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FLORIAN FIEBIG DOCTORAL THESIS Active Memory Processing on Active Memory Processing on Multiple Time-scales in Simulated Cortical Networks with Hebbian Plasticity FLORIAN FIEBIG Multiple Time - scales Simulated Cortical in NetworksHebbian with Plasticity TRITA-EECS-AVL-2018:91 ISBN 978-91-7873-030-8 Active Memory Processing on Multiple Time-scales in Simulated Cortical Networks with Hebbian Plasticity Thesis Submitted to KTH Royal Institute of Technology and University of Edinburgh towards PhD in Computer Science and Doctor of Philosophy By FLORIAN FIEBIG FLORIANunder the guidance FIEBIG of Prof. Anders Lansner KTH Stockholm and Prof. Mark van Rossum University of Edinburgh Stockholm, Sweden 2018 Abstract This thesis examines declarative memory function, and its underlying neural activity and mechanisms in simulated cortical networks. The included simulation models utilize and synthesize proposed universal computational principles of the brain, such as the modularity of cortical circuit organization, attractor network theory, and Hebbian synaptic plasticity, along with selected biophysical detail from the involved brain areas to implement functional models of known cortical memory systems. The models hypothesize relations between neural activity, brain area interactions, and cognitive memory functions such as sleep-dependent memory consolidation, or specific working memory tasks. In particular, this work addresses the acutely relevant research question if recently described fast forms of Hebbian synaptic plasticity are a possible mechanism behind working memory. The proposed models specifically challenge the “persistent activity hypothesis of working memory”, an established but increasingly questioned paradigm in working memory theory. The proposed alternative is a novel synaptic working memory model that is arguably more defensible than the existing paradigm as it can better explain memory function and important aspects of working memory-linked activity (such as the role of long-term memory in working memory tasks), while simultaneously matching experimental data from behavioral memory testing and important evidence from electrode recordings. 1 Sammanfattning Denna avhandling undersöker deklarativ minnesfunktion och dess underliggande neurala aktivitet och mekanismer i simulerade kortikala nätverk. De medföljande simuleringsmodellerna utnyttjar och syntetiserar föreslagna universella beräkningsprinciper i hjärnan, såsom modulariteten hos den kortikala organisationen, attraktornätteori och Hebbsk synaptisk plasticitet, tillsammans med utvalda biofysiska detaljer från de involverade hjärnområdena för att implementera funktionella modeller av kända kortikala minnesystem. Modellerna genererar hypoteser om relationen mellan neural aktivitet, hjärnområdesinteraktioner och kognitiva minnesfunktioner såsom sömnberoende minneskonsolidering och specifika arbetsminnesuppgifter. I synnerhet behandlar detta arbete den aktuella och relevanta forskningsfrågan om huruvida nyligen beskrivna snabba former av Hebbsk synaptisk plasticitet utgör en möjlig mekanism bakom arbetsminnet. De föreslagna modellerna utmanar specifikt hypotesen att arbetsminnet lagras i form av pågående aktivitet, ett etablerat men alltmer ifrågasatt paradigm inom arbetsminnesteorin. Det föreslagna alternativet är en ny synaptisk arbetsminnemodell som är mer försvarlig än det befintliga paradigmet, eftersom den bättre kan förklara minnesfunktionen och viktiga aspekter av arbetsminnesbunden aktivitet (såsom rollen för långtidsminnet i arbetsminnesuppgifter), samtidigt som den matchar experimentella beteendedata och elektrofysiologiska mätningar från minnesexperiment. 2 Acknowledgements My deepest gratitude is to my main supervisor, Professor Anders Lansner. As a student representative in the PhD Council over many years I heard hair-raising stories about the difficulties other students sometimes have in navigating their relationship with their supervisor. I simply felt blessed to have a calm, senior supervisor, a dedicated scholar with a legacy that has seen it all and knows what he can expect of a highly committed student. A PhD is never just about results, it’s about growth and opportunity as well. You have given me plenty of time and resources to explore my field at conferences, workshops, and summer schools across the globe. Even more time to explore computational models and the unending pile that constitutes the neuroscientific experimental literature. But you also knew exactly when to push towards the finish whenever I was about to get lost in the deep end of my curiosity. You drew the lines that define milestones in a continuous journey of learning and exploration that by its very nature knows no end. Your contributions to this