Abstract P791: A Lesion-Based Toolbox to Study Ischemic Stroke in Primates

Abstract

The primate cortex is a highly complex structure responsible for a variety of sophisticated tasks and behaviors including long-term memory storage, sensation, movement, and vision. However, little is understood with respect to the underlying cortical physiology and dynamics following injury. It is essential that these phenomena are studied in a model which shares a high degree of complexity and evolutionary history with human cortex: the non-human primate (NHP) cortex. Such studies would allow for the development of improved tools and strategies for treating neurological disorders such as stroke. However, current methods of inducing cortical lesions in NHP pre-clinical studies often require surgical skill, produce variable results, and lack controllability of lesion size and location. Methods: To address these challenges for the development of effective therapies, we developed a versatile lesion-based toolbox for studying NHP cortical physiology.First, we demonstrated the photothrombotic technique, wherein intravenous infusion of a photosensitive dye followed by targeted cortical illumination leads to the formation of localized thrombi in the vasculature. With this method, we induced ischemic lesions extending through all layers of sensorimotor cortex in 5 adult macaques. To validate the disruption of blood flow in cortical microvasculature in vivo , we employed optical coherence tomography angiography (OCTA) imaging. Additionally, we implanted a semi-transparent electrocorticography array to record neural activity before, during, and after the induction of lesions. The transparency of the array enabled us to illuminate through the array to induce lesions and acquire OCTA images to register electrodes to ischemic areas in vivo . Thus, we observed the dynamics of the underlying network neural activity as lesions were developing. Histological staining validated neuronal cell death and was used to estimate lesion volumes. Finally, we developed a computational model to predict lesion sizes based on illumination parameters. In combination with behavioral findings, this toolbox can drive the development of future rehabilitative therapies for stroke at clinically relevant time scales in pre-clinical studies.