<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div><div>Call for applications:</div><div>(Apologies for duplicate postings)</div><div><br></div><div>We invite applicants to this new summer course in</div><div>"Mining and modeling of neuroscience data"<br>to be held July 11-22 at UC Berkeley.<br>A description of the course is below and also at:<br><a href="http://crcns.org/course">http://crcns.org/course</a><br>Application deadline is April 5.<br><br>Berkeley summer course in mining and modeling of neuroscience data<br>July 11-22, 2011<br>Redwood Center for Theoretical Neuroscience, UC Berkeley<br>Organizers: Fritz Sommer, Jeff Teeters<br><br>Scope<br>This course addresses students and researchers with backgrounds in<br>mathematics and computational sciences who are interested in applying<br>their skills toward problems in neuroscience. It will introduce the<br>major open questions of neuroscience and teach the state-of–the-art<br>techniques for analyzing and modeling neuroscience data sets. The<br>course is designed for students at the graduate level and researchers<br>with background in a quantitative field such as engineering,<br>mathematics, physics or computer science who may or may not have a<br>specific neuroscience background. The goal of this summer course is to<br>help researchers find new exciting research areas and at the same time<br>to strengthen quantitative expertise in the field of neuroscience. The</div><div>course is partially sponsored by the National Science Foundation from<br>a grant supporting activities at <a href="http://CRCNS.org">CRCNS.org</a>, which hosts a public<br>repository of experimental neuroscience data.<br><br>Format<br>The course is "hands on" in that it will include exercises in how to<br>use and modify existing software tools and apply them to data sets,<br>such as those available in the <a href="http://CRCNS.org">CRCNS.org</a> repository.<br><br>Course Instructors<br>Sonja Gruen, Institute for Neuroscience and Medicine INM-6, Research<br>Center Juelich, Germany and RIKEN Brain Science Institute, Wako-Shi,<br>Japan<br>Robert Kass, Carnegie Mellon University, Pittsburgh<br>Jonathan Pillow, University of Texas, Austin<br>Maneesh Sahani, Gatsby Unit, University College London<br>Odelia Schwartz, Albert Einstein College of Medicine<br>Frederic Theunissen, University of California, Berkeley<br><br>Speakers<br>To complement the main course instruction there will be lectures by<br>other neuroscientists presenting their research using quantitative<br>approaches. These speakers, and their research areas are: </div><div>Jose Carmena, UC Berkeley: Brain-machine interfaces (BMI) </div><div>Yang Dan, UC Berkeley: Encoding and processing of visual information in the</div><div>mammalian brain</div><div>Walter Freeman, UC Berkeley: Developing dynamical theories of brain function</div><div>using recordings from high-density electrode arrays</div><div>Jack Gallant, UC Berkeley: Use of fMRI and other data to understand the human</div><div>visual system at a quantitative, computational level</div><div>Mark Goldman, UC Davis: Deducing operation of networks of large numbers of</div><div>interconnected neurons using single neuron measurements</div><div>Jennifer Linden, University College London: Structure and function of cortex and</div><div>sensory systems<br></div><div>Bin Yu, UC Berkeley: Statistical machine learning and methodologies involving</div><div>large data sets</div><br><div>Requirements<br>Applicants should be familiar with linear algebra, probability,<br>differential and integral calculus and have some experience using<br>MatLab or other software for performing interactive mathematical<br>computations (such as Python or Mathematica). MatLab is<br>recommended because most exercises will be geared for MatLab. Each<br>student should bring a laptop with the software installed.<br><br>Cost<br>$800 for tuition. Room and board not included. Financial assistance<br>may be available and must be requested on the application form.<br><br>Housing<br>Dorm housing is available. The lowest rate is $384 for the entire two<br>weeks per person in a double occupancy room (about $27.50 per night).<br>Details: The room rate is $64 per night or $384 per week (seven<br>consecutive nights) for a single or double occupancy room. Since the<br>price of a double occupancy room is the same if one or two people are<br>in it, sharing the room with someone will reduce the price per person<br>to one half of the above. We will help coordinate sharing of rooms<br>for those who wish to do that. Information about the dorm rooms is<br>at: <a href="http://conferenceservices.berkeley.edu/summervis_index.html">http://conferenceservices.berkeley.edu/summervis_index.html</a><br><br>Food<br>Meals are available in the dorm cafeteria and in local restaurants.<br>They are not included with the course.<br><br>How to apply<br>To apply, fill out the form online linked from:<br><a href="http://crcns.org/course">http://crcns.org/course</a>. The application is done entirely on-line.<br>A curriculum vitae and a letter of recommendation is required. The<br>course is limited to 20 students.<br><br>Application Deadline<br>Applications must be received by April 5. Notifications of acceptance<br>will be given by the end of April.<br><br>Payment deadlines<br>If admitted, deposit of $300 must be made by May 9. Remainder payment<br>for the course ($500) is due May 31. If using dorm housing, to<br>guarantee a room, reservations must be made by May 31. After that,<br>reservations may be made on space available basis. Payment for<br>housing is made directly to the housing office when checking in (on<br>July 10).<br><br>Questions<br>Questions about the course can be sent to course [at] <a href="http://crcns.org">crcns.org</a>.<br><br>Topics covered<br>Basic approaches:<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>The problem of neural coding<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Spike trains, point processes, and firing rate<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Statistical thinking in neuroscience<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Theory of model fitting / regularization / hypothesis testing<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Bayesian methods<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Spike sorting<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Estimation of stimulus-response functionals: regression methods,<br>spike-triggered covariance,<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Variance analysis of neural response<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Estimation of SNR. Coherence<br>Information theoretic approaches:<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Information transmission rates and maximally informative dimensions<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Scene statistics approaches and neural modeling<br>Techniques for analyzing multiple-unit recordings:<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Cross-correlation and JPSTH<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Sparse coding/ICA methods, vanilla and methods including statistical<br>models of nonlinear dependencies<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Unitary event analysis<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Proper surrogates for spike synchrony analysis<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Methods for assessing functional connectivity<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Advanced topics in generalized linear models<br>-<span class="Apple-tab-span" style="white-space:pre"> </span>Low-dimensional latent dynamical structure in network activity –<br>Gaussian process factor analysis and newer approaches<br></div><div><br></div><div><br></div><div><div>----------------------------------------------------------------------------<br></div><div>Friedrich T. Sommer, Ph.D.<br></div><div>Redwood Center for Theoretical Neuroscience &<br></div><div>Helen Wills Neuroscience Institute<br></div><div>UC Berkeley<br></div><div>575A Evans Hall, MC# 3198 <br>
Berkeley, CA 94720-3198 </div><div><a href="http://redwood.berkeley.edu/wiki/Fritz_Sommer">http://redwood.berkeley.edu/wiki/Fritz_Sommer</a></div></div><div><br></div></div><br></body></html>