Background
In young people, musical instrumental training triggers functional and structural brain plasticity and may enhance general cognitive and perceptual-motor function, explained by the widely distributed brain areas involved in music performance that support many other cognitive and perceptual-motor skills [
1‐
12]. Evidence accumulates that this also applies to healthy elderly, at least in the behavioral domain [
13‐
16].
We postulate showing advantages of music education for faculties generally acknowledged to decay during ordinary aging: executive functions, different types of memory, processing speed, language function, logical thinking, hearing in noise (auditory selective attention), manual dexterity, bimanual coordination, and to provoke functional and structural brain plasticity. Last but not least, we anticipate increased well-being. Optimal aging cannot be defined solely by objective factors such as mental performance and health, but also by subjective features such as quality of life [
17]. Intriguingly, these objective and subjective factors appear to be closely related (for a review see [
18]). The ultimate objective, if our study results confirm our hypotheses, is systematic implementation of government-funded musical practice facilities in elderly centers and nursing homes.
Whereas cross-sectional studies indicate a definite decrease for different cognitive functions from early adulthood onwards, longitudinal studies however only demonstrate marked deterioration for most functions after midlife. In the majority of healthy older adults, executive functions decline [
19,
20], and its sub-processes such as working memory updating, inhibition and task-switching (cognitive flexibility) all gradually deteriorate with age [
19]. Actually, decrease of working memory function, a fundamental component of general cognition, may explain several of the other higher order cognitive aging phenomena, like for instance deterioration of executive functions [
21,
22]. In a lifespan perspective however [
23‐
25], development during aging results from the combination of decline of certain physiological and cognitive functions, with the lifelong prospect of evolving through learning and interventions.
Brain aging in healthy elderly
Unraveling brain processes that underlie cognitive decline symptoms, and developing training regimens that stimulate neuroprotection mechanisms to delay or even reverse those symptoms, may represent a key to potential remedies [
19,
20]. Cognitive regression in healthy elderly people follows local structural and functional brain modifications such as reduction of prefrontal cortex and hippocampal gray matter (GM) and loss of anterior white matter integrity and functional connectivity [
26‐
29]. Global connectivity however, i.e. networks of long-range cortical fiber structural connections (white matter), and functional connections (as measured by resting state functional MRI (fMRI; functional Magnetic Resonance Imaging) carrying information flow dynamics throughout the whole brain [
30‐
32], critical for cognitive functioning, also becomes less performant in the aging brain.
Recently evidence accumulated that hippocampal function is vital to all types of relational memory, independently of the time span between learning and recollection [
33,
34]. Atrophy of the hippocampus, in general occurring in late adulthood [
19], provokes deterioration of working memory and long term memory, decrease of abstract thinking (fluid intelligence) [
35] and progressively increased risk for dementia [
36].
Cognitive activities and physical exercise -in addition to treatment of general medical conditions- may delay age-related atrophy in the hippocampus, or even expand its size [
36‐
38]. Musical practice can induce functional and structural plasticity in the anterior and middle part of the hippocampus, and these changes are accompanied by increased proficiency in musical tasks, working memory and fluid intelligence [
4,
39‐
41].
Therapies based on real life experiences, like musical practice, dancing or playing chess, more naturally induce far-reaching transfer of learning as they are complex and variable compared to laboratory training [
42,
43]. This illimited complexity allows progressive increase in difficulty, keeping learning challenging at all times. As these activities are pleasant for an average individual, they are intrinsically motivating and therefore easy to maintain over long periods of time, meanwhile increasing well-being.
Among a multitude of cognitive training research in the elderly, [
21,
22,
44‐
46], only two used piano or keyboard training [
13,
14], over periods of 6 and 4 months, in musically untrained healthy elderly between 60 and 85 years. In one study [
13] the piano group significantly improved in executive function and working memory, compared to a passive control group. Another more recent study [
14] also showed improved executive function and enhanced well-being, and also a trend for motor advantages, as compared to a control group performing other leisure activities. In yet another study in healthy elderly (mean age 77 years) 15 weeks of drumming and singing improved verbal and visual memory as compared to literature training [
16].
Musical training as a model for behavioral and cerebral plasticity
As musical performance relies on widely distributed brain areas involved in many other cognitive and perceptual-motor skills [
6,
7,
47‐
51], musical instrumental training provides a strong means of improving cognitive and perceptual-motor function provoking functional and structural brain changes. Most studies on brain and behavioral plasticity induced by musical practice concerned cross-sectional studies in young adults with differing levels of musical practice from childhood. Progressive music intrinsic and overall cognitive advantages in combination with widespread functional and structural brain plasticity occurred as a function of training intensity in auditory, limbic, perceptual-motor and higher order cognitive networks [
1,
3‐
6,
9,
11,
40,
52‐
58].
Brain areas most susceptible to age-related cognitive decay, in inferior frontal and temporal cortices and their interconnecting white matter tracts, are strongly involved in musical instrumental practice and share neural substrates with language functions [
7,
9,
47,
53,
55,
59,
60], working memory [
5,
7,
53,
55,
59,
60] and broad-spectrum cognitive function, including executive functions (see next sub-chapter) [
3‐
5,
55,
61]. A study comparing elderly mono- and dizygotic twins, of whom only one practiced music, demonstrated that musical instrumental practice, controlling for sex, education-level and physical activity, reduced the probability of dementia and other age related cognitive impairments [
62]. Overall, cognitive decline and dementia can be postponed by recent and past musical activities [
63,
64]. Music-supported therapy also proved effective in restoration of motor skills in elderly suffering from decline of motor function following stroke [
65,
66]. Increased gray matter in qualified musicians as compared to less proficient musicians or non-musicians could be consistently demonstrated in the inferior frontal cortex [
1,
3,
55,
67], the hippocampus [
4,
39,
40,
68], and the entorhinal cortex that projects to the hippocampus [
69]. Common age-related shrinking of inferior frontal cortices appeared absent in older male orchestra musicians [
67]. A recent review article acknowledges music training as a promising approach for age-related cognitive decline [
70]. Strikingly, even people practicing music moderately and exclusively during their childhood, experienced advantages for neural timing in speech perception at an advanced age [
71].
Far transfer effects in young and older people following music training
Far transfer effects for higher-order cognitive functioning following musical training occurred in adult musicians for verbal (auditory & visual modality) and tonal working memory [
4,
6,
58], verbal long-term memory [
72], executive control [
73,
74], fluid intelligence [
4,
75], visuo-spatial ability [
55,
63] and attention [
61]. Specifically in healthy elderly far transfer after musical training showed for executive function, attention, working memory, verbal and visual memory, sensorimotor function and subjective well-being [
13,
14,
16]. Musical practice sharpens auditory attention and hearing in noise in children, young and elderly adults [
61,
76,
77], both recurrent problems in normal aging. Perceptual-motor skills, that decline with advanced age, may also profit [
14] and interact with higher order cognitive functions [
78]. The triple auditory, visually and sensory feedback on the precision of motor performance yielded during musical practice may explain this observation.
Intervention studies provoking brain and behavioral changes in elderly and older adults
Not only were older adults (mean age 60 years) able to learn three-ball cascade juggling over 3 months, moreover their gray matter increased transiently in the left hippocampus, bilateral nucleus accumbens and associative visual areas, quite similarly as in young adults [
79]. Four weeks of video action gaming in elderly (60 to 85 years) modified frontal task related electroencephalography) and changes persisted after a 6 months delay [
80]. Aerobic training in elderly induced volume increase in the prefrontal cortex and anterior hippocampus after 6 to 12 months of training [
36,
81], and white matter integrity improved in frontal, temporal and parietal tracts [
29]. In mature adults (≈35–40 years of age), increase in volume of the posterior hippocampus occurred, after acquiring their taxi drivers license in London, thus learning by heart the map of the city [
82]. Piano tuners, also trained in advanced adulthood, showed volume increase in the anterior hippocampus and frontal operculum [
83]. Learning to read musical notation over 3 months induced specific effects on visuo-spatial skills and on the function of the fusiform gyrus and superior parietal areas in initially musically naïve adults [
84,
85]. Five-week musical training of adult musical novices sufficed to induce functional audio-motor (temporal-frontal) coupling, thus brain plasticity [
86‐
88]. Specifically in elderly, 4 to 6 months piano training enhanced executive functions and working memory, compared to control groups [
13,
14]. In another study involving healthy elderly, drumming and singing could improve verbal and visual memory [
16]. Moreover, learning a new skill engages neural plasticity more strongly in older adults [
89]. Also specifically in elderly, advantages of intensive new skill learning for memory function manifested [
90].
We conclude that piano training in elderly musical novices may induce functional and morphological brain plasticity in the auditory and prefrontal cortex, hippocampus and elsewhere in the brain, as well as in long- and short-range white matter tracts and functional connectivity, together with concomitant cognitive and sensorimotor advantages, even at an advanced age. Intensive music listening and learning may already provoke a subset of these cognitive advantages.
Although decline of certain physiological and cognitive functions during aging is inevitable, brain and behavior remain plastic from cradle to grave. Therefore, lifelong education for seniors should become a significant policy focus in the framework of population ageing [
79].
Methods / design
For the sake of clarity and brevity, a great deal of comprehensive information concerning Methods and Design, is provided in the Tables:
Table 1: Trial Registration Data Set (according to WHO guidelines), p. 6
Table 2: Prescreening procedure in order to verify inclusion/exclusion criteria, p. 8
Table 3: Documents: information & consent forms, agreements, p. 9
Table 4: Behavioral Test Battery (psychometric tests), p. 10
Table 5: (f)MRI measurements, p. 11
Table 6: Study procedure with timelines, p. 12
List of Abbreviations, p. 15
Table 1
Trial Registration Data Set (according to WHO guidelines)
Primary registry and trial identifying number | |
Date of registration in primary registry | 17.09.2018 |
Secondary identifying numbers | Study ID number: 81185 |
Source(s) of monetary or material support | Swiss National Science Foundation (SNSF no. 100019E-170,410) and Deutsche Forschungsgemeinschaft (DFG no.323965454) |
Primary sponsor | SNSF and DFG: Lead Agency grant (two-countries study) |
Contact for public and scientific queries | Prof. Clara E. James: clara.james@hesge.ch |
Title | Train the Brain With Music: Brain Plasticity and Cognitive Benefits Induced by Musical Practice in Elderly People in Germany and Switzerland (TBM) |
Countries of recruitment | Switzerland, Germany |
Health condition(s) or problem(s) studied | Age-related cognitive decline |
Intervention(s) | Experimental group: intensive piano learning over 1 year |
Active control group: musical culture learning over 1 year (history and listening) |
Key inclusion and exclusion criteria | Ages eligible for study: 64 to 78 years Sexes eligible for study: both, Accepts healthy volunteers: only |
Inclusion criteria: Healthy right-handed volunteers, between 64 and 78 years of age, native French/German speakers. No regular musical practice over the lifespan. Only retired individuals may participate. |
Exclusion criteria: Impaired/not-corrected auditory or visual accuracy, neurological diseases in the present or the past, cardiovascular diseases, excessive hypertension, obesity, diabetes mellitus, beginning dementia, mild cognitive impairment, clinical depression |
Study type | Interventional |
Allocation: randomized intervention model according to 4 stratification factors (age, gender, score at the COGTEL (global cognition test) and socioeconomic status). Groups are balanced for those factors. Single blind study (subject) |
Primary purpose: prevention of cognitive and sensorimotor decline in retired elderly |
Date of first enrolment | May 2018 |
Target sample size | 150 |
Recruitment status | Completed |
Primary outcome(s) | Positive transfer effects from intensive piano training (intervention group) - as compared to listening and learning about music without practice (control group) - on age-related cognitive decline: for working memory, executive functions, speed of information processing, auditory selective attention (hearing in noise) and abstract thinking. Associated functional and structural brain plasticity may show in gray and white matter in temporal (medial and lateral), prefrontal and parietal areas. Less decline or increase of gray matter volume and activation change may show in the hippocampus, as well as improved functional networking in frontal areas during working memory tasks. |
Key secondary outcomes | Benefits of fine perceptual-motor skills may also manifest in the intervention group as compared to the control group associated with functional and structural brain plasticity in sensorimotor areas. Subjective quality of life, verbal memory and hearing in noise may improve in both groups, the latter two associated with functional and structural brain plasticity in auditory and frontal areas. Epigenetic alterations may be induced by piano learning in relation with functional and structural imaging parameters. |
Research hypothesis
We intend exhibiting for the first time that musical activities, particularly musical instrumental practice, can countervail cognitive and perceptual-motor decline supported by functional and structural brain plasticity.
