A new study published in Scientific Reports provides evidence that blinking acts as a subtle but meaningful marker of attention and can become synchronized with the dynamic features of music. This synchronization appears to shape how attention functions. The findings suggest that music not only affects attention during listening but may also influence how people prepare for and respond to cognitively demanding tasks once the music stops.
The new study was conducted by Schea Fissel Brannick, an associate professor in the Speech-Language Pathology Program at Midwestern University and principal investigator of the Translational Adapted Group (TAG) Lab, and Arianna N. LaCroix, an assistant professor in the Department of Speech, Language, and Hearing Sciences at Purdue University and director of the Aphasia Brain Injury Communication and Cognition (ABC) Lab. Their shared research interests center on cognitive rehabilitation and the role of attention in language recovery, particularly in populations affected by stroke.
“This study grew out of our interest in supporting persons with aphasia—a language disorder that can also affect attention after a stroke. However, some attentional functions also decline as we age, even in the absence of stroke/neurological injury,” the researchers told PsyPost.
“So in general, I think there’s a lot of interest in how we might strengthen or ‘tune’ attention in the growing populations of aging adults, many who are at risk for stroke and aphasia. As a first step, or proof-of-concept, we designed this study to evaluate music as a potential way to strength/tune attention in aging adults without neurological problems, with the hope to extend our findings to stroke survivors with aphasia.”
The study involved 57 participants between the ages of 50 and 84. Participants were randomly assigned to one of three listening conditions: high dynamic music, low dynamic music, or silence. The high dynamic piece was a fast, emotionally bright violin sonata by Mendelssohn, while the low dynamic piece was a slower, emotionally somber string quartet by Shostakovich. Both pieces were selected based on their acoustic features, including tempo, volume changes, and spectral novelty (which refers to how much the frequency content of the music varies over time).
Before and after the 10-minute listening period, participants completed the Attention Network Test, a task designed to measure three components of attention: alerting (readiness), orienting (shifting focus), and executive control (handling conflicting information). During all phases of the experiment, researchers used high-precision eye-tracking to record blinking behavior, which has been shown in previous research to reflect shifts in attention.
To analyze the data, the researchers used advanced statistical modeling techniques to compare blink probability across the different listening conditions and during specific time windows. They also examined how blinking aligned with changes in the music’s acoustic structure, especially spectral novelty, in order to assess whether attention was entraining, or synchronizing, to the rhythm and complexity of the music.
During the music listening phase, the researchers found that participants showed non-linear patterns of blinking that aligned with the music’s changing acoustic features. Those listening to the high dynamic music tended to blink more in response to rapidly shifting sound patterns, suggesting early-stage coupling between attention and music. This group exhibited small increases in blink probability roughly 400 milliseconds after spikes in spectral novelty.
By contrast, the low dynamic music group showed delayed and reduced blinking during similar moments, with blink suppression occurring about 1.35 seconds after changes in the music. These patterns point to distinct modes of attentional engagement, with high dynamic music prompting more immediate attentional shifts and low dynamic music potentially supporting more sustained focus.
After the listening phase, the groups showed different patterns of blink behavior during the attention test. When measuring the alerting component—how well participants responded to advance warning cues—those who listened to low dynamic music blinked less following double cue trials, which typically signal the start of an upcoming task. This blink suppression suggests heightened readiness to act. In contrast, participants who listened to high dynamic music were more likely to blink in these moments, which may reflect a shift toward internally guided timing rather than external cue monitoring.
The researchers also observed group differences in executive control, measured by participants’ responses to conflicting information. The low dynamic music group blinked more frequently and earlier during these high-conflict trials, suggesting more efficient attentional resetting. Earlier blinking was associated with better performance on the task, although not necessarily with faster response times.
“In the behavioral predecessor to this paper (Dovorany et al., 2023), we were surprised to find that participants were faster on incongruent trials after listening to sad (low-dynamic) music, but not happy (high-dynamic) music,” Fissel and LaCroix explained. “So, in the present study where we analyzed eye blinking in relation to behavioral performance, we were on the lookout for unique eye blinking patterns in the low-dynamic group, but weren’t exactly sure what this might look like.
“Interestingly, participants who listened to Shostakovich (i.e., ‘low-dynamic’ piece), blinked earlier and before execution of their motor responses, which compared to the other groups, were more accurate and slightly faster than the other groups.”
“Converging publications suggest that blink inhibition (i.e., not blinking) constitutes an information processing phase that ends at the onset of a blink, which is timed to avoid missing relevant information,” the researchers continued. “Recently, Callara (2023) and colleagues suggested that in addition to signaling the end of an attentional processing window, the onset of a blink may also serve to compare post blink information to pre blink information; possibly embodying temporal difference learning.”
“While our trial and cue types were unpredictable, the timing of cue/trial onset was kept predictable within our attention network task. This allowed us to capture some universal effects of stimulus-blinking relationships, such as to alerting cues (e.g., double cue, versus no-cue trials). For example, we found that all participants, when expecting a cue but not seeing one (as in the no-cue condition), tended to blink. This result shows that all participants attended to the violation of their prediction, which further appeared to require a brief reset of the attentional system (i.e., the blink), which aligns with some of Callara’s ideas.”
“Overall, those assigned to listen to Shostakovich showed more gradual but sustained synchrony to the dynamics of this piece and after listening, performed better on incongruent trials which were the most attentionally demanding. Their performance was accompanied by a pattern of earlier blinking that tended to align with but precede their motor responses.”
As with any study, there are some limitations. Only two musical pieces were used, which narrows the range of conclusions that can be drawn about how different types of music affect attention. Future research could explore whether other genres, rhythms, or levels of acoustic complexity produce similar effects. It also remains unclear how long these effects last beyond the immediate post-listening period. Longitudinal studies would help determine whether repeated exposure to certain types of music can offer more lasting cognitive benefits.
Still, the findings provide promising early evidence that certain musical characteristics—particularly those found in slower, less complex compositions—can entrain attention in meaningful ways, potentially boosting readiness and executive function in aging adults. The researchers hope to apply this work to clinical populations, such as individuals recovering from stroke or living with aphasia, for whom attentional tuning could play a key role in rehabilitation.
“The idea that attentional synchrony to a specific category of rhythmic inputs, such as the dynamics of the Shostakovich composition, improves attentional efficiency in older adults without neurological problems, is fascinating and one that we hope will be explored further,” Fissel and LaCroix said. “We have lots of outstanding questions about this constellation of findings. Was our older demographic specifically more attuned to the slower more somber music of Shostakovich, making it easier to synchronize with the dynamics of this composition? Or would we see a similar response in a younger demographic?”
“Does earlier blinking on sufficiently challenging trials, implying a shorter processing window, suggest greater response confidence and/or the lack of self-referential processing, as in a state of flow? Or was this group simply more computationally efficient at selectively attending to the target, or conversely perhaps, better at encoding the distractors as irrelevant? We are looking forward to (hopefully) exploring some of these questions in the future.”
The study, “Blinking indexes dynamic attending during and after music listening,” was published July 16, 2025.
