PMC11335534 DOI: 10.3389/fnhum.2024.1382102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 07/22/2024] [Indexed: 08/23/2024] Open
Abstract
Introduction Functional magnetic resonance imaging (fMRI) can improve our understanding of neural processes subserving motor speech function. Yet its reproducibility remains unclear. This study aimed to evaluate the reproducibility of fMRI using a word repetition task across two time points. Methods Imaging data from 14 healthy controls were analysed using a multi-level general linear model. Results Significant activation was observed during the task in the right hemispheric cerebellar lobules IV-V, right putamen, and bilateral sensorimotor cortices. Activation between timepoints was found to be moderately reproducible across time in the cerebellum but not in other brain regions. Discussion Preliminary findings highlight the involvement of the cerebellum and connected cerebral regions during a motor speech task. More work is needed to determine the degree of reproducibility of speech fMRI before this could be used as a reliable marker of changes in brain activity.
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Affiliation(s)
- Katherine H. Kenyon
- Department of Neuroscience, School of Translational Medicine, Melbourne, VIC, Australia
| | - Frederique Boonstra
- Department of Neuroscience, School of Translational Medicine, Melbourne, VIC, Australia
| | - Gustavo Noffs
- Department of Neuroscience, School of Translational Medicine, Melbourne, VIC, Australia
- Redenlab Inc., Melbourne, VIC, Australia
| | - Angela T. Morgan
- Murdoch Childrens Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia
- Department of Audiology and Speech Pathology, Faculty of Medicine, Dentistry and Health Sciences, Melbourne School of Health Sciences, University of Melbourne, Carlton, VIC, Australia
| | - Adam P. Vogel
- Redenlab Inc., Melbourne, VIC, Australia
- Department of Audiology and Speech Pathology, Parkville, VIC, Australia
| | - Scott Kolbe
- Department of Neuroscience, School of Translational Medicine, Melbourne, VIC, Australia
| | - Anneke Van Der Walt
- Department of Neuroscience, School of Translational Medicine, Melbourne, VIC, Australia
- Department of Neurology, Royal Melbourne Hospital, Melbourne, VIC, Australia
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Vogel AP, Sobanska A, Gupta A, Vasco G, Grobe-Einsler M, Summa S, Borel S. Quantitative Speech Assessment in Ataxia-Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Markers. CEREBELLUM (LONDON, ENGLAND) 2024; 23:1128-1134. [PMID: 37897626 PMCID: PMC11102369 DOI: 10.1007/s12311-023-01623-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/19/2023] [Indexed: 10/30/2023]
Abstract
Dysarthria is a common and debilitating symptom of many neurodegenerative diseases, including those resulting in ataxia. Changes to speech lead to significant reductions in quality of life, impacting the speaker in most daily activities. Recognition of its importance as an objective outcome measure in clinical trials for ataxia is growing. Its viability as an endpoint across the disease spectrum (i.e. pre-symptomatic onwards) means that trials can recruit ambulant individuals and later-stage individuals who are often excluded because of difficulty completing lower limb tasks. Here we discuss the key considerations for speech testing in clinical trials including hardware selection, suitability of tasks and their role in protocols for trials and propose a core set of tasks for speech testing in clinical trials. Test batteries could include forms suitable for remote short, sensitive and easy to use, with norms available in several languages. The use of artificial intelligence also could improve accuracy and automaticity of analytical pipelines in clinic and trials.
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Affiliation(s)
- Adam P Vogel
- Centre for Neuroscience of Speech, The University of Melbourne, Melbourne, Australia.
- Division of Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Germany & Center for Neurology, University Hospital Tübingen, Tübingen, Germany.
