NeuroSummerSchools

This readme will contain a list of summer (and seasonnal) summer schools in neuroscience and related fields. The courses are ordered by deadlines (DL) for those who provided it. This is not an exhaustive list, but contains all the summer schools I found over the last two years. To add, remove or update a school in this list, please open an issue or create a pull request (the latter being preferred). To open an issue, click on the issues sections above and then click on the New issue bottom on the top right.

Note that some summer schools are free and sometimes even cover all expenses or offer grants for those in need.

If you would like to add some summer schools to this list, go here.

Neuroscience
Related Fields (modeling, machine learning, etc.)

Neuroscience

Barcelona summer school for Advanced Modelling of Behavior (BAMB!)

Barcelona, Spain ~ 4-10 September 2019

Application Deadline : 3 June, 2019

The new Barcelona summer school for Advanced Modelling of Behavior (BAMB!) teaches advanced techniques in model-based analysis of behavior (humans and other species) to cognitive and computational neuroscientists at PhD and early career levels. This will be achieved through structured lectures, talks, hands-on tutorials and group project aimed at making knowledge obtained directly applicable to the participants' own research. We want the trainees to acquire both the conceptual bases and the technical skills that will enable them to pursue a full modelling approach on their own when they come back to their lab.

The course is intended for PhD students and postdocs in cognitive and computational neuroscience with solid background in computational/quantitative analysis to benefit maximally from the advanced training offered by the course. Proficiency in either Python or Matlab is also required. We will seek a nice blend of experimentalists (cognitive psychology / neuroscience) and theoreticians (with or without experience in cognitive modeling).Female scientists and scientists from underrepresented countries are especially encouraged to apply.

Organizers: Chris Summerfield (Oxford / Deepmind), Klaus Wimmer (CRM, Barcelona), Alex Hyafil (UPF/CRM, Barcelona)

Confirmed Faculty: Jean Daunizeau (ICM, Paris), Alex Hyafil (UPF/CRM, Barcelona), Kerstin Preuschoff (Geneva), Alfonso Renart (Champalimaud), Maneesh Sahani (UCL)

Memory School (DL: 8 January, 2017)

Centre de Recerca Matemàtica, Barcelona, Spain ~ January 16 - 20, 2017

This is a week-long intensive school on the biology and mathematics of memory. Topics covered will be: synaptic plasticity, memory recall and consolidation, hippocampal and cortical models and more. This school is appropriate for graduate students, post-doctoral researchers and advanced researchers.

Advanced Course on Neural Data Analysis (DL: 31 January, 2017)

Juelich, Germany ~ March 26 - April 8, 2017

Techniques to record neuronal data from single neurons and population of neurons are rapidly improving. Meanwhile recordings are possible from hundreds of channels simultaneously while animals perform complex tasks. Thus also the analysis of such data becomes increasingly challenging. This advanced course aims at providing deeper insights in state-of-the-art questions in neuroscience, analysis approaches and how to formalize questions to neuronal data so they can be answered quantitatively.

Neurobiology (DL: February 1, 2017)

Marine Biological Laboratory, Woods Hole, US ~ June 2 - July 31, 2017

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.

Neural Systems & Behavior (DL: February 1, 2017)

Marine Biological Laboratory, Woods Hole, US ~ June 4 - July 31, 2017

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.

OIST Computational Neuroscience Course (DL: February 5, 2017)

Okinawa Institute of Science and Technology, Okinawa, Japan ~ June 26 - July 13, 2017

The aim of the Okinawa Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling.

OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have lectures by international experts. We invite those who are interested in integrating experimental and computational approaches at each level, as well as in bridging different levels of complexity.

Kavli Summer Institute in Cognitive Neuroscience (SI) (DL: February 10, 2017)

Santa Barbara, CA, US ~ June 26 - July 7, 2017

The Kavli Summer Institute in Cognitive Neuroscience (SI), supported by NIMH, NIDA and the Kavli Foundation, advances the cognitive neurosciences by training the next generation of researchers in emerging information, methods and theoretical perspectives in mind-brain science, including how this knowledge is applied in translational research that addresses major mental health challenges.

Chemical Neuromodulation: Neurobiological, Neurocomputational, Behavioural and Clinical (DL: February 13, 2017)

Bertinoro, Italy ~ June 18 - 24, 2017

Chemical neuromodulation refers to that set of neurotransmitter systems that arise in the subcortical brain to influence the functions of forebrain networks to produce behaviour and cognitive outputs, under a variety of different states of arousal. These neurotransmitter systems, which include the monoamines such as dopamine, noradrenaline and serotonin, as well as acetylcholine and orexin, are implicated in diverse behavioural and physiological functions and have been implicated in many neuropsychiatric and neurological disorders. The systems have been extensively researched in isolation but have rarely been directly compared experimentally or in conceptual terms; hence one theme of this School will be to make such comparisons.

The basic neuroscience of these neurotransmitter systems will be covered by lectures and discussion groups by an international faculty. Organization and functions of the systems will be compared using a range of multidisciplinary techniques and approaches. These will include the use of novel neuroscience tools provided by opto- and chemo-genetics, electrophysiology, neuropharmacological techniques such as in vivo voltammetry, combined with sophisticated theoretical approaches from cognitive and behavioural neuroscience, including neurocomputational approaches and neuroimaging in experimental animals and humans. Clinical applications will also be covered.

Nengo Summer School (DL: February 15, 2017)

Waterloo University, Waterloo, Canada ~ June 4 - June 16, 2017

This two-week school will teach participants how to use the Nengo simulation package to build state-of-the-art cognitive and neural models. Nengo has been used to build what is currently the world's largest functional brain model, Spaun, and provides users with a versatile and powerful environment for modelling cognitive and neural systems to run in simulation and on neuromorphic hardware. We welcome applications from all interested graduate students, research associates, postdocs, professors, and industry professionals. No specific training in the use of modelling software is required, but we encourage applications from active researchers with a relevant background in psychology, neuroscience, cognitive science, computer science, robotics, neuromorphic engineering, or a related field.

The main goal of the summer school is to have participants learn to build state-of-the-art neural or cognitive models using Nengo. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, modelling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or provide a proof-of-concept of various neural mechanisms. Projects can be focused on software, hardware, or a combination of both.

Frontier in Neurophotonics (DL: March 1, 2017)

Neurophotonic Center, Québec, Canada ~ June 2 - 21, 2017

Frontiers in Neurophotonics is an opportunity to meet fellow researchers and students from around the world, discuss and discover the latest advances in live cell optical imaging techniques put in perspective by experimental challenges in the field of neuroscience. The school will combine tutorials given by experts in photonics and neuroscience and hands-on experiments involving advanced optical approaches to measure, manipulate and follow molecular events in living neuronal cells.

Transylvanian Experimental Neuroscience Summer School (DL: March 5, 2017)

The Pike Lake, Transylvania, Romania ~ June 1 – 19, 2017

TENSS concentrates top-level international expertise to teach a dozen students techniques and concepts in experimental systems neuroscience. We focus on modern optical and electrophysiological methods to study the connectivity and function of neuronal circuits. The course is designed to be intensive and highly interactive, including both lab sessions and theoretical lectures. Coursework will take place in a land of myth and legend, beyond large forests (Transylvania), on the shores of a picturesque natural reserve called Pike Lake. Applications are welcome from interested (and interesting) graduate students and postdocs.

Methods in Computational Neuroscience (DL: March 7, 2017)

Marine Biological Laboratory, Woods Hole, US ~ July 30 – August 25, 2017

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?

Brains, Minds and Machines (DL: March 14, 2017)

Marine Biological Laboratory, Woods Hole, US ~ August 13 – September 3, 2017

The basis 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 computations 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 and will lead the development of true biologically inspired AI.

