The IBRO Simons Computational Neuroscience Imbizo
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The IBRO Simons Computational Neuroscience Imbizo 2017 Final Report im’bi-zo | Xhosa - Zulu A gathering of the people to share knowledge. HTTP://ISICNI.GATSBY.UCL.AC.UK DIRECTORS Professor Peter Latham, Gatsby Computational Neuroscience Unit, Sainsbury Wellcome Centre, 25 Howland Street London W1T 4JG, United Kingdom, Email: [email protected] Dr Joseph Raimondo, Department of Human Biology, University of Cape Town, Anzio Road, Cape Town, 7925, South Africa, Email: [email protected] Professor Tim Vogels CNCB, Tinsley Building, Mansfield Road Oxford University, OX1 3SR, United Kingdom, Email: [email protected] LOCAL ORGANIZERS Alexander Antrobus, Gatsby Computational Neuroscience Unit, Sainsbury Wellcome Centre, 25 Howland Street London W1T 4JG, United Kingdom, Email: [email protected] Jenni Jones, Pie Managment, 17 Riverside Rd., Pinelands, Cape Town Tel: +27 21 530 6060 Email: [email protected] SPONSORS Simons Foundation, 160 Fifth Avenue, 7th Floor, New York, New York 10010, USA International Brain Research Organisation (IBRO) & IBRO African Center for Advanced Training in Neurosciences at UCT, Faculty of Health Sciences, Anzio Rd, Observatory, Cape Town, South Africa, 7925 Wellcome Trust, Gibbs Building, 215 Euston Road, London NW1 2BE, England Muizenberg, January 2017 Contents I The Imbizo Neurotheory in Africa . 9 Philosophy 9 Action 9 Course Structure . 11 Lectures and Projects 11 Week 1 - Neural anatomy and higher-order brain function . 11 Week 2 - Biophysics, plasticity & machine learning . 12 Week 3 - Network dynamics and spiking systems . 15 Extracurricular Activities 16 Students . 19 Origins 19 Gender and ethnicity 20 Levels of education 20 Student roster 20 Student Case Studies 23 Abib Duut . 23 Kira Düsterwald . 24 Phumlani Khoza . 25 Ryan Sweke . 26 Fatima Hussein . 27 Kay Ayodele . 28 Lungile Mtetwa . 29 Tutors . 31 Merav Stern . 31 Athanasia Papoutsi . 31 William Podlaski . 31 Alex Antrobus . 32 Eszter Vertes . 32 Sina Tootoonian . 33 Faculty . 35 Larry Abbott . 35 Emery Brown . 35 Surya Ganguli . 36 Peter Latham . 36 Timothy Lillicrap . 36 Máté Lengyel . 37 Panayiota Poirazi . 37 Joseph Raimondo . 37 Srikanth Ramaswamy . 37 Rajnish Ranjan . 38 Tim Vogels . 38 Daniel Wolpert . 38 Location, Accommodation, and Board . 39 Lecture Hall 40 Accommodation 40 Board and Catering 40 II Feedback and Improvements Feedback . 43 Academic feedback 43 Week 1 - Neural anatomy and higher-order brain function . 43 Week 2 - Biophysics, plasticity & machine learning . 44 Week 3 - Network dynamics and spiking systems . 45 Tutor feedback 46 Administrative and general feedback 46 Parting comments 47 Thank you 48 Future Improvments . 51 Course structure and technical aspects 51 Beyond the science 52 III Summary & Impact Summing-up 55 I The Imbizo Neurotheory in Africa . 9 Philosophy Action Course Structure . 11 Lectures and Projects Extracurricular Activities Students . 19 Origins Gender and ethnicity Levels of education Student roster Student Case Studies Tutors . 31 Faculty . 35 Location, Accommodation, and Board 39 Lecture Hall Accommodation Board and Catering Theoretical Neuroscience in Africa Philosophy Understanding the brain is one of the most challenging scientific problems faced by mankind. The payoffs are huge, not only for mental health, but many scientific spinoffs, like artificial intelligence, brain-computer interfacing and treatment of neurological disease. Consequently developed coun- tries are pouring ever increasing research funds into brain science – witness the BRAIN initiative in the US and the Human Brain Project in Europe. In this area, as in many areas, developing countries are at a huge disadvantage, simply because research is expensive. In South Africa (and the African subcontinent more generally) experimental neuroscience is a small but energetic field with a proud history; however, running a a technologically advanced lab is often financially unsustainable. Theoretical neuroscience, on the other hand, needs little more than a laptop, pencil and paper. And yet, this rapidly emerging discipline is critical for analyzing and understanding increasingly complex experimental data and for modelling the brain in its own right. With a rich background in mathematical sciences and similarly good educational programmes in physics and engineering, it should be relatively easy to create world class scientific centers focusing on theoretical neuroscience. These in turn could serve as bridgeheads for the development and strengthening of all aspects of neuroscience in Africa. Action To accelerate the development of neuroscience in southern Africa, we organised a 3-week long Imbizo (from Zulu - Xhosa, “a gathering to share knowledge”) in Muizenberg, South Africa. We brought together 12 world leaders in computational/theoretical neuroscience and machine-learning with 31 African and International students. Over 21 days, we lectured and learned, coded, brain- stormed, ate, and celebrated together, and created a tight knit network of inspired young scientists. In the century of the brain, African scientists and educators are poised to make important contribu- tions to global neuroscience research. The “IBRO Simons Computational Neuroscience Imbizo” aimed to further this goal, offer insight into the status quo, and enable knowledge transfer from the current leaders of the field. In the following pages we will argue that we were largely successful. The announcement poster for the Imbizo. Course Structure Lectures and Projects The Imbizo took place from the 9th to the 28th of January 2017. The school was structured in three thematic weeks, each with a different director. Each week featured 6 working days and one day for social activities. Days began with 4 hours of lectures from 9:00 to 13:00. After a common lunch, the afternoons and evenings were dedicated to work, either in the form of tutorials or free project time. All dinners were held together at various locations around Muizenberg. Each student worked with a tutor on a dedicated mini research project. On the last day of the Imbizo, students presented their results. Week 1: Neural anatomy and higher-order brain function The goal of the first week was twofold. First, provide a broad overview of neuroscience (a near impossible task, given the breadth of the field, but we tried anyway). Second, give the students insight into the difficulty of the problems faced by the brain. Lectures on the first day were given by Peter Latham (University College London). Because of the mixed audience, his lectures focused on relatively basic neuroscience. This included low level facts, such as how single neurons work, how they communicate, and what spikes mean. But it also included a high level view of the computations performed by the brain, which can be loosely divided into sensory processing, action selection and motor control. In addition, there was a large, and possibly highly biased, component on how to figure out how the brain works. The David Marr approach was introduced, and the difficulty of the algorithmic step was discussed in detail. Lectures on the second day were given by Emery Brown (Harvard and MIT). The first of his lecture focused on the analysis of spike trains, including generalized linear models – probably the most popular model of spike trains in the field, and a critical component of almost all neural data analysis. The second lecture focused on anaesthesia: what it does, and how brain states are controlled by various drugs. 12 Intense homework sets in week 1, and beach football matches over lunch. Lectures on the third and fourth days were given by Máté Lengyel (University of Cambridge). The focus was on learning under uncertainty and risk. Basically, life. Here Mate drove home one of the main points of the first lecture, which is that the problems faced by animals are very difficult. He introduced reinforcement learning, and discussed many of the algorithms. He also touched on the important topic of how networks of neurons might be able to implement some of these algorithms. Lectures on the fifth day were given by Daniel Wolpert (University of Cambridge), one of the world’s experts on motor control. This was a very comprehensive foray into the problems faced by the motor system, and how we currently think they are solved. The lecture on the sixth (and last, for this week) day was given by Peter Latham. In the first part of the lecture he tied together the previous lectures, and re-emphasize the big picture of the brain: the problems it faces, and how neuroscientists go about figuring out how it works. In the second part, the students each wrote one question, and he – along with the other faculty who were present, tutors, and even, sometimes, students – spent 90 minutes answering them. The students asked very good questions, and this was probably a useful exercise, as the students had not been asking very many questions during the lectures. During the first week the students were assigned homework based on tutorials (which covered the Bayesian approach, information theory, sparse coding models, and mathematical techniques). They were very serious about working the homework problems; math was discussed in the local pub until late into the night. This work ethic – combined with extensive socializing – set the stage for the rest of the course. Week 2: Biophysics, plasticity & machine learning After the broad and comprehensive overview provided by the first week of isiCNI2017, the second week involved in depth exploration of a variety of themes in computational neuroscience.