Objective

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.

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Invited lecturers

    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
    Florian Engert – Harvard University, USA
    TomᚠHromαdka – Slovak Academy of Sciences, Slovakia
    Na Ji – UC Berkeley, USA
    Benjamin Judkewitz – Einstein Center for Neuroscience, Germany
    Georg Keller – Friedrich Miescher Institute, Switzerland
    Alexei Koulakov – Cold Spring Harbor Laboratory, USA
    Emilie Mace – Max Planck Institute of Neurobiology, Germany
    Hannah Monyer – University of Heidelberg, Germany
    Tom Mrsic-Flögel – Sainsbury Wellcome Centre, UCL, UK
    Ruben Portugues – Max Planck Institute of Neurobiology, Germany
    Tobias Rose – Max Planck Institute of Neurobiology, Germany
    Katharina Schmack – Francis Crick Institute, UK
    Wolf Singer – Max Planck Institute for Brain Research, Germany
    Nao Uchida – Harvard University, USA
    Daniela Vallentin – Max-Planck-Institute for Ornithology, Germany
    Chris Xu – Cornell University, USA
    Petr Znamenskiy – Francis Crick Institute, UK


Organizers

  • 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

Topics

  • 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.

© TENSS 2022