The putamen is a major hub of the basal ganglia that emerges early in gestation. However, whether its mature organization is established before birth or emerges postnatally remains unknown. Using cross-sectional and longitudinal quantitative MRI (R1 and R2*, related to tissue density and iron, respectively), and diffusion MRI, we characterized the development of putamen’s microstructure and its white matter connectivity with cortex from birth to 12 months and compared their trajectories with those in adults. Despite its prenatal emergence, the putamen undergoes substantial postnatal development. R1 increases from birth to 12 months, producing a prominent anterior–posterior gradient, whereas R2* increases primarily between age one and adulthood, producing a medial– lateral gradient. Cortico-putamen white matter connectivity is diffuse in infants but becomes topographic in adults, with anterior putamen linked to frontal cortex and posterior putamen to sensorimotor cortex. In autism spectrum disorder, this organization is largely preserved and accompanied by increased anterior putamen–prefrontal connectivity. Our findings reveal distinct spatial developmental trajectories of putamen microstructure and cortical connectivity providing a developmental framework for understanding the organization of the putamen in infancy, which has implications for assessing neurodevelopmental disorders of the basal ganglia. Teaser From birth to one year, the putamen develops distinct microstructural gradients and increasingly topographic cortical connections.
Vaidehi S. Natu, Christina Tyagi, Xiao-Qian Yan et al.· bioRxiv· 0 citations
Purpose To develop a Field-Correcting GRAPPA (FCG) technique to correct the spatiotemporal-varying phase errors in EPI caused by eddy currents. Methods The fast-changing gradient in EPI causes strong eddy current effects and associated spatiotemporal-varying phase errors, producing significant image artifacts. The use of higher gradient amplitude, slew rate, and ramp sampling factor for faster imaging exacerbates this problem. In this work, FCG was developed to address this challenge by using a multi-layer perceptron (MLP) to provide a compact representation of a family of GRAPPA-like kernels that correct the spatiotemporal-varying phase errors in the data. A dedicated calibration pipeline was designed to acquire high-quality source and target data for MLP training in both slice-by-slice and simultaneous multi-slice (SMS) acquisitions. To validate FCG’s assumptions and performance, a field camera was used to provide ground-truth measurement of phase patterns. The performance of FCG was further validated on phantom and in vivo experiments using demanding EPI trajectories across multiple 3T and 7T systems. Results Field camera measurements revealed strong spatiotemporal phase variations along the kx direction that repeat along ky during EPI readouts. The experiments on high-performance systems across 3T and 7T demonstrate that FCG can provide superior correction for the artifacts induced by spatiotemporal-varying phase errors compared with existing approaches. Conclusion FCG is an effective and robust method for correcting spatiotemporal phase errors in EPI, enabling improved image quality on high-performance systems.
Nan Wang, D. Abraham, Zachary Shah et al.· bioRxiv· 0 citations
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