Two-Photon Microscopy for Recording Multi-Neuronal Activity in Behaving, Untethered, Intact Animals

 Understanding how neural systems encode and coordinate behavior requires the ability to record multi-neuronal activity in freely behaving animals. This dissertation focuses on developing advanced imaging techniques to overcome the challenges associated with imaging in unrestrained organisms, particularly in larval Drosophila melanogaster, whose deforming brains present unique challenges.
   
   A new tracking microscope is developed using acousto-optic deflectors (AODs) and an acoustic GRIN lens (TAG lens) to achieve axially resonant 2D random access scanning. With high axial scanning rates (70 kHz) and low latency (0.1 ms), this microscope enables the recording of neural activities from various neurons in the moving larval central nervous system (CNS) and ventral nerve cord (VNC), such as premotor neurons, bilateral visual interneurons, and descending command neurons. The technique allows for fast 3D tracking and scanning, providing valuable insights into the neural dynamics during behavior.
   
   This work also presents a method to compensate for the spatial and temporal dispersions introduced by AODs. This method only utilizes off-the-shelf components, including a transmission grating and a telescope. The compact design corrects for distortions by tuning the group delay dispersion (GDD) based on the translation of the telescope without adjustment of any other elements.
   
   Furthermore, an alternative method is developed to expand the capabilities of the tracking microscope by incorporating two excitation beams. This approach enables simultaneous tracking and imaging of a volume of the brain, providing a comprehensive view of neural activity in densely labeled neurons and neuropils.
   
   The dissertation demonstrates the potential of these new tracking and imaging techniques in recording the activity of multiple neurons and neuropils in the squishy brain of small transparent animals. These advancements facilitate investigations into neural network activity and contribute to a deeper understanding of the neural correlates of behavior.