Next Article in Journal
Behavioral and Cultural Insights, a Nationwide Study Based on Repetitive Surveys of WHO Behavioral Insights Tool in Greece Regarding COVID-19 Pandemic and Vaccine Acceptance
Previous Article in Journal
Dental Care for Older Adults
Previous Article in Special Issue
Evaluation of Movement Restriction of Spinal Orthoses Using Inertial Measurement Units
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 20
Issue 1
10.3390/ijerph20010215
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Mapping Research Trends from 20 Years of Publications in Rhythmic Auditory Stimulation

by
Meiqi Zhang
1,2,*,†,
Fang Li
3,†,
Dongyu Wang
4,
Xiaohong Ba
3 and
Zhan Liu
1
1
Department of Physical Education and Health Education, Springfield College, Springfield, MA 01109, USA
2
Yale/VA Learning-Based Recovery Center, Yale University, New Haven, CT 06510, USA
3
Department of Neurology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou 121001, China
4
Department of Neurology, The Center Hospital of Jinzhou, Jinzhou 121001, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2023, 20(1), 215; https://doi.org/10.3390/ijerph20010215
Submission received: 19 October 2022 / Revised: 5 December 2022 / Accepted: 7 December 2022 / Published: 23 December 2022
(This article belongs to the Special Issue Health Services and Assistive Technology in Rehabilitation)
Browse Figures
Review Reports Versions Notes

Abstract

:
This study aims to create an all-around insight into the evolutions, status, and global trends of rhythmic auditory stimulation (RAS) research via enhanced bibliometric methods for the 2001–2020 time period. Articles concerning RAS were extracted from the Web of Science database. CiteSpace, Bibliometrix, VOSviewer, and Graphpad Prism were employed to analyze publication patterns and research trends. A total of 586 publications related to RAS between 2001 and 2020 were retrieved from the Web of Science database. The researcher Goswami U. made the greatest contribution to this field. The University of Toronto was the institution that published the most articles. Motor dysfunction, sensory perception, and cognition are the three major domains of RAS research. Neural tracking, working memory, and neural basis may be the latest research frontiers. This study reveals the publication patterns and topic trends of RAS based on the records published between 2001 and 2020. The insights obtained provided useful references for the future research and applications of RAS.

1. Introduction

Rhythmic auditory stimulation (RAS) is a therapeutic technique that uses predictable time cues to improve different outcomes related to movement [1,2]. RAS is characterized by acoustic stimuli that synchronize motor response through rhythmic cueing, and the synchronous connection is produced by neuronal substrates with effects on movements, therefore the synchronization is created between the subject’s movements and external auditory stimuli through an internal timing process [3,4,5]. Consequently, the subject will perform the time-coordinated movements and the rhythmic sequence programmed by the RAS model [4,6].
A large number of clinical research and systematic reviews have examined the effectiveness of RAS in the rehabilitation of Parkinson’s disease (PD) [5,7], stroke [8], language disorders [9], and other sensorimotor dysfunctions. Combined strategies (e.g., integrating auditory cues and visual stimuli) have also been investigated to optimize the use of the technique.
Bibliometric analysis is used for analyzing literature characteristics, research impact, and trends over time [10]. In comparison to other reviewing methods, bibliometrics provide a more quantitative way of measuring research impact, so are seen as relatively objective. Bibliometric analysis has been widely applied to public health, rehabilitation, and medical fields [11,12,13]. A growing number of practitioners have focused on conducting RAS research over the past two decades. However, a report on RAS using bibliometric analysis has not been found yet.
This study conducts a bibliometric analysis of RAS based on articles published between 2001 and 2020 to provide an all-around insight into the evolutions, status, and global trends of RAS research. The results can also be used to facilitate further experimental designs, study submissions, and clinical applications.

2. Methods

2.1. Source of Data and Search Strategy

Published papers were retrieved via a topic search of the Science Citation Index Expanded (SCI-Expanded) from the Web of Science Core Collection database (WoSCC) in September 2021. The searching strategy was based on free-terms: TS = (rhythmic + auditory + cue* OR rhythmic + auditory + stimulation* OR rhythmic + auditory + training* OR rhythmic + auditory + therapy* + rhythmic + acoustic + stimulation*), index = SCI-Expanded, and time span = 2001–2020.

2.2. Inclusion Criteria

Only studies designated as “article” were included, covering all types of studies. Other document types such as meeting abstracts and letters, were excluded. The critical information (i.e., titles, abstracts, journals, countries/regions, institutions, and cited references) were comprehensively collected. Only studies that were published in English were considered. Finally, a total of 586 records published during the period 2001–2020 met the inclusion criteria.

2.3. Analytical Methods

The data were analyzed by three bibliometric analysis tools: Bibliometrix R Package [14], VOSviewer 1.6.11 [15], Citespace [16], and GraphPad Prism 8 for Windows [13]. Bibliometrix was conducted to analyze the frequency distribution of annual outputs, authors, articles, journals, countries, collaboration between countries, and institutions according to the titles and abstracts. VOSviewer 1.6.11 [15] was used to design the social network maps for co-occurrence keywords that appeared in at least 10 papers. Citespace was applied to detect the keywords with citation bursts. A citation burst has two characteristics: strength and duration [12,17]. A citation burst indicates increased attention to the underlying work over a certain period, which is a key indicator for determining emerging trends [18,19,20]. GraphPad Prism 8 was applied to analyze the time trend of annual publication outputs.

