Brain Training: Do Computerized Games Improve Cognitive Ability?

Post by Flora Moujaes

What's the science?

In recent years, a billion-dollar industry has emerged.  It posits that you can enhance your cognitive ability, and even your IQ, simply by completing computerized games. But does science really support this claim? A limited number of studies have shown that training on a cognitive task can improve your performance on other tasks that recruit similar cognitive mechanisms; however many studies have failed to replicate these results. Even when training involves different tasks that engage multiple cognitive systems, research has shown that participants just get better at completing the specific tasks, rather than improving their general cognitive ability. This week in the Journal of Experimental Psychology, Stojanoski and colleagues conducted a large-scale online study, investigating whether brain-training tasks improve cognitive ability.

How did they do it?

The authors recruited 11,000 individuals online from a total of 145 countries. Over 1000 participants were active users of commercially available brain training programs including Luminosity, Peak, Elevate, Brian HQ and Neural Nation. The brain-training participants had used such programs for an average of 8.5 months. The authors assessed the participants’ general cognitive function using the Cambridge Brian Sciences online assessment battery, which measures cognitive skills such as working memory, verbal ability, reasoning, decision-making, and inhibitory control.

What did they find?

To see if brain training produces generalizable improvements in high-level cognition, the authors compared whether on average the 1009 participants with an active history of active brain training performed better than a demographically matched group who had no such history. The authors found that there was no difference in performance between active brain trainers and non-brain trainers, even when they compared non-brain trainers to those brain trainers who had been training for longest. They also examined whether the amount of time spent using brain training programs increased cognitive performance, but found that there was no relationship between self-reported length of time participants devoted to brain training and cognitive performance.

What's the impact?

The findings of this study do not support computerized games as a way to improve cognitive performance. Given that a billion-dollar industry with over 70 million active users has been built on this premise, more research is needed into whether such brain-training programs are really worth people’s time and money. In particular, studies that employ a within-subject design or follow participants over time are needed in order to draw stronger conclusions.

A word of caution: The methodology in this study did not take into account individual improvements within-subjects (comparing each participant’s cognitive ability before and after brain training), and participants were not randomly assigned to receive brain training.

Stojanoski et al. Brain training habits are not associated with generalized benefits to cognition: An online study of over 1000 “brain trainers”. Journal of Experimental Psychology: General (2020). Access the original scientific publication here.

More Than a Watch: How Wearable Tech is Helping Advance Neuroscience

Post by Lincoln Tracy

What's the science?

Wearable technology is a fast-moving and financially lucrative industry. The adoption of this technology is primarily being driven by smartwatches. These devices can measure a range of physiological signals including heart rate, blood oxygen levels, and sweat gland activation – all while looking sleek and stylish on your wrist. Smartwatches allow scientists to collect a wide range of long-term, real-time physiological data from large numbers of people at the same time. This week in Neuron, Johnson and Picard provide a broad overview of wearable technology and highlight its potential clinical applications.

What have we learned?

One type of smartwatch data is electrodermal activity, or EDA. EDA refers to changes in the electrical properties of our skin. When our sympathetic nervous system is activated, we begin to sweat. These increases in sympathetic activity can be measured by passing a small electric current across two electrodes on the surface of the skin and calculating the electrical conductance, giving us a measure of EDA. Measuring EDA allows scientists to examine purely sympathetic activity, as EDA does not have any known parasympathetic drivers.

However, EDA is more than a simple measure of arousal. One wider-ranging application of EDA is the detection and characterization of seizures, particularly generalized tonic-clonic seizures. The association between EDA and seizure activity has been identified from concurrent electroencephalography (EEG) and EDA recordings from patients having a seizure. The recordings show unusual electrical activity across all EEG channels during the seizure. But after the seizure stops, there is a flattening of EEG activity and a surge in EDA. Several studies in both children and adults have shown that measures of EDA correlate with the duration of the post-seizure suppression of EEG activity.

Why does it matter?

