Abstract
We propose a new, modular, open-source, Python-based 3D+time realistic functional magnetic resonance imaging (fMRI) data simulation software. SNAKE or Simulator from Neurovascular coupling to Acquisition of K-space data for Exploration of fMRI acquisition techniques. It is the first simulator to simulate the entire chain of fMRI data acquisition, from the spatio-temporal design of evoked brain responses to various 3D sampling strategies of k-space data with multiple coils. We now have the possibility to extend the forward acquisition model to different noise and artifact sources while remaining memory-efficient. Using this in-silico setup, we can provide a realistic and reproducible ground truth for fMRI reconstruction methods in 3D accelerated acquisition settings and explore the influence of critical parameters. This includes the acceleration factor and signal-to-noise ratio (SNR), on downstream tasks of image reconstruction and statistical analysis of evoked brain activity. In this paper, we present three scenarios of increasing complexity to showcase the flexibility, versatility, and fidelity of SNAKE: From a temporally fixed full 3D Cartesian to various 3D non-Cartesian sampling patterns, we can compare-with reproducibility guarantees-how experimental paradigms, acquisition strategies, and reconstruction methods contribute and interact together, affecting the downstream statistical analysis.