The course is focused on experimental and theoretical methods to study how the brain operates at the level of neuronal circuits. We cover various optical and electrophysiological concepts and techniques used currently in systems neuroscience from the basics to advanced topics on both theoretical and experimental grounds. TENSS also provides important insights into modern machine learning techniques and artificial intelligence, with application to advanced neuroscience data analysis.
The course is designed to be a highly interactive, hands-on experience, reflecting the atmosphere of CSHL, Woods Hole or Champalimaud courses.
Typically, each course day will contain an extended lab session and several theoretical lectures.
Hard work will be combined with a few trips through the beautiful Transylvanian countryside.
The course is addressed to a graduate student/postdoc audience.
Athena Akrami Sainsbury Wellcome Centre, UCL, UK
Upinder Bhalla National Centre for Biological Sciences, India
Federico Carnevale DeepMind Technologies, London, UK
Ann Clemens University of Edinburgh, UK
Ashesh Dhawale Centre for Neuroscience, IISc Bangalore, India
Michael Dickinson California Institute of Technology, USA
Florian Engert Harvard University, USA
Nadine Gogolla Max Planck Institute of Psychiatry, Germany
Sonja Hofer Sainsbury Wellcome Centre, UCL, UK
Helen Xun Hou Cold Spring Harbor Laboratory, USA
Tomα Hromαdka Slovak Academy of Sciences, Slovakia
Benjamin Judkewitz Einstein Center for Neuroscience, Germany
Georg Keller Friedrich Miescher Institute, Switzerland
Emilie Mace Max Planck Institute of Neurobiology, Germany
Eve Marder Brandeis Unversity, USA
Hannah Monyer University of Heidelberg, Germany
Tom Mrsic-Flögel Sainsbury Wellcome Centre, UCL, UK
Bence Ölveczky Harvard University, USA
Ruben Portugues Max Planck Institute of Neurobiology, Germany
Tobias Rose University of Bonn, Germany
Wolf Singer Ernst Strόngmann Institute, Germany
Daniela Vallentin Max-Planck-Institute for Ornithology, Germany
Jakob Voigts HHMI, Janelia Research Campus, USA
Chris Xu Cornell University, USA
Petr Znamenskiy Francis Crick Institute, UK
Tony Zador Cold Spring Harbor Laboratory, USA
- Florin Albeanu Cold Spring Harbor Laboratory, NY, USA
- Adam Kampff Sainsbury Wellcome Centre, University College London, UK
- Raul Mureşan Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
Teaching assistants & organizing team
- Harald Bârzan Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Antonin Blot Sainsbury Wellcome Centre, UCL, UK
- Andrei Ciuparu Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Medorian Gheorghiu Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Matνas Goldin Institut de la Vision, Paris, France
- Priyanka Gupta Cold Spring Harbor Laboratory, NY, USA
- Yiran He Francis Crick Institute, UK
- Mitra Javadzadeh Sainsbury Wellcome Centre, UCL, UK
- Ana Maria Ichim Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Mateusz Kostecki Nencki Institute for Experimental Biology, Warsaw, Poland
- Fred Marbach Sainsbury Wellcome Centre, UCL, UK
- Vasile V. Moca Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Adriana Nagy-Dăbâcan Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Jon Newman Massachusetts Institute of Technology, USA
- Bruno Pichler INSS (Independent NeuroScience Services), UK
- Nacho Sanguinetti Bernstein Center for Computational Neuroscience, Berlin, Germany
- Pavithraa Seenivasan Indian Institute of Science, Bangalore, India
- Iuliu Vasilescu Politechnica University, Bucharest, Romania
- Jakob Voigts Massachusetts Institute of Technology, USA
- Anqi Zhang Harvard University, USA
Support and administration
- Laura Rus Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Cosmina Pavel Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Attila Kelemen Babes-Bolyai University, Cluj-Napoca, Romania
- Gabriel Pavel Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Loredana Dan Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Basic Optics Diffraction and Resolution. Illumination Techniques. Numerical Aperture.
- Optical bench exercises Lenses, optical systems, illumination methods, basic microscopy techniques. How to custom build different kinds of microscopes.
- Noise measurements and photo-sensors Shot noise, optical detectors, amplifiers, NI-DAQ, CCD cameras, photodiodes, photo multiplier tubes (PMTs).
- Light and fluorescence microscopy Fluorescence, FRAP, photo-activation, photo-conversion. Point spread function measurements, basic image analysis (deconvolution, denoising, PCA).
- Fluorescence probes GFP, GFP based chromophores, organic calcium dyes, genetically encoded calcium dyes, pHluorins, voltage sensitive dyes.
- Intrinsic Optical Imaging Visual, auditory & barrel cortex; olfactory bulb. Students will build a custom wide field fluorescence and intrinsic optical imaging rig.
- Scanning microscopy Confocal and two-photon microscopy. Lasers. Students will build a two-photon microscope and write custom scanning and acquisition software in MATLAB and NI DAQmx. The ScanImage API.
- Viral approaches to label, monitor and alter neuronal circuits.
- Optogenetics Light activated ion channels and pumps. Patterned photo-stimulation techniques.
- Benchtop electronics and basic electrophysiology Impedence and Dipoles. Amplifiers. Extracellular and intracellular recordings. LFP; single unit, multi-unit extracellular recordings, tetrodes, electrode arrays; patch clamp.
- Awake head fixed and freely moving optical and electrophysiological recording strategies in rodents Microdrives. Fiber optic based systems. Open source systems. Open Ephys.
- Techniques for electrophysiological data analysis.
- Monitoring animal behavior Open Source tools for acquisition and analysis of video data. Intro to Bonsai and Arduino. Training Strategies. Closed loop systems.
- Neuronal functional connectivity and neuronal connectomics Serial electron-microscopy and trans-synaptic labeling methods.
- Synchrony and oscillations.
- Cortical attention, sparse neuronal codes.
- Decision making, uncertainty, neuro-modulatory systems.
- Machine learning and artificial intelligence.
- Governance and ethics.
- Laboratory animal science.