3. Results

3.1. Literature Distribution

A total of 586 articles were identified. As Figure 1 shows, since 2001, the number of publications concerning RAS has risen considerably. A sharp increase was observed in 2014, which the number of articles surged from 29 in 2013 to 69 in 2014. Then, the annual outputs held steady at around 50 articles.
Research relating to RAS has been published in 234 journals. PLoS One published the most RAS-relevant studies, with 32 articles (Table 1). The Frontiers in Neuroscience ranked second with 20 articles. The Experimental Brain Research, Frontiers in Human Neuroscience, Human Movement Science, Journal of Neuroscience, and Neuroimaging tied for the third, publishing 16 articles on RAS research, respectively. The Frontiers in Neurology (n = 15), European Journal of Neuroscience (n = 14), and Gait & Posture (n = 14) ranked from eighth to tenth. Amongst the ten journals, there were six neuroscience journals, one multidisciplinary journal, one psychological journal, one neuroimaging journal, and a rehabilitation journal.
Authors from 40 countries have contributed to research on RAS. As shown in Figure 2, the United States was the most productive country in RAS research and ranked the first in publication outputs, accounting for around 30% (n = 176) of the total. The United Kingdom (n = 60), Germany (n = 54), Canada (n = 53), Italy (n = 33), France (n = 30), The Netherlands (n = 25), Australia (n = 24), South Korea (n = 23), and China (n = 22) ranked from second to tenth and were all far behind on article totals. Figure 3 shows the collaborative relationships of the Top 20 most productive countries within RAS research. It is obvious that the United States plays an irreplaceable leading role, which has built relatively stable collaborative relationships with at least ten countries. What should also be noticed is that the UK and Germany also demonstrated the high centrality to collaborative research in RAS. The collaborations displayed a significantly regional characteristic.
Aligned with the contribution of countries, Table 2 shows the 10 most contributive institutions in the RAS research field. The University of Toronto was the most productive institution, which had 42 publications related to RAS. The Colorado State University and Radboud University Nijmegen tied for second with 26 publications. They were followed by the University of Cambridge (n = 25), Northwestern University (n = 22), Washington University (n = 22), McMaster University (n = 21), University of Maryland (n = 21), University of California Irvine (n = 20), and Max Planck Institute for Human Cognitive and Brain Sciences (n = 18). Half of the institutions were American colleges. The other five included two Canadian institutions, and The Netherlands, Germany, and the UK each had one.
A total of 2263 authors contributed to the total output of RAS research. The top 10 authors published a total of 101 papers (Table 3), which accounted for 17.23% of all the literature in this field. Dr. Usha Goswami from the University of Cambridge published the most research on RAS with 15 papers, followed by Dr. Michael H. Thaut from the University of Toronto and Dr. ‪Simone Dalla-Bella from the University of Montreal, who had 13 and 12 articles, respectively. Ranking from fourth to tenth were Nieuwboer A. (n = 10), Rochester L (n = 10), Kotz S. (n = 9), Trainor L. (n = 9), Grahn J. (n = 8), Kwakkel G. (n = 8), and Earhart G. (n = 7).

3.2. Research Topics and Hotspots

The keywords co-occurrence analysis produced a network map to reflect high-frequency keywords and topics within RAS research. As Figure 4 shows, there are 3 clusters for 60 high-frequency keywords within the field of RAS research. The keywords in cluster 1 (colored by red) are mainly related to movement dysfunctions, cluster 2 (colored by blue) covers keywords related to perception, and cluster 3 (colored by gold) tends to be more related to cognition. This represents that previous research is mainly based on these three directions.
The frequency of citations could reflect the research topics within the field. The top ten cited articles in the field of RAS were shown in Table 4. Among the ten articles, there were two stroke studies and two PD studies, and the other six were related to perception and cognitive process. The article that received the highest citation, “Rhythm and beat perception in motor areas of the brain”, was published in the Journal of Cognitive Neuroscience in 2007 and received a total of 501 citations. Most of the articles (i.e., 7/10) were published in journals in the field of neuroscience, and the other three appeared in medical and multidisciplinary journals. The top ten cited RAS articles in the past five years (2016–2020) were shown in Table 5. The ten articles tended to focus more on the neural mechanisms of RAS. The most cited article was “Motor origin of temporal predictions in auditory attention”, which was published in Proceedings of the National Academy of Sciences of the United States of America in 2017. Among these ten articles, four were published in neuroscience journals, four in multidisciplinary journals, one in a biological journal, and one in a psychological journal.
Burst detection was applied to investigate the research hotspots further. Burst keywords can be identified as indicators of emerging trends [42]. Figure 5 presents keywords with the 25 strongest citation bursts between 2011 and 2020. The most recent burst keywords were working memory, tracking, and neural basis.
Clinically, RAS has been widely applied as a rehabilitation strategy. According to the analysis of high-frequency keywords, PD was the most focused disease within RAS research (Figure 6). A total of 97 publications focused on PD. Stroke and speech impairment ranked second and third with 50 and 47 publications, while the other six were well below: dyslexia (18 articles), dementia (18 articles), multiple sclerosis (10 articles), apraxia (6 articles), cognitive impairments (6), cerebral palsy (5 articles), and depression (5 articles). All the diseases were neurological and psychiatric disorders.

