Embryology: Concepts & Techniques in Modern Developmental Biology
Course Date: June 4 – July 17, 2016
Deadline: February 1, 2016
Directors: Alejandro Sánchez Alvarado, Stowers Institute for Medical Research; and Richard R. Behringer, University of Texas M. D. Anderson Cancer Center
An intensive six-week laboratory and lecture course for advanced graduate students, postdoctoral fellows, and more senior researchers who seek a broad and balanced view of the modern issues of developmental biology. Limited to 24 students.
The integrated lectures and laboratories provide a comprehensive coverage of the paradigms, problems, and technologies of modern developmental biology, cast within a framework of metazoan evolution. Students are exposed to a wide variety of embryonic systems, including intensively studied genetic model systems ( e.g. C. elegans , Drosophila , zebrafish mouse) and others with well-established experimental attributes ( e.g. chick, sea urchins, frogs, ascidians). In addition, students will be introduced to a wide range of emerging systems, including locally available marine organisms, that help fill in the evolutionary history of animal diversity ( e.g. cnidarians, nemerteans, planaria, crustaceans, mollusks, and annelids) and that are becoming established as experimental systems in their own right. This broad coverage of metazoan phylogeny allows for the analyses of the developmental strategies that drive evolutionary change. Analytical and experimental techniques used to explore invertebrate and vertebrate development include embryological manipulation (e.g. cell ablation, tissue grafting), molecular genetic ( e.g. RNAi, electroporation) and cell biology approaches ( e.g. analysis of cell lineage and migratory behaviour), and microscopic and imaging technologies (e.g. confocal and 3-D time lapse), using state-of-the-art instrumentation and methodology. Conceptual topics include cell specification and differentiation, pattern formation, embryonic axis formation, morphogenesis, intercellular signaling, transcriptional regulation, organogenesis, and modern comparative embryology.
Neural Systems & Behavior
Course Date: June 4 – July 31, 2016
Deadline: February 1, 2016
Directors: André Fenton, New York University; and Hans A. Hofmann, University of Texas
This is an intensive eight-week laboratory and lecture course focusing on the neural basis of behavior. The course is intended for graduate students, postdoctoral researchers, and independent investigators. Limited to 20 participants.
This course provides broad training in modern approaches to the study of neural mechanisms underlying behavior, perception, and cognition. Through a combination of lectures, exercises, and projects, students investigate neural systems at the molecular, cellular, and organismal levels using state-of-the-art techniques. The eight weeks are divided into two-week cycles, providing participants with an in-depth familiarity with several different experimental model systems. In the first cycle, students study a simple invertebrate model system to develop general experimental skills in electrophysiology, neuroanatomy, and quantitative analysis of physiological and behavioral data. In subsequent cycles, students work on a series of different preparations, providing them with a breadth of knowledge in the field. The list of experimental model systems is updated year-to-year, but always includes a diverse array of vertebrate and invertebrate preparations, chosen to illustrate key concepts and novel techniques in the field. The goal of the course is to expose students to diverse approaches to the investigation of the neural basis of behavior.
The students in this course learn by doing real science. For instance three students and two faculty in the 2012 version of NS&B published a paper in the Journal of Neuroscience based upon their course experiences.
Each experimental preparation is taught by a team of leading experts, and topics include: the cellular basis of pattern generation, the development and neuromodulatory control of cell and circuit specificity, learning and plasticity, sensory processing and feature detection, sensory-motor integration, spatial memory, and social communication. The laboratory provides access to many complementary methods including intracellular recording; single-cell dye-injection; patch-clamp; whole-cell voltage and current clamp; analysis of synaptic transmission and plasticity; neural genetics; quantitative behavioral methods; and computational analysis. Although students will use and be exposed to many different techniques, this is not a course for learning particular techniques. Students spend a portion of each cycle designing, performing, and analyzing the results of their own project. These projects offer an exceptional opportunity to combine newly learned skills in a creative manner.
In addition to the daily course lecture, the course sponsors a weekly seminar, given by invited lecturers and distinguished Visiting Scholars.
