Protocol of the Healthy Brain Study: An accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context.

The endeavor to understand the human brain has seen more progress in the last few decades than in the previous two millennia. Still, our understanding of how the human brain relates to behavior in the real world and how this link is modulated by biological, social, and environmental factors is limited. To address this, we designed the Healthy Brain Study (HBS), an interdisciplinary, longitudinal, cohort study based on multidimensional, dynamic assessments in both the laboratory and the real world. Here, we describe the rationale and design of the currently ongoing HBS. The HBS is examining a population-based sample of 1,000 healthy participants (age 30-39) who are thoroughly studied across an entire year. Data are collected through cognitive, affective, behavioral, and physiological testing, neuroimaging, bio-sampling, questionnaires, ecological momentary assessment, and real-world assessments using wearable devices. These data will become an accessible resource for the scientific community enabling the next step in understanding the human brain and how it dynamically and individually operates in its bio-social context. An access procedure to the collected data and bio-samples is in place and published on https://www.healthybrainstudy.nl/en/data-and-methods/access. Trail registration: https://www.trialregister.nl/trial/7955.

Introduction

The human brain is seen as civilization’s most precious resource [1], both creating and interacting with our increasingly complex environment, it enables us to be conscious and social human beings. Brain functioning also plays a pivotal role in major societal challenges such as health, demographic change, and well-being. Due to developments in different scientific fields, the endeavor to understand the human brain has seen more progress in the last few decades than in the two millennia before. However, we think that current brain research suffers from at least five key limitations and we set up the Healthy Brain Study (HBS) to tackle these five limitations together and, thereby, to facilitate our understanding of how the human brain relates to behavior in the real world and how this link is modulated by biological, social, and environmental factors. In the following paragraphs, we explain the five main design choices of the HBS.

Firstly, a reductionist approach–in which researchers try to understand reality by focusing on a limited number of variables–has been understandably popular as it is vital to obtain detailed mechanistic insights. However, complex dynamical systems, like the human brain, cannot be properly understood by focusing on just one aspect at a time [2-4]. Human brain functioning includes enabling consciousness and cognition, generating emotions, and producing adaptive behavior, and it performs all of these functions while embedded in its biological and social (bio-social) environment [5]. To enable researchers to understand the complexity of human brain functioning in its bio-social context, the HBS provides a broad range of variables within a holistic approach.

Secondly, the brain’s operations cannot be fully understood by single assessments obtained at a specific point in time, but require repeated measurements or continuous monitoring. Single-session assessments may be sufficient to uncover stable traits or processes. However, they do not capture changes in brain functioning that constitute a core feature of our plastic and adaptive brain [6, 7]. Similarly, the body and the social environment are subject to change. For example, seasonality is observed in affect [8, 9], behavior [9, 10], and biological [11-14] and social [9] factors. Most of the studies mentioned were cross-sectional and explicitly stress the need for longitudinal studies that assess within-subject variation. Therefore, in the HBS, participants perform repeated assessments in three different seasons over one year starting at varying time points within a year. Thereby, we aim to reliably and validly capture changes in human brain operations that may be related not only to seasonality, but also to relevant life events and incidental or dynamic changes in biological factors (e.g., inflammation markers), social factors (e.g., household composition, work relations, friendships, politics, media exposure, lockdown), and environmental factors (e.g., daylight hours, exposure to chemicals).

Thirdly, group averages are critical in revealing general principles, but they gloss over differences that make us individual human beings. The human brain is arguably the most individual organ we have and is shaped by our experiences throughout life. Therefore, a large and rich sample is required before single subject inferences can be made about underlying principles of diversity in cognition, affect, and behavior [15, 16]. Given this, the HBS aims to include a broad range of repeated assessments of 1,000 participants.

Fourthly, laboratory assessments enable well-controlled analyses, but they may show low ecological validity in generalizing cognition, affect, and behavior to real-world settings. To understand cognition, affect, and behavior more comprehensively, there is a need for assessments both in the laboratory as well as in the real world [17, 18]. In the HBS, we perform a real-world assessment of physical activity, stress, and sleep with validated wearable devices. Furthermore, we apply ecological momentary assessments using a smartphone application. Taken together, these assessments enable us to understand cognition, affect, and behavior in the context where they naturally occur.

Finally, a healthy volunteer selection bias is a frequent problem in both cohort studies and neuroscience studies. For example, UK Biobank participants were more likely to be female, have a healthy lifestyle, and live in less socioeconomically deprived areas compared to the general population [19]. Also, students, the usual participants in cognitive neuroscience studies, function well, are often relatively healthy and have a high socioeconomic status [20]. Also, most population-based cohorts and large-scale studies include either developing populations [21-23] or advanced aging populations [24-27]. Therefore, the HBS includes a broad population-based sample of individuals who are 30–39 years old that reflects the general population in terms of gender and educational attainment. The age range was chosen to represent adults beyond the age of developmental brain changes and before the onset of brain changes due to advanced aging or neurodegenerative disease. The lower limit of 30 years excludes any neurodevelopment effect as the brain has matured by this point [28]. Also, 30–39 is a socially challenging age range because it is generally characterized by a relatively high number of rather impactful life events (e.g., family planning, career-related changes, buying a house).

In conclusion, the unique feature of the HBS is that it combines the five above-mentioned strengths resulting in in-depth phenotyping of a large range of cognitive, affective, behavioral, and social dimensions with a biological sampling of brain and body-related processes. This enables the extraction of a detailed bio-social fingerprint for the participants in the cohort. Such a detailed fingerprint is currently not available. The availability of HBS will contribute to a better understanding of risks and potentials in behavior in the real world at the individual level. This paper describes the rationale and design of the currently ongoing HBS, which originated from an interdisciplinary, team science [29] based cross-faculty initiative from the Radboud campus in Nijmegen, the Netherlands, including Radboud University, Radboud University Medical Center, and the Max Planck Institute for Psycholinguistics.

Methods/Design

Study design and setting

The HBS is a longitudinal cohort study in both laboratory and real-world settings. All laboratory assessments take place at a single-center on Radboud campus, Nijmegen, the Netherlands.

Participants

The HBS aims to include 1,000 participants (500 men and 500 women) from the Nijmegen region (≤ 15 km) of whom 220 have a low, 340 a middle, and 430 a high level of education. Nijmegen is a medium-sized city in the east of the Netherlands with 176,731 citizens on the 1st of January 2019 of whom 74% are native Dutch, which is comparable to the overall proportion of native Dutch citizens of the Netherlands (76%) [30]. In contrast, large cities (> 500,000 citizens) in the west of the Netherlands like Amsterdam, Rotterdam, and The Hague have respectively 46%, 48%, 45% native Dutch citizens [30]. Regarding educational attainment, 22% of Nijmegen citizens are primary and secondary educated (low level), 34% are primary, secondary, and vocationally educated (middle level), and 43% of the population have also a university degree (high level). Nijmegen has less citizens with low and middle level of education and more citizens with high level of education compared to the overall proportions of Dutch citizens (28%, 41%, 30% of citizens have respectively low, middle, and high level of education) [30]. In comparison, some large cities in the Netherlands have a higher proportion of citizens with a high level of education (e.g., Amsterdam 48%, Utrecht 52%), while other large cities have a higher proportion of citizens with a low level of education (e.g., Rotterdam 32%, The Hague 31%) [30].

