Comprehensive Summary
This study introduces SpinalTRAQ, a new imaging and computational pipeline for analyzing corticospinal tract (CST) connectivity in the cervical spinal cord. Using serial two-photon tomography in fluorescently labeled mice, the authors generated high-resolution volumetric datasets and applied automated registration plus machine learning methods to map presynaptic CST terminals into distinct spinal laminae. In healthy mice, CST terminals were densest in contralateral laminae 5 and 7, with additional labeling in ipsilateral lamina 7 and modest connections to motor neurons in lamina 9. After focal motor cortex stroke, there was marked degeneration of CST terminals on the injured side and robust sprouting of terminals from the opposite hemisphere. Over the course of several weeks, this contralesional growth increased ipsilateral synapses nearly fivefold, especially in laminae overlapping original CST targets. The authors conclude that SpinalTRAQ can uncover level- and lamina-specific reorganization of CST projections following injury.
Outcomes and Implications
This work is important because recovery from stroke and spinal cord injury depends heavily on corticospinal reorganization, but quantifying these changes has been difficult. By providing a high-throughput, lamina-specific mapping tool, SpinalTRAQ enables researchers to track where and how new CST connections form after injury. Clinically, such knowledge could inform rehabilitation strategies, regenerative therapies, or neuromodulation approaches by identifying which spinal circuits are most responsive to plasticity. While SpinalTRAQ itself is a preclinical mouse tool, the principles underlying it may guide the development of future imaging and analytic methods in humans, potentially leading to more targeted therapies for motor recovery after neurological injury