A new study suggests that subtle patterns in background electrical brain activity are linked to everyday verbal communication abilities in autistic youths. Scientists discovered that higher levels of background electrical activity, often described as neural noise, tend to correspond with greater difficulties in real-world communication among children with autism spectrum disorder. The research was published in the scientific journal Scientific Reports.
Autism spectrum disorder is a neurodevelopmental condition characterized by unique social interactions, communication differences, and repetitive behaviors. Structural language abilities can vary widely across the autism spectrum, but daily communication challenges remain common and significantly influence social outcomes.
To understand why these communication differences occur, researchers examine the underlying neurobiology of the brain. One primary area of focus involves the balance between neural excitation and neural inhibition within central brain networks.
Neural excitation occurs when brain cells send signals that prompt other cells to fire, whereas neural inhibition occurs when cells release signals that dampen electrical activity. When the balance between excitation and inhibition shifts too far toward excitation, it can create a noisy background signal in the cortex that makes information processing less efficient.
Lead author Vardan Arutiunian, a researcher at Seattle Children’s Research Institute, along with senior author Sara Jane Webb, a professor at the University of Washington and Seattle Children’s Research Institute, sought to observe how these electrical patterns unfold during speech processing. The authors aimed to determine whether specific brain wave signatures recorded while children listened to spoken sounds could reflect this signaling balance and correlate with practical communication skills.
To carry out the investigation, the authors evaluated 306 children and adolescents between the ages of 7 and 18 years old. The sample consisted of 162 youths diagnosed with autism spectrum disorder and 144 typically developing peers who served as a comparison group. The two groups were matched by age and sex assigned at birth.
During the experiment, participants wore electroencephalography, or EEG, caps fitted with 128 sensors that measure electrical impulses on the scalp. Electroencephalography is a non-invasive technique that records the rhythmic electrical activity generated by networks of brain cells. The youths listened to recordings of spoken three-syllable nonsense words, such as “pa-bi-ku,” while viewing a static image of a robot on a monitor.
The researchers recorded electrical signals generated across nine distinct regions of interest on the scalp. They separated these complex raw signals into periodic oscillations, which are rhythmic repeating brain waves, and aperiodic components, which represent non-repeating background electrical activity.
The aperiodic signal yields two specific measures known as the exponent and the offset. The exponent indicates how quickly electrical power decreases across higher frequencies and provides evidence regarding the balance of excitation and inhibition, while the offset reflects the total overall amount of background nerve cell firing.
The scientists also measured periodic gamma activity, which refers to fast-frequency electrical brain waves ranging between 35 and 55 Hertz. Fast gamma oscillations are known to rely heavily on specialized inhibitory nerve cells that help coordinate brain signaling during sensory tasks.
Behavioral assessments were administered to all participants to evaluate different aspects of language and cognition. Overall structural language ability, including formal grammar and vocabulary, was evaluated using the Clinical Evaluation of Language Fundamentals.
Everyday functional communication skills were measured using the Vineland Adaptive Behavior Scales, an assessment tool that relies on parent reports to evaluate practical daily verbal interaction. Cognition was assessed using standard cognitive test batteries to determine verbal and nonverbal intelligence quotients.
Statistical analyses revealed noticeable differences in background brain signals between the two participant groups. Autistic youths exhibited a lower aperiodic exponent and a lower aperiodic offset compared to their typically developing peers.
The autistic participants also displayed elevated levels of periodic gamma power during the speech listening task. Together, these three brain patterns point toward a functional shift in the autistic brain, characterized by higher baseline excitation and an increase in overall background neural noise.
When evaluating how these brain signals connected to behavioral traits, the authors observed a specific relationship. A lower aperiodic exponent and offset were associated with lower scores in everyday verbal communication on the Vineland assessment among autistic youths.
This pattern suggests that children whose brain signals reflected higher neural noise tended to experience greater challenges with practical daily communication. These same electrical signals showed no significant association with formal structural language scores, such as vocabulary and grammar knowledge.
The researchers also tracked age-related changes in these brain patterns across childhood and adolescence. Gamma oscillations tended to increase with age in both groups, while the aperiodic exponent and offset steadily decreased as participants grew older.
Interpretation of these findings requires consideration of several important study parameters and limitations. The majority of the autistic participants in the sample possessed average or above-average intellectual and verbal abilities.
Because of this sample profile, the findings might not generalize directly to individuals with autism who are nonverbal or possess minimal verbal skills. Future research will need to include participants with a wider range of cognitive and communication profiles to confirm these patterns.
In addition, scalp electroencephalography provides an indirect, system-level estimation of brain excitation and inhibition rather than a direct physical measurement of specific brain chemicals. The technology measures broad electrical field changes across the scalp rather than individual microscopic connections between nerve cells.
Future studies could combine electroencephalography with advanced imaging techniques such as magnetic resonance spectroscopy. Magnetic resonance spectroscopy is an imaging method that allows scientists to measure concentrations of specific chemical messengers in brain tissue, including gamma-aminobutyric acid and glutamate.
Despite these limitations, the research suggests that measuring background electrical signals offers a promising avenue for understanding communication differences in autism. Tracking these broad electrical properties could assist researchers in evaluating how developmental therapies influence underlying brain function over time.
The study, “Altered aperiodic EEG spectral power during speech perception task is associated with verbal communication in youths with Autism Spectrum Disorder,” was authored by Vardan Arutiunian, Megha Santhosh, Emily Neuhaus, Heather Borland, Raphael A. Bernier, Susan Y. Bookheimer, Mirella Dapretto, Abha R. Gupta, Allison Jack, Shafali Jeste, James C. McPartland, Adam Naples, John D. Horn, Kevin A. Pelphrey, and Sara Jane Webb.