Computational and Cognitive Neuroscience (CCN) Summer School (DL: March 15, 2017)

NYU Shanghai, Shanghai, China ~ July 6 – 29, 2017

Designed to emphasize higher cognitive functions and their underlying neural circuit mechanisms, the course aims at training talented and highly motivated students and postdoctoral fellows from Asia and other countries across the world. Applicants with quantitative (including Physics, Mathematics, Engineering and Computer Science) or experimental background are welcomed. The lectures will introduce the basic concepts and methods, as well as cutting-edge research on higher brain functions such as decision-making, attention, learning and memory. Modeling will be taught at multiple levels, ranging from single neuron computation, microcircuits and large-scale systems, to normative theoretical approach. Python-based programming labs coordinated with the lectures will provide practical training in important computational methods.

Optical Imaging and Electrophysiological Methods in Neuroscience (DL: March 15, 2017)

Paris, France ~ June 12 - 24th, 2017

Optical Imaging and Electrophysiological Methods in Neuroscience is a 11 day residential course of lectures, demonstrations and practical work in electrophysiology and microscopy applied to neurophysiology. It was initiated by the ENP in 2009.

Interacting with neural circuits (DL: March 20, 2017)

Champalimaud Centre for the Unknown, Portugal ~ July 2 – 22, 2017

Understanding how activity in neural circuits drives behavior is a fundamental problem in neuroscience. Making this link requires detailed information about the cell types and their connectivity, as well as the spatiotemporal patterns of activity in neural circuits in the intact brain during behaviour. Moreover, probing causal relationships between cellular and circuit-level processes and behaviour requires perturbation of specific elements of the circuit in a temporally and spatially precise manner. This course will highlight the new anatomical, optical, genetic, electrophysiological, and pharmacogenetic approaches that are available for addressing these challenges. The faculty will discuss tool development through to their implementation in diverse model systems. Students will learn the potential and limitations of these techniques, allowing them to both design and interpret experiments correctly.

Advanced Techniques for Synapse Biology (DL: March 20, 2017)

Bordeaux Neurocampus, France ~ July 3 – 23, 2017

Synapses are the major sites of information processing in the brain. The complexity of the synapse has been described in the past few years in great molecular details and major achievements have been gained in the understanding of networks of proteins occurring at the pre-synaptic cytomatrix and the postsynaptic compartment of both excitatory and inhibitory synapses. Synaptic dysfunction is a central aspect of many brain disorders (“synaptopathies”) and synapses are and potentially will be the main target of drugs for brain diseases. Synapses integrate complex signals through temporal and spatial codes and undergo rapid structural and functional changes (synaptic plasticity) that underlie the formation of engrams in the brain. Maladaptation of such processes can lead to aberrant perception, cognitive dysfunction or neurodegeneration. The study of the molecular mechanisms of synaptic function and -plasticity are the key to understanding of how the brain works and what goes wrong in brain disease. The advanced course will expose students to state-of-art techniques for molecular imaging and functional methodologies, through direct hands-on experiments.

CAJAL Course in Computational Neuroscience (DL: March 20, 2017)

Champalimaud Centre for the Unknown, Portugal ~ August 6 – 26, 2017

Computational Neuroscience is a rapidly evolving field whose methods and techniques are critical for understanding and modeling the brain, and also for designing and interpreting experiments. Mathematical modeling is one of the few tools available to cut through the vast complexity of neurobiological systems and their many interacting elements. This school teaches the central ideas, methods, and practice of modern computational neuroscience. Our mission with the course is to train the future generation of both computational and experimental neuroscientists, and to foster theory-driven experimental research. We provide a broad overview of theoretical techniques, from the introductory to the more advanced that are critical for understanding and modeling the brain, and for designing and interpreting experiments. A range of theoretical topics is covered, including cellular biophysics, neural network dynamics, neural coding and computation, statistical analysis of neural data, and behavioral and cognitive aspects of neural function. The course includes a strong hands-on and project-oriented component. Furthermore, the course will be held in Lisbon, Portugal with its many nearby sites and beaches offering ample opportunities to relax/explore during course breaks.

SysNeuron on System, Computational Neuroscience & Neurodynamics Summer School (DL : March 30, 2017)

Budapest, Hungary ~ June 12 - August 4th, 2017

The Systems Neuroscience program follows the approach of systems theory in understanding the brain. The aim is to provide undergraduate students a view of the brain as a whole via unfolding, at least in part, its immense complexity. This is a major challenge of all time, but the right answer should be one that can integrate actual knowledge. As we are in the fortunate period of time when high performance tools (both hardware and software) and large datasets are getting more and more available, systems thinking is inevitable in brain research. Therefore, throughout the course students will learn how different approaches - reductionist, holist and functionalist - are all useful and necessary in understanding the brain.

In one way the course is structured by introducing the students the different levels of organization all being complex systems themselves. We start with molecular machineries at the subcellular level (course A.I.) then turn into the cellular level by learning why the neuron is considered as the unit of brain organization (course A.II.). In the next step it is shown how the milliards of neurons make up the cerebral cortex and how this evolutionarily new structure can perform diverse cognitive and other functions (course A.II.). Finally, whole brain functions and functioning will be approached via its role in behavior (course C.I.).

Computational Neuroscience Vision (DL : March 31st, 2016)

Cold Spring Harbor, NY, US ~ July 11 - 14, 2016

Computational approaches to neuroscience will produce important advances in our understanding of neural processing. Prominent success will come in areas where strong inputs from neurobiological, behavioral and computational investigation can interact. The theme of the course is that an understanding of the computational problems, the constraints on solutions to these problems, and the range of possible solutions can help guide research in neuroscience. Through a combination of lectures and hands-on experience with MATLAB-based computer tutorials and projects, this intensive course will examine visual information processing from the retina to higher cortical areas, spatial pattern analysis, motion analysis, neuronal coding and decoding, attention, and decision-making.

Microelectrode Techniques for Cell Physiology (DL: March 31st, 2017)

Plymouth, United-Kingdom ~ August 30 - September 13, 2017

A variety of marine and other preparations will be used to illustrate the possibilities and limitations of the following techniques ;

Electronics, Patch clamp, Intracellular injection, Slice recording, Optogenetics, Voltage clamp, Ion-sensitive electrodes, Fluorescent indicators, Photolysis, Multielectrode Arrays, Amperometry & Transgenic labelling.

The workshop is intended mainly for postgraduate students and postdoctoral workers from any discipline who wish to learn these techniques for use in their research.

Summer Workshop on the Dynamic Brain (DL: April 1st, 2017)

Friday Harbor Laboratories, Washington, US ~ August 19 - September 3, 2017

This intensive, two-week, projects-based, interdisciplinary course aims to give advanced students in neuroscience, biology, physics, engineering and computer science a rapid introduction to the current state of understanding of the neurobiology of sensory processing, including anatomy, physiology and neural coding.

The workshop will include include data analyses, Python and other software boot-camps, and lectures, taught by faculty from the University of Washington and the Allen Institute for Brain Science, on topics focused on the mammalian cortex and closely associated satellite structures. Lecture topics will include biophysics of cortical neurons, neuroanatomy and neurophysiology of cortex, genomics, neuronal cell types, neuronal development, connectomics, network analysis, voltage- and calcium-dependent brain imaging, theories and modeling of neocortex and associated structures, big data approaches and perceptual neuroscience (with a focus on vision).

Telluride Neuromorphic Cognition Engineering Workshop (DL : April 2nd, 2017)

Telluride, Colorado, US ~ June 25th - July 16th, 2017

Neuromorphic engineers design and fabricate artificial neural systems whose organizing principles are based on those of biological nervous systems. Over the past 18 years, this research community has focused on the understanding of low-level sensory processing and systems infrastructure; efforts are now expanding to apply this knowledge and infrastructure to addressing higher-level problems in perception, cognition, and learning. In this 3-week intensive workshop and through the Institute for Neuromorphic Engineering (INE), the mission is to promote interaction between senior and junior researchers; to educate new members of the community; to introduce new enabling fields and applications to the community; to promote on-going collaborative activities emerging from the Workshop, and to promote a self-sustaining research field. The 2017 workshop will be focused on the theme of Neuromorphic Autonomous Agents.

NRSN Summer School in Neuroscience on Neural Circuits and Behavior (DL: April 3rd, 2017)

Kavli Institute for Systems Neuroscience, NTNU, Trondheim, Norway ~ August 13 - 19, 2017

Our goal is to bring together a wide range of experts in diverse approaches from electrical and optical measurements of brain activity to molecular, anatomical, behavioral and computational tools to study the function of brain circuits. We aim to show students the application of these wide ranges of techniques in a range of model species including rodents, zebrafish, flies, and humans.

We will also discuss about the advantages of these techniques, their potential pitfalls and how they can be synergistically combined. In addition to lectures, research talks and journal club sessions, the course will provide practical experience through demos and hands on training. Moreover, we will have group discussions and students’ presentations for combining the theoretical and the practical parts of the course.

Visual Neuroscience: From Spikes to Awareness (DL : 3 April, 2018)

Giessen, Germany ~ September 2-14 2018

The European Summer School exposes young vision researchers—at the late pre-doctoral or early post-doctoral level—to the principal methods and seminal issues of contemporary visual neuroscience. In addition, it seeks to build a basic fluency in the emerging lingua franca of computational neuroscience. The range of topics is broad, literally from spikes to awareness, and the pace correspondingly brisk. This intensive experience should allow participants take a broader view of, and make more informed decisions about, their future research direction.

The European Summer School is taught by leading researchers in neurobiology, neuropsychology, psychophysics, and theoretical neuroscience. Two thematically related topics are covered each day, with approximately 3 hours allotted to each (including discussion time). An after-dinner discussion provides an opportunity to contrast and compare the day’s lectures. In addition, students pursue computational and theoretical projects (based on Matlab) during the afternoon, to experiment with key concepts and techniques of computational neuroscience.

Summer School in Computational Sensory-Motor Neuroscience (DL: April 11, 2016)

University of Minnesota, Minneapolis, MN, USA ~ July 30 - August 13, 2017

This unique summer school focuses on computational techniques integrating the multi-disciplinary nature of sensory-motor neuroscience through combined empirical-theoretical teaching modules and makes use of databases of movement data (NSF CRCNS). Major breakthroughs in brain research have been achieved through computational models. The goal of the Summer School in Computational Sensory-Motor Neuroscience is to provide cross-disciplinary training in mathematical modeling techniques relevant to understanding brain function, dysfunction and treatment. In a unique approach bridging experimental research, clinical pathology and computer simulations, students will learn how to translate ideas and empirical findings into mathematical models. Students will gain a profound understanding of the brain’s working principles and diseases using advanced modeling techniques in hands-on simulations of models during tutored sessions by making use of data / model sharing. This summer school aims at propelling promising students into world-class researchers.

Computational Approaches to Memory and Plasticity (DL: April 15, 2017)

National Centre for Biological Sciences, Bangalore, India ~ July 19 - August 3rd, 2017

CAMP @ Bangalore (Computational Approaches to Memory and Plasticity at NCBS, Bangalore) is a 16-day summer school on the theory and simulation of learning, memory and plasticity in the brain. PhD students and post-docs from theoretical and/or experimental backgrounds (physics, math, neuroscience, engineering, etc.) are invited to apply. Familiarity with programming, dynamical systems, and/or computational neuroscience is desirable, but not necessary. We may also select a small number of exceptional undergraduate and Masters level students for the course, if they have sufficient background via courses and especially via project / hobby work related to these areas (write in your statement of interest & CV). The course will start with remedial tutorials on neuroscience / math / programming and then work upwards from sub-cellular electrical and chemical signaling in neurons, onward to micro-circuits and networks, all with an emphasis on learning, memory and plasticity.

Berkeley summer course in mining and modeling of neuroscience data (DL: End April, 2016)

Redwood Center for Theoretical Neuroscience, UC Berkeley, US ~ July 11 - 22, 2016

This course is for students and researchers with backgrounds in mathematics and computational sciences who are interested in applying their skills toward problems in neuroscience. It will introduce the major open questions of neuroscience and teach state-of–the-art techniques for analyzing and modeling neuroscience data sets. The course is designed for students at the graduate level and researchers with background in a quantitative field such as engineering, mathematics, physics or computer science who may or may not have a specific neuroscience background. The goal of this summer course is to help researchers find new exciting research areas and at the same time to strengthen quantitative expertise in the field of neuroscience. The course is sponsored by the National Institute of Health, the National Science Foundation from a grant supporting activities at the data sharing repository CRCNS.org, and the Helen Wills Neuroscience Institute.

NEURON Simulation Environment Summer Course (DL : May 15, 2017)

Wright State University, Fairborn, Ohio, US ~ June 5 - 10, 2017

This intensive multi-day course is designed for those who are planning to use NEURON in neuroscience research or teaching, or already have active modeling projects that involve NEURON. It presents what you need to know to build and work with models of individual neurons and networks of neurons.

This course is suitable for users at all levels of expertise.

G-Node Course on Neural Data Analysis (DL : May 15, 2017)

Munich, Germany ~ July 31 - August 4, 2017

The German Neuroinformatics Node (G-Node) organizes its eighth international one-week course on neural data analysis (formerly known as the G-Node Winter Course) at the LMU in Munich. The course offers hands-on experience in state-of-the-art methods for analyzing complex neural data to PhD students and postdocs from theoretical or experimental backgrounds. Applicants should have an elementary understanding of linear algebra and statistics, as well as basic programming knowledge in either Matlab or Python.

Summer Neurolinguistics School 2017 (DL : May 15, 2017)

Moscow, Russia ~ June 22 - 24, 2017

This year, the topic is Brain Stimulation in Language Research and Therapy. The event will take place in Moscow, Russia, June 22–24, 2017. The purpose of the school is to serve both as an educational event for students entering the field and as an academic environment where researchers and clinicians can exchange ideas and discuss the latest achievements in the field. This year the school will be devoted to various brain stimulation methods and their applications in neurolinguistic research and in language therapy. The school program includes lectures by such world-renowned researchers as Nina Dronkers (University of California), Roelien Bastiaanse (University of Groningen), and Dirk-Bart den Ouden (University of South Carolina).

Summer Course on Computational Neuroscience (DL: June 24, 2017)

Gôttingen, Germany ~ September 6 - 16, 2017

The school consists of consecutive two day thematic blocks dedicated to a particular theoretical approach to neural circuit dynamics. Each lecturer will give a self-contained introduction to his/her particular theoretical approach in two sets of morning lectures. In the afternoon, participants will work on problem sets designed to develop proficiency in these theoretical tools and approaches, for an in-depth understanding of the mathematical techniques presented earlier that day. Every second day, participants will present the results of their problems sets followed by a closing discussion lead by the lecturer in charge. A laid back style evening lecture by a senior scientist will take place right after that.

Latin American School on Computational Neuroscience (LACONEU) (DL: September 30th, 2016)

Valparaiso, Chile ~ January 9 – 27, 2017

The principal aim of LACONEU2017: 4th Latin-American Summer School in Computational Neuroscience is to promote in Latin America the field of Computational Neuroscience through cutting edge mathematical and computational science tools and its applications in Biomedical Research and Clinical Application. The multidisciplinary study of brain function using neuroscience, mathematics and computational approaches helps to a better understanding of brain functionalities under normal or pathological states, as well as, to enhance important advances in education, theoretical frameworks, brain imaging, and biomedical therapies

In this Summer School we expect to generate a participative and interactive environment where the exchange between students and researchers, based on fundamental theoretical and practical knowledge in computational neuroscience, will foster regional internationalization establishing a strong and long-lasting collaborations between Latin America and more developed countries. The excellence of the Faculty team willing to participate in this Summer School is a unique opportunity that will help to boost this research area in our countries.

School on Neurotechniques (DL: ???)

University of Padua – Italy ~ 15 – 19 February, 2016

Investigating information processing and identifying operational rules of brain neural circuits relies on the capability to selectively record and stimulate multiple neurons within a network. The toolbox of available techniques conceived to meet this need is rapidly expanding.The CSN School on Neurotechniques 2016 will offer an overview on advanced electrical- and light-based recording methods of neuronal excitability, focusing on those that are most relevant for the investigation of neural networks ‘in vitro’ and ‘in vivo’ and for application in neuroprosthetics. Methods and protocols on laboratory techniques and signal analysis will be presented.

{FR} Connectivité multimodale, de la théorie aux applications (DL: ???)

Domaine Cataraqui, Québec, Canada ~ May 15 – 16, 2017

L'École d'Été 2017, offrira une formation théorique et pratique de base sur les analyses de connectivité appliqués à des données de différents types tels que l'EEG/MEG et l'IRM. L'École se déroule sur deux jours : une première journée sera dédiée à la formation pratique et accueillera plusieurs conférenciers et la deuxième journée sera consacrée à une formation pratique sous forme d'ateliers. L'École d'été aura lieu les lundi et mardi 15 et 16 mai 2017 en journée, au Domaine Cataraqui. Les participants auront la possibilité d'assister qu'à la journée théorique (première journée) ou de participer aux deux journées.

Summer Institute in Neuroimaging and Data Science (Neurohackweek) (DL: ???)

The University of Washington eScience Institue, September 4th-8th, 2017

Neurohackweek is a 5-day hands-on workshop in neuroimaging and data science, held at the University of Washington eScience Institute. Participants learn about technologies used to analyze human neuroscience data, and to make analysis and results shareable and reproducible. Morning sessions are devoted to hands-on lectures and afternoon sessions are devoted to participant-directed activities: hackathon and breakout sessions on topics of interest.

Ion channels in the brain in health and disease (DL: ???)

Bordeaux Neurocampus, France ~ September 4 – 22, 2017

Ion channels play a major role in neuronal excitability. Diseases, termed channelopathies, are related to inherited or acquired dysfunctions of ion channels: epilepsy, migraine, ataxia and deafness. Roughly 15% of known therapeutic drugs including anaesthetics, analgesics, anti-epileptics and anxiolytics have their primary action on ion channels, making them the second largest target class after G-protein coupled receptors. With the advent of a better understanding of cellular physiology and identification of the molecular components that constitute individual channel types and/or control their activity, rational molecular-based strategies to identify ion channel modulators are now within reach.

We are organizing a summer course to provide promising young investigators with a comprehensive introduction to state-of-the-art techniques in ion channel study, including - but not limited - to genetics, electrophysiology, imaging, as well as structure-function and pathophysiological approaches. This 3-week course is a practical “hands-on” introduction to advanced methods in ion channel recording and analysis and will cover sufficient background such that all participants will be able to establish these techniques in their home laboratories.

Connectomics: from Micro- to Meso- and Macro-Scales (DL: ???)

Bordeaux Neurocampus, France, Portugal ~ October 2 – 21, 2017

The CAJAL course in Connectomics is an intensive three-week course that guides participants through the theory and practice of state-of the art methods to address pertinent questions in the field of structural/functional connectomics from mice to man. This goal will be achieved through a unique balance of lectures from world-wide experts in their respective fields to experimental demonstrations and hands-on laboratory work in small groups. During the course each participant will become familiar with a range of approaches, ranging from connectivity studies in the brain slice and in vivo in the behaving brain using electrophysiological, calcium imaging, optogenetic, viral trans-synaptic tracing, whole brain clearing and neuroimaging approaches with magnetic resonance imaging (functional and structural imaging) in both mice and human subjects (performed on the participants) and postmortem tissue.

Related Fields (modeling, machine learning, etc.)

This list will contain some summerschools in programming, machine learning, dynamical systems and more.

Complexity Summer School List

This webpage contains a list of summer schools, workshops and conferences in the field of complex systems and related fields. I will not copy all the links as this webpage is nicely organized already.

Connecting Biological Data with Mathematical Modelsl (DL: Feburary 3, 2017)

University of Tennessee, Knoxville, US ~ June 19 - 23 2017

This graduate program will have instructors from across North America whose research expertise is mathematical modeling in biological systems using real data. Some of the techniques to be covered include:

Maximum likelihood and Bayesian approaches to inference
Parameter estimation
Model identifiability
Uncertainty and sensitivity analysis

The program will include lectures on techniques and modeling using specific data sets, and there will be computer activities focusing on learning techniques and sessions to receive feedback on participants’ own research problems. Researchers from the mathematical and biological sciences will be featured speaker

The Machine Learning Summer School (DL: Feburary 17, 2017)

Tübigen, Germany ~ June 19 - 30 2017

The MLSS is a renowned venue for graduate students, researchers, and professionals. It offers an opportunity to learn about fundamental and advanced aspects of machine learning, data analysis and inference, from intellectual leaders of the field. We are very happy to announce a faculty of highly acclaimed speakers.

VISion Understanding and Machine intelligence (DL: April 8, 2017)

INES TEC Porto, Portugal ~ July 7-14, 2017

VISion Understanding and Machine intelligence – visum 2017 is the fifth edition of a Summer School that aims to gather Ph.D. candidates, Post-Doctoral scholars and researchers from academia and industry with research interests in computer vision and machine intelligence.

Deep Learning Summer School (DL: April 11, 2016)

University of Montreal, Montreal, Canada ~ August 1-7, 2016

Deep neural networks that learn to represent data in multiple layers of increasing abstraction have dramatically improved the state-of-the-art for speech recognition, object recognition, object detection, predicting the activity of drug molecules, and many other tasks. Deep learning discovers intricate structure in large datasets by building distributed representations, either via supervised, unsupervised or reinforcement learning.

This summer schools is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.

Summer School in Image Based Biomedical Modeling (DL: May 20, 2017)

Park City, SCI Institute, University of Utah, UT, USA ~ July 10-20, 2017

This two-week course offers field-specific expertise and hands-on experience solving bioelectric or biomechanical problems that arise in current biomedical research and clinical practice. Participants will receive training in numerical methods, image analysis, and computational tools necessary to carry out end-to-end, image based, subject specific simulations in bioelectricity or biomechanics, using freely available software. The course also offers keynote presentations by internationally known speakers as well as career related sessions on topics like Integrity in Research, Simulation Based Research Strategies, and a Grants and Funding in Science. The course is set in the beautiful setting of Park City, UT, with endless hiking, biking and mountain living experiences directly accessible.

Twelfth Madrid UPM Advanced Statistics and Data Mining Summer School (DL: June 5th, 2017)

Technical University of Madrid, Madrid, June 26th to July 7th

The summer school comprises 12 week-long, 15 lecture hours, courses, in subjects such as Neural Networks and Deep Learning, Bayesian Networks, Bayesian Inference, Text Mining, and Time Series. Attendees may register in each course independently, and attend from one up to six different courses. Each course has theoretical as well as practical classes, in which each technique is put into practice, using mainly R and python. The summer school will be held at UPM's Montegancedo Campus. Extended information on course programmes, price, venue, accommodation and transport is available at the school's website.

Advanced Scientific Programming in Python (DL: May 31, 2017)

Nikiti, Greece ~ August 28 – September 2, 2017

Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game.

PhABC / neuroSummerSchools

readme

NeuroSummerSchools

Table of Contents

Neuroscience

Related Fields (modeling, machine learning, etc.)