  Oscillating Steady-State Imaging (OSSI) is a recent fMRI acquisition method
that exploits a large and oscillating signal, and can provide high SNR fMRI.
However, the oscillatory nature of the signal leads to an increased number of
acquisitions. To improve temporal resolution and accurately model the
nonlinearity of OSSI signals, we build the MR physics for OSSI signal
generation as a regularizer for the undersampled reconstruction rather than
using subspace models that are not well suited for the data. Our proposed
physics-based manifold model turns the disadvantages of OSSI acquisition into
advantages and enables joint reconstruction and quantification. OSSI manifold
model (OSSIMM) outperforms subspace models and reconstructs high-resolution
fMRI images with a factor of 12 acceleration and without spatial or temporal
resolution smoothing. Furthermore, OSSIMM can dynamically quantify important
physics parameters, including $R_2^*$ maps, with a temporal resolution of 150
ms.
