The Association Between Post-Traumatic Stress Disorder (PTSD) and Heart Disease

Post by Leanna Kalinowski 

The takeaway

There is an increased risk of heart disease among individuals with PTSD. This risk strengthens following chronic PTSD and is attributable to impaired microvascular function.

What's the science?

The human body is designed to rapidly respond to threats and stressful situations by activating the sympathetic nervous system during the stress response. This leads to an increase in cardiovascular activity, helping one to fight or flee from a stressful stimulus. This is a normal physiological response; however, it can become dysregulated in disorders such as posttraumatic stress disorder (PTSD), which is a chronic psychiatric disorder that develops in some individuals who have experienced a traumatic event. When individuals with PTSD experience a reminder of their trauma, such as a loud noise, their sympathetic nervous system is activated despite the lack of an active threat. This repeated activation is believed to cause an increased risk of heart disease among individuals with PTSD, perhaps through repeated bouts of inflammation and vascular “wear and tear”. However, the exact mechanisms underlying this risk have not been demonstrated. This week in Biological Psychiatry, Vaccarino and colleagues conducted a longitudinal twin study with war veterans to determine the mechanisms underlying the association between PTSD and heart disease.

How did they do it?

A group of 275 twins was selected from the Vietnam Era Twin Registry, which is a large national sample of adult male twins who served on active duty during the Vietnam war era. Studying twins allows for the researchers to separate out factors that are often associated with both PTSD and heart disease but do not causally link the two disorders, including genetic and environmental factors that run in families and are shared among twins. Participants each underwent two examinations that were twelve years apart, each of which included a clinical assessment of PTSD. Participants were classified into one of three groups: no history of PTSD, late-onset PTSD (i.e., not diagnosed at visit 1 but diagnosed at visit 2), and longstanding PTSD (i.e., diagnosed at both visits).

Participants also underwent myocardial perfusion at both examinations, which is a positron emission tomography (PET) imaging test that shows how well blood flows through the heart muscle. PET scans of the heart were taken before and after administration of adenosine, which is a drug that increases the workload of the heart to uncover subclinical disease. From these scans, the researchers were first able to determine whether participants lacked blood flow to the heart because of obstructive coronary artery disease, which is when plaque accumulation leads to a narrowing or blockage of the large arteries that supply blood to the heart. They were also able to assess myocardial flow reserve, which is a measure of the health of the small coronary vessels that bring blood to the heart. Unlike obstructive coronary artery disease, coronary microvascular dysfunction is caused by damage to blood vessels rather than blockage by plaque. 

What did they find?

The researchers found that PTSD is associated with coronary microvascular dysfunction, indicated by lower myocardial flow reserve. This association was particularly noted among twins with longstanding PTSD. Twins with longstanding PTSD also experienced a lower myocardial flow reserve during their second visit compared to the first, suggesting a worsening of microvascular function following prolonged PTSD. These associations persisted even after comparing twin brothers with different PTSD trajectories, ruling out shared genetic and environmental factors, as well as when accounting for other psychiatric disorders, such as depression and substance abuse. Furthermore, there was no evidence that twins with PTSD had more obstructive coronary artery disease, suggesting that the association between PTSD and heart disease is due to damage to blood vessels rather than an increase in plaque accumulation.

What's the impact?

In summary, this unique study design allowed for the researchers to examine how heart disease progresses in relation to PTSD status and duration over a 12-year period. Their findings support a link between PTSD and heart disease and suggest that microvascular function is the mechanism underlying this association. Understanding this mechanism will help in long-term efforts for risk prediction, prevention, and treatment to reduce the burden of heart disease among individuals with PTSD. 

Vaccarino et al. Posttraumatic stress disorder, myocardial perfusion and myocardial blood flow: A longitudinal twin study. Biological Psychiatry (2021). Access the original scientific publication here.

Identifying the Neural Mechanism Behind Team Flow

Post by Lincoln Tracy

The takeaway

People can get “in the zone” when playing sports, listening to music, or working — either alone or as part of a team or group. Now, researchers have identified the neural mechanism responsible for getting “in the zone” during a team-based activity.

What's the science?

“Getting in the zone”—or entering a flow state—is a psychological phenomenon characterized by intense attention and effortless reflexes, leading to a reduced sense of external awareness and a reduced sense of time. Developing a flow state can occur during individual or team-based activities, with previous research reporting the flow state from team-based activities as being more intense than individual flow states. However, the neural mechanism underlying team-based flow states is unknown. This week in eNeuro, Shehata and colleagues propose a model of these mechanisms by investigating the neural activity of partners in a team-based activity.

How did they do it?

Researchers recruited 15 participants (five males, 18-35 years) to form 10 sets of pairs—meaning some participants were paired twice. Participants played the music rhythm game “O2JAM U”, an iPad game in the same vein as Guitar Hero, under three different conditions designed to manipulate how easy it would be for participants to get “in the zone” while playing as a team. During the Team Flow condition participants played a particular song while they could see their partner and the area on the screen they had to tap to “play” the song. The Team Only condition had the same setup, but participants played a reversed and shuffled version of the song. Finally, the Flow Only condition played the same song as the Team Flow condition, but participants could see neither their partner nor the tapping area. Irrelevant beeping sounds were played throughout the songs in all conditions to test how much attention participants were paying to the game. Researchers specifically recruited people who were good at the game (i.e., they missed less than 10 cues during a song with nearly 300 cues during a practice round) and preferred playing the game with someone else, rather than by themselves.