Inclusion criteria are age 30–39 years, living in the Nijmegen region (≤ 15km; because of feasibility), willingness, and ability to follow the study protocol. Exclusion criteria are: not speaking, reading, and/or understanding the Dutch language (minimum B1 level), a prior history of significant psychiatric or neurological illness (self-report), a current disease that affects the brain, a current medication that is therapeutically targeted at the brain (e.g., antidepressants, methylphenidate), pregnancy, contra-indication for MRI (metal or devices in the upper body (cardiac pacemaker, cochlear implant, aneurism clip), previous brain surgery, moderate to severe claustrophobia), contra-indication for the submaximal Åstrand cycle test (current use of beta-blockers, a current disease that hinders physical exercise), contra-indication for the cold pressor test (Raynaud’s phenomenon, chronic pain syndrome in shoulder or arm, open wounds on arm or hand, scleroderma, arteriovenous fistula or shunt, presence of (unstable) angina pectoris).

Recruitment

We aim to acquire full longitudinal datasets of 1,000 participants. We expect a withdrawal rate of 15%, and will therefore recruit 1,150 individuals to participate in the study. We apply different strategies to recruit participants. Firstly, municipalities, general practitioners, and employers of different sectors based in the Nijmegen region send the HBS invitation and research flyer to their citizens, clients, and employees, respectively. Employers are asked to sponsor the study by (partly) exempting their employees from three working days which allows them to participate in three lab visits. Employees remain entirely free to decide whether or not they want to participate. Also, campaigns to increase awareness of the HBS have been launched.

Potential participants fill out contact details in an online form on the website https://www.healthybrainstudy.nl and receive the study brochure. Participants can watch short videos on the website that explain the various tests and assessments or learn about the experiences of an HBS participant. Participants are contacted via phone and invited to a face-to-face information meeting on the Radboud campus. Participants provide written informed consent at this meeting before participation.

Ethics

The Institutional Review Board of Radboud University Medical Center approved the HBS on the 23rd of May, 2019 (reference number: 2018–4894) in accordance with the latest revision of the Declaration of Helsinki [31]. Incidental findings could occur both while conducting the study (e.g., observed during assessments) and while using the data and biosamples in the future to answer research questions. If a researcher or research assistant notices a potential finding incidentally, he/she will contact the principal investigator, who approaches an incidental findings committee. At the Radboud Campus, such committees exist for neuroimaging and genetics. For other findings, the principal investigator contacts a medical doctor with relevant expertise. If, according to the committee or medical expert, no clinically relevant finding is identified, the participant remains uninformed. In all other cases, the participant’s general practitioner is sent a letter describing the findings. At the same time, the participant receives a request to contact their general practitioner. Participants must consent to this procedure and provide the contact details of their general practitioner, otherwise, they are not allowed to participate.

Participant panel, feedback of participants, incentives, and citizen science

A participant panel consisting of twelve people (age 30–39, 6 women and 6 men) was set up to aid in the design of the study. The panel advises on communication materials and incentives. For example, the panel gives feedback on the website, study information, posters, and flyers. Moreover, the first 243 participants filled out a questionnaire on their experience of the first lab visit, which provided us with feedback on the study procedures and on keeping participants involved. For example, we developed an online dashboard, because participants indicated that they would prefer more individual feedback on results. Participants receive gadgets after each assessment, and we organize (online) participant events. After completion of the study protocol, participants receive €150 with a maximal addition of €50 for assessment specific incentives.

Besides, a citizen science platform is used to involve participants as well as other citizens in generating research topics and questions that can be investigated with the HBS resource [32]. We ‘crowdsource’ lists of research topics and/or research questions that participants and citizens think are useful for examining with the HBS resource. At the same time, they also rate the importance of the crowd-generated suggestions by other participants and citizens resulting in an overview that reflects the relevance and prioritization of their overall input.

Quality management and safety

Research assistants and nurses received extensive training for the assessments undertaken as part of the study protocol. We adapted existing standardized operating procedures (SOPs) if available and developed a new SOP otherwise. An independent study monitor annually performs checks to ensure that the study protocol is followed.

Data management and data availability

We use Ldot [33], which is a web application that only stores personal and logistical data, for communication with our participants. For data acquisition, we use Castor EDC [34] to provide electronic case report forms and online questionnaires. In addition, a smartphone application for ecological momentary assessments was developed. After participants have performed the real-world assessments, our data managers extract the raw data that is stored locally on the device. Bio-samples are stored at the Radboud Biobank with their sample tracking system, sample processing SOPs, and standardized sample storage conditions being employed [35]. Furthermore, a Polymorphic Encryption and Pseudonymization (PEP) infrastructure was developed for the HBS to protect all data streams and the privacy of participants [36, 37] (Fig 1). Ldot, Castor EDC, the smartphone application, and PEP meet the requirements of the European General Data Protection Regulation.

Fig 1

The Polymorphic Encryption and Pseudonymization (PEP) infrastructure.

For each participant, the PEP-system generates unique pseudonyms for the different assessments to avoid the coupling of data to an individual participant during the data collection phase (step 1: collect). A backup of the data is stored locally (step 2: produce) and a copy is encrypted and transferred to the data repository (step 3: store). In the same step, the data are cryptographically pseudonymized. The data can only be decrypted in the processing environment where scientific analyses are performed (step 4: process). The PEP method ensures that different datasets obtained from the repository cannot be linked easily by different research projects because pseudonyms identifying a single participant are personalized at the project level, and data transfer can be minimized based on researchers’ requirements. Derived data, produced by researchers, can be stored in the data repository (step 5: contribute) for future use by other researchers using their researcher-specific pseudonyms.

The PEP-system was created to deal with the rigidity of the traditional encryption/decryption process by using polymorphic encryption. PEP ensures that there is no need to a priori fix the encryption key for the data. The PEP system enables different research teams to have access to the entire dataset or only a subset (of participants and variables) of the data source with a specific, personalized decryption key. Due to its additional security, the PEP system is an ideal approach to store, manage, and share sensitive personal data in a research data repository that reduces the risk of a participant’s privacy being violated.

Measures

The following paragraphs describe the measures briefly, while the supplementary information provides detailed descriptions (S1 File). Each assessment starts with pre-visit online questionnaires, followed by a burst week of real-world assessments, followed by a whole day lab visit, which in turn is followed by post-visit online questionnaires and assessments (Fig 2). Only those constructs that may be sensitive to change during one year (states) are repeated during the second and third assessments. The stable (trait) measures are equally distributed over the three assessments. The majority of measures are validated in prior research.

Fig 2

Design of data collection in the healthy brain study.

Pre-visit online questionnaires

Participants fill out questionnaires before the start of the burst week to assess baseline characteristics. The questionnaires cover general demographic questions and questions about lifestyle and well-being (Table 1).

Table 1

Pre-visit online questionnaires.

Domain	Name of the questionnaire	What does it measure?	Duration (minutes)	Assessment 1	Assessment 2	Assessment 3	Ref
General information	Demographic and socio-economic background	Demographic data, the highest level of education, income, household composition	10	x	x	x	[38]
	Pregnancy	Number of pregnancies, time to pregnancy, pregnancy outcome, hormones (anticonception), current child wish	3	x
	Menstrual cycle	Menstrual cycle	1	x	x	x
Lifestyle	Smoking history	Past behavior, age of onset	1	x
	Smoking	Current behavior, frequency, and quantity	1	x	x	x
	Fagerstrom Test of Nicotine Dependence (FTND)	Nicotine dependence (for current or ever smokers)	2	x	x	x	[39]
	Alcohol	Frequency and quantity in the last month, age of onset of alcohol use, binge drinking	2	x	x	x
	Alcohol Use Disorder Identification Test (AUDIT)	Heavy alcohol use and associated problems	3	x	x	x	[40]
	Substance matrix Mate-q	Amount and frequency of substance use	5	x	x	x	[41]
	Food Frequency Questionnaire (FFQ)	Quantitative food intake	45	x			[42–45]
	Sedentary Behavior Questionnaire (SBQ)	Sedentary behavior in various domains (e.g. home, work, transportation)	5	x	x	x	[46]
	Pittsburgh Sleep Quality Index (PSQI)	Sleep quality	5	x	x	x	[47]
	Dream Recall Frequency Scale (DRFS)	Dream recall	1	x	x	x	[48]
	The Internet Gaming Disorder Scale	Problematic gaming	2	x	x	x	[49]
	The Social Media Disorder Scale	Problematic social media use	2	x	x	x	[50]
	Short Media Multitasking Measure (S-MMM)	Use of different media simultaneously	1	x	x	x	[51]
Well-being	Satisfaction with life scale	Well-being	2	x	x	x	[52]
	Cantril ladder	Well-being	1	x	x	x	[53]
	Five Facet Mindfulness Questionnaire–Short Form (FFMQ)	Mindfulness	10	x	x	x	[54]

Burst week with real-world assessments

The burst week consists of a real-world assessment of physical activity, stress, and sleep using validated wearable devices (Table 2) and ecological momentary assessments (EMA) using a smartphone application. The questionnaire for EMA covers mood, social company, online social interactions, context, control items, retrospection, anticipation, and substance use. In addition, participants perform the home collection of stool, urine, saliva, and diffusive sampling of chemicals using silicone wristbands during the burst week (Table 3).

Table 2

Physiological assessments.

Domain	Measure	Location	Assessment 1	Assessment 2	Assessment 3	Ref
Physical activity	Fitness	Campus	x	x	x	[55]
	Sedentary behavior	Home1	x	x	x	[56, 57]
Stress	Heart rate	Campus	x	x	x
		Home1	x	x	x	[58]
	Heart rate variability	Home1	x	x	x	[58]
	Skin conductance	Home1	x	x	x	[58]
	Skin temperature	Home1	x	x	x	[58]
	Startle eye-blink	Campus	x	x	x	[59]
	Subjective stress levels	Campus	x	x	x	[60]
		Home2	x	x	x
Sleep	Sleep duration	Home1	x	x	x
	Sleep stages	Home1	x	x	x
Body composition	Weight	Campus	x	x	x
	Height	Campus	x	x	x
	Waist-hip circumference	Campus	x	x	x
	Body fat	Campus	x	x	x	[61]
	Fat weight	Campus	x	x	x
	Total body water	Campus	x	x	x
	Skeletal muscle mass	Campus	x	x	x
	Body fat mass index	Campus	x	x	x
	Fat-free mass index	Campus	x	x	x
Pain	Subjective pain levels	Campus	x	x	x	[60, 62]
		Home1	x	x	x
	Electrical pain thresholds	Campus	x	x	x	[63, 64]
Cardiovascular	Blood pressure	Campus	x	x	x	[65]
	Carotid artery reactivity	Campus	x	x	x	[66]

1 By wearable device,

2 By ecological momentary assessment (EMA).

Table 3

Bio-samples and silicone wristband.

Bio-sample	Measure	Location	Assessment 1	Assessment 2	Assessment 3	Ref
Stool	Gut microbiome	Home	x	x	x	[12, 35, 67]
Urine (first morning)	Ions, such as calcium, potassium, sodium, magnesium	Home	x	x	x	[35, 68]
Saliva	Cortisol levels (short term; two baseline samples)	Home	x	x	x	[69]
	Cortisol levels (short term; before, immediately after, and 20 minutes after acute challenge)	Campus	x	x	x
Blood—EDTA plasma	DNA	Campus	6 ml*			[35]
Blood—PAX gene	RNA	Campus	3x 2,5 ml*	3x 2,5 ml*	3x 2,5 ml*
Blood—EDTA plasma	Future analyses	Campus	4x 10 ml*	4x 10 ml*	4x 10 ml*
			1x 3 ml*	1x 3 ml*	1x 3 ml*
Blood—serum	Future analyses (e.g., antibodies, proteomics)	Campus	10 ml*	10 ml*	10 ml*
Blood—heparin plasma	Future analyses (e.g., hormones, metabolomics)	Campus	2x 10 ml*	2x 10 ml*	2x 10 ml*
Hair	Cortisol levels (long term)	Campus	x	x	x	[70]
Silicone wristband	Exposure to chemicals in the surrounding environment	Home	x	x	x	[71, 72]

*The indicated volumes refer to whole blood volumes.

Lab visit Radboud campus

Each eight-hour lab visit includes bio-sampling (Table 3), neuroimaging (Table 4), physiological (Table 2), cognitive (Table 5), affective (Table 5), behavioral (Table 5), and sensory assessments (Table 6). To avoid systematic carry-over and fatigue effects, the order of assessments varies between and within participants except for fasting blood sampling and blood pressure at the start of the day.

Table 4

Neuroimaging at the campus.

Scan	Description	Duration (minutes)	Assessment 1	Assessment 2	Assessment 3	Ref
Dummy scanner		10	x
T1w 3D MPRAGE	Anatomical scan	5	x	x	x
rfMRI	Resting-state functional scan followed by resting-state questionnaire	10	x	x	x	[73, 74]
mfMRI	Movie functional scan	4,5	x	x	x
Scout, fieldmap, single-band reference EPIs	Auxiliary scans	2	x	x	x
Diffusion-weighted imaging scan	Structural connectivity characterizations and white matter tissue microstructural modelling	10	x
High-resolution T1w 3D MP2RAGE anatomical scan	Quantitative T1 and cortical myelin mapping	10		x		[75]
High-resolution T2*w scan	Quantitative T2* and magnetic susceptibility mapping for identification and quantification of iron deposition across the brain	10			x	[76]

Table 5

Overview of cognitive, affective, and behavioral assessments at the campus.

Domain	Name of task	Measure	Description	Duration (minutes)	Assessment 1	Assessment 2	Assessment 3	Ref
Cognition	Foraging task	The tendency to explore alternatives vs. to exploit a chosen alternative	Participants are presented with a tree and have to decide whether to harvest it for apples and incur a short harvest delay or move to a new tree and incur a longer travel delay	30	x	x	x	[77]
Cognition	Serial random-dot motion discrimination task	How predictions from the past are weighted with uncertain sensory information in the present	Participants judge the motion direction of moving dots (up vs. down) and receive auditory feedback about the correctness of their response	25	x	x	x	[78]
Cognition	Reward-driven reach-adaptation task	How willing people are to search for more rewarding outcomes in a motor task	Participants make shooting movements toward a target while holding a handle that records pulling and hand rotation movements	20	x	x	x	[79]
Cognition	Paired associate memory task	Associative Memory	Participants memorize the associations between pictures of people and names in a study phase and the memory for these associations is tested in a test phase using a cued-recall-test	7	x	x	x	[80]
Cognition	Tower of London	Executive function (planning)	Participants are presented with a startling array of different colored, same-sized balls and are requested to move the balls one-by-one, with as little moves as possible to a predefined goal array.	5	x	x	x	[81]
Affect	Contextual fear generalization task	Fear generalization	Participants are instructed to attend to the presented stimuli and learn to predict the shock in multiple contexts while assessing eye-blink startle electromyography, subjective report, and avoidance tendencies.	40	x	x	x	[82]
Affect	Emotion regulation task	Emotion regulation	Participants are asked to actively regulate their emotions while either neutral or aversive pictures are presented on the computer screen	15	x	x	x	[83]
Affect	Self-referent encoding Task	Positive and negative memory bias	Participants endorse and memorize positive and negative words	8	x	x	x	[84]
Affect	Stimulus-response compatibility task	Automatic approach or avoidance tendency	Participants are presented with pictures (alcohol vs. soda) and are instructed to approach or avoid a certain condition	10	x	x	x	[85]
Behavior	Columbia card task	Risk preference	A card game that gives participants the repeated choice between risky options and safe options	22	x	x	x	[86]
Behavior	Food auction task	Reliable index of people’s preference for hedonic (short-term reward) vs. healthy food (long-term reward)	Participants bid on different food items (e.g., package of M&Ms, apple)	15	x	x	x	[87]

Table 6

Sensory assessments.

Domain	Measure	Duration (minutes)	Assessment 1	Assessment 2	Assessment 3
Vision	Contrast sensitivity	5	x
	Visual acuity	5		x
	Color vision	5			x
Hearing	Hearing ability	1	x	x	x

Post-visit online questionnaires and assessments

Participants fill out an online questionnaire assessing (mental) health, life events, social/relationships, work, politics, personality, and literacy after each lab visit (Table 7). Also, participants perform several online assessments about decision-making, narrative reading, and solidarity (Table 8). After their third and final lab visit, participants are invited to complete the ‘Individual Differences in Language Skills’ test battery (Table 9) assessing participants’ linguistic knowledge, as well as linguistic processing and general cognitive skills.

Table 7

Post-visit online questionnaires.

Domain	Name of the questionnaire	What does it measure?	Duration (minutes)	Assessment 1	Assessment 2	Assessment 3	Ref
Exposure	Exposure	Exposure from environment	5	x	x	x
Health	Over-the-counter medication	Use of nonprescription medication like pain relievers, cough suppressants, etc.	1	x	x	x	[88]
	Health complaints	Complaints like tiredness, nausea, back pain, headache, etc.	5	x	x	x	[89]
Mental Health	Adult ADHD Self-Report Scale (ASRS)	Symptom scale for ADHD	10	x			[90]
	Autistic Trait Questionnaire (ATQ)	Autistic traits	5	x			[91]
	Self-Report Inventory of Depressive Symptomatology (IDS-SR)	Presence and severity of depressive symptoms	5	x	x	x	[92]
	Anxiety Sensitivity Index (ASI)	Anxiety (trait)	5			x	[93]
	State and Trait Anxiety Inventory (STAI-S)	Anxiety (state)	5	x	x	x	[94]
	Perceived Stress Scale (PSS)	Stress	5	x	x	x	[95]
	Utrecht Burnout Scale (UBOS)	Burnout	3	x	x	x	[96]
	Reactive Proactive Aggression Questionnaire (RPQ)	Aggression	5	x	x	x	[97]
	Daily hassles	Daily hassles	5	x	x	x	[98]
	Cognitive emotion regulation questionnaire (CERQ)	Cognitive regulation of emotion	5	x	x	x	[99]
Life events	Childhood Trauma Questionnaire (CTQ)	Adverse childhood experiences	5		x		[100]
	Life events	Threatening life experiences	10	x	x	x	[101]
Social/ Relationship	UCLA loneliness scale	Loneliness	5	x	x	x	[102]
	Need to belong scale	Belongingness	3	x	x	x	[103]
	Multidimensional scale of Perceived Social Support (PSS)	Perceived social support	5	x	x	x	[104]
Work	Exposure to work	Working hours, working schedules, type of employment	4	x	x	x
	Survey Work-home Interaction–NijmeGen (SWING)	Work-life balance	4	x	x	x	[105]
	Workplace commitment		5	x	x	x	[106]
	Employability		5	x	x	x	[107, 108]
	Questionnaire on the Experience and Evaluation of Work (QEEW)	Job characteristics	7	x*			[109]
Politics	Populism index	Attitude toward populism	2	x	x	x
	Political efficacy	Attitude towards national government and politics	2	x	x	x	[110]
	Political participation	Political activities	1	x	x	x
	EU membership	Attitude towards EU membership	1	x	x	x	[111]
Personality	BIG-5 NEO-FFI-3	Openness to experience, conscientiousness, neuroticism, extraversion, and agreeableness	10	x			[112]
	Sensory Processing Sensitivity (SPS)	High sensitivity	5			x	[113]
	Barratt Impulsiveness Scale (BIS-11)	Impulsiveness	10		x		[114]
	Self-control		10	x			[115]
	New general self-efficacy scale	Self-efficacy	5		x		[116]
	Dispositional greed	Greediness	3			x	[117]
	Dark triad	Narcissism, Machiavellianism, psychopathy	5	x			[118]
	Social investment attitudes	Attitudes toward corporate social responsibility	5		x		[119]
Literacy	Numeracy test	Mathematical abilities	12		x		[120]
	Financial literacy	Financial attitudes, skills	20			x	[121]
	Graph literacy	Ability to understand the meaning of graphs	10	x			[122]
	Cultural intelligence	Ability to relate and work effectively across cultures	2			x	[123]

*Participants fill out their job characteristics at the first assessment. In the second and third assessments, they fill out their job characteristics only in case of a new job.

Table 8

Post-visit online assessments.

Domain	Online task	What does it measure?	Duration (minutes)	Assessment 1	Assessment 2	Assessment 3	Ref
Decision-making	Higher-order risk preferences	Risk attitudes, prudence, and temperance in financial decision-making	15	x	x	x	[124]
	Equality equivalence test	Social preferences	10	x	x	x	[125]
	Ambiguity	Ambiguous risk attitudes	10	x	x	x	[126]
	Trust game	Trust and trustworthiness	10	x	x	x	[127]
	Public good game	Altruism, conditional reciprocity	15	x	x	x	[128]
	Time preferences	Temporal discounting	8	x	x	x	[129]
Language	Narrative reading	Comprehension of and immersion into a narrative	15	x	x	x	[130]
Solidarity	Vignettes	Culpability, in/out group	15	x	x	x	[131, 132]

Table 9

Individual differences in language skills test battery.

Domain	Online task	What does it measure?	Duration (minutes)	Ref
Cognition	Auditory simple and choice reaction time task	Processing speed	7	[133]
	Letter comparison	Processing speed	5	[134, 135]
	Visual simple and choice reaction time task	Processing speed	7	[133, 136]
	Digit span (forward & backward)	Auditory working memory	7	[137]
	Corsi block tapping (forward & backward)	Visual working memory	7	[138, 139]
	Raven’s advanced progressive matrices	Non-verbal intelligence	25	[140]
Linguistic knowledge	Stairs4Words (2 Runs)	Linguistic experience: Vocabulary	7
	Peabody Picture Vocabulary Test	Linguistic experience: Vocabulary	10	[141, 142]
	Idiom recognition test	Linguistic experience: Knowledge of idiomatic expressions	3
	Spelling test	Linguistic experience: Spelling	5
	Author recognition test	Linguistic experience: Print exposure	5	[143]
	Prescriptive grammar	Linguistic experience: Prescriptive grammar knowledge	10	[144]
Linguistic processing	Picture naming	Word production	7	[133]
	Rapid automatized naming	Word production	7
	Verbal fluency	Word production	5	[145]
	Antonym production	Word production	5	[146]
	Maximal speech rate	Word production	3
	Phrase generation	Sentence production	10
	Sentence generation (active/passive sentence formulation)	Sentence production	12
	Sentence generation (event apprehension)	Sentence production	10
	Spontaneous speech	Sentence production	4	[147]
	Non-Word monitoring in non-word lists in noise	Word comprehension	10
	Rhyme judgment	Word comprehension	5
	Lexical decision	Word comprehension	7	[133]
	Semantic categorization	Word comprehension	5
	Word monitoring in sentences in noise	Sentence comprehension	10
	Grammatical gender cues	Sentence comprehension	10	[148]
	Verb-specific selective restrictions	Sentence comprehension	7	[149, 150]
	Self-paced reading	Sentence comprehension	5

COVID-19 questionnaire

From March until July 2020, when the assessment of participants was not allowed due to the COVID-19 measures, the included participants at that point (N = 158) received a monthly questionnaire addressing behavior and worries regarding COVID-19, currently experienced anxiety [94], stress [95], and well-being [53]. Moreover, loneliness [102], sedentary behavior [46], and sleep quality [47] were assessed. We used the same questionnaires as we use in the three repeated assessments (Tables 1 and 7).