- Redenlab Inc., Melbourne, Australia.
| | - Anna Sobanska
- Department of Clinical Neurophysiology, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - Anoopum Gupta
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Gessica Vasco
- Bambino Gesù Children's Hospital, IRCCS, 00050, Rome, Italy
| | - Marcus Grobe-Einsler
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Susanna Summa
- Bambino Gesù Children's Hospital, IRCCS, 00050, Rome, Italy
| | - Stephanie Borel
- Sorbonne Université, Paris Brain Institute (ICM Institut du Cerveau), AP-HP, INSERM, CNRS, University Hospital Pitié-Salpêtrière, F-75013, Paris, France
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Németh AH, Antoniades CA, Dukart J, Minnerop M, Rentz C, Schuman BJ, van de Warrenburg B, Willemse I, Bertini E, Gupta AS, de Mello Monteiro CB, Almoajil H, Quinn L, Perlman SB, Horak F, Ilg W, Traschütz A, Vogel AP, Dawes H. Using Smartphone Sensors for Ataxia Trials: Consensus Guidance by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers. CEREBELLUM (LONDON, ENGLAND) 2024; 23:912-923. [PMID: 38015365 PMCID: PMC11102363 DOI: 10.1007/s12311-023-01608-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/25/2023] [Indexed: 11/29/2023]
Abstract
Smartphone sensors are used increasingly in the assessment of ataxias. To date, there is no specific consensus guidance regarding a priority set of smartphone sensor measurements, or standard assessment criteria that are appropriate for clinical trials. As part of the Ataxia Global Initiative Digital-Motor Biomarkers Working Group (AGI WG4), aimed at evaluating key ataxia clinical domains (gait/posture, upper limb, speech and oculomotor assessments), we provide consensus guidance for use of internal smartphone sensors to assess key domains. Guidance was developed by means of a literature review and a two stage Delphi study conducted by an Expert panel, which surveyed members of AGI WG4, representing clinical, research, industry and patient-led experts, and consensus meetings by the Expert panel to agree on standard criteria and map current literature to these criteria. Seven publications were identified that investigated ataxias using internal smartphone sensors. The Delphi 1 survey ascertained current practice, and systems in use or under development. Wide variations in smartphones sensor use for assessing ataxia were identified. The Delphi 2 survey identified seven measures that were strongly endorsed as priorities in assessing 3/4 domains, namely gait/posture, upper limb, and speech performance. The Expert panel recommended 15 standard criteria to be fulfilled in studies. Evaluation of current literature revealed that none of the studies met all criteria, with most being early-phase validation studies. Our guidance highlights the importance of consensus, identifies priority measures and standard criteria, and will encourage further research into the use of internal smartphone sensors to measure ataxia digital-motor biomarkers.
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Affiliation(s)
- Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Chrystalina A Antoniades
- Neurometrology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Martina Minnerop
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Clara Rentz
- Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | | | - Bart van de Warrenburg
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, 6525, Nijmegen, Netherlands
| | - Ilse Willemse
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Enrico Bertini
- Unit of Neuromuscular and Neurodegenerative Disorders, Dept Neurosciences, Bambino Gesu' Children's Research Hospital, IRCCS, Rome, Italy
| | - Anoopum S Gupta
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Carlos Bandeira de Mello Monteiro
- Faculty of Medicine, University of São Paulo, São Paulo, SP, Brazil
- School of Arts, Science and Humanities, University of São Paulo, São Paulo, SP, Brazil
| | - Hajar Almoajil
- Physical Therapy Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Damman, Saudi Arabia
| | - Lori Quinn
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, USA
| | | | - Fay Horak
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- APDM Precision Motion, Clario, Portland, OR, USA
| | - Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany
| | - Andreas Traschütz
- Research Division "Translational Genomics of Neurodegenerative Diseases", Hertie Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen, Germany
| | - Adam P Vogel
- Centre for Neuroscience of Speech, The University of Melbourne, Melbourne, Australia
- Division of Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Center for Neurology, University Hospital Tübingen, Tübingen, Germany
- Redenlab Inc, Melbourne, Australia
| | - Helen Dawes
- NIHR Exeter Biomedical Research Centre, Medical School, Faculty of Health and Life Sciences, College of Medicine and Health, St Lukes Campus, University of Exeter, Heavitree Road, Exeter, UK.
