Intro Courses

SAIN

Advances in Brain Circuit Research: Exploring Technology in Systems and Behavior

– Brief explanation

This meeting explores advanced neuroscience technologies to understand functional circuits and their role in behavior. By merging cutting-edge innovations with foundational neuroscientific and computational principles, the symposium aims to deepen our understanding of brain function in both physiology and pathophysiology. Bringing together global experts, it provides a platform where classic questions intersect with pioneering concepts in brain circuit research.

Depending on the level of participation we intend to open with a half-day series of introductory courses designed for students and postdoctoral researchers to provide a practical overview of core experimental and computational approaches in modern systems neuroscience. These sessions will cover state-of-the-art methods for large-scale neuronal recordings, including the use of Neuropixels probes, with emphasis on data acquisition, data processing, spike sorting, and analysis pipelines. Complementary modules will focus on voltage and calcium imaging techniques, addressing experimental design, signal extraction, and interpretation. Finally, the courses will introduce machine learning tools for neural and behavioral data analysis, including classification, clustering, and pose estimation approaches.

Together, these tutorials aim to give participants a solid grounding in the methods that underpin contemporary circuit neuroscience, bridging experimental and analytical perspectives and preparing them for the discussions and research presented during the main meeting.

If you want to participate in this pre-course, we strongly invite you to indicate your interest by clicking this link and completing the registration form. Please select 4 of the following 6 introductor topics that best match your interests.

 

  1. Large-scale electrophysiology and analysis
  2. Machine learning approaches in neuroscience (e.g. dimensionality reduction, classification, pattern recognition)
  3. 3-D imaging approaches (e.g. iDisco and clarity)
  4. Functional calcium and voltageimaging with GECI and GEVIs
  5. Quantification of animal behavior (.e.g DeepLabCut and Cebra)
  6. Computational modelling of  neural systems