Results—Progress so far

Fig 3 presents the progress and milestones of the Healthy Brain Study. The first participant was included on the 9th of September, 2019.

Fig 3

Progress and milestones of the healthy brain study.

At the end of June 2021, the HBS included 418 participants. Seventeen-one participants (17%) withdrew from the study so far, mostly because they experienced too much burden (n = 41; 58%), got pregnant (n = 11; 15%), or had been given a diagnosis or medication treatment (n = 8; 11%). Most participants withdrew after the first assessment. To date, participants performed 755 lab visits: 380 participants carried out the first assessment, 237 participants the second assessment, and 138 participants the third assessment completing the entire study protocol.

The COVID-19 pandemic interrupted the data acquisition phase. At that point, the HBS included 158 participants. Due to the lockdown, we canceled all assessments involving physical interaction as of the 16th of March, 2020. The HBS resumed participant assessments on the 15th of July, 2020 in compliance with the directives in force in the Netherlands. As a result, some participants (48%) have more than four months between repeated assessments. Besides, some participants (10%) have a delay between the burst week with real-world assessments and the lab visit at the Radboud campus.

Discussion

This paper presents the design of the currently ongoing HBS, which will result in a unique and accessible resource for the scientific community and its public and private partners. Data are collected through cognitive, affective, behavioral, and physiological testing, neuroimaging, bio-sampling, questionnaires, ecological momentary assessment, and real-world assessment using wearable devices. We believe that the HBS complements other studies–small and large–, which together enable the scientific community to take the next step in understanding the human brain and how it dynamically and individually operates in its bio-social context. Here, we present examples of research opportunities including citizen science, reflect on the HBS design choices and study population, and discuss our data security system which enables future data sharing.

Examples of research opportunities

The HBS resource will be used to address expert and citizen-driven research questions that usually pertain to complex interactions between multiple factors. The first example of an expert-driven research question pertains to the association between income and positive affect. It was found among US residents that higher income was associated with more happiness and enjoyment, and less sadness and worry, but only up to a point ($75.000 per year), above that, there was no relationship between income and emotional well-being [151]. The HBS resource can help explain the interplay between affect, social and biological data, and income. A second example of a complex interaction is that sedentary behavior is associated with poor health and higher mortality [152, 153]. Merely standing up from time to time, e.g., to walk around a bit protects against part of this health risk [154]. Existing research on this topic has mainly focused on the consequences of prolonged sitting and has overlooked the key question of why people choose to stand up (when they sit) or sit down (when they stand), in the first place. In other words, what psychological processes (e.g., related to effort, reward, affect, and fatigue) are associated with healthy and unhealthy sedentary behavior? Answering this question will pave the way for the development of novel, targeted interventions that will improve (occupational) health [155].

The HBS resource will also be used for citizen science. Different forms of citizen science exist. Projects can be led by experts, community-led, or co-created with different aims and levels of participation [156]. HBS participants and other citizens generate research questions to be answered with the HBS resource. In traditional designs, scientists test hypotheses that are often based on previous findings within their research domain or their intuitions. However, people living in or with specific conditions (i.e., being in their thirties and going through a key life event) may have additional insight on top of existing expert-knowledge. These insights are uncovered by a citizen science platform. The essence of the platform is to leverage collective intelligence from a large group of participants versus a smaller number of experts. This can reveal topics and research questions that have a significant influence on people’s behavior in the real world and their health status, which experts may have left untouched [157-160]. By giving citizens a voice in scientific research, it can contribute considerably to the valorization of research results.

Reflection on design choices and study population

Comprehension of complex interactions as illustrated above requires an interdisciplinary, team science approach [29]. The HBS design is the result of an orchestrated cross-campus process over 22 months in which 250 scientists from all classical faculties were involved and were challenged to look past the horizons of their disciplines in a few plenary meetings and several smaller working groups, all providing input to a multidisciplinary scientific board that made the final design decisions. Here, we reflect on our design choices and the study population selected.

First of all, to capture the complexity of the human brain and its environment, a large set of measures was provided. We sought a balance between comprehensiveness, local expertise, costs, and burden for the participants. This resulted in an extensive number, variety, duration of mostly validated assessments, albeit not perfectly comprehensive. For example, the neuroimaging protocol is largely aligned with the Human Connectome Project [161] and UK Biobank [162] brain imaging, but includes a movie fMRI scan that is not included in the Human Connectome Project and UK Biobank, while the latter include scans that are not included in the HBS. Furthermore, instead of continuous monitoring over one year with validated wearable devices, the HBS covers three times a burst week of real-world assessments. Also, the collection of GPS data, financial transactions, and social media interactions were not allowed due to legal restrictions and privacy concerns.

Secondly, the HBS includes three repeated assessments for about one year. These repetitions aim to capture changes in human brain operations that may be related to relevant life events, seasonality, and/or incidental or dynamic changes in the biological and social environment. Regarding seasonality, the HBS participants start at varying time points within a year, so, although we sample only three instead of four times over one year, across participants we sample seasonal transitions in a fine-grained manner.

Thirdly, the HBS aims to include 1,000 participants. Due to differences in measurement-specific signal-to-noise properties, it is not possible to provide a straightforward power and sample size calculation because the data enables analyses of various cognitive, affective, and behavioral interactions in their bio-social context. To decide on the number of participants, we sought a balance between sensitivity and feasibility. The chosen number of participants is high compared to traditional neuroscientific experiments revealing general principles but is low compared to disease risk-oriented cohorts (which is not the aim of the HBS) like the UK Biobank [26], the Rotterdam Study [24], or the Rhineland Study [25]. However, the number is comparable to other studies designed to capture inter-individual differences like the Human Connectome Project, which included 1,200 young healthy adults [161], or the Personalized Parkinson Project, which included 650 patients [163]. We consider the number large given the comprehensive range of repeated measures both in the laboratory as in the real world.

Fourthly, we believe that assessing real-world events with wearable devices is more objective than scales and questionnaires. When we designed the study in 2017, hardly any longitudinal study included wearable devices. As the field of wearable technology has developed rapidly, in the meantime, several longitudinal studies have added wearable devices to their data collection methods. For example, subsets of UK Biobank participants and Rotterdam Study participants wore an accelerometer [164, 165]. We would like to stress that including real-world assessments is one of the five strengths of the HBS, so it is not unique by itself. In particular, the HBS includes repeated assessments with wearable devices in three different seasons over one year starting at varying time points within a year. When we designed the study, to our knowledge, this was unique for HBS. In the meantime, a subset of UK Biobank participants is performing seasonal repeats with a wearable device [166]. Furthermore, the HBS combines physiological recordings with wearable devices with ecological momentary assessments using a smartphone application. We consider the additional collection of momentary assessments of mood and behavior and context information innovative.

Fifthly, we developed a recruitment strategy targeted at a sample that represents the 30-39-year-old population of Nijmegen and its surroundings in terms of gender and educational attainment. However, a reasonable level of reading, speaking, and understanding Dutch (B1 level) is required to be able to complete the study protocol, e.g., to fill out questionnaires. This implies that the HBS participants do not fully represent the Nijmegen population at large, because in this example the illiterate, people with low literacy, or non-Dutch speaking individuals are excluded. However, the aim of including 220 participants with a low, 340 with a middle, and 430 with a high level of education enables the study of interacting social factors.