Aims and objectives of the study
Our long-term aim is to promote healthy mental aging in elderly and therefore independence, autonomy and well-being through musical activities, specifically musical instrumental training of a complex instrument.
The preparatory phase of our study consisted in developing distinct musical interventions specifically designed for musically naive elderly aiming to support cognitive and sensorimotor development. Our study objective is investigating whether piano practice (intervention group) over one full year, as compared to listening and learning about music without practice (active control group), can provoke multiple far transfer effects on working memory, executive functions, speed of information processing, auditory selective attention (hearing in noise), abstract thinking, manual dexterity and bimanual coordination, all of which are strongly involved in piano practice and most relevant for independence and autonomy in everyday life. In association with these behavioral benefits we anticipate functional and structural brain plasticity in temporal (medial and lateral), prefrontal and parietal areas and the basal ganglia. We foresee potential benefits in both groups for verbal memory, hearing in noise and well-being, with more moderate cerebral plasticity in prefrontal, auditory and emotion regulation areas.
The ultimate goal, if our study results confirm our hypotheses, is systematic implementation of government-funded musical practice facilities in activity centers for elderly and nursing homes.
Design
The study is a two-site Hannover-Geneva longitudinal randomized single blind intervention study in altogether ~ 155 retired healthy elderly (64–78) years, (63 in Geneva, 92 in Hannover, selected according to our inclusion/exclusion criteria out of ~ 500 applications), divided into 2 parallel groups, offering either piano training (intervention group) or musical sensitization training (active control group), both provided by professional musicians.
The active control group serves to control for music listening of similar styles, acquiring general knowledge, social interaction, attentional aspects, weekly instruction away from home, and daily homework.
All participants were informed before enrolling that the study aim is to compare two distinct music interventions and that both may have positive impact on cognitive functioning and brain plasticity (single blind procedure).
In order to prevent strong inhomogeneity between the groups, we use a blocked (“stratified”) randomized design, in order to prevent strong inhomogeneity between the groups at baseline. Stratification involved the factors age, gender, score at the COGTEL
1 [
95,
97] and socioeconomic status. After recruiting all participants, we applied a clustering procedure, separately at each site, to obtain the closest pairs of participants based on the stratification factors. We transformed the latter to z-scores and computed the Euclidian distance between participants, and finally, an algorithm attributed randomly 1 participant of each pair to each group. So, half of the participants ended up in the intervention group, and the other half in the control group at both sites.
Over 12 months participants receive weekly training for 1 hour (we aim at providing 40 courses over the 12 months, adapting to the holidays of the seniors), and also exercise at home for ~ 30 min per day. Participants committed not to miss more than maximum 8 courses on the full curriculum. Both groups study similar different music styles (classical music, world music, jazz, etc.). Subjects will be tested at 4 time points (0, 6, 12 months, and post-training at 18 months) on cognitive, perceptual and motor abilities (Behavioral Test Battery; Table
4), as well as via wide-ranging functional and structural neuroimaging assessments (Table
5).
Our research is inspired by Bugos and colleagues [
13], but uses an extended methodology: 1) an active (vs passive) control group also learning music, 2) longer training (12 vs 6 months), 3) a narrower age bracket (64–78 vs 60–85 years of age), 4) extensive inclusion and exclusion criteria (for instance no prior musical education for more than 6 months (vs 5 years), 5) no major health problems, 6) a greater number of participants (150 vs 31), thus increased statistical power, and 7) more comprehensive psychometric testing involving cognitive, auditory, musical, sensorimotor and well-being measures. In addition, our study includes 8) comprehensive demographic, cognitive reserve index, sport leisure activities, well-being and food frequency questionnaires, as well as 9) multimodal (f)MRI brain imaging. Then 10) we also apply blood sampling, in order to perform genetic and epigenetic analyses with respect to music training and learning. Finally, 11) the piano groups will be trained in dyads, as group interaction is supposed to be specifically effective for learning in older adults [
113].
Setting
In Geneva (GE) all music courses and passage of the behavioral test battery take place at the Geneva School of Health Sciences (Haute Ecole de Santé de Genève (HEdS-GE) of the University of Applied Sciences and Arts Western Switzerland (HES-SO)). In Hannover (HA), Germany, music courses and passage of the behavioral test battery take place at the Hannover University of Music Drama and Media (HMTMH: Hochschule für Musik, Theater und Medien Hannover), and its Institute for Music Physiology and Musicians’ Medecine (IMMM: Institut für Musikphysiologie und Musikermedizin).
Professional musicians provide the music lessons, some of which are finishing their Master studies at the Geneva University of Music (Haute Ecole de Musique de Genève, HEM-GE) or at the HMTMH, but all already possess a Bachelor degree. Others are already established music/piano teachers and performers with a recently obtained Master’s degree. All music teachers possess several years of teaching experience prior to our study and were prepared to teach our specific population of elderly under the supervision of a team of music education specialists: Prof. Thomas Bolliger of the HEM-GE, and Prof. Wolfgang Zill and Prof. Andrea Welte in Hannover (HMTMH), who worked out a workflow together for both courses.
In Geneva, all brain imaging (MRI) is performed at the BBL, the Brain and Behavior Laboratory of the Geneva University. In Hannover all brain imaging takes place at the Hannover Medical school.
Registered nurses perform the blood sampling, in Geneva they are collaborators of the Geneva School of Health Sciences and in Hannover of the Hannover Medical School. Participants may refuse the blood sampling.
Participants
The following criteria were verified by means of initial phone calls, a comprehensive demographic questionnaire, questionnaires on musical activities, tests on major hearing impairment, tests on cognitive functioning and clinical depression. A comprehensive list of all (pre) screening tests, that ensured the criteria were met, can be found in Table
2.
