Fair

We investigate visual and premotor circuits in zebrafish. We use behavioral experiments, two-photon microscopy, optogenetics and computational analyses in our work. We have recently developed a novel virtual reality arena for larval zebrafish, which we use to study how the brain processes naturalistic motion stimuli. We are furthermore interested in the control of eye movements and the modulation of visual representations during ongoing behavior (e.g. saccadic suppression). Our research aims at a better understanding of the sophisticated neural computations that take place already in the early visual system, in particular, the retina. The computational capabilities of this intricate neuronal network rely on more than 100 types of neurons organized in complex microcircuits. Our work aims at unravelling function and organization of retinal microcircuits towards a better understanding of the underlying computational principles – specifically in the context of the animal’ s natural environment. Furthermore, we are also interested in how these circuits are altered during degeneration and disease. Our key technique is two-photon microscopy, which enables us to excite fluorescent probes in the intact living retinal tissue using infrared laser light, with minimal effects on the light-sensitive photoreceptor pigment. Therefore, we can simultaneously record activity in neurons at both population and subcellular levels while presenting a range of light stimuli – from simple spots to natural movies. This approach is complemented by single-cell electrophysiology and immunocytochemistry, as well as large-scale data analysis and modelling in close collaboration with the groups of Philipp Berens, Matthias Bethge, and Katrin Franke at Tübingen University. We are part of the Institute of Ophthalmic Research at the University of Tübingen, the Center for Integrative Neuroscience (CIN) and the Bernstein Center for Computational Neuroscience in Tübingen. functional interoception the physiological the which crucial for the emergence and of subjective We have several that include the analysis of unique data, combining fMRI with optogenetics, electrical microstimulations, or local field potential recording in the insular cortex in macaque monkeys. We also have histological preparations that will enable us to map the distribution of the von Economo neuron in the anterior cingulate cortex in monkeys, and in the entorhinal cortex in monkeys and humans. group, we develop novel neuromodulation tools and work closely together with biomedical companies to gain access to innovative neurotechnology. We combine basic studies on healthy subjects with clinical studies on patient populations, and apply the knowledge gained from these studies to refine our treatment protocols. Our research aims to investigate the neural mechanisms through which visual perception interacts with motor control. We employ techniques for monitoring and focally perturbing neural activity to understand the functional contribution of individual brain circuits in coordinating perception and action. Besides clarifying our understanding of the sense of vision, our research also sheds light on how neural activity that is distributed across multiple brain areas is organized to support behavior. Our research relies on neurophysiological experiments in animals, combined with comparative psychophysical studies in human participants to allow us to link the mechanistic observations in animals to the human visual and oculomotor systems. Our studies span the range from oculomotor control (e.g. how the brain moves the eyes), to cognitive processing (e.g. how the brain pays attention to potential objects that we might want to direct our eyes towards), to investigating perceptual stability (e.g. why we do not see a moving world even though our eyes are continuously moving and, therefore, jittering our retinal images). The goal of our group is to understand the neural network mechanisms supporting higher cognitive functions and their disturbances underlying neuropsychiatric disorders. We study the functional architecture of human cognition with a spatiotemporal resolution spanning single units to large-scale network activity. In particular, we seek to understand context-dependent, goal-directed behavior in humans through the study of neural network dynamics with a particular emphasis on prefrontal cortex (PFC) physiology. The key hypothesis is that context dependent endogenous brain activity shapes cognitive processing in different cortical states, i.e. wakefulness or sleep. A core interest is the systematic investigation of the functional network architecture of cortico-cortical and subcortico-cortical interactions supporting cognitive processes such as attention and memory and their impairment in healthy aging, neurodegenerative diseases and unconsciousness. Our research is focused on patients with neuropsychological disorders following stroke such as spatial neglect, apraxia, acalculia, and pusher syndrome. Normalized lesions and a specific symptom (presence or severity) are correlated using standardized research pipelines to identify grey matter structures and white matter disconnections associated with the respective deficit. For predictive modelling, we apply machine learning-based algorithms. We also investigate the deficits on a behavioral level, e.g. using eye- and motion tracking. investigate the role of sleep for visual perception and learning. Our main focus is on how supports the extraction and abstraction of statistical regularities from visual experiences. To address this question, we measure behavioral performance, high-density EEG, and polysomnography in healthy human volunteers. Our studies indicate that sleep specifically optimizes memory representations for effective and efficient prediction of the environment. We study the first topic using state of the art awake-behaving mouse methods, such as monitoring and training mouse behavior, multi-site neuronal activity measurements and optogenetic manipulation. The second is based on rodent (whisker) work but interest has been shifted toward finding out if our novel hypothesis of “temporally local coding” is also realized in the human fingertip. Here we use behavioral experimental paradigms combined with EEG/MEG recordings of cortical (S1) activity. The central goal of our department is to investigate how cognition and behavior emerges from dynamic interactions across widely distributed neuronal ensembles. How do sophisticated cognitive processes such as perception, decision-making, and motor behavior emerge from dynamic interactions across the brain? Which neural mechanisms coordinate these interactions, how are they dynamically regulated in a goal-directed fashion, and how are these interactions disturbed in neuropsychiatric diseases? To address these questions, we apply an interdisciplinary multi-scale approach combining animal electrophysiology, psychophysics and sophisticated analytical techniques.

• Zhang et al. (2022). A robust receptive field code for optic flow detection and decomposition during self-motion. Current Biology, Jun 6;32 (11) We are looking for students with the following qualifications: • Programming skills are helpful (Python/Matlab) for projects involving calcium imaging at the two-photon microscope.
Specific projects, opportunities, qualifications that we offer: • Visual tuning properties of pretectal neurons (using virtual reality arena and calcium imaging) • Behavioral projects, e.g. regarding the ethology of the optomotor response • Modelling of saccadic suppression • Molecular projects (development of novel transgenic lines).
We are looking for students with the following qualifications: Of course, the required qualifications strongly depend on project type (rotation, MSc, PhD). For rotation and MSc projects, we typically look for candidates with some experience in experimental techniques (e.g. microscopy, electrophysiology, etc.) or in computational methods (e.g. data analysis, modelling, etc.). More specific requirements depend on which of the current projects in the lab can meaningfully integrate a student.

Specific projects, opportunities, qualifications that we offer:
• Projects & qualifications -Depending on the interest and background of the rotation/MSc candidate, we offer more experimentally or more theoretically focused projects. These projects are usually tied into a project topic in the lab (e.g. visual ecology, neuromodulation, neurodegeneration, etc.). Independent of the rotation/MSc projects' methodological focus, experimentally oriented students will have the opportunity to learn about the data analysis/modelling side, while theoretically oriented students can get insights into the experimental methods that generate the data.
• Opportunities -We will have an open position for a PhD student in a CRC "Robust Vision" project focused on computationally modelling the mouse retina (starting in ~winter 2022). Our lab examines the anatomical and functional pathways of interoception (sense of the physiological state of the body), which is crucial for the emergence and shaping of subjective feelings. We have several projects that include the analysis of unique data, combining fMRI with optogenetics, electrical microstimulations, or local field potential recording in the insular cortex in macaque monkeys. We also have histological preparations that will enable us to map the distribution of the von Economo neuron in the anterior cingulate cortex in monkeys, and in the entorhinal cortex in monkeys and humans.

AG Evrard
Representative work from our group: We are looking for students with the following qualifications: • Matlab • Some experience in fMRI analysis helps • Some experience in electrophysiology analysis helps Specific projects, opportunities, qualifications that we offer: • Introduction to bodily states (interoception) and their relation to brain states and cognition.
• Analysis of electrophysiological data (LFP/spikes), with or without fMRI.
• Analysis of the effects of optogenetics and electrical microstimulations on fMRI BOLD signal.
• Brain histology and neuroanatomy in monkeys and humans (mapping of VEN and of brain connections). We investigate memory consolidation during sleep and wakefulness in humans, often utilizing diverse neuroimaging methods like fMRI, dwMRI, EEG, or MEG. For data analysis, we often rely on multivariate pattern analyses and machine learning classification.

AG Gais
Representative work from our group: Specific projects, opportunities, qualifications that we offer: • Currently, we can offer behavioral and methodological studies: • One question regards the effect of media consumption before sleep on consolidation of prospective memory. • Another potential study would investigate how incidental presentation of factual material affects semantic and source memory. • Finally, there is a methodological concern regarding spurious autocorrelations in time series data, which might strongly affect resting-state fMRI analyses. We are looking for a methods-minded student who would want to investigate this in simulated and real data. As a translational group, we develop novel neuromodulation tools and work closely together with biomedical companies to gain access to innovative neurotechnology. We combine basic studies on healthy subjects with clinical studies on patient populations, and apply the knowledge gained from these studies to refine our treatment protocols.

AG Gharabaghi
Representative work from our group: Scherer et al. Neuroimage. 2020, Milosevic et al. Mov Disord. 2020, Naros et al. Cereb Cortex. 2020, Vukelić et al. Neuroimage. 2019, Ziegler et al. Brain Stimul. 2019, Guggenberger et al. Brain Stimul. 2018, Naros et al. Mov Disord. 2018, Khademi et al. Cereb Cortex. 2018, Kraus et al. J Neurosci. 2018 We are looking for students with the following qualifications: • Background in the field of Neuroscience, Cognitive Science, Biology, Computer Science, Engineering, Data Science or related areas. Solid understanding of statistical data analysis, digital signal processing and/or programming principles. • Programming skills in Python or MATLAB and/or experience in applying statistical tools, e.g., machine learning for data analysis.

Specific projects, opportunities, qualifications that we offer:
• Projects in the research fields and with the methods mentioned above.
• Access to novel brain stimulation paradigms to expand the understanding of the human brain and develop new therapies. • Opportunity to work with in vivo electrophysiological data from patients and healthy controls.
• Support of your work with a broad range of pre-built analysis tools and assistance in designing your own approaches. • Access to state-of-the-art technologies to generate reliable results.
• A team that is united by one vision: to enhance the understanding of the human brain in order to invent and implement new and more effective therapies. Our research is dedicated to molecular mechanisms of Parkinson's disease with an emphasis on the functional and biochemical characterization of PD drug targets and their dynamic protein interactomes. For this purpose, we combined different techniques in the lab, starting with the proteomic analysis of protein-protein interaction networks by affinity-based methods as well as proximity labelling combined with mass-spectrometric analysis. Learning form functional networks should not only allow us to better understand molecular disease mechanism but also helps to potentially identify novel drug targets and biomarkers. For specific drug development, it is important to understand the biochemical as well as structural properties of a disease protein and potential drug target. For this reason, we extensively studied the enzymatic properties of our major target LRRK2, including its GTPase as well as kinase activities. In addition, we are actively involved in projects dedicated to the drug development for this target. Furthermore, we are using our expertise in mass spectrometry to analyze structure-function relationships by chemical crosslinking, combined with the mapping of the cross-linked residues to provide constraints for structural modelling. Together with further biophysical analyses, this will help to understand dynamic changes in proteins, i.e. to identify determinants of inactive vs active conformations as a prerequisite for a rational drug design.
Representative work from our group: We are looking for students with the following qualifications: • Motivated students to join a team of protein biochemists, cell biologists and mass spectrometrists • Basic skills in working with human cell culture • Basic skills in protein and DNA analytics Specific projects, opportunities, qualifications that we offer: • We have several projects around LRRk2 using BioID proximity labelling combined with mass spectrometry to analyze the dynamic context-specific interactome of LRRK2 • Development of novel a BioID tag to study luminal protein interactions in lysosomes at low pH. • Study of protein complexes by CL-MS (chemical crosslinking combined with mass spectrometry) • We offer training in basic protein biochemistry and protein purification from mammalian cells. • Basic training in sample preparation and analysis of mass spectrometric data Further information can be found on our home page: https://www.dzne.de/forschung/forschungsbereiche/populationsforschung/forschungsgruppen/gloe ckner/forschungsschwerpunkte/ Our research aims to investigate the neural mechanisms through which visual perception interacts with motor control. We employ techniques for monitoring and focally perturbing neural activity to understand the functional contribution of individual brain circuits in coordinating perception and action. Besides clarifying our understanding of the sense of vision, our research also sheds light on how neural activity that is distributed across multiple brain areas is organized to support behavior.

AG Hafed
Our research relies on neurophysiological experiments in animals, combined with comparative psychophysical studies in human participants to allow us to link the mechanistic observations in animals to the human visual and oculomotor systems.
Our studies span the range from oculomotor control (e.g. how the brain moves the eyes), to cognitive processing (e.g. how the brain pays attention to potential objects that we might want to direct our eyes towards), to investigating perceptual stability (e.g. why we do not see a moving world even though our eyes are continuously moving and, therefore, jittering our retinal images).
Representative work from our group: We are looking for students with the following qualifications: • Background in neuroscience, biology, psychology, computational neuroscience, computer science, engineering, or related fields. • Strong academic record. • Proficiency in or willingness to learn Matlab and related programming languages. • Willingness to work with animals. • Strong hard-working ethic. • Highly collegial and collaborative with other group members.

Specific projects, opportunities, qualifications that we offer:
• 1-2 PhD positions are available immediately to work on brainstem neurophysiology, exploring hitherto-uncharacterized visual responses in deep premotor nuclei driving the eye muscles. • Data analysis projects (on already-collected data) are also available. • 1 computational modeling project (on already-collected neuronal responses) is also possible as a rotation or Master's thesis project. • All projects involve relating neuronal results to human perception, via direct psychophysical experiments in human participants. We use high field, high-resolution Magnetic Resonance Imaging (MRI) combined with quantitative methods to investigate tissue microstructure in vivo at 9.4T. For validation purposes, ex vivo samples are measured using the same techniques and verified with histology and synchrotron-radiation imaging in 3D. Research topics cover methodological advancements (dielectric properties, structural underpinnings of MRI contrast), clinical applications (plaque detection in Alzheimer's, mapping of vasculature), as well as themes in the neurosciences (myelination and cognitive performance).

Representative work from our group:
• GTC Lab rotations: o Detection of amyloid-β in ex vivo hippocampus of Alzheimer's Disease using Quantitative Susceptibility Mapping at 14.1T o Tractography of hippocampus in Alzheimer's disease by diffusion weighted imaging at 14.1T o Age-related dynamic alterations in thickness, myelinization and cognition as assessed at 9.4T • GTC Master thesis: o Developing a brain fixative agent compatible with whole brain measurements at ultra high magnetic field strengths o Mapping of venous vasculature in vivo and ex vivo using Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging at high fields We are looking for students with the following qualifications: • A strong interest in using MRI and learn about quantitative image processing (Linux). For a Master Thesis, previous experience in this field and programming skills is an asset Specific projects, opportunities that we offer: • MRI and cellular structures in Klüwer-Barrera stained human brain stem • Vasculature in Alzheimer's • Age-related variation in quantitative MRI at different cortical depths

AG Helfrich -Human Intracranial Cognitive Neurophysiology Essay rotation
Lab rotation

PhD position
Our Research: The goal of our group is to understand the neural network mechanisms supporting higher cognitive functions and their disturbances underlying neuropsychiatric disorders. We study the functional architecture of human cognition with a spatiotemporal resolution spanning single units to large-scale network activity. In particular, we seek to understand contextdependent, goal-directed behavior in humans through the study of neural network dynamics with a particular emphasis on prefrontal cortex (PFC) physiology. The key hypothesis is that context dependent endogenous brain activity shapes cognitive processing in different cortical states, i.e. wakefulness or sleep. A core interest is the systematic investigation of the functional network architecture of cortico-cortical and subcortico-cortical interactions supporting cognitive processes such as attention and memory and their impairment in healthy aging, neurodegenerative diseases and unconsciousness.

Representative work from our group:
• Weber, colleagues & Helfrich (2022)  We are looking for students with the following qualifications: • Interest in conducting cognitive neuroscience studies in a clinical environment • Learn about human cognition with a focus on prefrontal cortex dependent networks • Keen interest in coding (Matlab/Python) -learn state-of-the-art time series analysis • Interdisciplinary environment to study large-scale circuits using intracranial EEG, MEG, HD-EEG or eye-tracking Specific projects, opportunities, qualifications that we offer: • Theme 1: Neural basis of human attention using intracranial recordings • Theme 2: Neurophysiological mechanisms of predictive timing in humans • Theme 3: Self-organized network dynamics in the MTL-PFC during sleep • Theme 4: Unconsciousness: Shared mechanisms of sleep, anesthesia and coma The neuroimaging group currently consists of 4 PhD students, 1 Postdoc and several undergraduate students and myself. Our main research interest compromises the following topics: Study of synaptic (dys)functions in healthy rodents and animal models of neurological disorders using simultaneous PET/BOLD-fMRI. Structural disruptions and loss of synapses are a major hallmark of neurodegenerative disorders and result in network disruptions and loss of neuronal signaling. How early in the process of neurodegeneration synaptic dysfunctions appear is not yet understood. Our aim is to develop and apply protocols and methods (including pharmacological and optogenetic stimulations) to assess molecular changes of receptor expression by PET and functional changes by BOLD-fMRI at different time points of the disease to develop early read-outs of disease progression ( Figure 2). For this purpose, we use different rat models and genome engineering technologies (CRISPR/Cas9) to target specific genes and proteins in vitro (cell culture and primary neurons (Figure 3)) and in vivo in the mouse and rat brain. For data analysis of PET and MRI data we use several data analysis methods, including kinetic modeling and machine learning approaches. In addition, we are studying brain function with sound and music using human and small animal fMRI studies.

Tracer development and preclinical evaluation in neurology.
In the past, we have established several in vitro and in vivo screening assays to validate novel PET imaging agents. As our group holds a strong collaboration to the Radiopharmacy research group, we are always looking for novel interesting targets in the brain. Important targets are the proteins alpha-synuclein and tau, which play a major role in the pathology of Parkinson´s disease (PD) and Alzheimer´s disease (AD). In contrast to the situation in AD, PET tracers to detect alpha-synuclein oligomers or aggregates in synucleinopathies such as PD are still missing. Therefore, we aim for example to develop a PET tracer to non-invasively assess alpha-synuclein aggregation in the brain of patients with synucleinopathies.

Infrastructure
The Werner Siemens Imaging Center is located next to the woman's hospital and equipped with: -3 high-resolution small animal PET systems -1 small animal SPECT/CT system -2 whole body optical imaging systems -2 7-T small animal MRI systems equipped with specific brain coils for rats and mice (fMRI, MR spectroscopy, contrast enhanced MRI, diffusion weighted imaging and diffusion tensor imaging) -PET insert to measure PET and MR simultaneously anesthesia systems, cardiac and respiratory gating units, a ventilation machine cell culture labs including laminar flow and incubator, -1 gamma counter and 1 phosphor imager, -histology and microscopy labs including cryostat molecular biology labs -On-site cyclotron with PET tracers, both for preclinical and clinical use ( Figure 1). These include PET tracers for the dopaminergic, serotonergic, GABAergic and glutamatergic systems ( Figure 1)  Our research is focused on patients with neuropsychological disorders following stroke such as spatial neglect, apraxia, acalculia, and pusher syndrome. Normalized lesions and a specific symptom (presence or severity) are correlated using standardized research pipelines to identify grey matter structures and white matter disconnections associated with the respective deficit. For predictive modelling, we apply machine learning-based algorithms. We also investigate the deficits on a behavioral level, e.g. using eye-and motion tracking.

Representative work from our group:
• Röhrig L, Sperber C, Bonilha L, Rorden C, Karnath H-O (2022 We are looking for students with the following qualifications: • Background in neuroscience, cognitive sciences, psychology, biology or equivalent • Qualifications vary greatly depending on the specific project but can include o Basic Knowledge in magnetic resonance imaging o Basic/advanced programming skills (Matlab, R, and/or Python) • When handling patients German language skills are required • Interest in, e.g., investigations addressing the association of brain damage and cognitive deficits, corresponding neural correlates, biomarkers, and rehabilitation approaches Specific projects, opportunities, qualifications that we offer: • We are currently looking for an intern/a lab rotation to conduct apraxia diagnostics on a healthy sample in order to create a healthy movement model of pantomimed tool use • Please get in touch with us, if you are interested in our research! Possibly we have also other projects that might fit your interests. The quest of unraveling a person's motive has captivated our imagination since the dawn of humankind. To parse motivated behavior, our lab is using functional neuroimaging techniques in combination with detailed behavioral, physiological, and psychological assessments. Based on these rich assessments, we build statistical and computational models decoding motivation and latent desires. By capitalizing on big data from many different modalities, we envision predicting future actions in everyday life. Such detailed knowledge is indispensable in improving treatments for many mental disorders, which are characterized by seemingly inappropriate actions or desires: Why is he no longer enjoying his favorite dish? Why can she not stop eating the cake although she is no longer hungry? Our mission is to decompose the neurobiological mechanisms of action and desire using cutting-edge tools of data science to evaluate their translational potential in improving aberrant motivation in patients.
Representative work from our group: We are looking for students with the following qualifications: • Passion to work in a diverse team of scientists with complementary skills • Experience in coding or eagerness to learn how to code • A commitment to conduct deep and robust research (transparency & openness) • A good understanding of statistics and willingness to learn more • Interest in neurobiology, experimental psychology, or data analysis in the field of translational psychiatry Specific projects, opportunities, qualifications that we offer: • A collaborative spirit that will help you attain your professional goals as part of a dedicated team • Training in valuable skills such as statistical and computational modeling, neuromodulation, or science communication • The opportunity to take the lead on ambitious projects even if you are an early career scientist • Well-established procedures and innovative tools as well as ample funds to conduct challenging experiments that can move the needle in the field • Access to the vibrant neuroscience communities at the Universities of Excellence in Bonn and Tübingen and to our extensive net of collaborators We currently focus on the neural circuits involved in obesity and diabetes. Projects involve mainly functional magnetic resonance imaging (fMRI), and/or transcranial direct current stimulation (tDCS). Besides neuroimaging techniques, the project may involve the use of behavioral and metabolic assessments to investigate eating behavior, cognitive function, and reward related processes in different persons at risk to developing metabolic diseases, along with the potential to investigate individual responses to lifestyle or pharmacological interventions.

Representative work from our group:
• We are looking for students with the following qualifications: • Interested in studying brain-body-interactions in humans.
• Interest in fMRI research.
• Basic knowledge in statistical programs (as R or SPSS) and MATLAB programming.

Specific projects, opportunities, qualifications that we offer:
• Perform/learn fMRI measurements, and tDCS as a measurement and intervention technique.
• Analyze resting-state fMRI data using state-of the art tools.
• Analyze large data sets (including MRI: functional, and structural data), extensive metabolic, and behavioral characterizations. Our research is focused on diseases with a disturbed neuronal excitability, such as epilepsy and migraine, which are caused by variants in genes encoding ion channels, receptors or transporters. Disease mechanisms are examined in detail using molecular biological and electrophysiological techniques by studying the defects of disease-causing variants and their consequences on protein characteristics, channel gating, intrinsic neuronal properties and behaviour of neuronal networks. The ultimate goal is to predict response to specific existing and newly developed therapies for each of the examined diseases based on the explored mechanisms in the sense of personalized medicine. We are interested in how the systems (mainly neuronal) self-organize to the particular, suitable for computations states. We also aim to identify those states and uncover how they can be affected by changes in behavioral states or disease. To this end, we study network dynamics, self-organization by synaptic plasticities, computations close to the second-order phase transition, the balance of excitation and inhibition, and neuronal timescales. We use computational modeling, data analysis, machine learning methods, and optimization. We are looking for students with the following qualifications:

Representative work from our group
• Happy to learn • Has fun working with others • Can program or analyze data or solve analytical models • Can understand formal computations (and maybe perform them)

Research projects that we offer:
• Changes in timescales of LGM mediated by cortical feedback • Dissociating periodic and aperiodic neural dynamics during attention

• Plasticity of shunting and subtractive inhibition • Open for additional discussions
Literature review projects that we offer: • Dimensionality of population neural activity in the cortex, different techniques to uncover it, and its relation to neural computations • Plasticity of shunting and subtractive inhibition Our research focus is visual systems in the context of sensory and sensorimotor systems of the brain (www.lizhaoping.org). For that, we use theoretical and experimental techniques including computational modelling, fMRI imaging, EEG recording, eye tracking and human psychophysics. We aim to understand the brain by linking neural circuits with behavior through theories and models of computation for biological intelligence.
Representative work from our group: We are looking for students with the following qualifications: • good programming skills in MATLAB, Python or JavaScript • interested & good background knowledge in vision science • motivated, responsible and good teamwork skills Specific projects, opportunities, qualifications that we offer: • We offer you to learn how to manage and organize a complete project including planning, programming and writing up, not just parts of it. We provide several projects (come to the Project Fair and talk with us!), which we can adapt according to your interest and needs. Each project is extendable to a follow-up thesis project.

I am looking for students with the following qualifications:
The main things are curiosity and enthusiasm for the project, and a willingness to learn new things if necessary. These others would probably be useful:  working knowledge of some programming language  some familiarity with maths and statistics

Specific projects, opportunities, qualifications that we offer:
A non-exhaustive list of suggestions (and students are free to propose their own project); I can give more detail/pointers to relevant literature to interested students: The mammalian brain is a highly complex and spatially heterogeneous structure, which has changed significantly in mammalian evolution. Recent progress in stem cell biology has allowed us to model human brain development in a dish using different organoid protocols thus giving us unprecedented access to study human-specific features of brain development.
In the research group Molecular Brain Development, we are interested in revealing how genetic and environmental factors can shape developmental processes in two brain regions, the neocortex and the cerebellum, using human organoids.
Our vision: We aim to understand how plasticity mechanisms contribute to human brain development in health and disease.
Representative work from our group: We are looking for students with the following qualifications: • Cell culture We study mechanisms of axonal injury in mouse and in vitro models of injury. In addition to more standard microscopy techniques (conventional widefield imaging, confocal microscopy), we use modern super-resolution microscopy techniques, such as stochastic optical reconstruction microscopy (STORM), to obtain molecular-scale information. We are also using and developing new cutting-edge protein engineering tools based on selective incorporation of unnatural amino acids and click chemistry ( We are looking for students with the following qualifications: • Ideally, you have experience in at least one of these areas (for details see the section with specific opportunities below): • Cell culture techniques • Molecular biology techniques • Fluorescence microscopy techniques • Image analysis (ImageJ or similar) • Website development Specific projects, opportunities, qualifications that we offer: • These are best discussed on an individual basis since they depend on your qualifications, interests, timeline, and our ongoing projects. Some of the current opportunities involve: • We are looking for a HiWi to help us with our ongoing projects (e.g. cloning, preparation and isolation of DNA plasmids, cell culture, as well as some administrative & basic lab organizational tasks) • We are also about to start a collaboration with an industrial partner with whom we want to use click-based labeling to look at the localization of different drug targets with fluorescent microscopy  this we envision as a potential Master thesis project or long-term HiWi position • We are also currently thinking of (finally ) making our own external website so if you are into this and have some experience, this could be a potential task for a HiWi student • In general, our aim is to find the best match between your and our interests while providing you with the best possible training (with a focus on team work, good scientific practice, experimental design, problem solving, troubleshooting, etc.) • If any of these is interesting to you, reach out to Ivana (ivana.nikic@cin.unituebingen.de) We look forward to meeting you! The Rationality Enhancement Group investigates the computational principles of human intelligence and develops intelligent systems that help people realize their full potential. Our diverse, interdisciplinary team combines methods from computational cognitive science, artificial intelligence, psychology, and human-computer interaction to strengthen the scientific and technological foundations for understanding, supporting, and improving the human mind. Our international, interdisciplinary team combines methods from computational cognitive science, psychology, human-computer interaction, and artificial intelligence. The overarching long-term aim of this research program is to help lay the scientific foundations for increasing people's capacity and motivation to make the world a better place in a way that is sustainable and conducive to their wellbeing.

Specific projects, opportunities, qualifications that we offer:
• Extending our method for measuring individual differences in planning depth to the learning period o Description: We have developed a method to measure individuals' average planning depths using an online task (Felso & Lieder, 2022). This method could be useful for investigating planning biases such as under-or over-planning or making plans only with short-term outcomes in mind. However, our method depends on a model which assumes that people's' policies are not changing, which is not true when people are new to the task and still learning the possible outcomes of plans at varying time scales. Therefore, in this project, you will assist in adding the inverse reinforcement learning algorithm for learning agents introduced by  (Felso & Lieder, 2022). This method may be useful as a metric for people's general propensity to plan into the future, particularly as a baseline measure when developing planning interventions. However, little is known as far as how stable behavior is in the task. Will a person who underplans this week also underplan next week? Or will they behave optimally with no other intervention? In this project, you will work on answering this question by running longitudinal online experiments and analyzing the data using our method to infer individual differences in planning depth.
o Useful background / interests: familiarity with python programming, some familiarity with running online experiments, background in psychometrics, interest in reinforcement learning and computational modeling o Supervisor: Valkyrie Felso (remote) • Which research topics are most important for the future of humanity?
o Motivation: Answering crucial questions about how people decide might substantially improve our ability to positively influence decisions critical for existential risk and the wellbeing of future generations. However, identifying crucial research questions is very difficult for behavioral scientists. Moreover, there is no cost-effectiveness analysis method that funding agencies could use to identify crucial behavioral science research topics and compare them to existing funding priorities.
To overcome this limitation, we will develop and validate Bayesian, data-driven, model-based cost-effectiveness analysis methods for predicting how much behavioral science research on a given question might improve the wellbeing of humanity in the long run. We will use published data to derive research's impact from the impactfulness of the studied phenomenon and prior research's effectiveness at increasing our ability to influence similar phenomena. Our findings will make it possible to compare the cost-effectiveness of behavioral science research to the cost-effectiveness of some established priorities of philanthropy (e.g., poverty and global health). We will generate and regularly update a list of highimpact behavioral science research topics with cost-effectiveness estimates. o Concrete Activities: ▪ Building probabilistic models of the positive impact that research on a given topic might have with Guesstimate (www.getguesstimate.com) ▪ Literature search: extracting effect size estimates from scientific articles ▪ Documentation and critical assessment of the model's assumptions and sensitivity analysis o Useful background: probabilistic modeling, statistics, literature review, psychology o Relevant interests: effective altruism, meta-science, psychology o Supervisor: Falk Lieder • Implementing online experiments with a cognitive tutor that teaches people optimal strategies for group decision-making o Description: We have developed machine learning algorithms that can automatically discover good planning strategies. These strategies are better than strategies people discover by themselves -and the strategies can be taught to people using intelligent tutors. We have already applied this approach in multiple online experiments, where our cognitive tutor was successful in improving human decision-making in multiple toy environments. A major next step for us in this line of research is to apply our method to more realistic environments, where we ultimately hope to have a positive impact on people's lives by teaching them good planning strategies they can apply in the real world. In this project, you will help us design and implement the online experiments necessary for these next steps. Concretely, we are working on the problem of group decision-making and are envisioning a cognitive tutor that teaches people optimal advice taking: how much advice should people ask for when making important decisions and advice is costly; whom should they ask for advice? o Useful background: good knowledge of JavaScript, familiarity with implementing online experiments, general programming knowledge (version control) o Relevant interests: web development, intelligent tutors, (group) decision-making, reinforcement learning o Supervisor: Lovis Heindrich • Helping people achieve their goals by automatically breaking them down into helpful subgoals using computational models of goal pursuit o Description: Successfully attaining your goals requires you to plan several steps ahead and take into account all the factors that might potentially affect your progress. Since the human brain has limited planning and attentional resources, people often struggle to reach their goals. We want to help people in achieving their goals by automatically discovering helpful subgoals. As a first step, we have developed computational models of how people pursue goals in a behavioral task, that take people's attentional constraints and limited planning horizon into account (Prystawski et al., 2021). Subsequently, we have developed a method that can automatically find subgoals that improve the performance of the model. Now, we want to run online experiments to test if the subgoals discovered by the model can also help humans reach their goals. In this project, you will design and conduct online experiments to test the efficacy of the subgoals generated using our algorithm. You may also work towards understanding how our existing models differ from human behavior and subsequently improve the models. 1) predictive signals for motor control and cognition, and 2) tactile coding and perception. We study the first topic using state of the art awake-behaving mouse methods, such as monitoring and training mouse behavior, multi-site neuronal activity measurements and optogenetic manipulation. The second is based on rodent (whisker) work but interest has been shifted toward finding out if our novel hypothesis of "temporally local coding" is also realized in the human fingertip. Here we use behavioral experimental paradigms combined with EEG/MEG recordings of cortical (S1) activity.

Representative work from our group:
Project 1: • Chakrabarti S., Schwarz C. (2018) Cortical modulation of sensory flow during active touch in the rat whisker system. Nat. Commun. 9:3907. DOI: 10.1038/s41467-018-06200-6 Project 2: • Bhattacharjee A., Braun C., and Schwarz C. (2021). Humans use a temporally local code for vibrotactile perception. We are looking for students with the following qualifications: Project 1: • Interest in mouse work, behavior, single neuron/microcircuit electrophysiology, optogenetics Project 2: • Interest in human work, behavior, EEG/MEG Specific projects, opportunities, qualifications that we offer: • See above project 1 and 2 The central goal of our department is to investigate how cognition and behavior emerges from dynamic interactions across widely distributed neuronal ensembles. How do sophisticated cognitive processes such as perception, decision-making, and motor behavior emerge from dynamic interactions across the brain? Which neural mechanisms coordinate these interactions, how are they dynamically regulated in a goal-directed fashion, and how are these interactions disturbed in neuropsychiatric diseases? To address these questions, we apply an interdisciplinary multi-scale approach combining human MEG and EEG, animal electrophysiology, psychophysics and sophisticated analytical techniques. We are looking for students with the following qualifications:

AG Siegel & AG Braun
• Interest in systems neuroscience • MATLAB and/or Python programming skills • Interest in data analysis and numerical methods Specific projects, opportunities, qualifications that we offer: • MEG and EEG projects on human decision-making, visual and auditory perception and memory. • Basic and clinical research (cochlear implant, movement disorders) • Advanced multivariate data-analysis of invasive (non-human primates) and noninvasive (MEG) electrophysiological data