Early brain responses to words predict developmental outcomes in children with autism

The pattern of brain responses to words in 2-year-old children with autism spectrum disorder predicted the youngsters’ linguistic, cognitive and adaptive skills at ages 4 and 6, according to a new study.

The findings, published May 29 in PLOS ONE, are among the first to demonstrate that a brain marker can predict future abilities in children with autism.

“We’ve shown that the brain’s indicator of word learning in 2-year-olds already diagnosed with autism predicts their eventual skills on a broad set of cognitive and linguistic abilities and adaptive behaviors,” said lead author Patricia Kuhl, co-director of the University of Washington’s Institute for Learning & Brain Sciences.

“This is true four years after the initial test, and regardless of the type of autism treatment the children received,” she said.

In the study, 2-year-olds – 24 with autism and 20 without – listened to a mix of familiar and unfamiliar words while wearing an elastic cap that held sensors in place. The sensors measured brain responses to hearing words, known as event-related potentials.

The research team then divided the children with autism into two groups based on the severity of their social impairments and took a closer look at the brain responses. Youngsters with less severe symptoms had brain responses that were similar to the typically developing children, in that both groups exhibited a strong response to known words in a language area located in the temporal parietal region on the left side of the brain.

This suggests that the brains of children with less severe symptoms can process words in ways that are similar to children without the disorder.

In contrast, children with more severe social impairments showed brain responses more broadly over the right hemisphere, which is not seen in typically developing children of any age.

“We think this measure signals that the 2-year-old’s brain has reorganized itself to process words. This reorganization depends on the child’s ability to learn from social experiences,” Kuhl said. She cautioned that identifying a neural marker that predicts future autism diagnoses with assurance is still a ways off.

The researchers also tested the children’s language skills, cognitive abilities, and social and emotional development, beginning at age 2, then again at ages 4 and 6.

The children with autism received intensive treatment and, as a group, they improved on the behavioral tests over time. But the outcome for individual children varied widely and the more their brain responses to words at age 2 were like those of typically developing children, the more improvement in skills they showed by age 6.

In other studies, Kuhl has found that social interactions accelerate language learning in babies. Infants use social cues, such as tracking adults’ eye movements to learn the names of things, and must be interested in people to learn in this way. Paying attention to people is a way for babies to sort through all that is happening around them and serves as a gate to know what is important.

But with autism, social impairments impede children’s interest in, and ability to pick up on, social cues. They find themselves paying attention to many other things, especially objects as opposed to people.

“Social learning is what most humans are about,” Kuhl said. “If your brain can learn from other people in a social context you have the capability to learn just about anything.”

She hopes that the new findings will lead to brain measures that can be used much earlier in development – at 12 months or younger – to help identify children at risk for autism.

“This line of work may lead to new interventions applied early in development, when the brain shows its highest level of neural plasticity,” Kuhl said.

Brain-mapping increases understanding of alcohol’s effects on college freshmen

A research team that includes several Penn State scientists has completed a first-of-its-kind longitudinal pilot study aimed at better understanding how the neural processes that underlie responses to alcohol-related cues change during students’ first year of college.

Anecdotal evidence abounds attesting to the many negative social and physical effects of the dramatic increase in alcohol use that often comes with many students’ first year of college. The behavioral changes that accompany those effects indicate underlying changes in the brain. Yet in contrast to alcohol’s numerous other effects, its effect on the brain’s continuing development from adolescence into early adulthood — which includes the transition from high school to college — is not well known.

Penn State psychology graduate student Adriene Beltz, with a team of additional researchers, investigated the changes that occurred to alcohol-related neural processes in the brains of a small group of first-year students.

Using functional magnetic resonance imaging (fMRI) and a data analysis technique known as effective connectivity mapping, the researchers collected and analyzed data from 11 students, who participated in a series of three fMRI sessions beginning just before the start of classes and concluding part-way through the second semester.

"We wanted to know if and how brain responses to alcohol cues — pictures of alcoholic beverages in this case — changed across the first year of college," said Beltz, "and how these potential changes related to alcohol use. Moreover, we wanted our analysis approach to take advantage of the richness of fMRI data."

Analysis of the data collected from the study participants revealed signs in their brains’ emotion processing networks of habituation to alcohol-related stimuli, and noticeable alterations in their cognitive control networks.