Table 2
Prescreening procedure in order to verify inclusion/exclusion criteria
First contact | Telephone call; decision to proceed to Pre-screening Step 1 | Age – gender – musical history – general health – native language – retirement – MRI compatibility – overall availability – contact information |
PRE-SCREENING STEP 1 |
Demographic questionnaireb | Send/receive by post | In-house questionnaire, detailed information on languages; handedness; physical capability to come to the courses; health: hospitalizations (causes), locomotion, vision (correction), audition (hearing aids), height & weightc, sleep quality; cardiovascular & neurological diseases, hypertension, diabetes, arthrosis, arthritis, rheumatism, bone fractures, thyroid problems, memory problems, other health problems; consent yes/no to contact the family doctor in case of fortuitous findings; smoking habits over the lifespan; alcohol consumption over the lifespan; present medication; other drug use, remarks; sociodemographic information: age, gender, nationality, civil status, siblings, children, highest level of education (5 categories), main professional engagements, gross monthly household incomed (5 categories); MRI compatibility: claustrophobia, implants; Interest for the study: motivation |
Food Frequency Questionnaire FFQ e [ 91] | Send/receive by post | Detailed information on food consumption (quality and quantity) over the last 4 weeks |
Music questionnaires | Send/receive by post | Musical history (in-house questionnaire; GEMMI lab): amount and intensity of music listening and extracurricular music training: solfege/theory, instrumental training, choir singing, intracurricular music training in school Goldsmiths Musical Sophistication Index (GOLD MSI): self-report inventory and test battery for individual differences in musical sophistication (ability to engage with music) [ 92] |
Godin-Shephard leisure-time physical activity questionnaire [ 93] | Send/receive by post | Adapted to cover different parts of life (2–25 y.o., last 5 years and last year) |
In-house questionnaire on stressful life events | Send/receive by post | Self-report inventory on stressful events that may influence cognitive functioning, covering 6 time periods (12–25 y.o., 25–55 y.o, 55–64 y.o.; last 10 years, 5 years and year; GEMMI lab) |
Geriatric Depression Scale f [ 94] | Send/receive by post | Short version. Check for clinical depression |
PRE-SCREENING STEP 2 |
First laboratory visit - Basic clinical finger snap audition test - Psychometric tests i. Right-handedness | Verify /complete questionnaires of Step 1 Pass 3 psychometric tests | Check for major hearing impairmentg Pass the Edinburgh Handedness Inventory (revised) to check for right handedness [ 96]; Measure gross overall cognitive level and check for potential (mild) cognitive decline (COGTEL) |
Inclusion Criteria: good overall health; between 64 and 78 years of age; native or fluent French or German speakers; right-handed (for brain organizational reasons [
114]); no regular musical practice over the lifespan (< 6 months); retirement.
Exclusion criteria: impaired/not-corrected auditory or visual accuracy; neurological diseases in the present or the past; mild cognitive impairment or beginning dementia (assured via the COGTEL score); cardiovascular diseases; excessive hypertension; obesity; diabetes mellitus; clinical depression; MRI incompatibility (f.i. implants or claustrophobia). Concomitant musical training during the study is prohibited (see Trust Agreement; Table
3).
In Geneva, Professor Giovanni Frisoni of the Medical Faculty of the University of Geneva, neurologist, specialist in the field of dementia, agreed to consult us and to receive participants showing signs of risk of mild cognitive impairment. In addition, Dr. Philippe Schaller, medical doctor, Head of Cité Générations, specialist in chronic diseases, agreed to consult us concerning general health issues of our elderly population.
In Hannover, Prof Eckart Altenmüller (neurologist) and Prof. Tillmann Krüger (medical doctor specialized in geriatric medicine and psychiatry), investigators on the study, will cover these issues.
Different documents: information & consent forms and agreements, were read and or signed by our participants, they are listed in Table
3.
Table 3
Documents: information & consent forms, agreements
Information on the study | During presentations; via flyers; “participant information form” (distributed or sent by post or mail) | Objectives of the study; Information on the inclusion/exclusion criteria; information on procedures and timelines; announcement of randomization within two different groups of music education; information on measurements and their frequency (n = 4): MRI, behavioral testing and blood sampling; information of reimbursing of travel expenses; telephone numbers and mails of the research team | Answer questions during presentations or by mail or telephone and during first lab visit | Research team |
Declaration of informed consent | After inclusion in the study (following the 2 pre-screening steps see Table 2) | Consent to voluntary participate to the study with the right to withdraw at any time; accept the use of data for scientific and educational purposes, with assurance that the data will remain anonymous; to yes/no accept blood sampling (NOT an exclusion criterion); who to inform in case of potential unexpected detection of anomalies. | Read & Sign | Participant & member research team |
Trust agreement | Before the courses start | The participant declares aiming to perform homework at least 30 min per day, 5 times per week, not to miss more than maximum 8 courses (on 40 in total), and announce absences and holidays well in advance with reasons and not to engage in any supplementary musical education | Read & Sign | Participant & member research team |
MRI safety questionnaire | Before MRI measurements | Questions assuring MRI compatibility | Read & Sign | Participant & MRI operator |
Debriefing on the fMRI task | After MRI measurements | Answer questions on sound perception, comprehension of the task, rating of difficulty of different experimental conditions, used strategies to perform the task, remarks | Read, answer questions | Participant & member research team |
Homework questionnaire | 3, 6, 9 & 12 months after the beginning of the music interventions | Time per day and per week spent on homework on average | Read and -sign | Participant |
Consent to voluntary participate to the study involved: the right to withdraw at any time, accepting the use of the collected data for scientific and educational purposes –with the assurance that the data will remain anonymous-, to accept blood sampling or not -on a voluntary basis- and finally, whether to inform the participant or his or her treating physician in the event of unexpected potential detection of abnormalities.
