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Rallapalli, H.

Publications and source records attributed to Rallapalli, H..

2 recordsLinked to original sources

Manganese Accumulation for Genetically Induced Contrast (MAGIC) MRI in the brain across species

Mapping the mesoscale architecture of neural circuits is essential for understanding brain function, yet high-resolution anatomical tracing remains largely dependent on fluorescent reporters that require terminal histology. Here, we present Manganese Accumulation for Genetically Inducible Contrast (MAGIC) MRI, a gene expression reporter system based on the metal ion transporter Zip14 (Slc39a14) which enables noninvasive, in vivo neural tracing. In rodents, viral delivery of Zip14 enables both anterograde and retrograde tracing of cortico-thalamic and basal ganglia circuits. Mechanistic validation via laser ablation-inductively coupled plasma-time-of-flight-mass spectrometry (LA-ICP-TOF-MS) confirmed that MRI contrast changes are driven by specific Mn2+ accumulation. This permitted high-resolution visualization of neural populations and projections using clinical standard MRI sequences without supplementary contrast agents. However, addition of systemic Mn2+ further increased the signal by a factor of 2-5 fold. To facilitate objective, high-throughput analysis, we developed a fully automated pipeline for voxel-wise anomaly detection that accurately identifies and quantifies MAGIC enhanced regions in individual subjects. Finally, it is demonstrated that MAGIC is translatable to the large mammalian brain, providing the first functional demonstration of an MRI-visible reporter in the rhesus macaque. By enabling the non-invasive monitoring of neural connectivity across species, MAGIC provides a versatile, longitudinal tool for studying structural plasticity and circuit organization in the living brain.

neuroscience↗

Towards reliable reconstruction of the mouse brain thalamocortical connectivity using diffusion MRI

Diffusion magnetic resonance imaging (dMRI) tractography has yielded intriguing insights into brain circuits and their relationship to behavior in response to gene mutations or neurological diseases across a number of species. Still, existing tractography approaches suffer from limited sensitivity and specificity, leading to uncertain interpretation of the reconstructed connections. Hence, in this study, we aimed to optimize the imaging and computational pipeline for reliable reconstruction of the mouse brain thalamocortical network. We developed a dMRI-based atlas of the mouse forebrain with structural labels imported from the Allen Mouse Brain Atlas (AMBA). Using the atlas and tracer data from the Allen Mouse Brain Connectivity Atlas (AMBCA) as ground truth, we investigated the accuracy of reconstructed node-to-node thalamocortical structural connectivity and effects of imaging and tractography parameters. Our results suggest that these parameters significantly affect tractography outcomes and our atlas can be used to investigate macroscopic structural connectivity in the mouse brain. Furthermore, tractography in mouse brain gray matter still face challenges and need improved imaging and tractography methods.

bioengineering↗