Recent studies have indicated that young adults’ cognitive development continues through the ages of the mid-20s, particularly in those regions of the brain responsible for decision-making or judgment-related activity — the sort of cognitive “fine tuning” that potentially makes us, in some senses, as much who we are (and will be) as any other stage of our overall development.

Other recent studies suggest that binge drinking during late adolescence may damage the brain in ways that could last into adulthood.

Beltz’s study indicates that connections among brain regions involved in emotion processing and cognitive control may change with increased exposure to alcohol and alcohol-related cues. Those connections also may influence other parts of the brain, such as those still-developing regions responsible for students’ decision-making and judgment abilities.

"The brain is a complex network," Beltz said. "We know that connections among different brain regions are important for behavior, and we know that many of these connections are still developing into early adulthood. Thus, alcohol could have far-reaching consequences on a maturing brain, directly influencing some brain regions and indirectly influencing others by disrupting neural connectivity."

While in an fMRI scanner at the Penn State Social, Life and Engineering Sciences Imaging Center, students participating in the study completed a task: responding as quickly as possible, by pressing a button on a grip device, to an image of either an alcoholic beverage or a non-alcoholic beverage when both types of images were displayed consecutively on a screen. From the resulting data, effective connectivity maps were created for each individual and for the group.

Examining the final maps, the researchers found that brain regions involved in emotion-processing showed less connectivity when the students responded to alcohol cues than when they responded to non-alcohol cues, and that brain regions involved in cognitive control showed the most connectivity during the first semester of college. The findings suggest that the students needed to heavily recruit brain regions involved in cognitive control in order to overcome the alcohol-associated stimuli when instructed to respond to the non-alcohol cues.

"Connectivity among brain regions implicated in cognitive control spiked from the summer before college to the first semester of college," said Beltz. "This was particularly interesting because the spike coincided with increases in the participants’ alcohol use and increases in their exposure to alcohol cues in the college environment. From the first semester to the second semester, levels of alcohol use and cue exposure remained steady, but connectivity among cognitive control brain regions decreased. From this, we concluded that changes in alcohol use and cue exposure — not absolute levels — were reflected by the underlying neural processes."

Although the immediate implications of the pilot study for first-year students are fairly clear, there are still a number of unanswered questions related to alcohol’s longer-term effects on development, for college students after their first year and for those same individuals later in life.

To begin exploring those potential long-term effects, Beltz has planned a follow-up study to track a larger number of participants over a greater length of time.

Research shows why not everyone learns from their mistakes

Some people do not learn from their mistakes because of the way their brain works, according to research led by an academic at Goldsmiths, University of London.

The research, led by Professor Joydeep Bhattacharya in the Department of Psychology at Goldsmiths, examined what it is about the brain that defines someone as a ‘good learner’ from those who do not learn from their mistakes.

Professor Bhattacharya said: “We are always told how important it is to learn from our errors, our experiences, but is this true? If so, then why do we all not learn from our experiences in the same way? It seems some people rarely do, even when they were informed of their errors in repeated attempts.

"This study presents a first tantalising insight into how our brain processes the performance feedback and what it does with this information, whether to learn from it or to brush it aside."

The study, published in a recent issue of the Journal of Neuroscience, investigated brainwave patterns of 36 healthy human volunteers performing a simple time estimation task. Researchers asked the participants to estimate a time interval of 1.7 seconds and provided feedback on their errors. The participants were then measured to see whether they incorporated the feedback to improve their future performances.

'Good learners', who were successful in incorporating the feedback information in adjusting their future performance, presented increased brain responses as fast as 200 milliseconds after the feedback on their performance was presented on a computer screen.

This brain response was weaker in the poor learners who did not learn the task well and who showed decreased responses to their performance errors. The researchers further found that the good learners showed increased communication between brain areas involved with performance monitoring and sensorimotor processes.

Caroline Di Bernardi Luft, one of the research paper’s co-authors from the Federal University of Santa Catarina, commented: “Good learners used the feedback not only to check their past performance, but also to adjust their next performance accordingly.”

The brain responses correlated highly with how well the volunteers learned this simple task over the course of the experiment, and how good they were at maintaining the learned skill without any guiding feedback.

"Though these results are very encouraging in establishing a correlation between brains responses and learning performance, future studies are needed to identify a causal role of these effects," Professor Bhattacharya added.