Interventions
Music interventions
Intervention group: piano courses
Courses take place in dyads (2 participants together). Three Yamaha keybords P-45 B
2 are set up in the classroom, with height adaptable piano stools. A Yamaha keybord P-45 B and a height adaptable piano stool are provided to each participant for use at home. During the courses the teacher sits in the middle, and in the beginning imitation and listening exercises are performed. Most of them are playful and allow the participants to familiarize themselves with the keyboard and adopt a correct and relaxed body posture. Clapping and singing or even walking within a certain rhythm are part of the lessons. Progressively music reading is introduced using a method specifically developed for our elderly population based on Jens Schlichting “Piano Prima Vista” (Internote GmbH Musikverlag 2013), and the Hall Leonard piano method for adults (ISBN: 9789043134378 & 9789043152037). Both methods exist in German and French. This material is enriched by different other pieces out of different textbooks (“A dozen a Day volume 1 (ISBN 9780711954311); Bastien Piano Basics - Piano Level 1 (ISBN-10: 0849752663; Manfred Schmitz Jugend-album für Klavier (ISBN: 978-3-932587-41-2), etc.), and sometimes by transcriptions of a favorite piece of one of the participants, arranged by the music teachers. Individual instruction is alternated with playing together, accompanied by the teachers. Sometimes one participant plays the right-hand part, while the other plays the left and vice versa. Homework includes practicing the exercises, the pieces and also occasionally composing music to perform during the course. A certain choice is left to the participants concerning the repertoire. Some improvisation is also introduced in association with basic notions of tonality and chords. The relationship between the teachers and the participants is informal.
Control group: musical culture3
Courses take place in groups of 4 to 6 individuals in order to create a stimulating environment. Lessons involve learning about the timbre and functioning of different musical instruments, music history, learning about composers, styles, etc. Presented music includes medieval, renaissance, classical, romantic and also modern classical repertoire, comprising orchestra and chamber music, opera, but also world music of all 4 continents and other styles (for instance music from the south Americas, jazz, pop, funk, etc.). During the highly interactive courses, the teacher explains the structure of the pieces, the role of the different instruments and voices and affective aspects of the pieces and develops a structured way of listening (“auditory analysis”) among the participants. During the lessons music related vocabulary may be written down, reassembling those terminologies in a notebook is part of the homework. Each week a voluntary participant presents music of his/her choice. The support material consists of extracts from textbooks, internet pages, documentaries, radio broadcasts, and presentations (f.i. “TED talks”,
ted.com) and links for listening mainly of YouTube videos and audio material. Internet links and other materials for the upcoming course are provided in the week preceding the lessons. Homework involves resuming the course, listening to different musical pieces, reading texts and preparing presentations. Participants are continuously encouraged to express why he/she appreciates, or not, particular pieces or styles of music.
Measurements and procedures
Subjects will be tested at 4 time points (t0: baseline, t1: after 6 months, t2: after training completion (12 months), t3: 6 months after training completion (18 months)) on 1) cognitive, perceptual and sensorimotor abilities by means of a battery of psychometric tests (Table
4) as well as via 2) wide-ranging functional and structural neuroimaging data (Magnetic Resonance Imaging MRI; see Table
5 and 3) Blood sampling.
Table 4
Behavioral Battery (psychometric tests) (measured at all 4 time points: t0: baseline; t1: 6 months; t2: 12 months & t3: 18 months)
BASIC COGNITION |
Processing speed & Attention | Digit-symbol | WAIS-IV, Wechsler, 2011 [ 98] |
Short term memory | Forward Digit Span | WAIS IV, Wechsler, 2011 |
| Backward Digit Span | WAIS IV, Wechsler, 2011 |
EXECUTIVE CONTROL |
- Shifting | Number switch | |
| Perceptual switch + Prospective Memory | Zuber et al., 2016 |
- Inhibition | GoDigit -NoGo | |
| Stop-Signal Task | Enge et al., 2014 |
FLUID INTELLIGENCE |
Logical reasoning | Matrices test | WAIS IV, Wechsler, 2011 |
KNOWLEDGE |
Episodic memory | Rey Auditory Verbal Learning Test | Bean, 2011 [ 101]; Rey, 1964 [ 102]; Helmstaedter et al., 2001 [ 103] |
MUSIC COGNITION |
Musical aptitude | GOLD MSI (melody, rhythm) Harmony test (“Pietri”) | Oechslin et al., 2013 [ 5] |
AUDITIVE COGNITION |
Speech-in-noise perception | International Matrix Test (Oldenburg) | Kollmeier et al., 2015 [ 104] |
PERCEPTUAL MOTOR SKILL |
Visuo-manual aptitude | Purdue Pegboard | Tiffin and Asher, 1948 [ 105] |
Scale playing on keyboard | Scale analysis | Jabusch et al., 2004 [ 106] |
OTHER |
WHOQOL-BREFa | Well-being | WHO, 2014b |
Physical Activity Scale for Elderly | PASE (last two weeks activities) | |
Psychometric testing
A complete list of the psychometric tests is provided in Table
4.
Test-retest effects4
Test-retest effects are in principle corrected for by the existence of a control group.
However, most tests are modified from time point to time point, by
-
Using different test material (stimuli) at each time point (COGTEL, Matrices test; Rey Auditory Verbal Learning Test, Harmony test (“Pietri”); GOLD MSI, International Matrix Test)
-
Changing the order of the stimuli (Number Switch, Perceptual switch + Prospective Memory, Go-NoGo, Stop-Signal Task).
Only the tests: Digit-symbol and Digit Span forward and backward, and the sensorimotor tests Purdue Pegboard and Scale Analysis are repeated with an identical format at all time points. The questionnaire WHOQOL-BREF on subjective well-being is also repeated in identical format.
Finally, within time-points, the order of the tests is pseudo-randomized between individuals (as well as the lists of words in the International Matrix Tests).
(f)MRI measurements
Nota bene: the MRI measurements will not require any special preparation (such as having to drink or be injected with contrast materials or radioactive dye).
In Geneva the MRI measurements are performed on the imaging platform at the Brain and Behaviour Laboratory and benefit from support of the technical staff (BBL,
http://bbl.unige.ch/), situated at the University Medical Centre of the University of Geneva, at close proximity to the HEdS-GE; with consent of the Director of the BBL, Patrik Vuilleumier, Full Professor at the Medical Faculty of the University of Geneva, neurologist and also Head of the Laboratory for Behavioral Neurology and Imaging of Cognition.