Digital security system and data sharing

The HBS resource will be accessible to the scientific community at large. The resource contains sensitive personal data that needs to be protected from unauthorized access and unintentional disclosure. The sharing of (big) data within the scientific community is necessary for progress and maximizes scientific benefits derived from valuable and costly data. The HBS data is protected by a digital security system, a Polymorphic Encryption and Pseudonymization (PEP) infrastructure [36], which allows the sharing of data with researchers worldwide while safeguarding participants’ privacy in line with the European General Data Protection Regulation. The digital security system is based on a multi-point, privacy-by-design strategy: (a) participants provide informed consent, also for the important element of data sharing; (b) signed contractual agreements with researchers are in place to ensure that no attempts towards de-pseudonymization, linking or commercialization of the raw data will be attempted; (c) governance policies limit access to the data to qualified researchers only; (d) an innovative pseudonymization and encryption process is applied [37].

An access procedure is in place and published on https://www.healthybrainstudy.nl/en/data-and-methods/access. We stratify researchers into three tiers with different rights. Tier I consists of researchers from the Radboud campus that contributed to study design or data acquisition. Tier II consists of all other researchers from the Radboud campus. Tier III consists of publicly financed researchers from other academic institutions. Companies can apply in all tiers, but they cannot apply independently. Application for data starts with the submission of a data request for a project that has been preregistered, e.g., in the Open Science Framework. Then, the HBS scientific board reviews the application. After approval, the researcher signs a data/material transfer agreement. Next, the researcher receives data and/or samples. The Radboud Biobank provides the samples [35]. All processed data and samples with relevant documentation (including scripts and data and/or samples processing protocols) must be integrated back into the HBS resource so that it can be used by others. Finally, the researcher publishes the results by acknowledging the HBS consortium.

Conclusion

The HBS has been designed using a team science approach to integrate scientific disciplines and is characterized by a broad range of repeated assessments, a large number of participants, both laboratory and real-world assessments, and a population-based sample. Moreover, data is managed to allow data sharing with scientists worldwide while maintaining participants’ privacy. With the HBS resource, the scientific community can take the next step in understanding the human brain and how it dynamically and individually operates in its bio-social context.

Detailed descriptions of measures included in healthy brain study.

(DOCX)

Click here for additional data file.

23 Jun 2021

PONE-D-21-15454

Protocol of the Healthy Brain Study: an accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context

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Reviewer #1: This Study Protocol describes the ongoing Healthy Brain Study (HBS). I found the description comprehensive and I think the resulting database will be a much used resource. The access procedure is well described and reasonable. I have some comments that the authors may consider in a revision, listed in order of appearance in the ms:

* I agree that a reductionist approach is common, but several longitudinal studies surely include a broad range of variables and a holistic approach; this is not unique for HBS.

* Life events are highlighted. Such events have been explored in several other past studies, and a question is whether the authors in the quite short period of 1 year expect a sufficient number of significant events to substantiate analyses? Here, the timing with the pandemic is very interesting and it is a strength of the study to capture this major event.

* The protocol has an elegant assessment of factors such as physical activity, stress, and sleep that go beyond past studies. However, to be fair, also past studies meant to target real world events (even if with scales and questionnaires).

* I applaud the stress on population-based cohorts and the risk with selection bias in convenience samples. Here, it could also be mentioned that studies like the Swedish Betula project (e.g., Nyberg, et al, 2020 Ageing Res Rev) have used such an approach. In HBS, some comment is warranted on the exclusion criteria in relation to representativeness (such as taking antidepressants or having a disease that hinders physical exercise). Relatedly, the strategies to recruit participants could influence the final representativeness of the sample. For example, the involvement of employers can bias the sample to people who have a work. Have the authors any plans of assessing how representative for the general population their final sample actually will be?

* Opting out from a study and later dropping out from a study are important variables. So far, after a quite short period of time, as many as 13% withdrew (typically after the 1st assessment). I lacked information on whether the researchers will replace those who drop out at such an early stage, and also how they plan to deal with drop-out analyses.

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3 Sep 2021

Journal requirements

1) Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

We have applied the PLOS ONE style templates.

2) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

Sharing the full Healthy Brain Study (HBS) resource does not comply with the EU General Data Protection Regulation, because the HBS resource contains a substantial amount of sensitive personal data.

Applications for data access can be sent to hbs-data@radboudumc.nl. Then, the HBS scientific board reviews the application. Our governance policy ensures that all use of data is within the limits of the original purpose as described in the information brochure for participants and that only those data are shared that are relevant for answering the proposed research question.

3) Please amend your authorship list in your manuscript file to include author Lucy Overbeek.

We would like to propose that the Healthy Brain Study consortium is the only author and omit the names of the project leader Guillén Fernández and project manager Lucy Overbeek. In our view, mentioning the consortium as the only author would perfectly reflect the nature of the team-science based cross-faculty initiative from the Radboud campus in Nijmegen. We consider our roles as supportive and required for managing the project rather than as principal investigators. We understand that a corresponding author is required. Guillén Fernández fulfills the role of the corresponding author on behalf of the consortium. As stated, all members of the consortium contributed to the design of the study, edited the manuscript, and approved the final version.

Response to reviewer

* I agree that a reductionist approach is common, but several longitudinal studies surely include a broad range of variables and a holistic approach; this is not unique for HBS.

We fully agree with the reviewer that several longitudinal studies include a broad range of variables and a holistic approach. In lines 35-38 we mention that “we think that current brain research suffers from at least five key limitations and we set up the Healthy Brain Study (HBS) to tackle these five limitations together”. Thus, we consider the uniqueness of the HBS that it combines the following five strengths 1) a broad range of variables, 2) repeated assessments across one year, 3) single subject inferences, 4) real-world assessments, and 5) a population-based sample.

We propose stressing that tackling these five limitations together is the uniqueness of the HBS by adapting the sentence starting in line 94 into “In conclusion, the unique feature of the HBS is that it combines the five above-mentioned strength resulting in in-depth phenotyping of a large range of cognitive, affective, behavioral, and social dimensions with a biological sampling of brain and body-related processes.”.

However, there are other studies (e.g., Betula project) that have another focus on a longitudinal design with a very long-term perspective of more than 25 years (https://www.umu.se/en/research/projects/betula---aging-memory-and-dementia/).

* Life events are highlighted. Such events have been explored in several other past studies, and a question is whether the authors in the quite short period of 1 year expect a sufficient number of significant events to substantiate analyses? Here, the timing with the pandemic is very interesting and it is a strength of the study to capture this major event.

When designing the study, we hoped for some major national events around for example governmental elections or sports. A pandemic was of course not expected, but is indeed very interesting and offers additional opportunities.

We agree with the reviewer that one year is a rather a short period for capturing life events, but we chose the age range of 30-39 because it is a socially challenging age range that is characterized by a relatively high number of rather impactful life events (e.g., family planning, career-related changes, buying a house etc.). To assess life events, participants give responses to twenty types of life events (Brugha & Cragg, 1990). In addition, to assess the subjective impact of life events, we ask participants to rate the subjective impact the event had on their lives on a scale from 0 (no impact at all) to 10 (major impact, fundamental change). Preliminary data showed that 130 out of 298 (44%) of the HBS participants that completed the life event questionnaire at T1 experienced one or more life events in the year before participating and 78 out of 175 (45%) and 46 out of 100 (46%) of HBS participants that completed the life event questionnaire at T2 respectively T3 experienced one or more life events. As this is a protocol paper, we do not want to report any preliminary data and propose not to include the above-mentioned data on life events in the manuscript.

Reference:

Brugha, T. S. & Cragg, D. The list of threatening experiences: the reliability and validity of a brief life events questionnaire. Acta Psychiatr Scand 82, 77-81 (1990).

* The protocol has an elegant assessment of factors such as physical activity, stress, and sleep that go beyond past studies. However, to be fair, also past studies meant to target real world events (even if with scales and questionnaires).

We agree with the reviewer that many past and ongoing studies assess real-world events (even if with scales and questionnaires). We consider our approach innovative, because for two reasons.

