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.

Memory Performance is Linked to Neural Repetition Effects Across the Lifespan

Post by Amanda McFarlan

What's the science?

Researchers have long studied neural representations of memories to understand how memories are formed and stored in the brain. One way to do this is by investigating whether neural activity in the brain changes in response to repeated exposure to the same stimuli, known as the repetition effect. Repetition effects can be observed in two different forms: a repetition suppression effect, which occurs when neural activity is lower upon the second presentation of a stimulus, or a repetition enhancement effect, which occurs when neural activity is higher upon the second presentation of a stimulus. This week in Developmental Cognitive Neuroscience, Sommer and colleagues investigated whether memory formation, as measured by neural repetition effects, was associated with memory performance across the lifespan. 

How did they do it?

The authors recruited children (7-9 years), young adults (18-30 years) and older adults (65–76 years) to participate in their study. EEG recordings were acquired for each age group while participants performed an encoding task followed by a recognition task. During the encoding task, participants were shown pictures of objects belonging to different categories (e.g. hats, trees, guitars). The entire encoding task consisted of 720 trials for the adult groups and 360 trials for the children. After completing the encoding task, the authors surprised participants with a recognition task. Participants were not told to memorize the pictures during the encoding task and did not know that they would be tested on their memory. During the recognition task, participants were shown pictures of objects and were asked to identify whether that object was old (an image they had previously seen in the encoding task), similar (an imaging belonging to a category they had previously seen in the encoding task) or new (an image belonging to a novel category). The adult groups completed 480 trials for the recognition task, while the children completed 240.

What did they find?

The authors found that participants in all age groups were able to identify whether an image was old, similar, or new at levels above chance. They showed that children had higher specific item memory (correctly identifying whether an image was old or similar) compared to both adult groups and both children and young adults had a higher lure discrimination index (the difference between images correctly identified as similar and mistaken as old) compared to older adults. However, this finding did not persist after accounting for the fact that children performed an easier and shorter task. Next, the authors examined the EEG recordings to look for changes in neural activity related to repetition effects. They found repetition suppression effects in the posterior, frontal, and central electrode sites for all age groups. They also found a repetition enhancement effect in the frontal and temporal electrode sites for both adult groups as well as in the centro-parietal electrode sites for older adults. The repetition suppression effect (observed in all age groups) and the repetition enhancement effect (observed in adults) were positively correlated with item-specific memory performance.

What’s the impact?

This study shows that item-specific memory performance for all ages is positively correlated with both repetition suppression effects and repetition enhancement effects. This suggests that memory encoding may have similar neural mechanisms in children and adults. Together, these findings provide evidence that neural repetition effects may be a useful neural indicator of memory encoding across the lifespan.

Sommer et. al. Memory specificity is linked to repetition effects in event-related potentials across the lifespan. Developmental Cognitive Neuroscience (2021). Access the original scientific publication here.