4. Discussion

The bibliometric analysis aimed to investigate the developmental trends and hotspots of research on 586 RAS articles during 2001–2020 by using VOSviewer, Bibliometrix, and Citespace. This work summarized research trends, topics, sources, and contributions for RAS.
An exponential growth has been observed in the output of RAS research. If the overall growth rate that was observed also applies to the future, we can expect the publication volume in the RAS research field to double about every five years. This strong growth of research output may be partially attributed to the increased prevalence of neurologic and psychiatric diseases (those were major types of disease applying RAS treatment). Given this, researchers and practitioners worked on exploiting RAS to facilitate rehabilitation. Intervention methods and analysis strategies are being developed [16,43,44]. The surge of RAS research in 2014 might be influenced by the release of the Global Burden of Disease (GBD) 2010 study at the end of 2012 [45]. The GBD 2010 found 114% and 68% increases in the mortality of psychiatric and neurological disorders from 1990 [46,47,48,49].
Among the top-performing journals, more than half were neuroscience journals. It seems that RAS researchers preferred to submit studies to the neuroscience area. An explanation is that for promoting research in the relevant field, some of the neuroscience journals have set auditory cognition and/or brain stimulation research sections or special columns. Most RAS studies were published in multidisciplinary journals also reflected a trend. This could be attributed to how the multidisciplinary journals tended to have a larger number of articles published than subject-specific journals. In addition, RAS has always been considered a transdisciplinary subject [50]. Publishing in multidisciplinary journals may expand the influence of studies.
Of the top productive countries, the U.S. ranked first in the number of RAS publications. Five American affiliations came in the top 10 institutions in the research of RAS, symbolizing that the U.S. possessed the most elite institutions around the world. However, there is only one American author in the top ten authors, indicating the contributions of US researchers were more even. This may be because the concept of integrating RAS into rehabilitation was initially proposed by an American researcher [51] thus the U.S. went deeper in this field as compared with the rest of the world. It is also worth mentioning that the boost of RAS clinical research should be attributed to a Canadian researcher, Dr. Michael Thaut, who has revolutionized the use of auditory stimulation in rehabilitation around the world.
Keyword analyses can be used for detecting research topics, analyzing research hotspots, as well as monitoring the research frontier transitions [52]. Through the analysis of the high-frequency keywords in the RAS research of the past 20 years, the studies were closely related to the three themes: motor dysfunction, cognition, and perception. This hypothesis was also supported by burst detection.

4.1. Motor Dysfunctions

Facilitating walking rehabilitation is a major use of RAS [7,32]. RAS demonstrated significant effects on improving muscle coordination and balance performance to patients with PD and stroke [53,54]. Early researchers focused more on the patterns of auditory cues [4,6]. More recently, researchers began to investigate the integrated effects of RAS and other techniques, such as exercise and robot-assisted therapeutic devices [55]. The comprehensive efficacy of RAS is constantly being verified in clinical trials for the rehabilitation of various movement disorders/dysfunctions [7,56,57,58].

4.2. Cognition

Early studies regarding the beneficial effects of auditory stimuli on cognition (e.g., learning and memory) had been inconsistent [59]. However, more recent neurobiological research revealed the significant roles of RAS for cognitive performance of Alzheimer’s disease, developmental language disorders, and also PD [9,23,45,60]. To boost cognitive processing, a temporal sampling framework for specific disorders can be integrated into auditory stimuli [9]. Additionally, bass sounds were examined to be better at allocating attention than high-frequency sounds, providing incomplete evidence for the convention of using bass instruments to carry the rhythmic foundations of music [61].

4.3. Perception

The broad application of electrophysiological technologies (e.g., electroencephalogram) allowed researchers to explore the associations between RAS and sensory perception. Most early studies attempted to explain how neural sensory, and motor contributed to behavioral beat synchronization [62,63]. Over time, neural tracking, the mechanism of neural signals synchronizing to rhythmic sensory inputs [64], has been found to excel in rhythmic coordination of perception and action [61]. Clinically, RAS has been examined to be effective on improving perceptual performance, especially speech and visual perception [45,46].
We tried to provide information for future research and clinical uses based on quantitative bibliometrics, but a few limitations should be noticed. One is the findings of the study may be limited by the scope of the analytic tools. We only retrieved data from the WoS database, some vital information might have been missed. Another one is that the bibliometric data might not be adequate to assess the actual contribution of the research/researchers. Even though the quantitative metrics (e.g., number of publications) can reflect the popularity, the results should be explained carefully.

5. Conclusions

This study may help practitioners and researchers discover the publication patterns and emerging trends of RAS and present reference values for future research and applications. The most influential author, institutions, journals, and countries were Goswami U., University of Toronto, PLoS ONE, and the U.S., respectively. Motor dysfunction, sensory perception, and cognition are the three major clinical domains of RAS research. Neural tracking, working memory, and neural basis may be the latest research frontiers.

