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The mammalian primary sensory cortex (S1) is well-known for its precise topographic representation of body parts, yet the detailed organizational structure of motor cortices, particularly the primary (M1) and secondary motor cortex (M2), remains challenging to discern. Traditional mapping techniques, such as cytoarchitectural analysis and invasive intracranial stimulation, have yielded only coarse and imprecise representations of motor cortical organization.
To address these challenges, we utilized high-speed, multi-spectral wide-field optical mapping (WFOM) integrated with simultaneous behavioral monitoring and advanced tracking. This approach enabled real-time analysis of cortex-wide neuronal activity and whole-body behaviors in awake, spontaneously moving Thy1-jRGECO mice. By observing the dynamic and collective behavior of cortical circuits and networks over extended periods, we derived two detailed topographical maps of M1 and M2, based solely on the cortex’s intrinsic activity.
We first characterized cortical representations during resting states, where we identified structured, spontaneous fluctuations that were rapidly changing, bilaterally symmetric, and spatially heterogeneous. These distinct fluctuation patterns were highly informative of motor organization, despite their suppression during locomotion.
Using resting-state functional connectivity (RSFC) mapping, we discovered body-part–specific relationships between each S1 region and distinct areas of the medial frontal cortex, revealing a detailed M2 topography.
To map M1, we conducted retrograde tracing from the spinal cord to decorate corticospinal neurons (CSNs) with GCaMP. Real-time activity of these CSNs during locomotion provided precise evidence of forelimb and hindlimb M1 locations. Additionally, M1 regions can be consistently identified by an increase in coherence at lower frequencies (0–1.5 Hz) with S1 during transitions from rest to movement, allowing us to generalize M1 topography mapping in Thy1-jRGECO mice.
Within these mapped regions, we used the constrained least squares (CLS) method to “functionalize” the topographies of S1, M1, and M2. This allowed us to spatiotemporally unmix their unique contributions to cortical neural activity and afforded us the opportunity to investigate their distinct functional roles and dynamic interplay in generating a wide range of spontaneous behaviors. Through this investigation, we found M2’s anatomical activation became prominent only during complex and integrated movements, underscoring its critical role in higher-order motor control.