Course Date: June 2 – July 31, 2016
Deadline: February 1, 2016
Directors: Graeme Davis, University of California, San Francisco; Andreas Maricq, The University of Utah; and Timothy A. Ryan, Weill Medical College of Cornell University
An intensive and comprehensive laboratory-oriented course in cellular and molecular neurobiology intended for predoctoral students, postdoctoral or clinical researchers, and young investigators beginning independent research careers. Limited to 14 students.
A hallmark of this course is the extensive lab work done in close collaboration with expert faculty. The course is divided into three sections: Electrophysiology, Imaging, and Molecular Neurobiology. These are taught by separate groups of faculty, usually six in each section, and with many guest lecturers. Each section begins with specific training in core laboratory techniques; students then undertake one- to two-week directed or independent projects using the methods they have learned. Didactic lectures are combined with laboratory experience in order to establish a strong conceptual foundation for each section. A typical day has 3 hours of lecture and 10 hours of lab.
Electrophysiological methods focus on patch-clamp and sharp electrode recordings, performed on neurons in a variety of preparations, including tissue culture, brain slices, isolated squid synapses, rat cochlea, or whole fish. Optical methods include calcium imaging, confocal and 2-photon microscopy, videomicroscopy, and electron microscopy. Molecular techniques emphasize the use of forward and reverse genetics in diverse systems such as Drosophila, C. elegans, zebrafish, chick embryos, and primary cells in culture. The impact of genetic manipulations are assayed by real time PCR, laser microdissection, single cell PCR, in situ hybridization, and a variety of immunotechniques in addition to incorporating electrophysiological and imaging techniques.
The goal of the course is to emphasize the strengths of a multidisciplinary approach for studying the function of the nervous system at the cellular and molecular levels.
Physiology: Modern Cell Biology Using Microscopic, Biochemical and Computational Approaches
Course Date: June 12 – July 31, 2016
Deadline: February 1, 2016
Directors: Jennifer Lippincott-Schwartz, National Institutes of Health; Wallace F. Marshall, University of California, San Francisco; and Rob Phillips, California Institute of Technology
The Physiology Course has a rich history, dating back to 1892, of training the leaders in biology and generating Nobel Prize experiments. However, this is not your grandfather’s Physiology Course! This intensive laboratory course has been revamped to meet the new challenges in biology by providing a unique interdisciplinary training environment at the interface between cellular and computational biology. The Physiology Course will bring together biological and physical/computational scientists, both in the faculty and the student body, to work together on cutting-edge problems in cell physiology. Students will learn from leaders in the field of cellular physiology, microscopy, and computational analysis. Students with backgrounds in both the biological and physical/computational sciences are encouraged to apply.
The course design will promote learning by practice, with a particular emphasis on stimulating experimental creativity and interdisciplinary approaches. Biology students will leave the course able to understand and author computer simulations, and physical science students will leave understanding the language of biology, and with experience working on cutting edge biological problems. Students will participate in three research threads (cell division, cell migration, and signaling) that will run through the whole course. Each thread will intensively use microscopy, biochemistry, and computational analysis to address research problems in a highly collaborative setting. State-of-the-art microscopes, as well as other advanced equipment, will be available. It is anticipated that these threads will lead to research discoveries, as well as providing learning opportunities. Post course research opportunities exist for selected students.
To inspire students, and provide them with a sense of the history and future of cell physiology, a visiting scholar program has been established. This program brings four eminent scientists to the MBL for a week. They deliver one or more lectures to the entire community, and participate in both the intellectual and experimental aspects of the course.
Special Topics Courses
Analytical & Quantitative Light Microscopy
Course Date: May 4 – May 13, 2016
Deadline: January 25, 2016
Directors: Jagesh Shah, Harvard Medical School/Brigham and Women’s Hospital; and Justin Taraska, NIH
Course Laboratory Director: Wendy Salmon, Whitehead Institute
A comprehensive and intensive course in light microscopy for researchers in biology, medicine, and material sciences. This course provides a systematic and in-depth examination of the theory of image formation and application of video and digital methods for exploring subtle interactions between light and the specimen. This course emphasizes the quantitative issues that are critical to the proper interpretation of images obtained with modern wide-field and confocal microscopes. This course is limited to 32 students.
Laboratory exercises, demonstrations, and discussions include: (1) geometrical and physical optics of microscope image formation including Abbe’s theory of the microscope and Fourier optics; (2) interaction of light and matter; (3) phase contrast polarization and interference microscopy for the nondestructive analysis of molecular and fine-structural organization in living cells; (4) fluorescence microscopy, quantification of fluorescence, and GFP; (5) principles and application of digital video imaging, recording, analysis, and display; (6) digital image processing and quantitative digital image deconvolution; (7) ratiometric measurement of intracellular ion concentrations; (8) confocal microscopy; and (9) new advances in light microscopy such as FRET, FLIM, TIRF, and patterned illumination.
The program is designed primarily for: (1) university faculty, professional researchers, postdoctoral fellows, and advanced graduate students in the life sciences who wish to expand their experience in microscopy and to understand the quantitative issues associated with analysis of data obtained with optical microscopes; (2) individuals well-grounded in the physical sciences, who wish to exploit microscopy techniques for analyzing dynamic fine-structural and chemical changes; and (3) industrial scientists and engineers interested in advancing the design of equipment and techniques involving video and digital microscopy.
Lectures are followed by small group laboratory sessions and demonstrations. As a result, students will have opportunities for extensive hands-on experience with state-of-the-art optical, electronic, and digital imaging equipment guided by an experienced staff from universities and industry.
Brains, Minds and Machines
Course Date: August 15 – September 5, 2016
Deadline: March 14, 2016
Directors: Gabriel Kreiman, Harvard University; and Tomaso Poggio, Massachusetts Institute of Technology (L. Mahadevan, Harvard University, honorary director)
The problem of intelligence – how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines – is arguably the greatest problem in science and technology. To solve it we will need to understand how human intelligence emerges from computation in neural circuits, with rigor sufficient to reproduce similar intelligent behavior in machines. Success in this endeavor ultimately will enable us to understand ourselves better, to produce smarter machines, and perhaps even to make ourselves smarter. Today’s AI technologies, such as Watson and Siri, are impressive, but their domain specificity and reliance on vast numbers of labeled examples are obvious limitations; few view this as brain-like or human intelligence. The synergistic combination of cognitive science, neurobiology, engineering, mathematics, and computer science holds the promise to build much more robust and sophisticated algorithms implemented in intelligent machines. The goal of this course is to help produce a community of leaders that is equally knowledgeable in neuroscience, cognitive science, and computer science.
The first half of the course will focus on the intersection between biological and computational aspects of learning and vision. The second half will focus on high-level social cognition and artificial intelligence, as well as audition, speech and language processing.
The class discussions will cover a range of topics, including:
- Neuroscience: neurons and models
- Computational vision
- Biological vision
- Machine learning
- Bayesian inference
- Planning and motor control
- Social cognition
- Inverse problems & well-posedness
- Audition and speech processing
- Natural language processing
These discussions will be complemented in the first week by MathCamps and NeuroCamps, to refresh the necessary background for some of the students. Throughout the course, students will participate in workshops and tutorials to gain hands-on experience with these topics.
Core presentations will be given jointly by neuroscientists, cognitive scientists, and computer scientists who have worked together. Throughout the course intensive lectures will be followed by afternoons of computational labs, with some additional evening research seminars. To reinforce the theme of collaboration between (computer science + math) and (neuroscience + cognitive science), exercises and projects often will be performed in teams that combine students with both backgrounds.
The course will culminate with student presentations of their projects. These projects provide the opportunity for students to work closely with the resident faculty, to develop ideas that grew out of the lectures and seminars, and to connect these ideas with problems from the students’ own research at their home institutions.
This course aims to cross-educate computer engineers and neuroscientists; it is appropriate for graduate students, postdocs, and faculty in computer science or neuroscience. Students are expected to have a strong background in one discipline (such as neurobiology, physics, engineering, and mathematics). Our goal is to develop the science and the technology of intelligence and to help train a new generation of scientists that will leverage the progress in neuroscience, cognitive science, and computer science. The course is limited to 30 students.