Author Contributions

Formal analysis, F.L.; Data curation, D.W.; Writing—original draft, M.Z.; Writing—review & editing, Z.L.; Project administration, X.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethics approval is not required to the study as it does not analyze data collected from human or animal subjects.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available upon reasonable request from the authors.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. McIntosh, G.C.; Brown, S.H.; Rice, R.R.; Thaut, M.H. Rhythmic auditory-motor facilitation of gait patterns in patients with Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 1997, 62, 22–26. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Thaut, M.H.; McIntosh, G.C.; Rice, R.R.; Miller, R.A.; Rathbun, J.; Brault, J.M. Rhythmic auditory stimulation in gait training for Parkinson’s disease patients. Mov. Disord. 1996, 11, 193–200. [Google Scholar] [CrossRef]
  3. Thaut, M.H.; Abiru, M. Rhythmic Auditory Stimulation in Rehabilitation of Movement Disorders: A Review Of Current Research. Music Percept. 2010, 27, 263–269. [Google Scholar] [CrossRef] [Green Version]
  4. Rossignol, S.; Jones, G.M. Audio-spinal influence in man studied by the H-reflex and its possible role on rhythmic movements synchronized to sound. Electroencephalogr. Clin. Neurophysiol. 1976, 41, 83–92. [Google Scholar] [CrossRef] [PubMed]
  5. Yoo, G.E.; Kim, S.J. Rhythmic auditory cueing in motor rehabilitation for stroke patients: Systematic review and meta-analysis. J. Music Ther. 2016, 53, 149–177. [Google Scholar] [CrossRef] [PubMed]
  6. Przybylski, L.; Bedoin, N.; Krifi-Papoz, S.; Herbillon, V.; Roch, D.; Léculier, L.; Kotz, S.A.; Tillmann, B. Rhythmic auditory stimulation influences syntactic processing in children with developmental language disorders. Neuropsychology 2013, 27, 121. [Google Scholar] [CrossRef] [Green Version]
  7. Ellegaard, O.; Wallin, J.A. The bibliometric analysis of scholarly production: How great is the impact? Scientometrics 2015, 105, 1809–1831. [Google Scholar] [CrossRef] [Green Version]
  8. Franchignoni, F.; Lasa, S.M. Bibliometric indicators and core journals in physical and rehabilitation medicine. J. Rehabil. Med. 2011, 43, 471–476. [Google Scholar] [CrossRef] [Green Version]
  9. Moura, L.K.B.; de MESQUITA, R.F.; Mobin, M.; Matos, F.T.C.; Monte, T.L.; Lago, E.C.; Falcão, C.A.M.; Ferraz, M.Â.D.A.L.; Santos, T.C.; Sousa, L.R.M. Uses of bibliometric techniques in public health research. Iran. J. Public Health 2017, 46, 1435–1436. [Google Scholar]
  10. Tran, B.X.; Vu, G.T.; Ha, G.H.; Vuong, Q.-H.; Ho, M.-T.; Vuong, T.-T.; La, V.-P.; Nghiem, K.-C.P.; Nguyen, H.L.T.; Latkin, C.A.; et al. Global evolution of research in artificial intelligence in health and medicine: A bibliometric study. J. Clin. Med. 2019, 8, 360. [Google Scholar] [CrossRef] [Green Version]
  11. Zheng, K.-Y.; Dai, G.-Y.; Lan, Y.; Wang, X.-Q. Trends of Repetitive Transcranial Magnetic Stimulation from 2009 to 2018: A Bibliometric Analysis. Front. Neurosci. 2020, 14, 106. [Google Scholar] [CrossRef] [PubMed]
  12. Chen, C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inf. Sci. Technol. 2006, 57, 359–377. [Google Scholar] [CrossRef] [Green Version]
  13. Software Graphpad. GraphPad Prism Version 8.0 for Windows; GraphPad: La Jolla, CA, USA, 2018. [Google Scholar]
  14. Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017, 11, 959–975. [Google Scholar] [CrossRef]
  15. Waltman, L.; Van Eck, N.J. A smart local moving algorithm for large-scale modularity-based community detection. Eur. Phys. J. B 2013, 86, 1–14. [Google Scholar] [CrossRef]
  16. Braunlich, K.; Seger, C.A.; Jentink, K.G.; Buard, I.; Kluger, B.M.; Thaut, M.H. Rhythmic auditory cues shape neural network recruitment in Parkinson’s disease during repetitive motor behavior. Eur. J. Neurosci. 2019, 49, 849–858. [Google Scholar] [CrossRef] [PubMed]
  17. Chen, C.; Hu, Z.; Liu, S.; Tseng, H. Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opin. Biol. Ther. 2012, 12, 593–608. [Google Scholar] [CrossRef]
  18. Chen, C. The citespace manual. Coll. Comput. Inform. 2014, 1, 1–84. [Google Scholar]
  19. Liang, Y.D.; Li, Y.; Zhao, J.; Wang, X.Y.; Zhu, H.Z.; Chen, X.H. Study of acupuncture for low back pain in recent 20 years: A bibliometric analysis via CiteSpace. J. Pain Res. 2017, 10, 951. [Google Scholar] [CrossRef] [Green Version]
  20. Miao, Y.; Liu, R.; Pu, Y.; Yin, L. Trends in esophageal and esophagogastric junction cancer research from 2007 to 2016: A bibliometric analysis. Medicine 2017, 96, e6924. [Google Scholar] [CrossRef]
  21. Grahn, J.A.; Brett, M. Rhythm and beat perception in motor areas of the brain. J. Cogn. Neurosci. 2007, 19, 893–906. [Google Scholar] [CrossRef] [Green Version]
  22. Luft, A.R.; McCombe-Waller, S.; Whitall, J.; Forrester, L.W.; Macko, R.; Sorkin, J.D.; Schulz, J.B.; Goldberg, A.P.; Hanley, D.F. Repetitive bilateral arm training and motor cortex activation in chronic stroke: A randomized con-trolled trial. JAMA 2004, 292, 1853–1861. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Ngo, H.V.V.; Martinetz, T.; Born, J.; Mölle, M. Auditory Closed-Loop Stimulation of the Sleep Slow Oscillation Enhances Memory. Neuron 2013, 78, 545–553. [Google Scholar] [CrossRef] [PubMed]