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Kenyon KH, Strik M, Noffs G, Morgan A, Kolbe S, Harding IH, Vogel AP, Boonstra FMC, van der Walt A. Volumetric and diffusion MRI abnormalities associated with dysarthria in multiple sclerosis. Brain Commun 2024; 6:fcae177. [PMID: 38846538 PMCID: PMC11154149 DOI: 10.1093/braincomms/fcae177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 04/16/2024] [Accepted: 05/21/2024] [Indexed: 06/09/2024] Open
Abstract
Up to half of all people with multiple sclerosis experience communication difficulties due to dysarthria, a disorder that impacts the motor aspects of speech production. Dysarthria in multiple sclerosis is linked to cerebellar dysfunction, disease severity and lesion load, but the neuroanatomical substrates of these symptoms remain unclear. In this study, 52 participants with multiple sclerosis and 14 age- and sex-matched healthy controls underwent structural and diffusion MRI, clinical assessment of disease severity and cerebellar dysfunction and a battery of motor speech tasks. Assessments of regional brain volume and white matter integrity, and their relationships with clinical and speech measures, were undertaken. White matter tracts of interest included the interhemispheric sensorimotor tract, cerebello-thalamo-cortical tract and arcuate fasciculus, based on their roles in motor and speech behaviours. Volumetric analyses were targeted to Broca's area, Wernicke's area, the corpus callosum, thalamus and cerebellum. Our results indicated that multiple sclerosis participants scored worse on all motor speech tasks. Fixel-based diffusion MRI analyses showed significant evidence of white matter tract atrophy in each tract of interest. Correlational analyses further indicated that higher speech naturalness-a perceptual measure of dysarthria-and lower reading rate were associated with axonal damage in the interhemispheric sensorimotor tract and left arcuate fasciculus in people with multiple sclerosis. Axonal damage in all tracts of interest also correlated with clinical scales sensitive to cerebellar dysfunction. Participants with multiple sclerosis had lower volumes of the thalamus and corpus callosum compared with controls, although no brain volumetrics correlated with measures of dysarthria. These findings indicate that axonal damage, particularly when measured using diffusion metrics, underpin dysarthria in multiple sclerosis.
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Affiliation(s)
- Katherine H Kenyon
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
| | - Myrte Strik
- Spinoza Centre for Neuroimaging, Netherlands Institute for Neuroscience, Royal Academy for Arts and Sciences, KNAW, Amsterdam 1105 BK, The Netherlands
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC 3052, Australia
| | - Gustavo Noffs
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
- Department of Neurology, Royal Melbourne Hospital, Parkville, VIC 3052, Australia
- Redenlab Inc, Melbourne, VIC 3000, Australia
| | - Angela Morgan
- Murdoch Children’s Research Institute, Genomic Medicine, Speech and Language Group, Parkville 3052, Australia
- Department of Speech Pathology and Audiology, University of Melbourne, Parkville 3052, Australia
| | - Scott Kolbe
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Ian H Harding
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Adam P Vogel
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC 3052, Australia
- Redenlab Inc, Melbourne, VIC 3000, Australia
- Division of Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
- Center for Neurology, University Hospital Tübingen, Tübingen 72076, Germany
- The Bionics Institute, East Melbourne, VIC 3002, Australia
| | - Frederique M C Boonstra
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Anneke van der Walt
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Spinoza Centre for Neuroimaging, Netherlands Institute for Neuroscience, Royal Academy for Arts and Sciences, KNAW, Amsterdam 1105 BK, The Netherlands
- The Bionics Institute, East Melbourne, VIC 3002, Australia
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Bóna J. Pausing and fluency in speech of patients with relapsing-remitting multiple sclerosis. CLINICAL LINGUISTICS & PHONETICS 2024; 38:332-344. [PMID: 37339478 DOI: 10.1080/02699206.2023.2223347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/22/2023]
Abstract
Multiple Sclerosis (MS) causes a variety of symptoms in speech production, such as more frequent pauses and an increase in the duration of pauses in the speech. However, there is almost no data on whether the disease affects speech fluency in other ways, such as changes in the frequency of disfluencies in speech. The main question of this study is the following: if we examine speech fluency in speech tasks requiring different cognitive load, will there be a difference between patients and controls? Twenty people with relapsing-remitting MS (3 men and 17 women) and 20 age- and education-matched control speakers (4 men and 16 women) participated in the study. Speech samples were recorded with each participant in three speech tasks: 1) spontaneous narratives about their own lives, 2) narratives about their previous day, and 3) narrative recalls based on a heard text. In the speech samples, pauses and disfluencies were annotated and the duration of pauses was measured. Then, the frequency of pauses and disfluencies were calculated and the types of disfluencies were examined. The results show that there are differences in the frequency and duration of pauses between people with MS and controls. However, there were no significant differences in the frequency of disfluencies between the groups. The same types of disfluencies occurred in the same frequency in both groups. The results help to better understand the speech production processes in MS.
