Abstract: Despite decades of investigation, the cognitive effects of music listening remain inconsistent. While numerous studies demonstrate that music can improve attention, memory, and creativity, others reveal interference or null effects. These contradictory findings, often described as the “double-edged sword effect”, highlight the lack of a unifying theoretical framework explaining when and how music facilitates or impairs cognition. Moving beyond affective and motivational interpretations, this study redefines the problem through the lens of cognitive neuroscience by introducing a new Music-Attention Network Model grounded in the attention network theory (Posner & Petersen, 1990). This integrative model positions attention as the central mechanism through which music exerts its influence on cognitive processing.
The model proposes that music affects cognition via three interrelated regulatory pathways—emotional arousal, cognitive load, and temporal dynamics—each corresponding to distinct attentional sub-networks (alerting, orienting, and executive control). Together, these pathways explain the context-dependent and state-dependent nature of music’s cognitive impact.
The emotional arousal pathway proposes that music influences cognitive efficiency by altering both affective and physiological states. Drawing on the broaden-and-build theory, the model suggests that pleasant, moderately arousing music expands the scope of attention and improves orienting efficiency, whereas highly arousing or unpleasant music tends to narrow attentional focus and impair performance. Moderate emotional stimulation appears to promote flexible and adaptive allocation of attentional resources, while excessive arousal or negative affective tone triggers over-focusing and cognitive rigidity. This dual mechanism provides a coherent account of the bidirectional effects of music reported across behavioral, electrophysiological, and neuroimaging studies.
The cognitive load pathway emphasizes the interplay between external auditory input and the limited capacity of working memory. Background music competes with task-related processing for attentional resources; its impact follows a non-linear, inverted-U pattern consistent with the Yerkes-Dodson law. Moderate external load can stabilize alertness and reduce mind-wandering, whereas overload induces interference. Individual differences—such as working memory capacity, personality traits, and task complexity—further moderate this relationship. The concept of an “optimal cognitive load level” thus clarifies why music benefits simple or monotonous tasks but hinders complex or high-demand ones.
The temporal dynamic pathway introduces the dimension of time into understanding how music shapes cognitive processing. The effects of music are inherently dynamic rather than static, evolving through processes such as emotional aftereffects, habituation, and changes in arousal regulation over time. In advance music conditions, short-term facilitation often arises from residual arousal that gradually diminishes, whereas background music may initially sustain vigilance but later induce fatigue through prolonged engagement. This temporal dynamicity highlights that the impact of music depends not only on its acoustic features but also on the temporal distance between listening and task performance, revealing a time-sensitive pattern of cognitive modulation.
The model also incorporates insights from the Dynamic Attending Theory (DAT), which explains how rhythmic structures in music synchronize internal attentional rhythms with external temporal regularities through neural entrainment. This synchronization allows listeners to anticipate upcoming events and allocate attentional resources precisely at predicted moments of significance. In this way, musical rhythm transforms temporal predictability into enhanced attentional precision. Integrating this mechanism with the attention network framework bridges the temporal and spatial dimensions of attentional control, positioning DAT as a complementary account of how music dynamically guides the flow of attention over time.
Collectively, the Music-Attention Network Model provides a unified explanation for the dual nature of music’s cognitive effects. Whether facilitative or disruptive, the outcome depends on the dynamic interaction among emotional arousal, cognitive demand, temporal context, and individual characteristics. Rather than treating music as a fixed enhancer or distractor, the model conceptualizes it as a context-sensitive modulator operating through multiple, interacting pathways. A further theoretical innovation lies in the concept of functional generalization, which proposes that music-induced improvements in attentional efficiency can transfer to higher-order cognitive domains such as working memory, reasoning, and creativity. Within a top-down control framework, music optimizes executive networks by promoting rhythmic entrainment and cross-frequency phase synchronization, thereby improving neural efficiency across cognitive domains. Converging evidence from music training research and neuroimaging studies also supports this view: long-term musical experience enhances connectivity among auditory, parietal, and prefrontal cortices, reflecting domain-general neural plasticity.
This framework offers several methodological implications. Future studies should employ multi-level designs that integrate behavioral paradigms (e.g., the Attention Network Test) with neuroimaging techniques such as fMRI, fNIRS, or EEG to directly quantify how different musical conditions modulate each attentional sub-network. Computational modeling approaches—including reinforcement learning and neural dynamic simulations—can further characterize how musical features compete or cooperate with task demands in the allocation of cognitive resources.
In summary, this study advances a novel theoretical framework that reconceptualizes the relationship between music listening and cognitive processing. It demonstrates that attention—rather than emotion or motivation alone—serves as the core mediator linking musical experience to cognitive outcomes. By introducing the constructs of optimal arousal, optimal load, temporal dynamicity, and functional generalization, the model provides a cohesive and testable account of prior inconsistencies and establishes a foundation for future cross-disciplinary research. This integrative perspective enriches the understanding of music’s role in cognition, offering new insights for both theoretical inquiry and applied domains such as education, rehabilitation, and human-computer interaction.

Key words: music listening, attentional network, background music, advance music, emotional experience