Beyond Single-Source Cognitive Taskonomy:Multi-Source Task Relations through fMRI Transfer Learning

Cognitive tasks are organized by shared and specialized neural processes.

Masked fMRI reconstruction provides a common self-supervised objective for quantifying transfer relations among task states, but existing reconstruction-based taskonomies mainly study one-to-one transfer from a single source task to a target.

Here, we extend an fMRI cognitive taskonomy from single-source to multi-source transfer across 23 Human Connectome Project task states and use Boolean Integer Programming (BIP) to analyze budget-constrained task allocation.

We train 1,127 task-specific and transfer models.

Single-source transfer is directional and paradigm structured: motor states transfer well within the motor paradigm but provide limited support to most non-motor targets, consistent with a shared sensorimotor execution system and effector-specific representations.

Multi-source transfer depends on the composition of the source set, suggesting that many-to-one task relations are not fully captured by pairwise taskonomy alone.

Across supervision budgets, BIP repeatedly allocates direct supervision to several 0-back and 2-back working-memory states, although these states are not consistently the strongest individual sources.

This pattern may reflect the integration of perceptual, attentional, and executive processes in working-memory tasks.

Together, these findings reveal a cross-paradigm-limited motor cluster and working-memory states with high priority under the specified global allocation objective.

Our study extends reconstruction-based fMRI taskonomy from one-to-one transfer to many-to-one task relations and budget-constrained task dependencies.