Computational Image Analysis in Cellular and Developmental Biology
Course Date: October 9 – October 19, 2016
Deadline: July 25, 2016
Directors: Gaudenz Danuser, University of Texas Southwestern Medical Center and Harvard Medical School; Khuloud Jaqaman, University of Texas Southwestern Medical Center; Steve Altschuler, Pharmaceutical Chemistry at University of California, San Francisco and Lani Wu, Pharmaceutical Chemistry at University of California, San Francisco
Scope: Recent advances in fluorescence microscopy have enabled unprecedented progress in cellular and developmental biology. Imaging has become a component of nearly every cell-biological investigation at all scales, from single molecules to whole tissues, and research modalities, from reconstitution experiments to genome-wide screening;
However, these fast-paced developments in imaging technology have remained unmatched by developments in image analysis software. Most of the published image data in biology are still processed by hand and interpreted by qualitative visual inspection.
Currently, there are very few curricula, in universities and national laboratories, dedicated to the mathematical, statistical, software, and machine learning methods required to transform raw microscopy image data into rigorous biological knowledge. This course is targeted to fill this void by training a next generation of life scientists in the mathematical foundation and implementation of algorithms for image analysis.
Brief synopsis: Topics covered in this course include: image enhancement, segmentation, tracking, feature extraction, image classification, machine learning, noise analysis and uncertainty prediction, and statistical hypothesis testing. All topics will be covered in theory lectures and computer exercises. Exercises will be done on images from ongoing research projects in the instructors’ labs and will target actual research questions. An important subject in the course will be software design, addressing both the implementation of optimized algorithms and sharable code, including programming in teams.
Student requirements and course structure: The course will admit graduate students and junior postdocs with backgrounds in mathematics and physics, who are currently conducting research in cellular and developmental biology. Students with no formal training in the quantitative sciences may also be considered if space is available and if initial experience in the practice of computer image analysis in microscopy is documented in the application. We will accept a maximum of 12 students. This size has been proven ideal in the first implementation of the course in 2011, and is also defined by the funds made available through an NIH grant. The course will be free for all admitted students, with the exception of travel expenditure to and from Woods Hole.
The course will contain two theory lectures per day. The rest of the course time will be primarily devoted to computer exercises under the guidance of the four course instructors and two TAs. To broaden the perspectives and encourage discussions, there will also be several evening seminars by invited faculty and by the students themselves.
The software projects will be done in small teams. This course structure is designed to train the students in the practicalities of code sharing and collaborative problem solving, allowing them to tackle complex image analysis problems when they return to their home institutions. At the end of the course, students will be encouraged to take home their own projects and the library code they integrated. The course will use MATLAB as the programming language, one of the most widespread platforms for scientific computing.
Importantly, this is not a course for students who wish to get familiar with MATLAB programming. On the contrary, we expect students to have basic knowledge of MATLAB (or solid expertise in another modular and/or object-oriented programming language), allowing them to start using Matlab on Day 1 for solving image and data analysis problems related to cell and developmental biology. Once the student body is identified, we will publicize tutorial materials for self-study.
Frontiers in Stem Cells & Regeneration
Course Date: September 25 – October 1, 2016
Deadline: July 18, 2016
Contact for more information: firstname.lastname@example.org
Directors: Jennifer Morgan, MBL; and Gerald P. Schatten, University of Pittsburgh
The Stem Cells and Regeneration Course (formerly known as FrHESC) is a dynamic, evolving laboratory and lecture course that includes the complete array of biological and medical perspectives from fundamental basic biology of “stemness” and mechanisms of regeneration through evaluation of pluripotent stem cells for therapeutic benefit.
The NIH sponsored course is designed for postdoctoral fellows, newly independent scientists, and established investigators seeking comprehensive and sophisticated training in research strategies and state-of-the-art cellular, molecular and genetic approaches for advancing human embryonic stem cell research.
The course consists of daily lectures from resident faculty and other invited speakers, discussions and informal seminars, laboratory exercises and demonstrations, and one-on-one tutorials.
The Stem Cells and Regeneration Course will exclusively use human embryonic stem cell lines on the NIH Human Embryonic Stem Cell Registry and being routinely cultured at the Pittsburgh Development Center.
Gene Regulatory Networks for Development
Course Date: October 9 – October 22, 2016
Deadline: July 27, 2016
Directors: David McClay, Duke University; Isabelle Peter, California Institute of Technology
This Course is intended for advanced graduate students, postdoctoral scholars, and professional scientists. It will continue for 10 intense days and will comprise morning lectures followed by workshop discussions; afternoon computer practicals leading to student projects; and wet lab demonstrations of gene regulatory perturbation analysis in vivo. Lectures will provide in depth analyses of well studied gene regulatory networks (GRNs) in both embryonic and post embryonic developmental systems; a comprehensive theory of developmental GRN structure and of the explanatory value of GRNs; and discussion of the rapidly growing area of GRN evolution. The practicals will include introduction and use of BioTapestry, the leading computational platform for representation of GRNs; outlines of kinetic analysis and GRN modeling, and relevant special topics in gene regulation as they pertain to development and evolution.