At both sites, 3 T Siemens scanners are used, however In Geneva acquisitions are performed on a 3 T whole body Siemens Trio system (Siemens TIM-TRIO, Erlangen, Germany) whereas In Hannover acquisitions are performed on a 3 T whole body Siemens Skyra system (Siemens MAGNETOM Skyra, Erlangen). At both sites, the scanners are equipped with an identical standard Siemens 32-channel head coil.
We adapted the sequences parameters, opting for a compromise between a good signal to noise ratio and a minimum amount of time. For the functional acquisitions, we adopted a multiband echo planar imaging fMRI with an accelerator factor of 3, allowing us to reduce the repetition time to 1.350 s which represents a good temporal resolution for fMRI (see Table
5). As a consequence of these choices, we could reduce the total duration of the MRI scanning to less than 1 hour, which is important given our elderly population.
The fact that 3 T Siemens scanners will be used at both sites already favors blending the data [
115]. However, the challenge was to end up with matching MRI sequence parameters at both sites, allowing to pool the data with a minimum of post-hoc adaptations. We managed to end up with identical sequence parameters (see Table
5). Nevertheless, in all analyses, a “scanner” covariate will be included in order to disentangle scanner-effect from effects-of-interest.
A complete list of the different MRI measurements (
n = 5) and main protocol parameters at both sites is provided in Table
5.
Table 5
MRIa measurements (measured at all 4 time points: t0: baseline; t1: 6 months; t2: 12 months & t3: 18 months)
Grey matter volume assessment [ 108] | MP2RAGEb; duration: 8.22 min; voxel size: 1 mm isotropic; 176 slices; FOVc: 256x240x176 mm; TRd/TEe: 5000/2.98 ms; TI1f/TI2g: 700/2500 ms; flip angle 1/2: 4/5 degrees |
Functional MRI Tonal working memory task [ 109] | EPIh; duration: 20.00 min; voxel size: 2.5 mm isotropic; 54 slices; FOV: 210x210x135 mm; multiband accelerator factor: 3; TR/TE: 1350/31.6 ms |
Resting state functional MRI Allows to measure activity in the Default Mode Network (DMN) reflecting global functional connectivity of the brain [ 110] | EPI; duration: 10.31 min; voxel size: 2.5 mm isotropic; 54 slices; FOV: 210x210x135 mm; multiband accelerator factor: 3; TR/TE: 1350/31.6 ms |
White matter assessment Allows to compute i.a. Fractional Anisotropy for evaluating white matter integrity reflecting structural connectivity [ 111]. | DTIi; duration 7.38 min; voxel size: 1.5 mm isotropic; 84 slices; FOV: 222x222x126 mm; multiband accelerator factor: 3; TR/TE: 5163/109.2 ms; b-values: 0/1500 s/mm2; 65 directions, anterior to posterior phase encoding direction followed by a reverse direction for distortion correction; b-values: 0/ s/mm2) |
Blood perfusion assessment [ 112] | ASLj; duration 6.10 min; voxel size: 2.5 × 2.5 × 3.0 mm; 36 slices; FOV: 220x220x129 mm; TR/TE: 3640/21.0 ms; flip angle: 90 degrees |
fMRI tonal working memory task
We use an in-scanner tonal working memory task (courtesy of Prof. Robert Zatorre and Dr. Philippe Albouy) [
109]. We added a control condition to the original task that now comprises 3 experimental conditions, which can be used later on in different combinations for the fMRI contrasts in the analyses.
In all 3 conditions, 2 pitch patterns of 3 beeps (sinus tones, with a certain tone frequency or pitch) are played via MRI compatible earphones, with a visual number code displayed on the computer screen in between the 2 pitch patterns. In all conditions, the participant responds by pressing one of two buttons on a response pad (left vs. right).
In the simple condition, 2 pitch patterns with 3 different pitches are played, thus forming kind of a melody, the first always followed by the visual number code 123 that represents the order of the notes of this first pitch pattern (1 for the 1rst note, 2 for the 2nd note and 3 for the 3rd note). The task of the participant is thus to respond whether the second pattern was identical to the first. If the order of the second pitch pattern is indeed identical, he/she should respond “correct” (left button). If the second pitch pattern is different (different order of the notes), they should respond “incorrect” (right button).
In the complex condition the trial sequence is the same, but the visual number code is never 123. It can be 321, 312, 132, 231 or 213 (all combinations except 123) meaning that there will be a specific change in the order of the notes between the first and the second pitch pattern. The task of the participant is to determine, whether the visual number code, that represents the manipulation of the order of the notes of the first pitch pattern, corresponds to the order of the notes of the second pattern. For instance if the tonal pattern is reversed, i.e. the notes are played in reversed order in the second pattern, and the visual number code provides the numbers 321, he/she should respond “correct” (left button), if the order of the notes of second pitch pattern does not correspond to the visual number code, they should respond “incorrect” (right button).
In the control condition participants listen to a pitch pattern consisting of 3 beeps of identical frequency/pitch, followed by a visual number code of 3 identical numbers, either 111, 222 or 333. They then receive an instruction on the computer screen whether they have to push the right or the left button of the response pad.
Bloodsampling
In addition, we collect one blood sample (10 ml) of each consenting participant (until now most people consented), close to each MRI measurement (t0, t1, t2, t3), for analyzing genotypes (only once) and methylation status (all times) of specific neuronal plasticity and learning related parameters (e.g. brain derived neurotrophic factor (BDNF), dopamine, sertonine, protein phosphatase 1, reelin and some others).
Procedures
A Flowchart of the study procedures with timelines is provided in Table
6.