First, we believe that assessing real-world events with wearable devices is more objective than scales and questionnaires. When we designed the study in 2017, hardly any longitudinal study included wearable devices. As the field of wearable technology has developed rapidly, in the meantime, several longitudinal studies have added wearable devices to their data collection methods. For example, subsets of UK Biobank participants and Rotterdam Study participants wore an accelerometer (Doherty et al., 2017; Koolhaas et al., 2017). Furthermore, in line with our response to the first comment of the reviewer, we would like to stress that including real-world assessments is one of the five strengths of the HBS, so it is not unique by itself. In particular, the HBS includes repeated assessments with wearable devices in three different seasons over one year starting at varying time points within a year. When we designed the study, to our knowledge, this was unique for HBS. In the meantime, a subset of UK Biobank participants is performing seasonal repeats with a wearable device (https://biobank.ctsu.ox.ac.uk/crystal/label.cgi?id=1008).

Second, the HBS combines physiological recordings with wearable devices with ecological momentary assessments using a smartphone application. We consider the additional collection of momentary assessments of mood and behavior and context information innovative.

We added this explanation to the discussion section when reflecting on the HBS study design (line 393).

References:

Doherty A. et al. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One 12(2), e0169649 (2017).

Koolhaas C.M. et al. Objective Measures of Activity in the Elderly: Distribution and Associations With Demographic and Health Factors. Journal of the American Medical Directors Association 18 (10), 838-847 (2017).

* I applaud the stress on population-based cohorts and the risk with selection bias in convenience samples. Here, it could also be mentioned that studies like the Swedish Betula project (e.g., Nyberg, et al, 2020 Ageing Res Rev) have used such an approach. In HBS, some comment is warranted on the exclusion criteria in relation to representativeness (such as taking antidepressants or having a disease that hinders physical exercise). Relatedly, the strategies to recruit participants could influence the final representativeness of the sample. For example, the involvement of employers can bias the sample to people who have a work. Have the authors any plans of assessing how representative for the general population their final sample actually will be?

We defined a population-based sample as 1,000 HBS participants (500 men and 500 women) from the Nijmegen region (≤ 15 km) of whom 220 have a low, 340 a middle, and 430 a high level of education. We perform continuous monitoring of sex and level of education for enrollment and drop-out rates. For example, when we observed that our first wave of participants consisted of mainly higher educated people, we adapted the campaign by displaying pictures and stories of real, middle educated participants in promotion materials and focused on employers with low and middle educated staff. Concerning recruiting unemployed people, we reach them by their municipalities, our social media campaign and local influencers.

* Opting out from a study and later dropping out from a study are important variables. So far, after a quite short period of time, as many as 13% withdrew (typically after the 1st assessment). I lacked information on whether the researchers will replace those who drop out at such an early stage, and also how they plan to deal with drop-out analyses.

We aim to acquire full longitudinal datasets of 1,000 participants. We expect a withdrawal rate of 15%, and will therefore recruit 1,150 individuals to participate in the study. This information was lacking in the manuscript and has now been added to the recruitment paragraph in lines 138-139: “We aim to acquire full longitudinal datasets of 1,000 participants. We expect a withdrawal rate of 15%, and will therefore recruit 1,150 individuals to participate in the study.”.

How to deal with drop-out analyses is up to the researchers who will use the data. Partial datasets of withdrawn participants will be included in the data release, along with documentation of what parts of the data are available for each subject and information about the reasoning for withdrawal.

Submitted filename: HBS Consortium_Rebuttal letter_PLOS ONE.pdf

Click here for additional data file.

15 Sep 2021

15 Oct 2021

Dear Dr. Amir-Homayoun Javadi,

Thank you for judging our manuscript entitled ‘Protocol of the Healthy Brain Study: an accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context’ favorably. Herewith we would like to respond to the reviewer.

When we refer to line numbers in the following paragraphs, we refer to the line numbers in the revised manuscript with track changes.

Journal requirements

1) Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

We have applied the PLOS ONE style templates.

2) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

Sharing the full Healthy Brain Study (HBS) resource does not comply with the EU General Data Protection Regulation, because the HBS resource contains a substantial amount of sensitive personal data.

Applications for data access can be sent to hbs-data@radboudumc.nl. Then, the HBS scientific board reviews the application. Our governance policy ensures that all use of data is within the limits of the original purpose as described in the information brochure for participants and that only those data are shared that are relevant for answering the proposed research question.

3) Please amend your authorship list in your manuscript file to include author Lucy Overbeek.

We would like to propose that the Healthy Brain Study consortium is the only author and omit the names of the project leader Guillén Fernández and project manager Lucy Overbeek. In our view, mentioning the consortium as the only author would perfectly reflect the nature of the team-science based cross-faculty initiative from the Radboud campus in Nijmegen. We consider our roles as supportive and required for managing the project rather than as principal investigators. We understand that a corresponding author is required. Guillén Fernández fulfills the role of the corresponding author on behalf of the consortium. As stated, all members of the consortium contributed to the design of the study, edited the manuscript, and approved the final version.

Response to reviewer

* I agree that a reductionist approach is common, but several longitudinal studies surely include a broad range of variables and a holistic approach; this is not unique for HBS.

We fully agree with the reviewer that several longitudinal studies include a broad range of variables and a holistic approach. In lines 35-38 we mention that “we think that current brain research suffers from at least five key limitations and we set up the Healthy Brain Study (HBS) to tackle these five limitations together”. Thus, we consider the uniqueness of the HBS that it combines the following five strengths 1) a broad range of variables, 2) repeated assessments across one year, 3) single subject inferences, 4) real-world assessments, and 5) a population-based sample.

We propose stressing that tackling these five limitations together is the uniqueness of the HBS by adapting the sentence starting in line 94 into “In conclusion, the unique feature of the HBS is that it combines the five above-mentioned strength resulting in in-depth phenotyping of a large range of cognitive, affective, behavioral, and social dimensions with a biological sampling of brain and body-related processes.”.

However, there are other studies (e.g., Betula project) that have another focus on a longitudinal design with a very long-term perspective of more than 25 years (https://www.umu.se/en/research/projects/betula---aging-memory-and-dementia/).

* Life events are highlighted. Such events have been explored in several other past studies, and a question is whether the authors in the quite short period of 1 year expect a sufficient number of significant events to substantiate analyses? Here, the timing with the pandemic is very interesting and it is a strength of the study to capture this major event.

When designing the study, we hoped for some major national events around for example governmental elections or sports. A pandemic was of course not expected, but is indeed very interesting and offers additional opportunities.

We agree with the reviewer that one year is a rather a short period for capturing life events, but we chose the age range of 30-39 because it is a socially challenging age range that is characterized by a relatively high number of rather impactful life events (e.g., family planning, career-related changes, buying a house etc.). To assess life events, participants give responses to twenty types of life events (Brugha & Cragg, 1990). In addition, to assess the subjective impact of life events, we ask participants to rate the subjective impact the event had on their lives on a scale from 0 (no impact at all) to 10 (major impact, fundamental change). Preliminary data showed that 130 out of 298 (44%) of the HBS participants that completed the life event questionnaire at T1 experienced one or more life events in the year before participating and 78 out of 175 (45%) and 46 out of 100 (46%) of HBS participants that completed the life event questionnaire at T2 respectively T3 experienced one or more life events. As this is a protocol paper, we do not want to report any preliminary data and propose not to include the above-mentioned data on life events in the manuscript.

Reference:

Brugha, T. S. & Cragg, D. The list of threatening experiences: the reliability and validity of a brief life events questionnaire. Acta Psychiatr Scand 82, 77-81 (1990).

