Brain plasticity and functionality explored by non-linear opticalmicroscopy

In combination with fluorescent protein (XFP) expression techniques, two-photon microscopy has become anindispensable tool to image cortical plasticity in living mice. In parallel to its application in imaging, multi-photonabsorption has also been used as a tool for the dissection of single neurites with submicrometric precision withoutcausing any visible collateral damage to the surrounding neuronal structures. In this work, multi-photon nanosurgery isapplied to dissect single climbing fibers expressing GFP in the cerebellar cortex. The morphological consequences arethen characterized with time lapse 3-dimensional two-photon imaging over a period of minutes to days after theprocedure. Preliminary investigations show that the laser induced fiber dissection recalls a regenerative process in thefiber itself over a period of days. These results show the possibility of this innovative technique to investigateregenerative processes in adult brain.In parallel with imaging and manipulation technique, non-linear microscopy offers the opportunity to optically recordelectrical activity in intact neuronal networks. In this work, we combined the advantages of second-harmonic generation(SHG) with a random access (RA) excitation scheme to realize a new microscope (RASH) capable of optically recordingfast membrane potential events occurring in a wide-field of view. The RASH microscope, in combination with bulkloading of tissuewith FM4-64 dye, was used to simultaneously record electrical activity from clusters of Purkinje cells in acute cerebellarslices. Complex spikes, both synchronous and asynchronous, were optically recorded simultaneously across a givenpopulation of neurons. Spontaneous electrical activity was also monitored simultaneously in pairs of neurons, whereaction potentials were recorded without averaging across trials. These results show the strength of this technique indescribing the temporal dynamics of neuronal assemblies, opening promising perspectives in understanding thecomputations of neuronal networks