Cognitive Clock

We introduce model of Cognitive Clock that estimates age of an individual based on the performance in the 3 cognitive tests:

1. Sensomotor test. Reversed letters
2. Sensomotor test. Arithmetic expressions
3. Campimetry test. Object disrimination in different hues.

Cognitive tests description

The detailed description can be found in the supplementary materials of the paper.

Scheme of the campimetry test:

Scheme of the sensomotor test:

ApWay platform

The results of cognitive tests can be obtained on the ApWay platform: http://platform.apway.ru/

To use the platform in the Laboratory one should create an "Expert" account, add a new participant and assign the 3 tests from the pre-selected set. Next, participant takes part in the testing. Finally, an expert downloads results of tests and got 3 csv files. Examples of cognitive test results are presented in the data folder.

Getting Started

Prerequisites

• Python 3.8+
• pip
• sklearn
• pandas
• numpy
• pickle
• pathlib2

Installing

Clone repo:

git clone https://github.com/mike-live/cognitive-clock

Run

The cognitive age is computed for cognitive test results stored in the folder data. The format of those files is presented in the following section (Format of csv files).

To run the model:

python cognitive_clock_run.py data

Output for example cognitive test results:

Cognitive age: 25.180906058836847

Format of csv files

Sensomotor tests. Arithmetic expressions (SM1). Reversed letters (SM2)

Resulting file (See for ex. data/SM1.csv and data/SM2.csv) consists of the following columns: # -- the number of stimulus presentation Stimul -- the ID of stimulus Goal -- the goal of participant: 0 - shouldn't click, 1 -- should click Duration -- the duration of the stimulus presentation (ms) Interval -- the interval between two stimulus presentations (ms) Show -- the time of stimulus appearing from the test start (ms) Hide -- the time of stimulus disappearing from the test start (ms) Down -- the time of mouse down from the test start (ms) Up -- the time of mouse up from the test start (ms) SMR -- sensorimotor reaction; difference time between Up and Show -- duration of dicision making and response time (ms) MR -- motor reaction; difference time between Up and Down -- duration of time mouse were pressed (ms) ERR_1 -- the number of missed correct stimuli ERR_2 -- the number of double clicks ERR_3 -- the number of clicks on incorrect stimuli

Campimetry test

Resulting file (See for ex. data/CM.csv) consists of the following columns: Stimul -- the ID of stimulus H -- the starting hue of the background and object in the HSL model (0-360) H+ -- the finishing hue of the object given by participant to recognize object (normal campimetry task) dH+ -- the number of shades added by participant to recognize object (difference between H+ and H) H- -- the finishing hue of the object given by participant to recognize object (inverse campimetry task) dH- -- the number of shades until object hue matches background hue (difference between H- and H) t+ -- the time of solving normal campimetry task t- -- the time of solving inverse campimetry task ERR -- the number of incorrect object recognition ERR_LIM -- number of clicks after hue of the object is matches background hue

Citation

Krivonosov M.I., Kondakova E.V., Polevaya S.A., Franceschi C., Ivanchenko M.V., Vedunova M.V. A new cognitive clock matching phenotypic and epigenetic ages. [Preprint.] April 22, 2022.

Authors

• Krivonosov Mikhail -- Model implementation, data analysis mike_live
• Kondakova Elena -- Participants recruitment, study organisation
• Polevaya Sofia -- ApWay platform access, the cognitive tests inventor
• Franceschi Claudio -- Project vision
• Ivanchenko Mikhail -- Project vision
• Vedunova Maria -- Project vision

Acknowledgments

We acknowledge support by the grant of the Ministry of Education and Science of the Russian Federation Agreement No. 075-15-2019-871.