Correlations such as these allow for major advances in real-world diagnostic tests and interventions. For example, EEG suppression has been observed for all EEG-monitored cases of sudden unexpected death in epilepsy (SUDEP), the second leading cause of years of potential lives lost for neurological conditions. The exact mechanisms of SUDEP are unknown, but the risk of SUDEP is greatest with frequent seizures and being alone at the time of seizure. However, by applying machine learning to EDA and accelerometry data, life-threatening seizures can be detected in real-time with almost 100% sensitivity. Detecting the seizures before they end allows caregivers and loved ones to attend to the person seizing and provide aid, potentially preventing death.

What are the next steps?

Despite EDA being studied since the 19th century, the advent and popularity of wearable technology allow scientists to explore the role of this (and other) physiological signals in everyday life. The simplicity and practicality of smartwatches allow their use in vulnerable or underserved populations where typical neuroimaging technologies cannot be used. But it is important to note that wearable technology is not without its limitations. Many devices have their own proprietary algorithms, meaning that the underlying raw data is kept under strict lock and key. There are also issues surrounding the privacy, transparency, and ethical use of the data collected by these devices. These limitations aside, the addition of wearable technology to research kits and combining their use with existing neuroimaging techniques offer the possibility of a pipeline for the effective translation of basic science to new therapies, drug delivery, and personalized medicine.

Johnson and Picard. Advancing Neuroscience through Wearable Devices. Neuron (2020). Access the original scientific publication here.

Smartphone Use in School and Academic Performance

Post by Shireen Parimoo

What's the science?

Ever since smartphones gained popularity and became a seemingly indispensable part of our lives, they have been linked to a number of negative outcomes including low grades, poor sleep, reduced social engagement, and even depression. How much of this is supported by research? Does smartphone use really have a negative impact on students’ grades? This week in Psychological Science, Bjerre-Nielsen and colleagues report results from a 2-year observational study that investigated the relationship between smartphone use among young adults and their academic performance.

How did they do it?

Participants were 470 students (19-29 years old) who were part of the Copenhagen Networks Study in Denmark. The students agreed to have their smartphone usage tracked over the course of two years, which included tracking their GPS location, social interactions, and the on/off status of the smartphone screen. The authors combined the frequency of smartphone use and class attendance to obtain measures of in-class and out-of-class smartphone usage. They also obtained student-specific characteristics such as the participants’ age, sex, personality traits (e.g., Big Five Inventory), and grade-point averages (GPA) for each course.

The authors first assessed the correlation between in-class and out-of-class smartphone use and GPA. They then specified two types of statistical models to assess the effect of smartphone use on academic performance, each of which had its own set of advantages. Panel models included data for every student’s grades and smartphone use in each of their courses, which allowed the authors to examine the effect of both student characteristics (e.g., age) and course characteristics (e.g., difficulty) on academic performance. Conversely, a cross-sectional model included data for each student’s overall grade and smartphone use and allowed them to compare their results to previously published research on the topic.

What did they find?

Greater smartphone use was related to poorer academic performance, and this relationship was stronger for in-class smartphone use. Smartphone use was also negatively correlated with students’ high-school GPA. Thus, students who used their smartphone more frequently in class had a lower GPA in both high school and university. The cross-sectional model largely replicated previous findings on this topic, namely, that greater smartphone use during class is associated with lower grades. However, results from the panel model indicate that the relationship between smartphone use and academic performance is not as strong as previously thought. Specifically, when student and course-specific characteristics like personality traits and class difficulty are accounted for in the model, the association between smartphone use and GPA is not reliable.

What's the impact?

Smartphone use may not have as detrimental an impact on students’ academic performance as previously thought. Moreover, the study highlights the importance of considering individual- and context-specific characteristics in performing this type of research, which can have an impact on the magnitude of the observed effects. Overall, these findings provide some reassurance as smartphones are becoming increasingly pervasive and students are exposed to them at younger ages than before.  

Bjerre-Nielsen et al. The negative effect of smartphone use on academic performance may be overestimated: Evidence from a 2-year panel study. Psychological Science (2020). Access the original scientific publication here.