Same Networks, Different Dynamics: Parsimony in Auditory Cognitive Task Processing

Distinct cognitive states might be supported either by dedicated, task-specific brain networks or by flexible modulation within shared ones, a distinction central to understanding how the brain allocates neural resources. Guided by the principle of parsimony, we hypothesized that both language and numerical cognition, when matched for sensory modality and attentional demand, would engage a common network architecture differentiated primarily through targeted modulation of connectivity strength and temporal dynamics rather than wholesale reconfiguration. We applied a jackknife-based dynamic functional connectivity approach to examine time-varying network engagement during auditory language comprehension and auditory math problem-solving in 172 age- and sex-matched participants from the Human Connectome Project-Young Adult cohort, using the Desikan-Killiany atlas and an 85% participation threshold. Of the significant connections identified, many were retained across both tasks, with 87 connections common to story and math, compared with 26 story-associated and 11 math-associated connections. Rather than indicating a novel shared-core architecture, this overlap is consistent with prior evidence that task functional connectivity is strongly constrained by a common intrinsic connectivity backbone. We therefore used the shared edge set as a common network framework for testing how two modality-matched, but cognitively distinct auditory tasks differ in connectivity strength and temporal variability. Among the 87 shared connections, 84 showed significant task-related differences in mean connectivity strength, indicating that story-math differentiation was expressed primarily through quantitative modulation of shared connections rather than wholesale changes in edge membership. Exploratory rolling-correlation analyses further suggested that some edges may show temporal variability in math-story connectivity correspondence even when mean connectivity strength is similar, highlighting a potential dynamic feature not captured by static connectivity estimates alone. Together, these findings suggest that story and math processing rely on a broadly shared connectivity backbone, while task differentiation emerges through graded modulation of connection strength and, in some cases, temporal variability.