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Affiliation(s)
- Judit Bóna
- Department of Applied Linguistics and Phonetics, ELTE Eötvös Loránd University, Budapest, Hungary
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Schultz BG, Joukhadar Z, Nattala U, Quiroga MDM, Noffs G, Rojas S, Reece H, Van Der Walt A, Vogel AP. Disease Delineation for Multiple Sclerosis, Friedreich Ataxia, and Healthy Controls Using Supervised Machine Learning on Speech Acoustics. IEEE Trans Neural Syst Rehabil Eng 2023; 31:4278-4285. [PMID: 37792655 DOI: 10.1109/tnsre.2023.3321874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Neurodegenerative disease often affects speech. Speech acoustics can be used as objective clinical markers of pathology. Previous investigations of pathological speech have primarily compared controls with one specific condition and excluded comorbidities. We broaden the utility of speech markers by examining how multiple acoustic features can delineate diseases. We used supervised machine learning with gradient boosting (CatBoost) to delineate healthy speech from speech of people with multiple sclerosis or Friedreich ataxia. Participants performed a diadochokinetic task where they repeated alternating syllables. We subjected 74 spectral and temporal prosodic features from the speech recordings to machine learning. Results showed that Friedreich ataxia, multiple sclerosis and healthy controls were all identified with high accuracy (over 82%). Twenty-one acoustic features were strong markers of neurodegenerative diseases, falling under the categories of spectral qualia, spectral power, and speech rate. We demonstrated that speech markers can delineate neurodegenerative diseases and distinguish healthy speech from pathological speech with high accuracy. Findings emphasize the importance of examining speech outcomes when assessing indicators of neurodegenerative disease. We propose large-scale initiatives to broaden the scope for differentiating other neurological diseases and affective disorders.
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Plotas P, Nanousi V, Kantanis A, Tsiamaki E, Papadopoulos A, Tsapara A, Glyka A, Mani E, Roumelioti F, Strataki G, Fragkou G, Mavreli K, Ziouli N, Trimmis N. Speech deficits in multiple sclerosis: a narrative review of the existing literature. Eur J Med Res 2023; 28:252. [PMID: 37488623 PMCID: PMC10364432 DOI: 10.1186/s40001-023-01230-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 07/15/2023] [Indexed: 07/26/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory and demyelinating autoimmune disease. MS patients deal with motor and sensory impairments, visual disabilities, cognitive disorders, and speech and language deficits. The study aimed to record, enhance, update, and delve into our present comprehension of speech deficits observed in patients with MS and the methodology (assessment tools) studies followed. The method used was a search of the literature through the databases for May 2015 until June 2022. The reviewed studies offer insight into speech impairments most exhibited by MS patients. Patients with MS face numerous communication changes concerning the phonation system (changes observed concerning speech rate, long pause duration) and lower volume. Moreover, the articulation system was affected by the lack of muscle synchronization and inaccurate pronunciations, mainly of vowels. Finally, there are changes regarding prosody (MS patients exhibited monotonous speech). Findings indicated that MS patients experience communication changes across various domains. Based on the reviewed studies, we concluded that the speech system of MS patients is impaired to some extent, and the patients face many changes that impact their conversational ability and the production of slower and inaccurate speech. These changes can affect MS patients' quality of life.
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Affiliation(s)
- Panagiotis Plotas
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
- Laboratory of Primary Health Care, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Vasiliki Nanousi
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Anastasios Kantanis
- Laboratory of Primary Health Care, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Eirini Tsiamaki
- Department of Neurology, Medical School, University of Patras, Patras, Greece
| | - Angelos Papadopoulos
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece.
| | - Angeliki Tsapara
- Laboratory of Primary Health Care, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Aggeliki Glyka
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Efraimia Mani
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Fay Roumelioti
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Georgia Strataki
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Georgia Fragkou
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Konstantina Mavreli
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Natalia Ziouli
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece
| | - Nikolaos Trimmis
- Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece.
- Laboratory of Primary Health Care, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece.