Table 6
Study procedure with timelines
MONTH 1–3 | Preparatory phase | Recruitment of participants (n = ~ 70 in GE; n = ~ 100 in HA, on a total of ~ 500 applications) according to exclusion/exclusion criteria Detailed preparation of Behavioral Battery (psychometric testing) & (f)MRI protocols | Local journals/ elderly journals/ flyers/presentations HEdS-GE2 & IMMM3 BBL5 / HMS6 | Announcements (press & flyers) Presentations1/1rst check by telephone Creation of E-prime4 programs; preparation of paper and pencil tests; Synchronization of protocols between MRI scanners in Geneva and Hannover | |
Month 4 | | Piloting of (f)MRI protocols (N = 20) & Behavioral Battery (N = 10) on non-included elderly individuals | BBL / HEdS-GE / HMS / IMMM | Feasibility testing | |
| Pre-screening Step 1 | | At home | Send/receive (mail/post) | 60 min. |
Month 5–6 | Pre-screening Step 2 (N GE = 63, N HA = 92) | Check/completion of questionnaires of Step 1 Basic clinical audition test Psychometric tests i. Right-handedness ii. COGTEL | HEdS-GE/ IMMM | Come to HEdS-GE, IMMM 1x | 20 min. 2 min. 5 min. 15 min. |
After inclusion in the study |
Month 7–10 | | Recruitment and training of music teachers Preparing of music education materials | | | |
| t0/baseline | i. Behavioral Battery (psychometric testing) ii. (f)MRI measurements iii. Blood sampling (by registered nurse) | HEdS-GE / IMMM BBL / HMS HEdS-GE / IMMM | Come to HEdS-GE, IMMM 1x Come to BBL, HMS 1x Come to HEdS-GE, HMS 1x | 2.5 h7 1.5 h 10 min. |
Month 10–22 | Interventions | 12 months of 1 h weekly music courses & homework | HEdS-GE / IMMM At home | HEdS-GE / IMMM Practice daily at home | 1 h/week 5 × 30 min./week |
MONTH 16 | t1/ after 6 months of intervention | i. Behavioral Battery (psychometric testing) ii. (f)MRI measurements iii. Blood sampling | HEdS-GE / IMMM BBL / HMS HEdS-GE / HMS | Come to HEdS-GE, IMMS 1x Come to BBL, HMS 1x | 2.5 h 1.5 h 10 min. |
Month 22 | t2/directly after intervention completion | i. Behavioral Battery (psychometric testing) ii. COGTEL iii. (f)MRI measurements iv. Blood sampling v. Food Frequency Questionnaire vi. Cognitive reserve index1 (CRIq) 8 [ 116] | HEdS-GE / IMMM HEdS-GE / IMMM BB / HMS HEdS-GE / HMS At home HEdS-GE / IMMM | Come to HEdS-GE, IMMM 1x (same session as Behavioral Battery) Come to BBL, HMS 1x Come to HEdS-GE, HMS 1x Send (mail/post) Come to HEdS-GE, IMMM 1x | 2.5 h 15 min. 1.5 h 10 min. 30 min. 15 min. |
Month 23–26 | Cope with Delays, Analyses & Publications, Congress Attending |
Month 27 | t3/6 months after intervention completion | i. Behavioral Battery (psychometric testing) ii. (f)MRI measurements iii. Blood sampling | HEdS-GE / IMMM BBL / HMS HEdS-GE / HMS | Come to HEdS-GE, IMMM 1x Come to BBL, HMS 1x Come to HEdS-GE, HMS1x | 2.5 h 1.5 h 10 min. |
Month 28–36 | Cope with Delays, Analyses & Publications, Congress Attending |
Additional questionnaires
Progress measures
In order to evaluate the progress in both groups following training, we gather the following measures:
Data monitoring and quality assurance
At each site data acquisition and quality is constantly monitored by experimenters for each participant (Damien Marie and Laura Abdili in Geneva, Florian Worschech, Kristin Jünemann and Christopher Sinke in Hannover). Progress meetings (by Skype) are organized regularly between both sites. A second quality check is performed on the server where all data are backed up (see Declarations, Availability of data and materials, p. 16) and analyzed by Damien Marie (see Declarations p. 16). A third checkup is performed by an independant Data Manager (scientific collaborator at PhD level) both at the the HEdS-GE and the HMTMH, after each data point.
We will report reasons for withdrawal of individuals for each randomization group. Exact information on missing data at each time point will be reported in all publications. Missing data will be processed in the analyses with cutting edge means (for instance using the regularized iterative Principal Component Analysis (PCA) algorithm developed by Josse, Husson and Pagès (2009) [
117], implemented in the R package missMDA.
Statistical analyses
First, we will study cross-sectionally all relationships between behavior and brain data collected at baseline (data from t0) for all participants (1) based on a priori hypotheses using general linear models, correlations and regression analyses; (2) Using data-driven multivariate approaches that allow to reveal more intricate relationships between the data.
Brain data will mostly be analyzed using in-house script routines calling the last versions of the standard neuroimaging software pipelines (SPM12, FSL6, FreeSurfer, MRtrix etc.), all running on the same operating system on our server (Linux xfce4.12) to avoid any potential operating system bias [
118].
Second, we will examine and compare the development in both experimental groups over time (t0 vs. t1 vs. t2 vs. t3) for the comprehensive set of behavioral and brain data using univariate and multivariate methods. Individuals’ intensity of training, progress, demographic characteristics and post-hoc appreciation of the courses will be taken into account (implemented as co-variates).
Analyzing separately behavioral data and several kinds of brain imagery data cross-sectionally or over time provides valuable information on these specific data. However, blending diverse behavioral and different kinds of brain data within data-driven multivariate analyses may unravel hidden “covert” relationships [
119,
120]. For these advanced analyses we will be assisted by Prof. D. Van De Ville, computer scientist; expert in advanced (f)MRI data analyses).
In close collaboration with Prof. Van De Ville and his team of data scientists, we will perform final analyses on our data using multivariate data-driven techniques such as multimodal Independent Component Analysis (ICA) [
119,
120] and Partial Least of Squares (PLS) [
121,
122], which have both been used successfully on multimodal brain imagery data. These techniques allow to (1) significantly reduce the dimensionality of the data (as compared to a voxel-by-voxel analysis), reducing multiple comparison correction; (2) improve the interpretability by identifying brain regions or networks that can be more easily related to known processes. Two types of methods will be used:
1) Joint, fusion, and linked Independent Component Analysis (ICA) [
123,
124] represent several blends of multimodal extensions of ICA that allow combining different types of data such as functional and structural neuroimaging data. Depending on the type of ICA, weaker or stronger relationships between the modalities are assumed. In addition, we will also decompose the fMRI data into functional brain networks using innovation-driven co-activation patterns (iCAPs), a recent approach of dynamic functional connectivity [
125] that can quantify temporal interactions between different networks. The results of these analyses should reveal interactions between different types of information and consequently allow us to investigate differences between our groups [
119,
123].
2) Partial Least of Squares (PLS) is another powerful technique that can identify components of multivariate relationships between imaging and behavioral data [
122,
126].
Implementations of these approaches (1 & 2) are publicly available in addition to a number of in-house extensions that allow using them in the most flexible way, including machine-learning approaches [
127,
128].
Power analyses
No standardized computational tools exist for the power analysis of longitudinal neuroimaging studies [
129]. A true longitudinal design provides increased statistical power reducing the confounding effects of between-subject variability [
130]. Foreseeing an important attrition of 25% in our elderly population, we recruited ~ 30 participants per experimental and per control group in Geneva, and ~ 45 individuals per group in Hannover, so a total of 150 participants. Anticipating around 25% of attrition, final analysis will thus be performed in principle on more than 112 participants, ~ 56 in the experimental and ~ 56 in the control groups.
In order to acquire sufficient statistical power to reliably detect a 2% difference in Gray Matter volume [
36] between 2 groups at the whole brain level, a longitudinal study design requires on average 38 subjects, equally divided between the 2 groups [
131]. Colcombe and colleagues [
81] found reliable frontal GM and WM (White Matter) differences after only 6 months of aerobic training in elderly with much smaller sample sizes (n total = 59, divided evenly over an experimental and a control group) than in this study. To detect reductions in mean tract FA (Fractional Anisotropy, reflects fiber density, measure resulting from Diffusion Tensor Imaging (DTI)) of 2–20%, sample sizes between 7 and 28 subjects are recommended for cross-sectional analyses for an effect size of 5%, depending on the white matter tracts studied [
132], but longitudinal studies are more powerful.
Longitudinal intervention studies with 150 participants are rare. All the cited studies involved smaller sample size compared to the current study. Therefore, we consider to have opted for a fair compromise between feasibility of the study and number of participants.
Outcomes of the study
Primary outcomes
We expect positive transfer effects from intensive piano training (intervention group) - as compared to listening and learning about music without practice (control group) - over one full year on age-related cognitive decline: for working memory, executive functions, speed of information processing, auditory selective attention (hearing in noise) and abstract thinking. Associated functional and structural brain plasticity may show in gray and white matter in temporal (medial and lateral), prefrontal and parietal areas. We specifically anticipate - in connection with these cognitive changes - less decline or increase of gray matter volume and activation in the hippocampus, and improved functional networking in frontal areas during working memory tasks.
Broader impact
If this applied research study is successful, it may serve as a springboard for the development and implementation of targeted music practice interventions for different types of healthy elderly and patients in the context of population aging and lifespan development, prolonging autonomy, serving public health and thus reducing health costs.
Study specific risks/ inconveniences
Risks of (f)MRI scanning
1)
(f)MRI scans are non-invasive and yield few potential risks because they do not involve any radiation, only a strong magnetic field. A strictly protocolled MRI safety procedure will be applied in both labs (Hannover: Department of Neuroradiology of the Hannover Medical School, Geneva: Brain and Behaviour Laboratory of the University of Geneva), verifying for any metal objects outside and inside the body, as well as for special conditions (pacemaker, etc.).
2)
People not comfortable with (f)MRI scanning will be excluded from the experiment.
3)
Full information will be provided on the (f)MRI technique beforehand, group visits of the MRI room will allow participants to verify whether they can cope with the MRI environment.
Coverage of damages: insurance
Geneva:
Insurance « Responsabilité civile » de la Haute école de santé de Genève.
AXA Winterthur Police no. 4.626.347
Sum of insurance CHF 10′000’000.- Fixed sum per event, including bodily injury, property damage and insured expenses.
Hannover:
Insurance: Alte Leipziger, Police no 30–660–104-204 FD. Sum of Insurance Euro 3′000’000 Fixed sum per event, including bodily injury, property damage and insured expenses.
Discussion
This multi-site study required harmonization between the Geneva and Hannover site concerning all musical interventions, tests, measurements and questionnaires.
We managed (see Table
4) to create an identical test battery at both sites, by choosing tests existing in French and German, but also assured by translations performed by several bilingual members of the team.
The musical education programs were also composed in very similar ways, assured by continuous exchange between the team of musical education experts.
Concerning MRI protocols, the challenge was to end up with corresponding MRI sequence parameters at both sites, allowing to pool the data with a mimimum of post-hoc adaptations. As 3 T Siemens scanners are present at both sites, blending the data is possible [
115]. We managed to end up with identical sequence parameters (see Table
5). Even so, in all analyses, we will add a “scanner” covariate in order to disentangle potential scanner-effect from effects-of-interest.
Although some slight timing differences exists between the Geneva and Hannover sites, the protocols are identical and follow the same chronological path (see Table
6).
In this study, it is impossible for the experimenters to remain ignorant of group membership.
Acknowledgements
We would like to thank Prof. Wolfgang Zill (Hannover), Prof. Thomas Bolliger (Geneva) and Prof. Andrea Welte (Hannover) for their important input to the composition of the music courses; we also thank all music teachers.
Then we thank Yamaha Germany and Switzerland for the generous provision of the electronic keyboards.
We also would like to thank thank Professor Giovanni Frisoni, Director of the Memory Center of the Geneva University Hospitals for his support and advice concerning the study protocol, PD Dr. med. Markus Gschwind, senior physician in neurology of the Kantonsspital Aarau, Switzerland for his consulting on potentially abnormal brain scans, and Dr. Andreas Posada for his help composing the scripts of the computerized behavioral tasks.
Finally we thank our Master students on the project, David Müller, Cécile Mueller, Pauline Berthouzoz, Nadia Bersier and Cyrille Stucker for their contribution.
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