Flow state—or how much participants felt they were “in the zone”—during the task was measured in two ways. The first was by a series of ratings that participants completed after each trial (feeling in control, enjoyment, time perception, etc.). The second was via electroencephalography (EEG) hyperscanning—where brain activity from both participants was recorded at the same time. The researchers were specifically interested in the auditory-evoked potentiations (AEP), or the brain activity that occurred in response to the irrelevant beeps played during the tasks. The more brain activity in response to the beeps, the less “in the zone” the participant was. The researchers looked at the EEG data for participants individually, as well as looking at if the level and timing of brain activity were similar between the two participants in each of the pairs.

What did they find?

First, the authors found that the AEP response was greater during the Team Only condition compared to the Team Flow and Flow Only conditions, meaning that participants were less engaged in the task during that condition. Second, they found that the AEP displayed the strongest correlation with the participant’s flow ratings during the Team Flow condition. This suggests participants were more in the zone during the Team Flow condition. Third, the authors found the beta-gamma EEG band (brain waves) had the highest power when participants were in team flow, meaning the neural signature for team flow had been identified. Finally, they found that the Team Flow condition was associated with higher interbrain neural synchrony. This means that both individuals displayed higher levels of similar brain activity when completing the task—consistent with the phenomenological experience of team flow. 

What's the impact?

This is the first study to identify an objective neural measure of team flow. These results provide a proof of concept that team flow is a distinct brain state from solo or individual flow states. The novel method used in this study will be a useful tool for future research in this area.

Shehata et al. Team flow is a unique brain state associated with enhanced information integration and inter-brain synchrony. eNeuro (2021). Access the original scientific publication here. 

The Two Stages of Action-Stopping

Post by Shireen Parimoo

The takeaway

Stopping an action that we have already initiated requires inhibitory control. There are two stages of action-stopping: an early detection stage where the brain identifies the need to stop an action, which triggers motor suppression, followed by a specific action-stopping stage.

What's the science?

Response inhibition involves the ability to stop an already initiated action (like reaching for a cup of coffee), often in response to a stop signal. In the time between seeing a stop signal and the stopping response, there is initially widespread motor suppression at 150ms followed by frontal cortex activity at 300 ms, both of which are thought to reflect inhibitory processes. However, these neural signatures may not be specific to response inhibition because the initial motor suppression has been observed in response to salient, non-stopping signals (attentional capture) and the frontal activity may occur too late to have any impact on the stopping response. This week in The Journal of Neuroscience, Tatz and colleagues investigated the time course of response inhibition during action-stopping.

How did they do it?

Two groups of young adults performed a stop-signal task in which they viewed white arrows on the computer screen (Go signal) and had to indicate the direction of the arrow. On a small subset of the trials, the arrow would change colors to magenta (Stop signal) or cyan (Ignore signal) after a variable delay period. Participants were instructed to stop their response upon seeing the Stop signal, but to continue with their response upon seeing the Ignore signal.

In the first experiment, participants (n = 27) responded with foot-pedal presses while transcranial magnetic stimulation was applied to their motor cortex to stimulate muscles in their hand. They applied stimulation at 150ms, 175ms, and 200ms after the Stop/Ignore signal onset. Muscular responses known as muscular evoked potentials (MEP) were recorded from their hands using electromyography, which allowed the authors to observe the magnitude and timing of global motor suppression (i.e., in muscles unrelated to the task). In the second experiment, participants (n = 20) completed the task with manual responses while their brain activity was recorded using electroencephalography. They also recorded partial muscular activity (prEMG) from the hands, which increases in response to the Go signal but rapidly declines when the Stop signal appears. Together, MEP and prEMG recordings allowed them to assess whether motor suppression occurred specifically in response to the Stop signal or if it was also elicited by the salient Ignore signal. Lastly, they used multivariate pattern analysis to determine whether brain activity in response to the Stop and Ignore signals could be decoded from one another.

What did they find?

Participants were slower to respond on Ignore trials than on Go trials, indicating that the Ignore signal was indeed salient and triggered additional processing despite both trials requiring a response. The amplitude of MEPs was larger in response to Go signals than the Stop and Ignore signals, and larger on failed stopping trials compared to successful stopping trials. However, MEP amplitude didn’t differ between failed stopping and Ignore trials, as participants made a response in both cases. Importantly, there was no difference in MEP amplitude between Stop and Ignore trials when stimulation was applied at 150ms, which means that the early global motor suppression is not specific to Stop signals. Peak EMGs were observed less than 200 ms following successful Stop and Ignore signals and their latency did not differ between these trial types, further supporting the idea that early motor suppression is non-specific.

Neural activity on Go trials could be reliably decoded from Stop and Ignore signals immediately after the arrow appeared on the screen. However, neural responses on successful stopping and Ignore trials could not be distinguished from each other until ~180ms following signal onset. This timing coincides with the motor suppression response, suggesting that the inhibitory process associated with action-stopping is distinct from and occurs after the global motor suppression. On the other hand, activity associated with failed stopping and Ignore trials could only be distinguished ~400ms after signal onset, demonstrating that the failure to process the Stop signal elicits a similar neural response as the processing of a salient but non-stopping signal. Thus, Stop signals are initially treated as salient stimuli, and inhibitory mechanisms specific to action-stopping come online at a later stage of processing.

What's the impact?

This study found that action-stopping involves automatic and widespread motor suppression that is then followed by the engagement of selective response inhibition processes. These findings pave the way for future research to investigate alterations in the timescale of inhibitory control and the inhibitory processes that are impacted in populations with deficits in response inhibition (e.g., psychiatric disorders like ADHD).

Tatz et al. Common and unique inhibitory control signatures of action-stopping and attentional capture suggest that actions are stopped in two stages. The Journal of Neuroscience (2021). Access the original scientific publication here.