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Kieling MLM, Finkelsztejn A, Konzen VR, dos Santos VB, Ayres A, Klein I, Rothe-Neves R, Olchik MR. Articulatory speech measures can be related to the severity of multiple sclerosis. Front Neurol 2023; 14:1075736. [PMID: 37384284 PMCID: PMC10294674 DOI: 10.3389/fneur.2023.1075736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 05/11/2023] [Indexed: 06/30/2023] Open
Abstract
Background Dysarthria is one of the most frequent communication disorders in patients with Multiple Sclerosis (MS), with an estimated prevalence of around 50%. However, it is unclear if there is a relationship between dysarthria and the severity or duration of the disease. Objective Describe the speech pattern in MS, correlate with clinical data, and compare with controls. Methods A group of MS patients (n = 73) matched to healthy controls (n = 37) by sex and age. Individuals with neurological and/or systemic conditions that could interfere with speech were excluded. MS group clinical data were obtained through the analysis of medical records. The speech assessment consisted of auditory-perceptual and speech acoustic analysis, from recording the following speech tasks: phonation and breathing (sustained vowel/a/); prosody (sentences with different intonation patterns) and articulation (diadochokinesis; spontaneous speech; diphthong/iu/repeatedly). Results In MS, 72.6% of the individuals presented mild dysarthria, with alterations in speech subsystems: phonation, breathing, resonance, and articulation. In the acoustic analysis, individuals with MS were significantly worse than the control group (CG) in the variables: standard deviation of the fundamental frequency (p = 0.001) and maximum phonation time (p = 0.041). In diadochokinesis, individuals with MS had a lower number of syllables, duration, and phonation time, but larger pauses per seconds, and in spontaneous speech, a high number of pauses were evidenced as compared to CG. Correlations were found between phonation time in spontaneous speech and the Expanded Disability Status Scale (EDSS) (r = - 0.238, p = 0.043) and phonation ratio in spontaneous speech and EDSS (r = -0.265, p = 0.023), which indicates a correlation between the number of pauses during spontaneous speech and the severity of the disease. Conclusion The speech profile in MS patients was mild dysarthria, with a decline in the phonatory, respiratory, resonant, and articulatory subsystems of speech, respectively, in order of prevalence. The increased number of pauses during speech and lower rates of phonation ratio can reflect the severity of MS.
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Affiliation(s)
- Maiara Laís Mallmann Kieling
- Post-Graduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Neurology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
- Speech Language Pathology Course, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | | | - Viviana Regina Konzen
- Post-Graduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Neurology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Vanessa Brzoskowski dos Santos
- Post-Graduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Annelise Ayres
- Neurology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Iasmin Klein
- Speech Language Pathology Course, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Rui Rothe-Neves
- Phonetics Laboratory of the Faculty of Letters, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Maira Rozenfeld Olchik
- Post-Graduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Neurology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
- Speech Language Pathology Course, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Department of Surgery and Orthopedics, Faculdade de Odontologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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Yap SM, Davenport L, Cogley C, Craddock F, Kennedy A, Gaughan M, Kearney H, Tubridy N, De Looze C, O'Keeffe F, Reilly RB, McGuigan C. Word finding, prosody and social cognition in multiple sclerosis. J Neuropsychol 2023; 17:32-62. [PMID: 35822290 DOI: 10.1111/jnp.12285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 03/29/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Impairments in speech and social cognition have been reported in people with multiple sclerosis (pwMS), although their relationships with neuropsychological outcomes and their clinical utility in MS are unclear. OBJECTIVES To evaluate word finding, prosody and social cognition in pwMS relative to healthy controls (HC). METHODS We recruited people with relapsing MS (RMS, n = 21), progressive MS (PMS, n = 24) and HC (n = 25) from an outpatient MS clinic. Participants completed a battery of word-finding, social cognitive, neuropsychological and clinical assessments and performed a speech task for prosodic analysis. RESULTS Of 45 pwMS, mean (SD) age was 49.4 (9.4) years, and median (range) Expanded Disability Severity Scale score was 3.5 (1.0-6.5). Compared with HC, pwMS were older and had slower information processing speed (measured with the Symbol Digit Modalities Test, SDMT) and higher depression scores. Most speech and social cognitive measures were associated with information processing speed but not with depression. Unlike speech, social cognition consistently correlated with intelligence and memory. Visual naming test mean response time (VNT-MRT) demonstrated worse outcomes in MS versus HC (p = .034, Nagelkerke's R2 = 65.0%), and in PMS versus RMS (p = .009, Nagelkerke's R2 = 50.2%). Rapid automatised object naming demonstrated worse outcomes in MS versus HC (p = .014, Nagelkerke's R2 = 49.1%). These word-finding measures showed larger effect sizes than that of the SDMT (MS vs. HC, p = .010, Nagelkerke's R2 = 40.6%; PMS vs. RMS, p = .023, Nagelkerke's R2 = 43.5%). Prosody and social cognition did not differ between MS and HC. CONCLUSIONS Word finding, prosody and social cognition in MS are associated with information processing speed and largely independent of mood. Impairment in visual object meaning perception is potentially a unique MS disease-related deficit that could be further explored and cautiously considered as an adjunct disability metric for MS.
