Memory relies on the firing of simultaneously activated neurons (engram), whose synapses are strengthened by long-term potentiation mechanisms. Optogenetic tools and a fluorescence probe to map synaptic engrams, were combined with a digital light processor device (DLP), to create in-vitro engrams and study populations of potentiated spines.
A method to design gratings in integrated photonics, is presented. The method is based on a transfer matrix formalism enhanced by Finite Element Method (FEM) parameter calculations. The main advantages of the proposed technique are the easy of use, the fast optimization time and the versatility of the approach. Few examples of optimized gratings to obtain various scattered light field profiles for different applications are presented: a double-Gaussian profile, a flat top square profile, a spot profile on a chip surface, profiles suited to get efficient and selective coupling to single mode and multimode fibers. A discussion of the limits of the method and some insights on how to improve it are also discussed.
To study the brain and the related neuronal network activity, many attempts were made to design and develop platforms able to induce and record neuronal signals. However, many brain processes -like memory formation and storage -and diseases -like amnesia or epilepsy -need more basic studies. For these, a bottom-up approach is needed, starting from 2D in-vitro neuronal cultures. In this work, we will present two experimental systems able to optogenetically interact with 2D neuronal networks with patternized light. One system consists in a Digital Light Projector (DLP) integrated in a microscope setup, which can illuminate neurons from the top; the other, is a compact and transportable photonic chip, properly designed to illuminate neurons plated on its surface.
In this proceeding we discuss the recent work involving our developed optogenetic tool, where we use digital light processor (DLP) as a light-stimulation source of neuronal culture and microelectrode array (MEA) system as the sampling unit. In this work we aim at developing an integrated experimental platform which should assist in the study of the structure and the function of neuronal networks. In particular, the setup proposed in this work should serve as an optogenetic tool for in-vitro experiments, controlled by a feedback from electrophysiological signals from the network to address specific neuronal circuits. In this manuscript some of the recent results from experiments involving optical stimulation and electrophysiological recording of neuronal cultures are shown. Additionally, we have developed an AI-based model which is trained according the recorded electrophysiological signals and reproduces the functionality and the macro-structure of the culture under test. The description and some preliminary results of this model are also discussed in this proceeding.
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