  24. Fujioka, T.; Trainor, L.J.; Large, E.W.; Ross, B. Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillations. J. Neurosci. 2012, 32, 1791–1802. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Bachlin, M.; Plotnik, M.; Roggen, D.; Maidan, I.; Hausdorff, J.M.; Giladi, N.; Troster, G. Wearable assistant for Parkinson’s disease patients with the freezing of gait symptom. IEEE Trans. Inf. Technol. Biomed. 2009, 14, 436–446. [Google Scholar] [CrossRef]
  26. Hausdorff, J.M.; Lowenthal, J.; Herman, T.; Gruendlinger, L.; Peretz, C.; Giladi, N. Rhythmic auditory stimulation modulates gait variability in Parkinson’s disease. Eur. J. Neurosci. 2007, 26, 2369–2375. [Google Scholar] [CrossRef]
  27. Thaut, M.H.; Leins, A.K.; Rice, R.R.; Argstatter, H.; Kenyon, G.P.; McIntosh, G.C.; Bolay, H.V.; Fetter, M. Rhythmic auditor y stimulation improves gait more than NDT/Bobath training in near-ambulatory patients early poststroke: A single-blind, randomized trial. Neurorehabilit. Neural Repair 2007, 21, 455–459. [Google Scholar] [CrossRef]
  28. Vuust, P.; Pallesen, K.J.; Bailey CVan Zuijen Tl Gjedde, A.; Roepstorff, A.; Stergaard, L. To musicians, the message is in the meter: Pre-attentive neuronal responses to incongruent rhythm are left-lateralized in musicians. NeuroImage 2005, 24, 560–564. [Google Scholar] [CrossRef]
  29. Kim, T.; Thankachan, S.; McKenna, J.T.; McNally, J.M.; Yang, C.; Choi, J.H.; Chen, L.; Kocsis, B.; Deisseroth, K.; Strecker, R.E.; et al. Cortically projecting basal forebrain parvalbumin neurons regulate cortical gamma band oscillations. Proc. Natl. Acad. Sci. USA 2015, 112, 3535–3540. [Google Scholar] [CrossRef] [Green Version]
  30. Corriveau, K.H.; Goswami, U. Rhythmic motor entrainment in children with speech and language impairments: Tapping to the beat. Cortex 2009, 45, 119–130. [Google Scholar] [CrossRef] [PubMed]
  31. Morillon, B.; Baillet, S. Motor origin of temporal predictions in auditory attention. Proc. Natl. Acad. Sci. USA 2017, 114, E8913–E8921. [Google Scholar] [CrossRef] [Green Version]
  32. Ghai, S.; Ghai, I.; Schmitz, G.; Effenberg, A.O. Effect of rhythmic auditory cueing on parkinsonian gait: A systematic review and meta-analysis. Sci. Rep. 2018, 8, 506. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Wagner, J.; Makeig, S.; Gola, M.; Neuper, C.; Müller-Putz, G. Distinct β band oscillatory networks subserving motor and cognitive control during gait adaptation. J. Neurosci. 2016, 36, 2212–2226. [Google Scholar] [CrossRef] [PubMed]
  34. Albouy, P.; Weiss, A.; Baillet, S.; Zatorre, R.J. Selective entrainment of theta oscillations in the dorsal stream causally enhances auditory working memory performance. Neuron 2017, 94, 193–206. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Bella, S.D.; Benoit, C.E.; Farrugia, N.; Keller, P.E.; Obrig, H.; Mainka, S.; Kotz, S.A. Gait improvement via rhythmic stimulation in Parkinson’s disease is linked to rhythmic skills. Sci. Rep. 2017, 7, 42005. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Zoefel, B.; VanRullen, R. EEG oscillations entrain their phase to high-level features of speech sound. Neuroimage 2016, 124, 16–23. [Google Scholar] [CrossRef] [PubMed]
  37. Habib, M.; Lardy, C.; Desiles, T.; Commeiras, C.; Chobert, J.; Besson, M. Music and dyslexia: A new musical training method to improve reading and related disorders. Front. Psychol. 2016, 7, 26. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Morillon, B.; Schroeder, C.E.; Wyart, V.; Arnal, L.H. Temporal prediction in lieu of periodic stimulation. J. Neurosci. 2016, 36, 2342–2347. [Google Scholar] [CrossRef] [Green Version]
  39. Effenberg, A.O.; Fehse, U.; Schmitz, G.; Krueger, B.; Mechling, H. Movement sonification: Effects on motor learning beyond rhythmic adjustments. Front. Neurosci. 2016, 10, 219. [Google Scholar] [CrossRef] [Green Version]
  40. Doelling, K.B.; Assaneo, M.F.; Bevilacqua, D.; Pesaran, B.; Poeppel, D. An oscillator model better predicts cortical entrainment to music. Proc. Natl. Acad. Sci. USA 2019, 116, 10113–10121. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Ripollés, P.; Rojo, N.; Grau-Sánchez, J.; Amengual, J.L.; Càmara, E.; Marco-Pallarés, J.; Juncadella, M.; Vaquero, L.; Rubio, F.; Duarte, E.; et al. Music supported therapy promotes motor plasticity in individuals with chronic stroke. Brain Imaging Behav. 2016, 10, 1289–1307. [Google Scholar] [CrossRef]
  42. Chen, C.; Dubin, R.; Kim, M.C. Orphan drugs and rare diseases: A scientometric review (2000–2014). Expert Opin. Orphan Drugs 2014, 2, 709–724. [Google Scholar] [CrossRef]
  43. Calabrò, R.S.; Naro, A.; Filoni, S.; Pullia, M.; Billeri, L.; Tomasello, P.; Portaro, S.; Di Lorenzo, G.; Tomaino, C.; Bramanti, P. Walking to your right music: A randomized controlled trial on the novel use of treadmill plus music in Parkinson’s disease. J. Neuroeng. Rehabil. 2019, 16, 68. [Google Scholar] [CrossRef] [PubMed]