Immunohistochemistry and Microscopy (IHCM)
Course Date: March 12 – March 17, 2016
Deadline: January 20, 2016
Directors: Eduardo Rosa-Molinar, The University of Kansas and Charles W. Frevert, University of Washington School of Medicine
Course Outline: The Immunohistochemistry & Microscopy (IHCM) course is four full days and evenings (11 hours daily) of lecture and laboratory sessions with experts in the field of immunohistochemistry (IHC) and microscopy. The IHCM course goal is to provide participants in-depth theory of and extensive hands-on experience with immunohistochemistry (IHC) techniques as well as theory and hands-on experience with a broad range of microscopic imaging techniques. The course emphasizes hands-on laboratory time and small breakout discussions with faculty and staff.
The laboratory demonstrations, exercises, discussions, and trouble-shooting sessions focus on: 1) Principles underlying the fixation of proteins in tissues; because fixation and preparation of tissue prior to IHC constitutes one of the most important processes affecting the success of IHC studies, students will learn about and have multiple hands-on experiences with tissue preparation; they will also learn how to trouble shoot problems; 2) Antigen retrieval; students will learn about and discuss how the detection of many antigens can be significantly improved by antigen retrieval; 3) Controls; because IHC experiments must include positive and negative controls to support the validity of staining and identify experimental artifacts, students will learn about, discuss, and use controls that support the specificity of IHC results as well as the variances in antibody specificity and conditions that may generate inconsistent immune-staining and lead to inaccurate conclusions; 4) Strategies for detecting the presence of specific antigens in cells; students will learn about and use antibodies labeled with different fluorescent probes and analyze the results with epi-fluorescence or confocal microscopies; they will also use antibody dilution studies; 5) Technologies that automate immunohistochemistry; to achieve a better understanding of when and how new technologies will benefit their research, students will be introduced to and use automated immunohistochemistry; 6) Basic elements of light and fluorescence microscopies; to gain insight into how to choose the correct imaging platform for their samples, students will learn to use various imaging platforms, including bright-field, epi-fluorescence, wide-field deconvolution, and confocal microscopies. Using images collected in the course as well as previously acquired images, students will also learn about and discuss ethics of imaging and acceptable practice for image capture and management and appropriate use of Photoshop to develop figures for publication; and 7) Troubleshooting; students will learn how to troubleshoot problems with immunohistochemistry and images will be an integral part of the course; troubleshooting sessions will be held daily.
This course is appropriate for undergraduate and graduate students, laboratory technicians, postdoctoral students, new and established faculty/clinicians seeking to expand their techniques and knowledge of IHC and microscopy. It is appropriate for beginning scientists and those with more advanced skills. Participants will be grouped appropriately. Registration is limited to thirty.
Students from groups underrepresented in science may apply for financial support for travel-related expenses and course registration.
Methods in Computational Neuroscience
Course Date: July 27 – August 24, 2016
Deadline: March 7, 2016
Directors: Michale Fee, Massachusetts Institute of Technology; and Mark Goldman, University of California, Davis
Animals interact with a complex world, encountering a variety of challenges: They must gather data about the environment, discover useful structures in these data, store and recall information about past events, plan and guide actions, learn the consequences of these actions, etc. These are, in part, computational problems that are solved by networks of neurons, from roughly 100 cells in a small worm to 100 billion in humans. Methods in Computational Neuroscience introduces students to the computational and mathematical techniques that are used to address how the brain solves these problems at levels of neural organization ranging from single membrane channels to operations of the entire brain.
In each of the first three weeks, the course focuses on material at increasing levels of complexity (molecular/cellular, network, cognitive/behavioral), but always with an eye on these questions: Can we derive biologically plausible mechanisms that explain how nervous systems solve specific computational problems that arise in the laboratory or natural environment? Can these problems be decomposed into manageable pieces, and can we relate such mathematical decompositions to the observable properties of individual neurons and circuits? Can we identify the molecular mechanisms that provide the building blocks for these computations, as well as understand how the building blocks are organized into cells and circuits that perform useful functions?