* The protocol has an elegant assessment of factors such as physical activity, stress, and sleep that go beyond past studies. However, to be fair, also past studies meant to target real world events (even if with scales and questionnaires).

We agree with the reviewer that many past and ongoing studies assess real-world events (even if with scales and questionnaires). We consider our approach innovative, because for two reasons.

First, we believe that assessing real-world events with wearable devices is more objective than scales and questionnaires. When we designed the study in 2017, hardly any longitudinal study included wearable devices. As the field of wearable technology has developed rapidly, in the meantime, several longitudinal studies have added wearable devices to their data collection methods. For example, subsets of UK Biobank participants and Rotterdam Study participants wore an accelerometer (Doherty et al., 2017; Koolhaas et al., 2017). Furthermore, in line with our response to the first comment of the reviewer, we would like to stress that including real-world assessments is one of the five strengths of the HBS, so it is not unique by itself. In particular, the HBS includes repeated assessments with wearable devices in three different seasons over one year starting at varying time points within a year. When we designed the study, to our knowledge, this was unique for HBS. In the meantime, a subset of UK Biobank participants is performing seasonal repeats with a wearable device (https://biobank.ctsu.ox.ac.uk/crystal/label.cgi?id=1008).

Second, the HBS combines physiological recordings with wearable devices with ecological momentary assessments using a smartphone application. We consider the additional collection of momentary assessments of mood and behavior and context information innovative.

We added this explanation to the discussion section when reflecting on the HBS study design (line 393).

References:

Doherty A. et al. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One 12(2), e0169649 (2017).

Koolhaas C.M. et al. Objective Measures of Activity in the Elderly: Distribution and Associations With Demographic and Health Factors. Journal of the American Medical Directors Association 18 (10), 838-847 (2017).

* I applaud the stress on population-based cohorts and the risk with selection bias in convenience samples. Here, it could also be mentioned that studies like the Swedish Betula project (e.g., Nyberg, et al, 2020 Ageing Res Rev) have used such an approach. In HBS, some comment is warranted on the exclusion criteria in relation to representativeness (such as taking antidepressants or having a disease that hinders physical exercise). Relatedly, the strategies to recruit participants could influence the final representativeness of the sample. For example, the involvement of employers can bias the sample to people who have a work. Have the authors any plans of assessing how representative for the general population their final sample actually will be?

We defined a population-based sample as 1,000 HBS participants (500 men and 500 women) from the Nijmegen region (≤ 15 km) of whom 220 have a low, 340 a middle, and 430 a high level of education. We perform continuous monitoring of sex and level of education for enrollment and drop-out rates. For example, when we observed that our first wave of participants consisted of mainly higher educated people, we adapted the campaign by displaying pictures and stories of real, middle educated participants in promotion materials and focused on employers with low and middle educated staff. Concerning recruiting unemployed people, we reach them by their municipalities, our social media campaign and local influencers.

* Opting out from a study and later dropping out from a study are important variables. So far, after a quite short period of time, as many as 13% withdrew (typically after the 1st assessment). I lacked information on whether the researchers will replace those who drop out at such an early stage, and also how they plan to deal with drop-out analyses.

We aim to acquire full longitudinal datasets of 1,000 participants. We expect a withdrawal rate of 15%, and will therefore recruit 1,150 individuals to participate in the study. This information was lacking in the manuscript and has now been added to the recruitment paragraph in lines 138-139: “We aim to acquire full longitudinal datasets of 1,000 participants. We expect a withdrawal rate of 15%, and will therefore recruit 1,150 individuals to participate in the study.”.

How to deal with drop-out analyses is up to the researchers who will use the data. Partial datasets of withdrawn participants will be included in the data release, along with documentation of what parts of the data are available for each subject and information about the reasoning for withdrawal.

Other changes

- Line 242, Table 1a: fertility treatment and breastfeeding are not part of the questionnaire.

- Line 295: “At the end of December 2020, the HBS included 298 participants. Forty participants (13%) withdrew from the study so far, due to personal circumstances (e.g., pregnancy) or too much burden. Most participants withdrew after the first assessment. To date, participants performed 376 lab visits: 257 participants carried out the first assessment, 83 participants the second assessment, and 36 participants the third assessment completing the entire study protocol.” has been adapted into “At the end of June 2021, the HBS included 418 participants. Seventeen-one participants (17%) withdrew from the study so far, mostly because they experienced too much burden (n=41; 58%), got pregnant (n=11; 15%), or had been given a diagnosis or medication treatment (n=8; 11%). Most participants withdrew after the first assessment. To date, participants performed 755 lab visits: 380 participants carried out the first assessment, 237 participants the second assessment, and 138 participants the third assessment completing the entire study protocol.”

- Table 1a is renamed to Table 1, Table 1b to Table 7, Table 7 to Table 8.

- Reference list: references 27, 164, 165, 166 have been added.

- Link for data access is adapted to https://www.healthybrainstudy.nl/en/data-and-methods/access in line 27 and 431.

We hope we have satisfactorily responded to the comments and are looking forward to your decision about publishing our manuscript in PLOS ONE.

On behalf of the Healthy Brain Study consortium,

Guillén Fernández Lucy Overbeek

Submitted filename: HBS Consortium_Rebuttal letter_PLOS ONE.docx

Click here for additional data file.

22 Nov 2021

Protocol of the Healthy Brain Study: an accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context

PONE-D-21-15454R2

Dear Dr. Fernández,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

The research question outlined is expected to address a valid academic problem or topic and contribute to the base of knowledge in the field.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses?

The manuscript should describe the methods in sufficient detail to prevent undisclosed flexibility in the experimental procedure or analysis pipeline, including sufficient outcome-neutral conditions (e.g. necessary controls, absence of floor or ceiling effects) to test the proposed hypotheses and a statistical power analysis where applicable. As there may be aspects of the methodology and analysis which can only be refined once the work is undertaken, authors should outline potential assumptions and explicitly describe what aspects of the proposed analyses, if any, are exploratory.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable?

Descriptions of methods and materials in the protocol should be reported in sufficient detail for another researcher to reproduce all experiments and analyses. The protocol should describe the appropriate controls, sample size calculations, and replication needed to ensure that the data are robust and reproducible.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors described where all data underlying the findings will be made available when the study is complete?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception, at the time of publication. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

(Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have responded well to my initial comments. I am fine with the ms in its current format and have no additional feedback to offer.

Reviewer #2: This manuscript describes the ongoing protocols employed by the HBS in Nijmegen. The study is a large-scale representative data gathering study that seeks to provide a major community resource in the form of a database of brain activation, brain structure, and cognitive function measurements. Overall, the study has been extremely well designed and is well under way. The major weakness of the study has been, in my opinion, that people in the neuroscience community are not generally aware of it. The manuscript would therefore be of potentially high impact because it would bring awareness of the study to a much wider audience. The manuscript is clear and well-written, which should add to its impact.

Comments

I realize that the manuscript has been in revision, although this is the first time I have seen it. While I believe that the manuscript is appropriate for publication in its current form, I have two comments.

First, I note that line 94 has a minor pluralization error. The word “strength,” should I believe, be “strengths.”

The second is somewhat more serious and it may be late in the study process to address this point. One of the great challenges with databases of this kind is the problem of multiple comparisons. It hundreds of scholars each perform hypothesis tests on the database, it is unclear how to deal with the problem of multiple comparisons effectively. This may be particularly acute in research conducted by citizen scientists. If the opportunity arose, I think it would be a great addition to the manuscript to include a section of statistical practices and multiple comparisons. I’m sure that the study has procedures in place for this, but more discussion would be welcome and might help other studies as well.

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Reviewer #1: No

Reviewer #2: No

13 Dec 2021

PONE-D-21-15454R2

Protocol of the Healthy Brain Study: an accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context

Dear Dr. Fernández:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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