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Affiliation(s)
- Siew Mei Yap
- Department of Neurology, St. Vincent's University Hospital, Dublin 4, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland
| | - Laura Davenport
- Neuropsychology Service, Department of Psychology, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Clodagh Cogley
- Neuropsychology Service, Department of Psychology, St. Vincent's University Hospital, Dublin 4, Ireland.,School of Psychology, University College Dublin, Dublin, Ireland
| | - Fiona Craddock
- Neuropsychology Service, Department of Psychology, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Alex Kennedy
- Trinity Centre for Biomedical Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
| | - Maria Gaughan
- Department of Neurology, St. Vincent's University Hospital, Dublin 4, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland
| | - Hugh Kearney
- Department of Neurology, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Niall Tubridy
- Department of Neurology, St. Vincent's University Hospital, Dublin 4, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland
| | - Céline De Looze
- Trinity Centre for Biomedical Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
| | - Fiadhnait O'Keeffe
- Neuropsychology Service, Department of Psychology, St. Vincent's University Hospital, Dublin 4, Ireland.,School of Psychology, University College Dublin, Dublin, Ireland
| | - Richard B Reilly
- Trinity Centre for Biomedical Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland.,School of Medicine, Trinity College, The University of Dublin, Dublin 2, Ireland.,School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
| | - Christopher McGuigan
- Department of Neurology, St. Vincent's University Hospital, Dublin 4, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland
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10
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Svoboda E, Bořil T, Rusz J, Tykalová T, Horáková D, Guttmann CRG, Blagoev KB, Hatabu H, Valtchinov VI. Assessing clinical utility of machine learning and artificial intelligence approaches to analyze speech recordings in multiple sclerosis: A pilot study. Comput Biol Med 2022; 148:105853. [PMID: 35870318 DOI: 10.1016/j.compbiomed.2022.105853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 04/09/2022] [Accepted: 05/23/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria. METHOD The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve. RESULTS The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant. CONCLUSION Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations.
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Affiliation(s)
- E Svoboda
- Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic; Institute of Phonetics, Faculty of Arts, Charles University, Prague, Czech Republic
| | - T Bořil
- Institute of Phonetics, Faculty of Arts, Charles University, Prague, Czech Republic
| | - J Rusz
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic; Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic; Department of Neurology & ARTORG Center, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - T Tykalová
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - D Horáková
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - C R G Guttmann
- Center for Neurological Imaging, Brigham & Women's Hospital and Harvard Medical School, USA
| | - K B Blagoev
- Department of Biophysics, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - H Hatabu
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V I Valtchinov
- Center for Evidence-Based Imaging, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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11
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An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis. THE CEREBELLUM 2022:10.1007/s12311-022-01435-y. [PMID: 35761144 PMCID: PMC9244122 DOI: 10.1007/s12311-022-01435-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/15/2022] [Indexed: 12/03/2022]
Abstract
Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.
