In this webinar, Andrea Benucci, PhD discusses a setup developed in his laboratory for high-throughput behavioral training of mice based on voluntary head fixation. He describes its flexible use for behavioral training and concurrent neural recordings, delving into some technical considerations related to user-specific customizations as well.
In Andrea's lab, they study the neural substrate of visual processing and vision-based decision making. To this end, they aim to define a research framework capable of linking neural architectures to the underlying computations. The solution they have developed is to integrate experimental methods for all-optical dissection of neuronal circuits with large-scale dynamical network models based on artificial neural networks (aNNs). The connectivity architecture of aNNs closely mirror that of biological neural networks, thus representing an effective theoretical framework to unify computational, algorithmic, and implementation levels of analysis.In this webinar, Andrea presents some examples of unique research achievements made possible by the use of this setup.
Forward movement by the animal first raises the latching mechanism and then allows it to fall, locking the head-plate into position. At the end of the training/task session a servo lifts the latch, releasing the animal.
Presenters
Andrea Benucci
Andrea’s laboratory studies the neural basis of sensory processing with a major focus on vision. They are particularly interested in understanding the computational rules used by populations of neurons in the visual cortex to process visual information. The experimental tools they use are based on cutting-edge methods in optogenetics, optical imaging, and electrode recording. Their research provides an ideal test-bed for understanding the neural mechanisms of visual perception and its outcomes have the potential to provide important clinical applications in the field of cortical visual prostheses.
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