work are immense, and will shape my professional life to come, as I intend to stay in science. I would also like to thank my second supervisor, Prof. Mark Van Rossum for making the academic exchange with Edinburgh University effortless and a second home on my two long visits. Despite the fact that you shot down one of my early ideas for a Paper (on very valid grounds of contradicting evidence, I should say), I am still grateful for the wider perspective your work and lab members gave me. The Erasmus Mundus Joint Doctoral Program (EuroSPIN) with its far flung academic partners enabled me to view my own field with more distance, enhanced my professional network and enriched my perspective on academia as a whole. The success of joint international programs relies on the hospitality and openness of its member faculty. So thank you for living up to that idea. The same goes for Prof. Stefan Rotter at the Bernstein Center Freiburg. I would like to particularly thank Professor Arvind Kumar for being a wonderfully contrarian sparring partner in all kinds of wild lunch discussions and debates. Some people are just better at playing devil’s advocate than others. Your healthy skepticism and critical attitude has made me better at articulating my work, more rigorous and steadfast in the defense of my own ideas. Thank you also to Professor Pawel Herman, with whom I shared countless quiet late night and weekend workshifts at the tail end of my time at KTH, when so often all was dark but for two nearby offices on second floor. In tea kitchen chats at 2am, you gave me a relatable perspective on the up- and down-sides of choosing academia. For your openness, honesty, and personal kindness, I owe you a debt of gratitude. Thank you to my office mates over the years - particularly Drs. Bernhard Kaplan, Phil Tully, Nathalie Dupuy, Wioleta Kijewska, Katharina Heil, and Martino Sorbaro. You made me feel like I’m in exactly the right place. A big shout-out to Julia Gallinaro, Nebojsa Gasparovic, and Han Lu for the video-conferenced, international journal club on computational plasticity models that we organized and ran on-and-off for two years, a story only EuroSPIN could write. I would also like to thank my fellow lab members and collaborators over all the years - Ylva Jansson, Mikael Lindahl, Henrik Lindén, Pradeep Krishnamurthy, Ramon Hernandez, Jeanette Hellgren-Kotaleski, Erik Fransén, Jan Pieczkowski, Anu Nair, Yann Sweeney, Dinesh Natesan, Daniel Trpevski, Sander Keemink, Marko Filipović, Luiz Tauffer and many, others. 3 A special thanks to my closest friends and fellow K9’ers, many of whom helped shape my publications, presentations, and this thesis by taking an active interest and helping review early drafts Caroline, Camelia, Sarah, Wiebke, Lynn, Joar, Niljana, Gatto, Van, Lucia, Niklas, Elise, Abishek… as we say in the house: “Co-create or die alone”. Particular thanks to Kaj Sennelöv for his Illustrator and Photoshop magic, creating some awesome cover art from my microcircuit drawings. I would also like to thank my mom Regine Fiebig, for always having my back when I left Germany a decade ago in search of a life purpose. The making of a scientist indeed starts much earlier than University, so I would also like to thank posthumously: My late uncle Stefan Zabanski for introducing me to Turbo Pascal, back when I was barely a teenager and my late dad Johannes Fiebig for lifting my scientific spirit at a young age, making natural science meaningful in a family dominated by musicians and school teachers. Despite all the hard work, the long-distance, the repeated acclimation at foreign universities with different bureaucracies, different lab cultures, and the long-drawn out drafting, redrafting, review and revision of research articles across borders, culminating in this thesis, this feels like a beginning, not an end at all. I still have so many questions and the future cannot wait. Funding Work included in this thesis was funded primarily through the Erasmus Mundus Joint Doctoral Program EuroSPIN (European Study Programme In Neuroinformatics, SGA2013-1478,), and further supported by grants from the Swedish Science Council (Vetenskapsrådet, VR- 621-2012- 3502), VINNOVA (Swedish Governmental Agency for Innovation Systems), the Swedish Foundation for Strategic Research (through the Stockholm Brain Institute) and the Swedish E- Science Research Centre (SeRC). Further, the EuropeanUnion’s BrainScaleS project (FP7 FET Integrated Project 269921), and HBP (FP7 under grant agreement 604102). The simulations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC Centre for High Performance Computing. Declaration I declare that this thesis was composed by myself, that the work contained herein is my own except where
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