Neural Data Science
July 11 - 24, 2023

Key Dates
Application DeadlineMarch 15, 2023
Arrival: July 10th by 6pm EST
Departure: July 24th around 12pm EST

The course will be held at the Laboratory's Banbury Conference Center located on the north shore of Long Island.  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.

COVID19: 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.


Mark Reimers, Michigan State University
Pascal Wallisch, New York University

Hadas Ben-Esti, Yale University
Jennifer Sun, University College, London

Michael X. Cohen, Donders Centre for Medical Neuroscience, Radboud University, The Netherlands

See the Roll of Honor - who's taken the course in the past

Today's technologies enable neuroscientists to gather data in previously unimagined quantities. This necessitates - and allows for - the development of new analysis methods to address dynamic systems function of brain networks.

This course is designed to help neuroscience practitioners to develop the conceptual and practical capabilities to meet the challenges posed by the analysis of these hard-won and large data-sets. We will emphasize statistical issues such as the pre-processing of data, sampling biases, estimation methods and hypothesis testing as well as data wrangling (in MATLAB and Python). We will work with data from a variety of recording technologies including multi-electrode array recordings, local field potentials and EEG as well as two-photon and wide-field optical imaging.

The course will give a solid conceptual and technical grounding in widely applicable methods such as:

  • Data Processing for each recording technique
  • Spectral Methods
  • Neural Population analysis
  • Behavioral analysis
  • How to integrate neural data with behavioral data 
The workshop will proceed in a seminar style, guided by leading neural data analysts, with demonstrations and practical lab data analysis exercises supervised by instructors.

Prior Year Speakers:

Megan Carey,  Champalimaud Center for the Unknown
Michael X. Cohen, University of Amsterdam
Saskia de Vries, The Allen Institute
Tatiana Engel, Cold Spring Harbor Laboratory
Konrad Kording, University of Pennsylvania
Loren Looger, HHMI Janelia
Alexander Mathis, Harvard University
Majid Mohajerani, Canadian Center for Behavioral Neuroscience
Liam Paninski ,  Columbia University
Jonathan W. Pillow, Princeton University
Cristina Savin, New York University
Matthew A. Smith, University of Pittsburgh
Nick Steinmetz,  University of Washington
Karel Svoboda, HHMI Janelia
Byron Yu, Carnegie Mellon University

The course is aimed primarily at advanced grad students and early postdocs, and will be held at the Laboratory’s Banbury Conference Center located on the north shore of Long Island. All participants stay within walking distance of the Center, close to tennis court, pool and private beach. Please contact the Course Registrar with all accessibility needs, and/or note them in your course application form. The workshop will begin on the morning of July 11th.

The course is supported with funds provided by: Helmsley Charitable Trust. Grant funds will be used to defray student tuition, room and board costs, subject to financial need.

Cost (including board and lodging): $4,210

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

Before applying, ensure you have:
  1. Personal statement/essay;
  2. Letter(s) of recommendation;
  3. Curriculum vitae/resume;
  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: