Imaging Structure & Function in the Nervous System
July 26 - August 15, 2023

Key Dates
Application Deadline:  April 1st, 2023
Arrival: July 25th by 6pm EST
Departure: August 15th around 12pm EST

CSHL Courses are intensive, running all day and often including evenings and weekends; students are expected to attend all sessions and reside on campus for the duration of the course.

Instructors:
Elizabeth Hillman, Columbia University
Ruben Portugues, Technical University, Munich, Germany
Philbert Tsai, University of California, San Diego

Co-Instructors:
Adam Charles
, Johns Hopkins University
Hod Dana, Cleveland Clinic

Associate Instructor:
Joseph Donovan,
Max Planck Institute of Neurobiology, Germany

Senior Teaching Assistant:
Clarissa Whitmire,
Max-Delbrück-Center for Molecular Medicine, Berlin, Germany

COVID-19: All participants planning to attend in-person will be required to attest to recent COVID vaccination (within one year of the course’s start date) with an FDA or WHO approved vaccine. Additional safety measures will be in line with current NY and Federal Guidelines applicable in Summer 2023.

See the roll of honor - who's taken the course in the past.

Advances in lasers, light microscopy, advanced data analysis techniques and the development of powerful optical indicators and actuators and model organisms present expanding opportunities for investigating the nervous system, from synaptic spines to networks in the brain. 

This intensive laboratory and lecture course will provide participants with the theoretical and practical knowledge to leverage and combine emerging imaging technologies for neuroscience research. The primary focus of the course will be on in vivo applications of light microscopy, particularly functional imaging with genetically encoded indicators.

Methods taught will include:

  • Multi-photon microscopy
  • Light-sheet microscopy 
  • Use of spatial light modulators and digital holography
  • Combination of imaging with optogenetics
  • Head-mounted microscopes and fiber-optic methods
  • Analysis of imaging datasets 
Lectures and hands-on lab modules overseen by leading experts will progress through basic concepts to cutting-edge imaging methods. Students will learn the fundamentals of optics, lasers, spectroscopy and microscopy, laser scanning systems, camera-based systems, methods for quantifying and optimizing signal to noise and resolution, in vivo preparations in mice and zebrafish larvae, and image processing and analysis approaches. Hands-on building exercises are a fundamental component of the course, enabling students to develop an intuitive understanding of optical principles and assemble their own two-photon microscope. The course will also host a range of state-of-the-art commercial imaging systems from a range of vendors who will actively participate in the course and provide ample opportunities to explore, compare and gain experience with these advanced systems.

We encourage applications from diverse interdisciplinary researchers (PhD students, post-doctoral fellows and early-career faculty or equivalent) seeking to expand their knowledge, skillsets and experience including those with expertise in experimental and computational neuroscience and neural engineering. Attendees working on a variety of model organisms are welcome including mouse, fish, fly, worm and organoid systems. 

In your personal statements, applicants should answer the following questions (point by point, ≤ 1 page total):

  1. What are your reasons for wanting to attend the course?
  2. How will the course help you in your current project?
  3. What unique skills and qualities will you be able to contribute to the course?
  4. How will you help others using the knowledge obtained during the course?
  5. What is your prior experience with neuroimaging techniques, and which imaging technologies are available to you?
  6. What is your experience with data analysis and programming in Python (or Matlab)?
  7. What are your long-term career goals?

Note, there are no wrong or right answers, we are just seeking to gather enough information to select a group with diverse perspectives and experiences, and for whom attending the course will have the highest impact.

All participants should familiarize themselves with the following concepts by the beginning of the course:
  1. Fundamentals of Fourier transform and matrix operations
  2. Basic programming experience in either MATLAB or Python (preferred) (see e.g.: 1, 2, 3, 4, 5)
2023 Lecturers:
Denise Cai, Mount Sinai Icahn School of Medicine
Adam Charles, Johns Hopkins University
Hod Dana, Cleveland Clinic
Stéphane Dieudonné, Institut de Biologie de l'École Normale Supérieure, France
Elizabeth Hillman, Columbia University
Na Ji, University of California, Berkeley
Jeff Lichtman, Harvard University
Bijan Pesaran, University of Pennsylvania 
Ruben Portugues, Technical University, Munich, Germany
Carsen Stringer, Howard Hughes Medical Institute
Karel Svoboda, Allen Institute
Lin Tian, UC Davis
Philbert Tsai, University of California, San Diego
Alipasha Vaziri, The Rockefeller University
Jennifer Waters, Harvard Medical School


Support & Stipends

We would like to acknowledge the following companies that provided invaluable support:
Microscope Systems:
Bruker Corporation, Intellegent Imaging Innovations, Scientifica, Sutter Instrument Company, Thorlabs, Inc
Equipment:
Andor Technology, Bitplane, Coherent, Inc, Conoptics, Crystalaser, Hamamatsu Photonics, Holoeye, Molecular Devices, Narishige International USA, Nikon Corporation, Photometrics, Thorlabs, Inc, Vidrio Technologies, LLC, World Precision Instruments
Incubation: Okolab, Tokai Hit USA Inc

Major support provided by the National Institute of Mental Health of the National Institutes of Health

         

Stipends are available to offset tuition costs as follows:

Please indicate your eligibility for funding in your stipend request submitted when you apply to the course. Stipend requests do not affect selection decisions made by the instructors. 

Cost (including board and lodging): $5,500

No fees are due until you have completed the full application process and are accepted into the course.

Before applying, ensure you have (all due April 1):
  1. Personal statement/essay;
  2. Letter(s) of recommendation;
  3. Curriculum vitae/resume (optional);
  4. Financial aid request (optional).
    More details.

If you are not ready to fully apply but wish to express interest in applying, receive a reminder two weeks prior to the deadline, and tell us about your financial aid requirements, click below: