The research interests in the Saggau Lab are twofold: First, to understand the biophysics of central mammalian neurons that control both the communication between cells and their individual computational properties Second, to develop advanced optical imaging tools for studying living brain tissue that help us to achieve the first goal.
Our lab mainly focuses on synaptic transmission and dendritic integration. We have described the short-term modulation of voltage-dependent calcium channels (VDCCs) in presynaptic terminals, where the transient influx of Ca2+ determines the timing and amount of neurotransmitter release. We have also studied postsynaptic VDCCs and their modulation in dendritic spines, where transient Ca2+ elevations can trigger long-term changes in synaptic transmission, such as LTP and LTD. Further, we are probing dendritic signal integration by investigating spatio-temporal summation of individual synaptic inputs.
Techniques used in our lab to address these and other challenging Neuroscience issues include high-speed micro-photometry, as well as combined whole-cell patch clamp and confocal/multiphoton microscopy. We also employ realistic computational models that are constrained by the morphology of automatically reconstructed living neurons.
Our lab is actively involved in developing advanced optical techniques to overcome the technical difficulties inherent in stimulating and recording in the very fine structures of neuronal dendrites and synapses. We are developing imaging systems based on standing wave microscopy that support studying sub-resolution structures in living tissue. We have developed next generation optical stimulation and recording systems with improved spatio-temporal resolution based on multiphoton excitation by acousto-optic control of near infrared ultra-fast laser pulses. These advanced techniques are employed for three-dimensional structural and functional optical imaging in intact neural tissue and can provide new insights into normal and pathological brain function.
Losavio, B.E., Iyer, V., Patel, S., and Saggau, P. Acousto-optic laser scanning for multisite photo-stimulation of single neurons in vitro. Journal of Neural Engineering, 7:045002, 2010.
Losavio, B.E., Iyer, V., and Saggau, P. Two-photon microscope for multi-site micro-photolysis of caged neurotransmitters in acute brain slices. Journal of Biomedical Optics, 14:064033, 2009.
Gliko, O., Saggau, P., and Brownell, W.E. Compartmentalization of the outer hair cell demonstrated by slow diffusion in the extracisternal space. Biophysical Journal, 97:1215-1224, 2009.
Mancuso, J.J., Larson, A., Wensel, T.G., and Saggau, P. Multiphoton adaptation of a commercial low cost confocal microscope for live tissue imaging. Journal of Biomedical Optics, 14:034048, 2009.
Gliko, O., Brownell, W.E., and Saggau, P. Fast two-dimensional standing wave total internal reflection microscopy using acousto-optic deflectors. Optics Letters, 34 (6):836-838, 2009.
Losavio, B.E., Santamaria-Peng, A., Liang, Y., Kakadiaris, I.A., Colbert, C.M., and Saggau, P. Live neuron morphology automatically reconstructed from multiphoton and confocal imaging data. Journal of Neurophysiology, 100:2422-2429, 2008.
Reddy, G.D., Kelleher, K., Fink, R., and Saggau, P. Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity. Nature Neuroscience, 11:713-720, 2008.
Bansal, V, Patel, S., and Saggau, P. High-speed addressable confocal microscopy for functional imaging of cellular activity. Journal of Biomedical Optics, 11:034003, 2006.
Iyer, V., Hoogland, T., and Saggau, P. Fast functional imaging of single neurons using random-access multiphoton (RAMP) microscopy. Journal of Neurophysiology, 95:535-545, 2006.
Reddy, G.D. and Saggau, P. Fast three-dimensional scanning scheme using acousto-optic deflectors. Journal of Biomedical Optics, 10:064038, 2005.
Shown are different representations of data from a live neuron. The Raw Images are data obtained with a 3D imaging system developed in our lab. Using our automatic Reconstruction Pipeline, a realistic Model Structure is generated that can be utilized to simulate the neuronís response to complex spatio-temporal stimulation pattern by means of a Computational Model. Such predicted neuronal responses can be used to guide complex imaging experiments and will increase the experimental success rate.