Why music might be the brain’s best focus tool

A new study reports that people with musical training are better at locking attention onto the sounds that matter when multiple sounds occur at once.

The work tracks brain activity while listeners follow one tune and ignore another. It shows which control systems in the brain help skilled listeners stay on task.

The message is straightforward. Practice in music appears to strengthen goal-directed focus and reduce the pull from distractions, especially during difficult listening tasks.

Study lead author Cassia Low Manting from Karolinska Institutet (KI) and collaborators in the U.S. analyzed how individual differences in musical skill relate to attention. Participants heard two melodies at the same time and were told to follow the pitch changes in one of them.

The team used magnetoencephalography (MEG) to measure the brain’s tiny magnetic fields as attention shifted across sounds.

Separating sound through brain waves

The experiment tagged each melody with a distinct rhythm in its amplitude to evoke an auditory steady-state response (ASSR) in the listener’s cortex.

That response is strongest around 40 Hz and can be measured with MEG or EEG, which lets researchers separate brain activity linked to one sound from another, as shown in a reliability study.

Each melody was tagged near 40 Hz at different rates, letting brain signals be separated in the frequency domain. This design allowed the team to monitor attention toward each tune with high precision without asking people to report moment by moment what they heard.

Attention systems that push and pull

Scientists often separate attention into two types. Top-down attention is the deliberate focus we apply to a goal. Bottom-up attention is the automatic pull of sudden or salient events.

A classic model describes how frontal and parietal regions support top-down control, while a ventral network detects unexpected, behaviorally relevant stimuli.

In the new dataset, higher musical ability aligned with stronger neural signals tied to top-down focus and weaker signals tied to bottom-up distraction.

“These results suggest that musical training enhances neural mechanisms in the frontoparietal regions,” wrote Manting.

The analysis also tracked when attention peaked during each two-second tone. People whose selective attention peaked later in the tone tended to perform better. This suggests they could sustain control as time went on.

Classifying music with precision

The study combined frequency tagging with machine learning to classify which melody the listener attended to.

That approach achieved high precision in separating the neural responses to the two simultaneous melodies in magnetoencephalography data from adult volunteers.

Performance on the pitch tracking task rose with musical skill across individuals. The correlation was strongest when both melodies overlapped in time, which made the goal of following one pitch stream especially demanding.

What counts as music skill

To gauge musical background in a way that works for musicians and nonmusicians alike, the team used the Goldsmiths Musical Sophistication Index (GMSI).

This self-report inventory captures skills, engagement, and training across several domains rather than relying only on years of lessons.

The scale has been adapted and validated in multiple languages and contexts. Researchers commonly use it in hearing and cognition studies to relate everyday musical behaviors to lab performance.

Brain signals show focus

The 40 Hz auditory steady state response reflects how the cortex locks onto rhythmic features of sound. Researchers have used it widely to assay auditory function and to reveal differences across clinical groups. It is also robust in both EEG and MEG recordings.

Because each melody carried its own tagging rate, the researchers could watch attention strengthen or weaken at the precise frequency tied to the attended or ignored tune. That is hard to do with natural sounds that lack distinct tags.

Music training builds skills

Researchers have linked musical training to stronger performance on speech-in-noise tasks.

Studies using the Hearing in Noise Test with young adults found that individuals with years of musical practice were better able to follow speech against competing background sounds. Those without such training did not perform as well.

A theory called the OPERA hypothesis proposes a mechanism for these benefits. Music places high demands on precision, emotion, repetition, and focus within auditory networks that speech also uses. These demands lead to adaptive changes that can generalize to other listening challenges.

Music training in education

The new findings suggest that targeted listening exercises built around musical structures might strengthen sustained attention during complex auditory tasks.

Such exercises could be relevant where students or patients need to follow instructions or voices under noisy conditions.

If educators use simple, repeatable pitch tracking tasks and gradually raise difficulty, they might train the same control systems that the study observed. Clinicians could explore similar tasks to support rehabilitation for attention control after injury.

Future research directions

This report links musical sophistication to specific neural markers of top-down focus and to better performance in a demanding listening task.

The design does not prove that training alone caused those differences, so longitudinal work will matter.

Future studies will test how much practice is needed, which elements of training matter most, and how long benefits last. They can also track whether specific instruments or ensemble work confer distinct advantages.

Broader implications of the study

The pattern of stronger frontal and parietal engagement for goal directed focus and reduced susceptibility to distraction matches long standing accounts of attention networks.

Those accounts emphasize the key roles of lateral prefrontal regions and parietal cortex in maintaining task sets and selecting relevant input.

By aligning those theories with precise neural readouts tied to individual sounds, this study narrows the gap between broad models and moment to moment control in real listening. It also shows how frequency tagging can isolate neural signals when sounds overlap in time.

The study is published in Science Advances.

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