Two separate, large cohorts reveal potential modifiers of age-associated variation in visual reaction time performance

To identify potential factors influencing age-related cognitive decline and disease, we created MindCrowd. MindCrowd is a cross-sectional web-based assessment of simple visual (sv) reaction time (RT) and paired-associate learning (PAL). svRT and PAL results were combined with 22 survey questions. Analysis of svRT revealed education and stroke as potential modifiers of changes in processing speed and memory from younger to older ages (ntotal = 75,666, nwomen = 47,700, nmen = 27,966; ages 18–85 years old, mean (M)Age = 46.54, standard deviation (SD)Age = 18.40). To complement this work, we evaluated complex visual recognition reaction time (cvrRT) in the UK Biobank (ntotal = 158,249 nwomen = 89,333 nmen = 68,916; ages 40–70 years old, MAge = 55.81, SDAge = 7.72). Similarities between the UK Biobank and MindCrowd were assessed using a subset of MindCrowd (UKBb MindCrowd) selected to mirror the UK Biobank demographics (ntotal = 39,795, nwomen = 29,640, nmen = 10,155; ages 40–70 years old, MAge = 56.59, SDAge = 8.16). An identical linear model (LM) was used to assess both cohorts. Analyses revealed similarities between MindCrowd and the UK Biobank across most results. Divergent findings from the UK Biobank included (1) a first-degree family history of Alzheimer’s disease (FHAD) was associated with longer cvrRT. (2) Men with the least education were associated with longer cvrRTs comparable to women across all educational attainment levels. Divergent findings from UKBb MindCrowd included more education being associated with shorter svRTs and a history of smoking with longer svRTs from younger to older ages.


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Behavioural & social sciences study design
All studies must disclose on these points even when the disclosure is negative. MindCrowd: Web-based voluntary response sample. We chose sample sizes based on final participant numbers after filtering and quality control steps. The data were filtered in an attempt to control some of the limitations of this sampling procedure.
The UK Biobank: With anywhere from 150,000 to over 500,000 participants, this is one of the most extensive cross-sectional studies in cognitive neuroscience; thus, the sample size is sufficient.
MindCrowd: Simple visual reaction time (svRT) After consenting to the study and answering five demographic questions (i.e., age, biological sex, years of education, primary language, and country where they reside), participants were asked to complete a web-based svRT task. We chose svRT because it is a simple central and peripheral nervous system-dependent task influenced by intelligence and brain injury. Participants were presented with a pink sphere that appeared at random intervals (between 1-10 seconds) on the screen, and they were instructed to respond as quickly as possible after the sphere appeared by pressing the enter/return key on their keyboard. Once the participant responded, the sphere disappeared until the subsequent trial. Each participant received a total of five trials. The sphere stayed on the screen until the participant responded. The dependent variable, response time in milliseconds (msec), was recorded from the sphere's appearance on the screen to the participant's key press or screen touch. Paired-associate learning (PAL) Next, participants were presented with the PAL task. For this cognitive task, during the learning phase, participants were shown 12 word pairs, one word pair at a time (2s/word pair). During the recall phase, participants were given the first word of each pair and were asked to use their keyboard to type in (i.e., recall) the missing word. This learning-recall procedure was repeated for two more trials. Before beginning the task, each participant received one practice trial consisting of three word pairs not contained in the 12 used during the test. Word pairs were presented in different random orders during each learning and each recall phase. The same word pairs and order of presentation were used for all participants. The dependent variable/criterion was the total number of correct word pairs entered across the three trials (i.e., 12 x 3 = 36, a perfect score). Demographic, medical, health, and lifestyle questions Upon completing the PAL task, participants were asked to fill out an additional 17 demographic and health/disease risk factor questions. These questions included: marital status, handedness, race, ethnicity, number of daily prescription medications, a firstdegree family history of dementia, and yes/no responses to the following: seizures, dizzy spells, loss of consciousness (more than 10 minutes), high blood pressure, smoking status, diabetes mellitus, heart disease, cancer, reported stroke, alcohol/drug abuse, brain disease, and memory problems). Next, participants were shown their results and provided different comparisons to other test takers based on the average scores across all participants' sex, age, and education demographics. On this same page of the site, participants were given the option to be recontacted for future research (see Supplementary Table 5 for the list of MindCrowd questions asked).
The UK Biobank: Complex visual recognition reaction time (cvrRT) and educational attainment. Each participant's cvrRT was based on 12 rounds of the card-game Snap. Participants were shown two cards at a time with a picture on them. Participants pressed a button on a table in front of them as quickly as possible if the images cards/matched. For each of the 12 rounds, the following data were collected: the pictures shown on the cards (Index of card A, Index of card B), the number of times the participant clicked the 'snap' button, and the latency to first click of the 'snap' button. This last record of "latency to click the button" was used as the UK Biobank's criterion for regression analyses. For Educational Attainment, the following conversions from UK Biobank (UKBb) answer codes (see http://biobank.ndph.ox.ac.uk/ showcase/coding.cgi?id=100305) to MindCrowd (MC) values were made: a) "UKBb -7 None of the above" to "MC No high school diploma," b) "UKBb 2 A levels/AS levels or equivalent" to "MC High school diploma," c) "UKBb 3 O levels/GCSEs or equivalent" to "MC High school diploma," d) "UKBb 4 CSEs or equivalent" to "MC High school diploma," e) "UKBb 5 NVQ or HND or HNC or equivalent" to "MC Some college," f) "UKBb 6 Other professional qualifications (e.g., nursing and teaching)" to" MC Some college," g) "UKBb 1 College or University degree" to "MC College degree." All UKBb participants selecting "-3 Prefer not to answer" were removed from the final dataset before model selection and analysis. While we did our best to ensure a similar education measure across UKBb MindCrowd and the UK Biobank, we realize that there are fundamental differences between US and UK schools that we cannot control or eliminate. Table 6 lists the specific UK Biobank data fields from which we derived our factors.
MindCrowd: Start: January 2013. Stop: March 2020 (i.e., data freeze to write the manuscript as new participants visit, consent, and take the test daily).
The UK Biobank: Began in 2006. The study is currently following about 500,000 participants in the UK, enrolled at ages 40 to 69. Initial enrollment took place from 2006 to 2010. All participants are monitored for at least 30 years after recruitment and initial assessment (i.e., termed "instance 0" by the Biobank).
We developed an extensive and automated data filtering pipeline (see Data Quality Control and Supplementary Figures 9-10) to address these concerns and enhance validity and accuracy. These data (i.e., raw or filtered) were excluded before analysis (i.e., listwise deletion). Exclusion resulted in dropping 0.3 % and 6.1% of MindCrowd and UK Biobank participants, respectively.

MindCrowd:
A final data set, including all qualifying participants up to 3-17-2020, was generated. See Supplementary Figure 9 for a flowchart detailing the following filtering steps. This dataset removed participants: a) with duplicate email addresses (only first entry kept), b)