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12
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Kent RD, Kim Y, Chen LM. Oral and Laryngeal Diadochokinesis Across the Life Span: A Scoping Review of Methods, Reference Data, and Clinical Applications. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2022; 65:574-623. [PMID: 34958599 DOI: 10.1044/2021_jslhr-21-00396] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
PURPOSE The aim of this study was to conduct a scoping review of research on oral and laryngeal diadochokinesis (DDK) in children and adults, either typically developing/developed or with a clinical diagnosis. METHOD Searches were conducted with PubMed/MEDLINE, Google Scholar, CINAHL, and legacy sources in retrieved articles. Search terms included the following: DDK, alternating motion rate, maximum repetition rate, sequential motion rate, and syllable repetition rate. RESULTS Three hundred sixty articles were retrieved and included in the review. Data source tables for children and adults list the number and ages of study participants, DDK task, and language(s) spoken. Cross-sectional data for typically developing children and typically developed adults are compiled for the monosyllables /pʌ/, /tʌ/, and /kʌ/; the trisyllable /pʌtʌkʌ/; and laryngeal DDK. In addition, DDK results are summarized for 26 disorders or conditions. DISCUSSION A growing number of multidisciplinary reports on DDK affirm its role in clinical practice and research across the world. Atypical DDK is not a well-defined singular entity but rather a label for a collection of disturbances associated with diverse etiologies, including motoric, structural, sensory, and cognitive. The clinical value of DDK can be optimized by consideration of task parameters, analysis method, and population of interest.
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Affiliation(s)
- Ray D Kent
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison
| | - Yunjung Kim
- School of Communication Sciences & Disorders, Florida State University, Tallahassee
| | - Li-Mei Chen
- Department of Foreign Languages and Literature, National Cheng Kung University, Tainan, Taiwan
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13
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Vogel AP, Pearson-Dennett V, Magee M, Wilcox RA, Esterman A, Thewlis D, White JM, Todd G. Adults with a history of recreational cannabis use have altered speech production. Drug Alcohol Depend 2021; 227:108963. [PMID: 34419853 DOI: 10.1016/j.drugalcdep.2021.108963] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 06/18/2021] [Accepted: 07/07/2021] [Indexed: 11/28/2022]
Abstract
Stereotypical depictions of speech in cannabis users often suggest slow, laboured output, yet objective evidence supporting this assumption is extremely limited. We know that depressants or hallucinogenic drugs such as cannabis can cause acute changes in communication and speech rate, but the long-lasting effects of cannabis use on speech are not well described. The aim of this study was to investigate speech in individuals with a history of recreational cannabis use compared to non-drug-using healthy controls. Speech samples were collected from a carefully described cohort of 31 adults with a history of cannabis use (but not use of illicit stimulant drugs) and 40 non-drug-using controls. Subjects completed simple and complex speech tasks including a monologue, a sustained vowel, saying the days of the week, and reading a phonetically balanced passage. Audio samples were analysed objectively using acoustic analysis for measures of timing, vocal control, and quality. Subtle differences in speech timing, vocal effort, and voice quality may exist between cannabis and control groups, however data remain equivocal. After controlling for lifetime alcohol and tobacco use and applying a false discovery rate, only spectral tilt (vocal effort and intensity) differed between groups and appeared to change in line with duration of abstinence from cannabis use. Differences between groups may reflect longer term changes to the underlying neural control of speech. Our digital analysis of speech shows there may be a signal differentiating individuals with a history of recreational cannabis use from healthy controls, in line with similar findings from gait and hand function studies.
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Affiliation(s)
- Adam P Vogel
- Centre for Neuroscience of Speech, The University of Melbourne, Parkville, VIC, 3010, Australia; Department of Neurodegeneration, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, 72076, Germany; Redenlab, Melbourne, Australia.
| | - Verity Pearson-Dennett
- UniSA Clinical & Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Michelle Magee
- Centre for Neuroscience of Speech, The University of Melbourne, Parkville, VIC, 3010, Australia; Redenlab, Melbourne, Australia
| | - Robert A Wilcox
- UniSA Clinical & Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia; Department of Neurology, Flinders Medical Centre, Bedford Park, SA, 5042, Australia; Human Physiology, Medical School, Flinders University, Bedford Park, SA, 5042, Australia
| | - Adrian Esterman
- UniSA Clinical & Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia; Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Australia
| | - Dominic Thewlis
- Centre for Orthopaedic & Trauma Research, The University of Adelaide, Adelaide, SA, 5000, Australia
| | - Jason M White
- UniSA Clinical & Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Gabrielle Todd
- UniSA Clinical & Health Sciences, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia; Alliance for Research in Exercise, Nutrition and Activity (ARENA), UniSA Allied Health & Human Performance, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
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