Talk 1: Heritability of the sleep EEG in adolescence
(Andjela Markovic, University of Bern)
Studying brain activity during sleep in adolescence reveals unique information about the developing brain. Our work shows that the adolescent sleep EEG is a rich metric capturing genetic as well as environmental factors with broad clinical applications.
Andjela Markovic is a PhD student at the Graduate School for Health Sciences at the University of Bern. Her PhD project at the University Hospital for Child and Adolescent Psychiatry and Psychotherapy in Bern is aiming to answer questions from the field of sleep research regarding the association between sleep, development and psychiatric disorders. Andjela received her BSc in Computer Science from the ETH Zurich in 2013, her MSc in Biomedical Engineering from the ETH Zurich in 2015 and her Piano Teaching Diploma from the Swiss Academy of Music and Music Pedagogy in 2013.
Talk 2: Developmental associations between sleep and gut microbiome on infants
(Sarah Schoch, University of Zurich)
Infancy is characterized by high variability in sleep behavior. The underlying reasons are not yet well understood. We are exploring whether the gut microbiome could explain some of the variability.
Sarah Schoch completed her Bachelor and Master in psychology at the University of Zurich. In her master thesis she investigated the role of dreams in memory consolidation during sleep with Prof. Dr. Björn Rasch. For her PhD she joined the newly established Baby Sleep Laboratory of Dr. Kurth at the clinical research priority program of the University of Zürich. She is interested in how sleep develops in infancy and factors associated with this development.
University of Bern
University of Zurich
Talk 1: ER-Mitochondria Axis in Amyotrophic Lateral Sclerosis
(Federica Pilotto, University of Bern)
Amyotrophic lateral sclerosis (ALS), is the most common motor neuron disease in adults with a prevalence of 6-7 per 100 000 people in Europe. Several cellular processes have been connected to ALS pathogenesis such as altered RNA processing, proteins aggregation, mitochondrial dysfunction and axonal transport defects, nevertheless it has been challenging to delineate causal from consequential pathogenic alterations. We focused our attention at the mitochondrial-associated endoplasmic reticulum (ER) membranes (MAMs) in preclinical models of ALS. A critical question that we have examined is whether homeostatic changes in the ER affects other cellular organelles, thereby directly contributing to the disease stage dependent pathological changes.
Talk 2: Differential cytotoxicity and seeding-properties of patient-derived TDP-43 aggregates
(Pierre Derossi, University of Zurich)
TDP-43 is an RNA binding protein found aggregated in 50% of the FTLD and 97% of ALS patients. Despite extensive research, little is known about the origin of these aggregates and how they contribute to neurodegeneration. The Polymenidou lab recently developed different techniques to isolate and characterize these aggregates. We uncovered subtype-specific biochemical characteristics, suggesting that the different TDP-43 pathologies are associated with different types of TDP-43 aggregates. We are currently investigating the seeding properties of these aggregates. Using confocal and super resolution microscopy, we are testing the hypothesis that different patient pathologies represent distinct TDP-43 strains with differential aggregate structures, toxicity and seeding profiles.
Failing Upward: Failure in (Psychological and Neuro) Science and the Journal of Trial and Error
McGill University, Canada
Sean Devine is a PhD candidate in Psychology at McGill University in Montreal, Canada. They study cognitive effort and decision-making. They are also the Editor of Psychology for the Journal of Trial and Error and an advocate for the reflection and discussion about failure in science.
As scientists, we are trained to think our job is to report groundbreaking discoveries that change our understanding of Nature (capital-N). In practice however, our job is one of trial and error; failing again and again; gaining knowledge of what is not to eventually learn what is. Despite the central role failure plays in the scientific process, there remains a stark gap between what is researched and what is published. In this talk, I detail the consequences of this gap on psychology and neuroscience and introduce the Journal of Trial and Error as a way to close this gap.
Talk 1: The borderland between wakefulness and sleep
(Dr. David Schreier, Inselspital Bern)
The talk will explain how the BERN criteria for the visual scoring of the wake-sleep transition zone evolved and which challenges the criteria face(d). Furthermore, the role of microsleep episodes as a biomarker for the quantification of sleepiness will be debated.
David Schreier is currently working as a neurology trainee at the Department of Neurology, Inselspital. The focus of his PhD, which he completed in 2019, was the vigilance assessment and the judgment of fitness to drive in patients suffering from excessive daytime sleepiness. Together with his colleagues, he developed the Bern continuous and high-resolution wake-sleep (BERN) criteria for the visual scoring of the wake-sleep transition zone.
Talk 2: Microsleeps under standard versus soporific conditions following sleep deprivation
(Sophia Snipes, Children's Hospital Zurich)
This talk will be about the relationship between microsleeps and sleep pressure. Specifically, evaluating the extent to which microsleeps reflect changes in sleep pressure due to time awake relative to external experimental conditions (i.e. a soporific environment). Can microsleeps be used as a reliable measure of sleep pressure during wake, or do they better reflect other processes involved in sleep regulation?
I am a PhD student in the lab of Prof. Reto Huber at the Children's Hospital of Zurich. I obtained my bachelor’s degree in Cognitive Psychology from the University of Trento, Italy, and my master's degree in Cognitive Neuroscience from the University of Maastricht, Netherlands. I am currently enrolled in the Department of Health Science and Technology at ETH, and my specialization is in local sleep during wake.
Model-based methods in Neuroscience
University of Bern
University of Zurich
Talk 1: Model-based inference of synaptic parameters
(Camille Gontier, University of Bern)
Abstract: Synapses are stochastic and dynamic transmission units, which can be described by a set of parameters: their number of neurotransmitter vesicles, the probability they will release neurotransmitters upon the arrival of a presynaptic spike, etc. Precisely inferring these parameters is critical for studying neuronal plasticity and homeostasis, but they cannot be measured directly. In this talk, I will introduce model-based inference and explain how to apply it to the problem of synaptic interrogation.
Bio: Camille Gontier graduated in space engineering from the ISAE-Supaéro (Toulouse, France) and in neuroscience from the ENS Ulm (Paris, France). He has been working for 2 years as an engineer for Airbus Defense and Space, and is now a PhD student at the Department of Physiology of the University of Bern, Switzerland. His work focuses on using statistical methods for studying synaptic stochasticity.
Talk 2: Algorithms and intuitions for model selection
(Victoria Shavina, University of Zurich)
Abstract: My work has been focused on designing and comparing models of behavior (based on stochastic differential equations) for a particular visual decision-making paradigm. Such model design and model selection are often somewhat subjective, as they involve several steps that ultimately rely on intuition. We have recently started to devise a strategy, which may work beyond our paradigm, to reduce the reliance on intuition, thus making model design more objective.
Bio: Victoria Shavina is a PhD student at the Neural Computation and Cognition lab, Institute of Neuroinformatics, University of Zurich & ETH Zurich. She has a Master's degree in military engineering and a Master in mathematics from the University of Trento, Italy.
Machine Learning Applications to Medical Imaging
University of Bern
University of Zurich
Talk 1: Studying Glioblastoma Multiforme on MRI with Radiomics, and Machine Learning Techniques
(Yannick Suter, University of Bern)
Glioblastoma multiforme is the most frequent primary brain tumor in humans. We use longitudinal Magnetic Resonance Imaging together with machine learning to analyze disease progression and survival. In this talk, I will briefly introduce radiomics, its challenges, and the application to brain tumor MRI.
Yannick is a Ph.D. student in the Medical Image Analysis Group supervised by Prof. Dr. Mauricio Reyes at the ARTORG Center for Biomedical Engineering Research, University of Bern. His project focuses on radiomics and machine learning techniques to analyze Glioblastoma multiforme on MRI data.
Talk 2: Learned Priors for Medical Imaging
(Anna Volokitin, University of Zurich)
Knowing what healthy anatomy looks is a prerequisite for interpreting medical images. Advances in generative modelling are allowing us to train networks to have such knowledge. We can incorporate such networks into many medical image analysis systems for better performance. In this talk, I will give an introduction to generative modelling, and demonstrate its use in reconstructing undersampled MRI images as well as the creation of anomaly detection systems.
Anna is a 5th year PhD student in the Computer Vision Lab at ETH Zürich supervised by Prof Ender Konukoglu and Prof Luc van Gool. Her main research interests are in computer vision and generative modelling.