How Does Physical Overtraining Affect the Brain?

Post by Shireen Parimoo

What is overtraining?

Every athlete, whether elite or recreational, strives to perform at their best. Behind every touchdown, race, or personal best is a dedicated training regimen. For example, marathon runners progressively increase their mileage week after week, with a mix of intense and easy training days. In the final “tapering” week before a race, they reduce the frequency and intensity (i.e. training load) of their running. The idea is to give the body enough time to recover from all the cumulative training in the weeks prior for optimal performance by race day.

Excessive exercise over a long period of time can lead to overtraining syndrome when there isn’t sufficient opportunity for recovery in between bouts of exercise. In addition to rest and recovery, adequate sleep, nutrition, and cross-training are also important for preventing overtraining. Functional overreaching is a common acute response to a high training load. At this stage, athletes tend to be fatigued from their training and feel like they need to exert more effort than usual to perform at their standard level. When the training load is reduced, the negative effects of functional overreaching on performance disappear within a week or so. In fact, athletes commonly experience a boost in their performance afterward, called “supercompensation”, which might explain the importance of tapering the week before a marathon.

What are the symptoms of overtraining?

Overtraining affects anywhere from 5-60% of professional athletes. If proper recovery is not built into a training regimen, then the effects of overreaching can persist and start to have a long-term impact not only on performance, but also on mood, lifestyle, and the brain. Some of the common symptoms include muscle soreness, fatigue, lowered immune response, depressive symptoms, cognitive problems like difficulty concentrating, and sleep issues.

There are three stages of overreaching and overtraining, with each stage becoming progressively worse and longer-lasting:

1. non-functional overreaching: increased stress, fatigue, and muscle soreness along with poor sleep quality. Most of the time, this can be overcome by reducing training intensity and frequency and ensuring adequate sleep (1-3 weeks).

2. sympathetic overtraining: further changes in fitness such as increased heart rate and muscular weakness, as well as higher cortisol levels and hormonal changes due to the prolonged stress (1-3 months). This is mostly observed in endurance athletes like long-distance runners.

3. overtraining syndrome: a prolonged version of overtraining that can seriously alter the brain’s stress response and impact physical and mental health (6-12+ months).

How does regular exercise affect the brain?

Neurotransmitter and hormonal imbalance contribute to overtraining. One way to think about overtraining is as a prolonged stress response to excessive exercise. Normally, the body’s stress response is regulated by the hypothalamic-pituitary-adrenal (HPA) axis. When a stressful event (i.e. an intense workout) occurs, noradrenaline levels increase and stimulate the hypothalamus in the brain. The hypothalamus releases the corticotropin-releasing factor, which stimulates the pituitary gland and also leads to increased heart rate. The pituitary gland then releases the adrenocorticotropic hormone, which stimulates the adrenal gland to produce the stress hormone cortisol. Cortisol suppresses the body’s immune response and triggers the “fight or flight” response by increasing blood glucose levels and heart rate. After a few hours, the cortisol circulating in the bloodstream inhibits the hypothalamus, terminating the stress response. Regular exercise helps the body adapt to physical stress and leads to decreased cortisol levels in response to future stressors. Importantly, this adaptation happens during the rest and recovery period. Exercise also increases serotonin levels in the brain and improves our sense of well-being. Serotonin is a neurotransmitter that affects mood, appetite, cognition, and sleep, among other important functions. Serotonin also regulates the stress response by acting on the HPA axis.

How does overtraining affect the brain?

There is little opportunity for adaptation in between bouts of exercise without recovery periods, and excessive serotonin production might further contribute to HPA axis dysfunction. With overtraining, the body remains in a chronically activated stress response state that, in the long run, can lead to changes in the structure and function of various brain regions. Though research on the effects of overtraining on the brain and cognitive functions is somewhat scarce, there is ample evidence showing that a chronically activated stress response leads to changes in the brain. For example, prefrontal areas that help us with decision-making start to change in size and have different activation patterns in chronically stressed individuals. These individuals also start to rely on automatic rather than more effortful or strategic decision-making processes.

A recent study showed that excessive training affects decision-making processes. Endurance athletes completed an overreaching or normal training phase for three weeks. They were then brought into the lab to perform a reward-based decision-making task while undergoing an fMRI scan. The overreached athletes tended to choose smaller but immediate rewards over bigger rewards in the future, and they showed reduced activity in the prefrontal cortex when making decisions. Even though the authors could not – for ethical reasons – overtrain the athletes, this study provides an exciting avenue for future research on how overtraining affects brain functioning and cognition, which has several practical implications. Not only will it improve our understanding of how overtraining might impact the important day-to-day decisions of athletes, but this knowledge can be used to inform training plans that help ensure athletes get adequate rest and nutrition.

References

Armstrong & VanHeest. The unknown mechanism of the overtraining syndrome. Sports Medicine (2002). Access the original scientific publication here.

Cadegiani. Classical understanding of overtraining syndrome. In Overtraining Syndrome in Athletes (2020). Access the original scientific publication here.

Fulford & Harbuz. Chapter 1.3 – An introduction to the HPA axis. Techniques in the Behavioral and Neural Sciences (2005). Access the original scientific publication here.

Heisler et al. Serotonin activates the hypothalamic-pituitary-adrenal axis via serotonin 2C receptor stimulation. Journal of Neuroscience (2007). Access the original scientific publication here.

Kreher & Schwartz. Overtraining syndrome – A practical guide. Sports Health (2012). Access the original scientific publication here.

Lin & Kuo. Exercise benefits brain function: The monoamine connection. Brain Science (2013). Access the original scientific publication here.

Meeusen et al. Prevention, diagnosis and treatment of the overtraining syndrome: Joint consensus statement of the European College of Sport Science (ECSS) and the American College of Sports Medicine (ACSM). European Journal of Sport Science (2013). Access the original scientific publication here.

Portugal et al. Neuroscience of exercise: From neurobiology mechanisms to mental health. Neuropsychobiology (2013). Access the original scientific publication here. 

Soares et al. Stress-induced changes in human decision-making are reversible. Translational Psychiatry (2012). Access the original scientific publication here.

Wolff et al. Chronic stress, executive functioning, and real-life self-control: An experience sampling study. Journal of Personality (2020). Access the original scientific publication here.

Twitter Behaviour is Related to Reflective Thinking

Post by D. Chloe Chung

What's the science?

Many of us are using at least one type of social media platform to help us connect with others and discuss important social issues. Despite these benefits, social media can also be misused to easily spread false information and fuel political polarization. Given the power of social media, several studies have looked at how personalities or demographic characteristics are related to the different ways people use social media. Adding to this line of research, this week in Nature Communications, Mosleh and colleagues examined how people’s cognitive style is associated with their behaviour on Twitter.

How did they do it?

The authors recruited approximately 2,000 people who regularly use Twitter, mostly from the United Kingdom and the United States. These participants took the Cognitive Reflection Test (CRT), which measures people’s tendency to follow their instinct and choose wrong answers. Specifically, this test measures one’s ability to perform self-reflective thinking to find correct answers while suppressing a “gut feeling” related to an incorrect response. A higher CRT score indicates that the participant is better at cognitive reflection. Next, the authors collected several pieces of information related to the Twitter activity of the participants, such as how many accounts they follow and what type of content they have recently tweeted. They also gathered demographic information about the participants including their education, political ideology, religion, and income. Based on these data, the authors created a co-follower network to examine what type of accounts are followed by participants who share similar CRT scores.

What did they find?

First, the authors focused on examining the content the participants consume on Twitter. The authors observed that Twitter users with higher CRT scores (i.e. more reflective thinking) showed a tendency to follow fewer Twitter accounts. From the co-follower network analysis, the authors found a distinct division in the types of Twitter accounts followed by people with higher and lower CRT scores, suggesting that critical thinking is reflected in an individual’s account-following behaviour on Twitter. Interestingly, there was a group of accounts followed by people with lower CRT scores (i.e. less reflective thinking), supporting the notion of “cognitive echo chambers,” in which people tend to interact with those who share similar ideologies. The authors analyzed the type of content participants tended to tweet and found that the degree of reflective thinking was associated with the quality of information shared. Specifically, people who think more reflectively were more likely to share higher-quality news from reliable sources, while people who engage less in reflective thinking shared political misinformation and scams more often. Upon analyzing individual words in participants’ tweets, the authors observed that more reflective people tended to use words related to morality, insight, and inhibition, which may indicate that these people are more likely to inhibit their instincts by engaging in analytical thinking.

What’s the impact?

This study demonstrates how different cognitive styles can be reflected in our behaviour on Twitter. In particular, this work shows what can drive the dissemination of misinformation on social media. In contrast to the “intuitionist” perspective that emphasizes the importance of intuition in everyday behaviours, findings from this study suggest that reflective or analytic thinking plays a crucial role in our day-to-day judgment on social media. It will be interesting to investigate whether these findings can be also applied to other social media platforms.

Mosleh et al. Cognitive reflection correlates with behavior on Twitter. Nature Communications (2021). Access the original scientific publication here.

Predicting Impulsivity in Young Adults

Post by Anastasia Sares

What's the science?

A failure to control impulsivity is common to many psychiatric conditions, which often emerge in young adulthood as the frontal lobe completes its development. Finding the specific neural mechanisms behind impulsivity could help us diagnose and treat this aspect of mental health. This week in Molecular Psychiatry, Steele and colleagues looked at the brain areas involved in impulsivity, using a large and diverse group of young adults with different mental health profiles.

How did they do it?

The authors collected functional MRI scans to measure the brain activity of a number of young adults (18-25 years old) who were seeking treatment for a variety of psychiatric conditions (as well as young adults who had no diagnosis and no treatment). Psychiatric conditions were evaluated in a structured interview, and some of those with a diagnosis also came back for a follow-up session.

During the MRI scan, participants looked at a series of faces with different emotions at varying intensities, as well as some gray ovals that had no facial information. This way, the authors could see which brain areas tracked emotional intensity.

The participants also completed an impulsivity questionnaire with 5 subcategories:

1. Negative urgency (urgency to act on negative emotions)

2. Positive urgency (urgency to act on positive emotions)

3. Lack of premeditation (not thinking ahead)

4. Lack of perseverance (giving up on things)

5. Sensation-seeking

Based on previous literature, the authors thought that impulsivity would predict:

1. Higher activity in the amygdala (a structure known for its response to fear)

2. Altered activity in the prefrontal cortex (known for inhibition and emotional control)

3. Lower connectivity between the amygdala and the prefrontal cortex (less regulation of emotional responses)

What did they find?

The authors found that the amygdala significantly responded to the emotional faces. As predicted, the strength of the left amygdala’s response to fearful faces was correlated with a person’s impulsivity, specifically negative urgency and lack of perseverance. The connectivity between the amygdala and prefrontal cortex was also related to impulsivity, with less connectivity in more impulsive people. This confirmed the authors’ second and third predictions. Finally, for the 30 participants who came for a follow-up evaluation 6 months later, the amygdala’s response to sad faces in the first session predicted overall impulsivity at follow-up.

What's the impact?

This work is a step forward in our understanding of the brain areas involved in impulsivity and may provide targets for diagnosis and treatment of psychiatric conditions. However, the authors are quick to point out that the study requires replication. Testing so many people with different psychiatric conditions is good for the generalizability of the results to the general population, but it also means that other factors related to these disorders could confound the results. Although this study attempts to remove the influence of other factors, the best confirmation is to repeat the experiment in an independent sample.

Steele et al. A specific neural substrate predicting current and future impulsivity in young adults. Molecular Psychiatry (2021). Access the original scientific publication here.