Neuroscience tools

• Patch-clamp recordings: this technique is the gold standard to identify the electrophysiological properties at the single cell scale. How do neurons respond to stimulation? Which type of activity this neuron can generate? Dissect the role of ionic channels and synapses.

• Calcium imaging: variations in the intracellular calcium concentration can be seen as a proxy for evaluating neural activity. By loading cells with a fluorescent calcium sensor, you can monitor the response of dozens of neurons to a stimulation, and determine the mechanisms involved.

• Optogenetics: usually, neurons are not sensitive to light. But when you genetically modify neurons to make them express light-sensitive ion channels, they become sensitive to blue or red light. Use light to switch on and off genetically defined cell types, and identify the role of these neurons.

• High speed movement recordings: to detect the role of specific neurons, it is important to record movements with high precision. We record movement at 300 frames per second to capture the role of genetically defined neural populations.

• Deep learning-based movement analysis: it takes time to analyze movements captured at 300 frames per second… You can show to a software, DeepLabCut, to recognize the part of the image you are interested in, and let the software train itself to recognize it 1 million times in 24h, while you are sleeping. The next day, the software will be able to track this part of the image on any new video, allowing you to measure movement speed with high precision.

• Fiber photometry: what is the activity of genetically defined cell types? Load the neurons you are interested in with a fluorescent calcium sensor and use an optic fiber coupled with a photodetector to track the variation of fluorescence.

• RNAscope: which genes are expressed by your neurons of interest? When genes are expressed, messenger RNAs can be made fluorescent, allowing you to establish the gene expression profile of any cell population at any time point.

• Neural tracing: what are the targets of those neurons? What is the origin of these neural fibers? Identify the anatomical connectivity between brain regions by making those appear in different colors by using tracers and viruses.

• Immunofluorescence: What are the proteins expressed in your neurons of interest? Are these cholinergic or dopaminergic neurons? Visualize protein expression in specific neurons by hacking the immune system. Use antibodies to see your proteins of interest.

• Matlab-based data analysis: What is the average amplitude of these responses? Do these responses follow a pattern, fit to a specific equation? Do these data follow a multimodal distribution? Is there a way to illustrate all these responses in one single graph? Learn to program in matlab and get the best out of your datasets.