Understanding Cognitive And Physiological Data Trends.

When you are monitoring an athlete's cognitive and physiological data trends you need to take into consideration multiple measures as well as the sessional load.

Understanding Cognitive And Physiological Data Trends.

When you are monitoring an athlete's cognitive and physiological data trends, you need to take into consideration multiple measures as well as sessional load and how this increases or decreases over the course of a mesocycle.

As cognitive load increases, you may notice negative trends in your athlete's data. This is perfectly normal because you have increased the overall cognitive load of the training sessions. Just like physical training, if you begin to reduce rest periods, increase the weight, or increase the overall volume of sets performed, an athlete's RPE may increase, bar speed decrease, or the amount of reps may slightly decrease as they adapt to the increased physical demands. The same rules apply to cognitive training. As training sessions become more demanding, cognitive and physiological data will fluctuate.

🔗 The Principles of Cognitive Progressive Overload

🔗 The Principles of Undulating Periodization and Cognitive Training

Fluctuations in cognitive and physiological data are normal when you are challenging your athletes. You cannot expect them to improve every single session if you continue to increase the overall cognitive load.

As your athlete is progressing through their mesocycle, be careful not to adjust the cognitive training plan too early in fear of it being too easy or too hard. If you notice after 9 sessions or 3 weeks that the training plan is not trending as expected, and the data is showing that they are struggling with the cognitive load, or the sessions are too easy, then review all the measures available to you and make adjustments as needed. Be careful not to chop and change things too much and too early in the name of more challenge or even "keeping things interesting" You may end up doing this at the expense of progress and lack of progression is certainly not interesting and will discourage you and your athlete.

Soma Analytics enables coaches to monitor cognitive and physiological measures from multiple views, allowing you to view independent tasks, minute-on-minute breakdowns and sessional averages. By having all views available you can identify the cognitive tasks that are creating the most cognitive stress to the athletes training program, and optimize the training plan as needed.

View an athlete's independent tasks in order to monitor progress.

Minute on Minute (MoM)

View an athletes minute on minute data to identify breaking points over a session.

Sessional Average

View all tasks combined for each session to view the sessional average.

For example, you may find every week your athlete's reaction time is improving and this could indicate that the cognitive training is too easy.  However, without looking at other measures, you can not be sure if this is the case. Just because they are getting faster, does not mean their consistency and error rate is improving. This could take another week to come together. Sometimes when you are following a diet plan your weight can fluctuate up and down before it drops and stabilizes. You may also notice your athlete's HRV decreasing over the course of a training session, but over time this will improve and their HRV will drop less sharply as adaptation occurs. This is also totally normal when pushing an athlete to their cognitive limits. Give the body and brain time to adapt to challenges and use the data as your guiding light when making any decisions. If you are not yet sure, wait another week and see what the data tells you.

Once your athlete has completed their cognitive training plan and you are analyzing the baseline data, you will need to take all measures into account. For example, if your athlete has a slower reaction time from pre to post-baseline testing, this is not necessarily a negative outcome if they have less variation in their data and their error rate has improved over the mesocycle. It is important we understand each measure and how they are linked with other measures. Below we have provided you with a quick summary of each measure so you can understand what it means if measures increase or decrease over the course of a mesocycle.

🔗 Understanding Cognitive Baseline Data


Cognitive & Physiological Measures

Reaction Time

is the amount of time it takes to respond to a stimulus, measured in milliseconds (thousands of a second).

Reaction Time ⬆

An increase in reaction time over the course of a mesocycle would indicate the athlete is performing slower, this is not the desired result for a cognitive training plan, therefore we suggest also looking at the athlete's accuracy and variation. If the athlete has slightly slower reaction times (within 5%) but their variation has improved and they are making fewer errors this is a sign of progress as they are more consistent with improved accuracy.

Reaction Time ⬇

A decrease in reaction time indicates the athlete is performing faster which is a good sign of progress but you need to ensure they are not trading speed for accuracy. You will also need to assess the athlete's variation. If the athletes variation has increased this indicates the athlete is inconsistent with their responses.


Speed

normalises the data distribution and reduces the effect of outliers (numbers that differ significantly from other observations or data points) in the data.

Speed ⬆

An increase in speed indicates the athlete is performing well and has fewer outliers in their data. It is also worth assessing the athlete's accuracy to ensure they are performing fewer errors over the course of the mesocycle.

Speed ⬇

A decrease in speed indicates the athlete is performing their cognitive training sessions with more outliers, indicating their responses are not consistent. You will notice an increase in variation to confirm this finding. We suggest also assessing the athlete's accuracy to check their error rate.


Variation

is used to measure the degree of variation between responses.

Variation ⬆

An increase in variation indicates that the athlete is performing inconsistently during their cognitive training session, you may notice the athlete has improved their reaction time but their variation has now increased. This indicates the athlete is not consistently responding to the stimulus. We suggest also looking at the athlete's accuracy to see if they are trading speed for accuracy.

Variation ⬇

A decrease in variation would indicate that the athlete is performing more consistently during their cognitive training session, this is the desired result but must also be matched with a lower reaction time, increased speed and improved accuracy.


Accuracy

is the proportion of correct responses.

Accuracy ⬆

An increase in accuracy indicates the athlete is making fewer errors but this must also be matched with low variation and fast reaction times.

Accuracy ⬇

A decrease in accuracy may indicate the athlete is not able to handle the current cognitive load or the task is too difficult or this also may indicate the athlete is trading speed for accuracy. We suggest looking at all data points to pinpoint why accuracy is decreasing over the course of the cognitive training plan.


RCS

is the number of correct responses per second.

RCS ⬆

An increase in RCS indicates the athlete is making fast responses with fewer errors, this measure takes the speed-accuracy trade-off into account but should also be linked with variation to ensure these responses are consistent.

RCS ⬇

A decrease in RCS indicates the athlete is making fast errorful responses which is not the desired result of any cognitive training plan, you will need to assess the athlete's variation to check their consistency of responses.


Physiological Measures

HRV

is the variance in time between the beats of your heart. The reason it is being discussed more now in terms of performance indicators is due to the link between HRV and the nervous system.

Heart Rate Variability (HRV) allows you to measure the effect of each cognitive task (or cognitive training plan) on your athlete’s autonomic nervous system. This can enable you to see if you are under-loading (i.e., not creating enough mental stress) or over-loading (i.e., creating too much stress) so that you can titrate your athlete’s cognitive training load by increasing and decreasing task demands, respectively. HRV is a key indicator of workload and provides you with another data measure to help you optimise your athlete's cognitive training.

rMSSD / SDNN⬆

High HRV can indicate that the athlete is adapting to the cognitive stress over the course of the mesocycle or that the task is not creating enough mental stress. This will need to be monitored over a 4-week period.

rMSSD / SDNN⬇

Low HRV can indicate the athlete is getting loaded sufficiently for the cognitive task or cognitive training plan, as long as the HRV can recover for the next cognitive training session. If the HRV continues to stay low and does not return to a baseline level you may need to adjust the cognitive training plan.


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