most citedUncovering cognitive taskonomy through transfer learning in masked autoencoder-based fMRI reconstruction

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

math.CO2026

Turán Numbers of Linear Stars and Expanded Trees

Xinmin Hou, Anyao Wang

For an -uniform hypergraph , let $\ex_r(n,\mathcal H)$ denote the maximum number of edges in an -vertex -uniform hypergraph containing no copy of .…

cs.CV2026

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

Junfeng Xia, Wendu Li, Mengjiao Zhang +1

Cognitive tasks are organized by shared and specialized neural processes. Masked fMRI reconstruction provides a common self-supervised objective for quantifying transfer relations…

cs.CV2026

BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics

Junfeng Xia, Wenhao Ye, Junxiang Zhang +3

Whole-brain 4D fMRI generation is valuable for modeling functional brain dynamics, yet existing fMRI foundation models mainly target representation learning and downstream predicti…

eess.IV2026

FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI

Mo Wang, Wenhao Ye, Junfeng Xia +3

The success of large-scale deep learning models in neuroscience is fundamentally constrained by severe data heterogeneity. Native fMRI data aggregated from diverse sources exhibit…

cs.CE2026

Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model

Mo Wang, Wenhao Ye, Junfeng Xia +6

Self-supervised fMRI foundation models have shown promising transfer performance, yet most rely on predefined region-level parcellations that discard fine-grained voxel information…

cs.CV2026★ 1 cited

SLIM-Brain: A Data- and Training-Efficient Foundation Model for fMRI Data Analysis

Mo Wang, Junfeng Xia, Wenhao Ye +5

Foundation models are emerging as a powerful paradigm for fMRI analysis, but current approaches face a dual bottleneck of data- and training-efficiency. Atlas-based methods aggrega…

q-bio.NC2024★ 1 cited

Uncovering cognitive taskonomy through transfer learning in masked autoencoder-based fMRI reconstruction

Youzhi Qu, Junfeng Xia, Xinyao Jian +5

Data reconstruction is a widely used pre-training task to learn the generalized features for many downstream tasks. Although reconstruction tasks have been applied to neural signal…