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Understand the input-output relationships in neural circuits

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Understand the input-output relationships in neural circuits
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Understand the input-output relationships in neural circuits
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To understand a neural circuit, we need to know the information it receives, the transformation it applies to its inputs, and the information it outputs to the rest of the brain. We use a data-rich approach to elucidate circuit computations by systematically characterizing the representational properties of large numbers of boutons and neurons in the input and output layers of a neural circuit. Currently, we focus our efforts on the mouse primary visual cortex, where the tuning properties of inputs and outputs at depth can be characterized accurately only after the optical aberrations are corrected. 

Fluorescence signals reflecting calcium transients measured without and with AO correction at six regions of interest under visual stimulations of gratings moving in eight different directions. Gray bars denote the duration with stimuli on. Orange arrowheads mark the example responses at the preferred directions of grating motion; red arrowheads label example responses dominated by neuropil contamination. Scale bars, 10 μm.

Summaries of our recent projects can be found here and here.