Teaching is a very complex, multilayered activity, going far beyond transfer of knowledge. The three main topics of this IK help to understand important aspects of teaching in higher education: Teaching is risky (which is not a defect but at its core), teaching is a reciprocal, social and interpersonal practice, and teaching is often a gendered practice. The course covers these three aspects with a mix of theoretical input and reflection. In the first session, we will reflect on our cultural, disciplinary, and personal understanding of teaching and then cover the three aspects risk, reward, and, finally curiosity.
Objectives
The objectives are to reflect on culturally common, but wrong or at least lopsided views on teaching (including teaching problems), to understand how teaching actually works and to gain a view on teaching that is both inspiring and realistic. A further objective is to understand the discipline-specific nature of teaching and how it is practiced in different fields.
Literature
Biesta, G. (2014). The beautiful risk of education. London: Routledge.
Kreber, C. (2013). Authenticity in and through teaching in higher education: The transformative potential of the scholarship of teaching. London: Routledge.
Kreber, C. (ed.) (2008): The university and its disciplines: Teaching and learning within and beyond disciplinary boundaries. New York, NY: Routledge.
Lecturer
Prof. Dr. Ingrid Scharlau
Ingrid Scharlau studied psychology, philosophy and pedagogics at Bielefeld University and Bochum University. She is professor for Cognitive Psychology and founder and head of the Academic Writing Center as well as the Mentoring Program for Female PhD students at Paderborn University. Her research interests cover cognitive psychology (visuo-spatial attention, time perception, modelling, history of psychology), academic writing (understanding and fostering academic writing in the different disciplines), and higher education didactics (disciplinary cultures, discipline-sensitive education, liberal arts education). Although being mainly an empirical researcher, she has a strong background in meta-theory (history, philosophy of science).
Lecturer:Marieke Van Vugt Fields: Neuroscience, cognitive science, psychology, contemplative science
Content
In the first session, we will introduce the methods of mindfulness, and discuss how mindfulness differs from mind-wandering. Contrary to popular belief, mindfulness is not the opposite of mind-wandering, but rather the cultivation of mindfulness involves becoming better friends with your mind so that you learn to become less stuck in thought processes. We will also review conceptual models of mindfulness and mind-wandering together with some research underpinnings. In addition, we will introduce the first and third-person perspective on studying the mind and basics of microphenomenology. We will also start a small experiment with our own mindfulness practice, which we will analyse in the last session of the course.
In the second session, we will continue our practice of mindfulness, and review research findings on the effects of mindfulness on cognitive function and brain activity.
In the third session, we will continue our practice of mindfulness. We will place mindfulness in the context of different meditation practices, discussing similarities and differences. We will also discuss in general how we can study mindfulness scientifically and how to do so rigorously.
In the fourth session, apart from practicing mindfulness, we will discuss the findings of our little experiments. There will also be ample space for questions and additional topics to discuss.
Objectives
Being familiar with mindfulness practices
Being familiar with research on mindfulness
Being familiar with the scientific study of mind-wandering
Being able to combine first- and third-person perspectives in research on mindfulness
Literature
Tang, Y. Y., Hölzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience, 16(4), 213. https://www-nature-com/articles/nrn3916
Vago, D. R., & David, S. A. (2012). Self-awareness, self-regulation, and self-transcendence (S-ART): a framework for understanding the neurobiological mechanisms of mindfulness. Frontiers in human neuroscience, 6, 296. https://www.frontiersin.org/articles/10.3389/fnhum.2012.00296
Dr. Van Vugt is an assistant professor at the University of Groningen in the Netherlands, working in the department of artificial intelligence. She obtained her PhD in model-based neuroscience from the University of Pennsylvania, then worked as a postdoc at Princeton University before moving to the University of Groningen. In her lab, she focuses on understanding the cognitive and neural mechanisms underlying decision making, mind-wandering and meditation by means of EEG, behavioural studies and computational modeling. In some slightly outside-the-box research, she also records the brain waves of Tibetan monks and dancers.
Civilization’s Sid Meier defined video games as a series of interesting choices. Game-design aims to balance risk and reward for each choice made in a game, with the goal to create compelling experiences that draw people in and keep them spellbound. In this course you will create your own game and explore how modifying formal game elements applying psychological theory affects play experience.
Each session is a combination of a lecture (45min), applied game-design (30 min), and discussion (15 min). Knowledge about digital games is not required!
In session one, we will learn the basics of game-design, prototype a game, and discuss your experiences with the game.
In session two, we will discuss how risk and reward a represented in games and how risk/reward trade-offs require player to take action and make decisions. You will modify your game to actively explore the effects of risk and reward design on play experience.
In session three, we will dive into psychological theories of decision making, biases, and how games leverage our expectations to manipulate play experience. In the game-design session we will change the paradigm of play to explore a different approach to manipulate the outcome of decision moments and the resulting experience.
In session four, we will have a close look into digital games and how they approach risk and reward and apply our knowledge about game-design, risk and reward, and psychological theories. We will break down design decisions to create tension and recreate the different experiences using play cards.
Conjure your most playful analytical self to face new challenges and learn about how risk and reward are fundamental to game design.
Objectives
1. Understand and apply the basics of game-design
2. Gain and leverage psychological knowledge on risk/reward mechanism to modify play experiences
3. Learn about biases and their application in contemporary game-design; apply your knowledge to consciously manipulate experience
4. Synthesize what you learned by deconstructing digital games and reproduce their risk/reward mechanism using play cards
Literature
Fullerton, T. (2018). Game design workshop: a playcentric approach to creating innovative games. AK Peters/CRC Press.
Weber, Elke U., and Eric J. Johnson. “Decisions under uncertainty: Psychological, economic, and neuroeconomic explanations of risk preference.” In Neuroeconomics, pp. 127-144. Academic Press, 2009.
Gutwin, Carl, Christianne Rooke, Andy Cockburn, Regan L. Mandryk, and Benjamin Lafreniere. “Peak-end effects on player experience in casual games.” In Proceedings of the 2016 CHI conference on human factors in computing systems, pp. 5608-5619. ACM, 2016.
Wuertz, Jason, Max V. Birk, and Scott Bateman. “Healthy Lies: The Effects of Misrepresenting Player Health Data on Experience, Behavior, and Performance.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, p. 319. ACM, 2019.
Lecturer
Max Birk is an Assistant Professor in the Department of Industrial Design at Eindhoven University of Technology. With an interdisciplinary background, Max draws from psychology, interaction design, data science, and game design, to investigate the effects of game-based design strategies on mental processes and design-induced behaviour change. His research contributes to games user research, digital health, and motivational interface design. He is interested in projects contributing to a healthy society, improving entertainment experiences, and developing tools and methods for researching interactive experiences.
Max’ research has been published in international top HCI venues, and he has contributed to research on player experience, individual differences in play, task adherence, crowdsourcing, and on the intersection between video games and mental health. He has organized well-received workshops across the globe and led research projects spanning multiple continents. Max has collaborated with game-designers in North America, Europe, and China, and experience working with independent developers like AlienTrap and global tech companies like Tencent.
The brain, the cause of – and solution to – all of life’s problems. According to our brains it is the most fascinating structure in the known universe. Consisting of about 86 billion neurons of which each can form thousands of connections to other neurons it is also the most complex structure in the known universe. In this course we would like to give you a rough guide and introduction to the basic principles, fundamental theories, and methods of neuroscience.
We will demonstrate that neuroscience can be seen as a multi-modal, multi-level, multi-disciplinary research framework that aims at addressing the challenges of this megalomaniac scientific endeavor. We will see that different frameworks and methods can lead to conflicting empirical evidence, theoretical assumptions, and heated debates. However, we argue that this might be the only way to uncover the mysteries of our brain.
In this course we will cover a variety of scopes and perspectives. We will teach some of the fundamentals of neuroscience in human and non-human animals, but we will also explore some explanatory gaps between the different levels of inference.
On a phenomenal level we will investigate the functions of individual neurons and small networks. We will discuss if and how we can learn from (genetically modified) model animals about neural functions. To what degree is this relevant for understanding human brain function, such as learning and decision making? On the other hand, we will also investigate the state of the art in human brain mapping and cognitive neuroscience. Can findings from neuroimaging tell us anything at all about neurobiology – or are they just fancy illustrations that are better suited for children’s books?
Objectives
To understand the anatomy and function of neurons
To understand the interaction of neurons in a functional network
To understand central methods and theories used in neurobiology and human cognitive neuroscience
To understand the scope of different methods and theoretical frameworks
Literature
Cacioppo JT, Berntson GG, Lorig TS, Norris CJ, Rickett E, Nusbaum H. Just because you’re imaging the brain doesn’t mean you can stop using your head: a primer and set of first principles. J Pers Soc Psychol. 2003 Oct;85(4):650-61. [Link]
Park HJ, Friston K. Structural and Functional Brain Networks: From Connections to Cognition. Science, 2013 Nov; 6158(342):1238411 [Link]
Kandel, ER, Schwartz, JH, Jessell, TM, Siegelbaum, S, Hudspeth, AJ, & Mack, S (2013). Principles of Neural Science.
Lecturer
Till Bockemühl studied biology and philosophy at Bielefeld University. He did his diploma thesis as well as his doctoral thesis with Volker Dürr in the lab of Holk Cruse at Bielefeld University. Currently, he is a postdoctoral researcher in the lab of Ansgar Büschges at the University of Cologne. His main research interests comprise the motor control of locomotion, neuroethology, and computational neurobiology. To investigate these topics, he uses the fruit fly Drosophila and the ever-expanding toolkit of methodological opportunities this model organism has to offer.
Ronald Sladky. My research focuses on the amygdala and emotion processing in the human brain. In addition, I am always working on new neuroimaging, data processing, and modeling methods. One of these new methods is real-time functional MRI, where people can learn to regulate their own brain states while they are inside the MRI scanner. This method is not only a promising therapeutic tool, it will also allow for completely new ways of discovering how our brains work.
Brains are built to avoid threats and seize rewards – the basic behavioral challenges from survival in the wild to navigating complex societies. Here, we explore the underlying neuronal circuit motifs, from individual to evolutionary time scales. We will also discuss how network function is genetically programmed and how dysfunction might lead to psychiatric symptoms.
Session 1: Neuronal circuit solutions for learning tasks
Individual brains learn and use stimulus-outcome contingencies to optimize responding to behavioral challenges by predicting future events from past experiences and current indicators. If these models are not correct, they are being updated to improve future predictions. Here, wecombine computational and experimental means to explore circuit motifs for predictive coding and behavioral decisions. We will investigate hierarchical cortico-limbic networks that store and recall short-term and long-term memories from emotional experiences. We will also investigate how basic affective circuitries may control more complex temporally and spatially structured behavioral patterns.
Session 2. Behavioral diversity from neurogenetic traits
Individuals behave differently, because of their life experiences (Session 1) and because of their genetic disposition. The current challenge in the neurosciences is to understand how genetic variation modulates circuit computation and, ultimately, behavioral traits. Data from social interaction experiments will showcase computational and experimental approaches to resolve the principle organization of such functional modules across genetic-, neuronal circuit- and behavioral-levels. Ultimately, this will uncover constraints and freedoms in the functional interrelation between genetic variance and behavioral traits in population and ultimately evolution.
Session 3. Reconstructing becoming human
Neurogenetic variance does not only bias individual differences at the population level (Session 2), but ultimately shapes neurocognitive adaptation at evolutionary scales. Tracing neurocognitive evolution typically relies on comparing behavioral or neuroanatomical features in mammalian phylogeny. Here, we will compare classical research to novel approaches that aim to address this problem computationally. Projecting genome-wide selection pressure onto the human brain reference space recreates evolutionary history of human brain function. Such atlases allow imputing functional features to archaic brains from extinct hominin genomes in silico. Here, we will use this data for computational archaeology of the human mind from early hominids to anatomically modern human. In this context, we will initiate an open discussion on human machine interfaces, the future of cognitive enhancement and emotional robots.
Objectives
Neuroscience is currently undergoing two revolutions. First, advanced local and global brain network imaging technologies and optogenetics allow to monitor and manipulate neuronal computations underlying specific brain functions in depth and with ever greater precision. Second, genetic initiatives (GWAS studies) and brain mapping projects (gene expression maps, connectomes) create a wealth of data and opportunities to be mined for insights into the genetic to systems level organization of brain function.
Participants will assemble these technologies to learn about the functional neuroanatomy and genetic control underlying basic behavioral challenges. To this end, we will design workflows integrating behavioral paradigms for cognitive functions and computational analysis, methods for recording and manipulation of neuronal activity, decoding and concepts of neuronal network activity, psychiatric and evolutionary neurogenetics, fusing and exploring brain gene expression, connectomic and functional network data.
Literature
Textbooks
Buzsáki G. “Rhythms of the brain.” Oxford University Press (2011).
Koch C. “The quest for consciousness.” Roberts and Company Publishers (2004).
Seung S. “Connectome: how the brain’s wiring makes us who we are.” Mariner Books (2013)
Wallisch P, Lusignan M, Benayoun M, Baker T, Dickey A. “MATLAB for Neuroscientists,.” Academic Press (2014).
Articles
Barrett LF, Simmons WK. “Interoceptive predictions in the brain.” Nat. Rev. Neurosci. 16, 419–429 (2015).
Doya K. “Metalearning and neuromodulation.” Neural Networks 15, 495–506 (2002).
Friston K. “Hierarchical models in the brain.” PLoS Comput. Biol. 4, (2008).
Ganglberger F, Kaczanowska J, Penninger JM, Hess A, Bühler K, Haubensak W. “Predicting functional neuroanatomical maps from fusing brain networks with genetic information.” Neuroimage. 2018 Apr 15;170:113-120. doi: 10.1016/j.neuroimage.2017.08.070. Epub 2017 Sep 4.
Ganglberger F, Swoboda N, Frauenstein L, Kaczanowska J, Haubensak W, Buehler K. “BrainTrawler: A visual analytics framework for iterative exploration of heterogeneous big brain data.” Computers & Graphics 82 (2019) 304–320.
Griessner J, Pasieka M, Böhm V, Grössl F, Kaczanowska J, Pliota P, Kargl D, Werner B, Kaouane N, Strobelt S, Kreitz S, Anderson DJ, Hess A, Haubensak W. “Central amygdala circuit dynamics underlying the benzodiazepine anxiolytic effect.” Mol Psychiatry. doi.org/10.1038/s41380-018-0310-32018. Epub 2018 Nov 30.
Grillner S. Megascience efforts and the brain. Neuron 82(6):1209-11 (2014). doi: 10.1016/j.neuron.2014.05.045. Review.
Grössl F, Munsch T*, Meis S*, Griessner J, Pliota P, Kargl D, Badurek S, Kraitsy K, Rassoulpour A, Lessmann V, Haubensak W. “Dorsal tegmental dopamine neurons gate associative learning of fear.” Nat Neurosci. 2018 Jun 27. doi: 10.1038/s41593-018-0174-5.
Josselyn SA, Frankland PW. “Memory Allocation: Mechanisms and Function.” Annu Rev Neurosci 8;41:389-413. D(2018)
Kaczanowska J, Ganglberger F, Galik B, Hess A, Moodley Y, Bühler K, Haubensak W “Molecular archaeology of the human brain.” bioRxiv, 598094.
Koechlin E, Jubault T. “Broca’s Area and the Hierarchical Organization of Human Behavior.” Neuron 50, 963–974 (2006).
O’Connell L, Hofmann HA. “Evolution of a Vertebrate Social Decision-Making Network.” Science (80-. ). 336, 1154–1157 (2012).
Pezzulo G, Rigoli F, Friston, KJ.”Hierarchical Active Inference: A Theory of Motivated Control.” Trends in Cognitive Sciences (2018). doi:10.1016/j.tics.2018.01.009
Pfaff D, Tabansky I, Haubensak W. “Tinbergen’s challenge for the neuroscience of behavior.” Proc Natl Acad Sci U S A. 2019 Apr 29. pii: 201903589. doi: 10.1073/pnas.1903589116. [Epub ahead of print].
Pliota P, Böhm V*, Grössl F*, Griessner J*, Valenti O*, Kaczanowska J, Pasieka M, Lendl T, Deussing JM, Haubensak W. “Stress peptides sensitize fear circuitry to generalize passive coping.” Mol Psychiatry. 2018 Jun 14. doi: 10.1038/s41380-018-0089-2.
Rubenstein DR, Ågren JA, Carbone L, Elde NC, Hoekstra HE, Kapheim KM, Keller L, Moreau CS, Toth AL, Yeaman S, Hofmann HA. “Coevolution of Genome Architecture and Social Behavior.”Trends Ecol Evol. 2019 Sep;34(9):844-855. doi: 10.1016/j.tree.2019.04.011. Epub 2019 May 24. Review.Pignatelli, Michele and Beyeler A. “Valence Coding in Amygdala Circuits.” Current Opinion in Behavioral Sciences 26:97–106 (2019).
Seidenbecher T1, Laxmi TR, Stork O, Pape HC. Amygdalar and hippocampal theta rhythm synchronization during fear memory retrieval. Science 301(5634):846-50 (2003).
van den Heuvel MP, Scholtens LH, Kahn RS. „Multiscale Neuroscience of Psychiatric Disorders.” Biol Psychiatry. 86(7):512-522 (2019). doi: 10.1016/j.biopsych.2019.05.015. Epub (2019) May 28. Review.
Lecturer
Dr. Wulf Haubensak
2019 Speaker “Assembling safe behavior towards objects in space”, Gordon Research Conference on Amygdala Function in Emotion, Cognition and Disease
2017 Symposium chair and speaker “Neuronal architectures for the basic mind”, Austrian Neuroscience Society, Institute for Science and Technology
2016 Steering committee, Vienna Doctoral School “Cognition, Behaviour and Neuroscience (CoBeNe)”
2016 Organizing committee, symposium chair and speaker “Shaping synapses, circuits and behavior with dopamine”, Dopamine 2016
2015 Symposium chair and speaker “Neurobiology of fear and anxiety: genes, circuits and behavior”, 94th Annual Meeting of the German Physiological Society
2015 Meeting organizer “Neural circuit dynamics of behavior and disease” Gumpoldskirchen
2013 Member of the Young Academy of the Austrian Academy of Sciences
2013 ERC Consolidator Grant
2012 Symposium chair and speaker “The mechanics of the emotional brain: dissecting fear and aggression in limbic circuits”, FENS Forum of Neuroscience
2011 Group leader “Circuit mechanics of emotional behavior”, Institute of Molecular Pathology (IMP) Vienna
2003 Postdoctoral research and staff scientist “Genetic dissection of fear circuits”, California Institute of Technology
2005 Otto-Hahn Medal, Max-Planck Society
2004 Postdoctoral fellowship, Human Frontier Science Program Organization
2003 PhD “Neurogenesis in the CNS”, University of Heidelberg
1997 Diploma “BDNF and neuronal plasticity”, University of Bochum
1997 Scholarship, Massenberg Foundation
1992 Studies in Biochemistry, University of Bochum