Core presentations in weeks one to three will be given jointly by theorists and experimentalists who have worked, often together, on the same problems. In the first week, to supplement the lectures, there will be numerous optional tutorials covering topics including dynamical systems, information theory, UNIX basics, and simulation using NEURON, MATLAB, and XPP. As each week progresses, the issues brought up in these presentations will be explored in laboratory demonstrations and exercises that invite the students to follow and generalize from the paths outlined in the lectures. Exercises involve both quantitative analysis of experimental data and exploration of models through analytic and numerical techniques. To reinforce the theme of collaboration between theory and experiment, exercises are often performed in teams that combine students with theoretical and experimental backgrounds.
The fourth week of the course is reserved for student projects. These projects provide the opportunity for students to work closely with the resident faculty, to develop ideas that grew out of the lectures and seminars, and to connect these ideas with problems from the students’ own research topics.
This course is appropriate for graduate students, postdocs and faculty in a variety of fields, from zoology, ethology, and neurobiology, to physics, engineering, and mathematics. Students are expected to have a strong background in one discipline, and to have made some effort to introduce themselves to a complementary discipline. The course is limited to 24 students, who will be chosen to balance the representation of theoretical and experimental backgrounds.
This course is partially supported by the National Institute of Mental Health, National Institute for Neurological Disorders and Stroke, and the National Institute for Drug Abuse, NIH.
Optical Microscopy & Imaging in the Biomedical Sciences
Course Date: September 7 – September 17, 2016
Deadline: June 13, 2016
Directors: Robert Hard, University at Buffalo and Hari Shroff, NIH
This course is designed primarily for research scientists, postdoctoral trainees, and advanced graduate students in animal, plant, medical, and material sciences. Non-biologists seeking a comprehensive introduction to microscopy and digital imaging will benefit greatly from the course. Some prior theoretical or practical understanding of the basic principles of optics and microscopy is necessary. This 10 day course is limited to 26 students. It consists of correlated lectures, laboratory exercises, demonstrations, and discussions that will enable the participant to obtain and interpret microscope images of high quality, to perform quantitative optical measurements, and to produce high quality digital video, and digital records for documentation and analysis.
Topics to be covered include: (a) fundamental principles of microscope design, image formation, resolution, contrast; (b) bright field, dark field, phase contrast, polarized light, differential interference contrast, interference reflection, and fluorescence microscopy; (c) cameras, signal to noise ratio, digital image recording, processing and analysis, multispectral imaging; (d) advanced fluorescence– fluorescent probes, TIRF, FRET, FLIM, FRAP, polarization of fluorescence, fluorescence correlation spectroscopy; (e) digital image restoration/deconvolution, and 3-D imaging principles, confocal scanning microscopy, multiphoton excitation fluorescence microscopy; application of the optical methods to live cells will be emphasized. Other specimens also will be covered.
Students will have direct hands-on experience with state-of-the-art microscopes, digital cameras, recorders, and image processing equipment provided by major optical, electronics, and software companies. Instruction will be provided by experienced staff from universities and industry. Students are encouraged to bring their own biological and material specimens, and to discuss individual research problems with the faculty.
Summer Program in Neuroscience, Ethics & Survival
Course Date: June 12 – July 11, 2016
Deadline: February 25, 2016
Directors: Keith Trujillo, California State University San Marcos; Jean King, University of Massachusetts Medical School; and Edward Castañeda, University of Texas at El Paso
The Summer Program in Neuroscience, Ethics & Survival (SPINES) provides a rich experience in neuroscience. The core of the program is an intensive one-month experience, in which students are exposed to neuroscience laboratory techniques, contemporary neuroscience research, ethics and survival skills (including grant writing, teaching, public speaking, and others). Lecture, lab, workshop and discussion formats are used. In a second optional month, students may apply to work full time in a research laboratory at the MBL, especially those funded by the National Institute of Mental Health. The program is targeted to groups underrepresented in neuroscience to increase the probability of professional success, although applications from any qualified students interested in the SPINES curriculum are welcome.