  44. Murgia, M.; Pili, R.; Corona, F.; Sors, F.; Agostini, T.A.; Bernardis, P.; Casula, C.; Cossu, G.; Guicciardi, M.; Pau, M. The use of footstep sounds as rhythmic auditory stimulation for gait rehabilitation in Parkinson’s disease: A randomized controlled trial. Front. Neurol. 2018, 9, 348. [Google Scholar] [CrossRef] [PubMed]
  45. Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2010 (GBD 2010) Results; Institute for Health Metrics and Evaluation: Seattle, WA, USA, 2012. [Google Scholar]
  46. Feigin, V.L.; Nichols, E.; Alam, T.; Bannick, M.S.; Beghi, E.; Blake, N.; Culpepper, W.J.; Dorsey, E.R.; Elbaz, A.; Ellenbogen, R.G.; et al. Global, regional, and national burden of neurological disorders, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019, 18, 459–480. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Lozano, R.; Naghavi, M.; Foreman, K.; Lim, S.; Shibuya, K.; Aboyans, V.; Abraham, J.; Adair, T.; Aggarwal, R.; Ahn, S.Y.; et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012, 380, 2095–2128. [Google Scholar] [CrossRef]
  48. Vos, T.; Flaxman, A.D.; Naghavi, M.; Lozano, R.; Michaud, C.; Ezzati, M.; Shibuya, K.; Salomon, J.A.; Abdalla, S.; Aboyans, V.; et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012, 380, 2163–2196. [Google Scholar] [CrossRef]
  49. Whiteford, H.A.; Ferrari, A.J.; Degenhardt, L.; Feigin, V.; Vos, T. The global burden of mental, neurological and substance use disorders: An analysis from the Global Burden of Disease Study 2010. PLoS ONE 2015, 10, e0116820. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. López-Ortiz, C.; Gaebler-Spira, D.J.; Mckeeman, S.N.; Mcnish, R.N.; Green, D. Dance and rehabilitation in cerebral palsy: A systematic search and review. Dev. Med. Child Neurol. 2019, 61, 393–398. [Google Scholar] [CrossRef] [Green Version]
  51. Silverman, F.H. The Effect of Rhythmic Auditory Stimulation on the Disfluency of Nonstutterers. J. Speech Hear. Res. 1971, 14, 350–355. [Google Scholar] [CrossRef]
  52. Ouyang, W.; Wang, Y.; Lin, C.; He, M.; Hao, F.; Liu, H.; Zhu, W. Heavy metal loss from agricultural watershed to aquatic system: A scientometrics review. Sci. Total Environ. 2018, 637–638, 208–220. [Google Scholar] [CrossRef]
  53. Pfeiffer, K.; Clements, J.; Smith, M.; Gregoire, M.; Conti, C. Does rhythmic auditory stimulation compared to no rhythmic auditory stimulation improve patient’s static and dynamic standing balance post stroke? Phys. Ther. Rev. 2019, 24, 216–222. [Google Scholar] [CrossRef]
  54. Suzuki, K.; Niitsu, M.; Kamo, T.; Otake, S.; Nishida, Y. Effect of exercise with rhythmic auditory stimulation on muscle coordination and gait stability in patients with diabetic peripheral neuropathy: A randomized controlled trial. Open J. Ther. Rehabil. 2019, 7, 79. [Google Scholar] [CrossRef]
  55. Park, J.; Chung, Y. The effects of robot-assisted gait training using virtual reality and auditory stimulation on balance and gait abilities in persons with stroke. NeuroRehabilitation 2018, 43, 227–235. [Google Scholar] [CrossRef] [PubMed]
  56. Hernandez, A.; Bronas, U.G.; Steffen, A.D.; Marquez, D.X.; Fritschi, C.; Quinn, L.T.; Collins, E.G. Rhythmic auditory stimulation increases 6-Minute walk distance in individuals with COPD: A repeated measures study. Heart Lung 2020, 49, 324–328. [Google Scholar] [CrossRef]
  57. Schwartz, A.E.; van Walsem, M.R.; Brean, A.; Frich, J.C. Therapeutic use of music, dance, and rhythmic auditory cueing for patients with Huntington’s disease: A systematic review. J. Huntingt. Dis. 2019, 8, 393–420. [Google Scholar] [CrossRef] [Green Version]
  58. Shahraki, M.; Sohrabi, M.; Torbati, H.T.; Nikkhah, K.; NaeimiKia, M. Effect of rhythmic auditory stimulation on gait kinematic parameters of patients with multiple sclerosis. J. Med. Life 2017, 10, 33. [Google Scholar]
  59. Toukhsati, S.; Rickard, N.S. Exposure to a rhythmic auditory stimulus facilitates memory formation for the passive avoidance task in the day-old chick. J. Comp. Psychol. 2001, 115, 132. [Google Scholar] [CrossRef]
  60. Fernández, A.; Maestu, F.; Campo, P.; Hornero, R.; Escudero, J.; Poch, J.J.A.E.P. Impact of auditory stimulation at a frequency of 5 Hz in verbal memory. Actas Esp. Psiquiatr. 2008, 36, 307–313. [Google Scholar]
  61. Lenc, T.; Keller, P.E.; Varlet, M.; Nozaradan, S. Neural tracking of the musical beat is enhanced by low-frequency sounds. Proc. Natl. Acad. Sci. USA 2018, 115, 8221–8226. [Google Scholar] [CrossRef] [Green Version]
  62. Colling, L.J.; Noble, H.L.; Goswami, U. Neural entrainment and sensorimotor synchronization to the beat in children with developmental dyslexia: An EEG study. Front. Neurosci. 2017, 11, 360. [Google Scholar] [CrossRef]
  63. Pecenka, N.; Engel, A.; Keller, P.E. Neural correlates of auditory temporal predictions during sensorimotor synchronization. Front. Hum. Neurosci. 2013, 7, 380. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Nozaradan, S.; Schwartze, M.; Obermeier, C.; Kotz, S.A. Specific contributions of basal ganglia and cerebellum to the neural tracking of rhythm. Cortex 2017, 95, 156–168. [Google Scholar] [CrossRef] [PubMed]
Ijerph 20 00215 g001 550
Figure 1. Number of publications and cumulative number of publications on rhythmic auditory stimulation publication. Alt text: A line graph plots the number of annual publications and cumulative number of publications among 2001–2020. A generally exponential growth is observed. A surge is observed in 2014.
Figure 1. Number of publications and cumulative number of publications on rhythmic auditory stimulation publication. Alt text: A line graph plots the number of annual publications and cumulative number of publications among 2001–2020. A generally exponential growth is observed. A surge is observed in 2014.
Ijerph 20 00215 g001
Ijerph 20 00215 g002 550
Figure 2. The top 10 most contributive countries within rhythmic auditory stimulation research. Alt text: A column graph demonstrates the ten most productive countries within rhythmic auditory stimulation research. The United States accounted for around 30% of total publications.
Figure 2. The top 10 most contributive countries within rhythmic auditory stimulation research. Alt text: A column graph demonstrates the ten most productive countries within rhythmic auditory stimulation research. The United States accounted for around 30% of total publications.
Ijerph 20 00215 g002
Ijerph 20 00215 g003 550
Figure 3. Country collaborations in rhythmic auditory stimulation research. Alt text: A network plot demonstrates the international collaborations within rhythmic auditory stimulation research. The United States has collaborated closely with most countries.
Figure 3. Country collaborations in rhythmic auditory stimulation research. Alt text: A network plot demonstrates the international collaborations within rhythmic auditory stimulation research. The United States has collaborated closely with most countries.
Ijerph 20 00215 g003
Ijerph 20 00215 g004 550
Figure 4. Visualization of the keywords co-occurrence analysis on rhythmic auditory stimulation research. Alt text: A clustering graph is plotting the research topics within rhythmic auditory stimulation research. There are three themes: motor dysfunction, cognition, and perception.
Figure 4. Visualization of the keywords co-occurrence analysis on rhythmic auditory stimulation research. Alt text: A clustering graph is plotting the research topics within rhythmic auditory stimulation research. There are three themes: motor dysfunction, cognition, and perception.
Ijerph 20 00215 g004
Ijerph 20 00215 g005 550
Figure 5. Keywords with the strongest citation bursts of publications on rhythmic auditory stimulation research. Alt text: The top 25 keywords with the strongest citation bursts of publications on rhythmic auditory stimulation research among 2011–2020. Working memory, tracking, and neural basis were the most recent three.
Figure 5. Keywords with the strongest citation bursts of publications on rhythmic auditory stimulation research. Alt text: The top 25 keywords with the strongest citation bursts of publications on rhythmic auditory stimulation research among 2011–2020. Working memory, tracking, and neural basis were the most recent three.
Ijerph 20 00215 g005
Ijerph 20 00215 g006 550
Figure 6. Top 10 most-focused diseases in rhythmic auditory stimulation research. Alt text: A bar chart demonstrates the ten most focused diseases within rhythmic auditory stimulation research between 2001–2020. Parkinson’s disease, stroke, and speech impairment received most attention for the 20 years.
Figure 6. Top 10 most-focused diseases in rhythmic auditory stimulation research. Alt text: A bar chart demonstrates the ten most focused diseases within rhythmic auditory stimulation research between 2001–2020. Parkinson’s disease, stroke, and speech impairment received most attention for the 20 years.
Ijerph 20 00215 g006
Table
Table 1. The top 10 journals that published articles on rhythmic auditory stimulation research.
Table 1. The top 10 journals that published articles on rhythmic auditory stimulation research.
SourcesNpIF 2020CategoryRegion
PLoS ONE323.240MultidisciplinaryUSA
Frontiers in Neuroscience204.677NeuroscienceSwitzerland
Experimental Brain Research161.972NeuroscienceGermany
Frontiers in Human Neuroscience163.169NeuroscienceSwitzerland
Human Movement Science162.161PsychologyThe Netherlands
Journal of Neuroscience166.167NeuroscienceUK
Neuroimage166.556NeuroimagingUSA
Frontiers in Neurology154.003NeuroscienceSwitzerland
European Journal of Neuroscience143.386NeuroscienceUK
Gait & Posture142.840RehabilitationIreland
Note. Np = number of publications.
Table
Table 2. The top 10 institutions of origin of rhythmic auditory stimulation research.
Table 2. The top 10 institutions of origin of rhythmic auditory stimulation research.
InstitutionCountryNpPublications, %
1University of TorontoCanada427.17%
2Colorado State UniversityUSA264.44%
2Radboud University NijmegenThe Netherlands264.44%
4University of CambridgeUK254.27%
5Northwestern UniversityUSA223.75%
5Washington UniversityUSA223.75%
7McMaster UniversityCanada213.58%
7University of MarylandUSA213.58%
9University of California IrvineUSA203.41%
10Max Planck Institute for Human Cognitive and Brain SciencesGermany183.07%
Note. Np = Number of publications.
Table
Table 3. Top 10 of most productive authors publishing on rhythmic auditory stimulation.
Table 3. Top 10 of most productive authors publishing on rhythmic auditory stimulation.
AuthorCountryNp
1.Goswami U.UK15
2.Thaut M.Canada13
3.Dalla-Bella S.Canada12
4.Nieuwboer A.Belgium10
5.Rochester L.UK10
6.Kotz S.Germany9
7Trainor L.Canada9
8.Grahn J.Canada8
9.Kwakkel G.The Netherlands8
10.Earhart G.USA7
Note. Np = Number of publications.
Table
Table 4. The top 10 most-cited articles during 2001–2020.
Table 4. The top 10 most-cited articles during 2001–2020.
PaperAutor(s)YearJournalDOI
1.Rhythm and beat perception in motor areas of the brainGrahn & Brett2007 [21]Journal of Cognitive Neuroscience10.1162/jocn.2007.19.5.893
2.Repetitive bilateral arm training and motor cortex activation in chronic stroke: A randomized controlled trialLuft et al.2004 [22]Journal of the American Medical Association10.1001/jama.292.15.1853
3.Auditory closed-loop stimulation of the sleep slow oscillation enhances memoryNgo et al.2013 [23]Neuron10.1016/j.neuron.2013.03.006
4.Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillationsFujioka et al.2012 [24]Journal of Neuroscience10.1523/jneurosci.4107-11.2012
5.Wearable assistant for Parkinson’s disease patients with the freezing of gait symptomBachlin et al.2010 [25]IEEE Transactions on Information Technology in Biomedicine10.1109/titb.2009.2036165
6.Rhythmic auditory stimulation modulates gait variability in Parkinson’s diseaseHausdorff et al.2007 [26]European Journal of Neuroscience10.1111/j.1460-9568.2007.05810.x
7Rhythmic auditory stimulation improves gait more than NDT/Bobath training in near-ambulatory patients early poststroke: A single-blind randomized trialThaut et al.2007 [27]Neurorehabilitation and Neural Repair10.1177/1545968307300523
8.To musicians, the message is in the meter: Pre-attentive neuronal responses to incongruent rhythm are left-lateralized in musiciansVuust et al.2005 [28]Neuroimage10.1016/j.neuroimage.2004.08.039
9.Cortically projecting basal forebrain parvalbumin neurons regulate cortical gamma band oscillationsKim et al.2015 [29]Proceedings of the National Academy of Sciences10.1073/pnas.1413625112
10.Rhythmic motor entrainment in children with speech and language impairments: Tapping to the beatCorriveau & Goswami2009 [30]Cortex10.1016/j.cortex.2007.09.008
Table
Table 5. The top 10 most-cited articles during 2016–2020.
Table 5. The top 10 most-cited articles during 2016–2020.
PaperAuthor(s)YearJournalDOI
1.Motor origin of temporal predictions in auditory attentionMorillon & Baillet2017 [31]Proceedings of the National Academy of Sciences10.1073/pnas.1705373114
2.Effect of rhythmic auditory cueing on parkinsonian gait: A systematic review and meta-analysisGhai et al.2018 [32]Scientific Reports10.1038/s41598-017-16232-5
3.Distinct β band oscillatory networks subserving motor and cognitive control during gait adaptationWagner et al.2016 [33]Journal of Neuroscience10.1523/JNEUROSCI.3543-15.2016
4.Selective entrainment of theta oscillations in the dorsal stream causally enhances auditory working memory performanceAlbouy et al.2017 [34]Neuron10.1016/j.neuron.2017.03.015
5.Gait improvement via rhythmic stimulation in Parkinson’s disease is linked to rhythmic skillsDalla-Bella et al.2017 [35]Scientific Reports10.1038/srep42005
6.EEG oscillations entrain their phase to high-level features of speech soundZoefel & Vanrullen2016 [36]Neuroimage10.1016/j.neuroimage.2015.08.054
7Music and dyslexia: A new musical training method to improve reading and related disordersHabib et al.2016 [37]Frontiers in Psychology10.3389/fpsyg.2016.00026
8.Temporal prediction in lieu of periodic stimulationMorillon et al.2016 [38]Journal of Neuroscience10.1523/JNEUROSCI.0836-15.2016
9.Movement sonification: Effects on motor learning beyond rhythmic adjustmentsEffenberg et al.2016 [39]Frontiers in Neuroscience10.3389/fnins.2016.00219
10.An oscillator model better predicts cortical entrainment to musicDoelling et al.2019 [40]Proceedings of the National Academy of Sciences10.1073/pnas.1816414116
Music supported therapy promotes motor plasticity in individuals with chronic strokeRipollés et al.2016 [41]Brain Imaging and Behavior10.1007/s11682-015-9498-x
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, M.; Li, F.; Wang, D.; Ba, X.; Liu, Z. Mapping Research Trends from 20 Years of Publications in Rhythmic Auditory Stimulation. Int. J. Environ. Res. Public Health 2023, 20, 215. https://doi.org/10.3390/ijerph20010215

AMA Style

Zhang M, Li F, Wang D, Ba X, Liu Z. Mapping Research Trends from 20 Years of Publications in Rhythmic Auditory Stimulation. International Journal of Environmental Research and Public Health. 2023; 20(1):215. https://doi.org/10.3390/ijerph20010215

Chicago/Turabian Style

Zhang, Meiqi, Fang Li, Dongyu Wang, Xiaohong Ba, and Zhan Liu. 2023. "Mapping Research Trends from 20 Years of Publications in Rhythmic Auditory Stimulation" International Journal of Environmental Research and Public Health 20, no. 1: 215. https://doi.org/10.3390/ijerph20010215

APA Style

Zhang, M., Li, F., Wang, D., Ba, X., & Liu, Z. (2023). Mapping Research Trends from 20 Years of Publications in Rhythmic Auditory Stimulation. International Journal of Environmental Research and Public Health, 20(1), 215. https://doi.org/10.3390/ijerph20010215

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop