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Recently, the use of resting-state functional MRI (rsfMRI) has been extended beyond the assessment of the brain’s functional organization to the monitoring of various aspects of cerebral hemodynamics. This has found practical applications in various disease states, particularly in cerebrovascular disorders, and has substantial methodological implications for the use of rsfMRI in clinical research. In this talk, I will: ● Discuss recent findings regarding the physiological sources and mechanisms of the components of the blood oxygenation level dependent (BOLD) signal that reflect the brain’s hemodynamic status ● Present recent methodological and practical developments to established rsfMRI-based methods for the assessment of blood flow within the brain ● Present some upcoming techniques for extracting hemodynamic parameters from rsfMRI data and their potential use in various diseases. [mehr]

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Computational visual neuroscience has come a long way in the past 10 years. For the first time, we have fully explicit, image-computable models that can recognise objects with near-human accuracy, and predict brain activity in high-level visual regions. I will present evidence that diverse deep neural network architectures all predict brain representations well, and that task-training and subsequent reweighting of model features is critical to this high performance. However, vision is not yet explained. The most successful models are deep neural networks that have been supervised using ground-truth labels for millions of images. Brains have no such access to the ground truth, and must instead learn directly from sensory data. Unsupervised deep learning, in which networks learn statistical regularities in their data by compressing, extrapolating or predicting images and videos, is an ecologically feasible alternative. I will show that an unsupervised deep network trained on an environment of 3D rendered surfaces with varying shape, material and illumination, spontaneously comes to encode those factors in its internal representations. Most strikingly, the network makes patterns of errors in its perception of material which follow, on an image-by-image basis, the patterns of errors made by human observers. Unsupervised deep learning may provide a coherent framework for how our perceptual dimensions arise. [mehr]

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Enhanced phase-amplitude coupling (PAC) between beta (13-30Hz) and broadband gamma (50-150Hz) oscillations has been suggested to be a biomarker of Parkinson’s disease (PD). It can be measured with non-invasive scalp EEG. However, the spatial origin and the neural mechanisms of PAC are still obscure, limiting its possible use for understanding and treating PD. In this talk, I will present our work using EEG source localization techniques to more precisely locate PAC in the brains of PD patients and healthy controls from scalp EEG. Besides, I will discuss the spatio-temporal characteristics of regional PAC and the related potential mechanisms underlying abnormal PAC. We demonstrated that beta and gamma activities involved in the abnormal PAC are not exclusively generated by a single oscillator. And the abnormal PAC generated from the interaction of beta and gamma frequency components across independent networks was more related to the Parkinsonian motor impairment than PAC originating from the interaction of components of the same network. Together, this talk will outline new insights into the pathological mechanisms of PAC in PD on both macroscopic and mesoscopic scale by non-invasive EEG. [mehr]

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Language comprehension seems effortless. But we encounter difficulties when speakers serve too much information per unit time. We may also get bored if speakers serve too little information per unit time. We try to be attentive and flexible, but our comprehension abilities are limited. Team Language Cycles searches for electrophysiological properties of the human brain that explain these limitations. How long are the time windows that our brain uses for linguistic information processing—and how much linguistic information can we process within a given time window? Based on our initial work, we hypothesize that cycles of endogenous electrophysiological activity—with periods in the range of seconds—underlie linguistic information sampling. The period range of these cycles may be a temporal limit on our ability to sample linguistic information. And if the duration of electrophysiological processing time windows constrains information sampling—shouldn’t all human languages have evolved to serve information units that fit these windows, maximizing information throughput? Our research combines classical psycholinguistic experiments, crowdsourcing (i.e., experiments on dozens of languages via the Language Cycles smartphone application), cognitive neuroscience (i.e., M/EEG), and computational linguistics (e.g., cross-linguistic corpora, information theory). We hope to characterize the electrophysiological timing limits of linguistic information sampling. And we hope to explain a bit of human language from the electrophysiological processing cycles of the human brain. [mehr]

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Introduction and hands-on (online) tutorial on DataLad [mehr]

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Iron plays a central role in brain development and brain aging. Transmission of neuronal signals, optimization and maintenance of brain structure demand substantial energy and require iron as co-factor for energy supply, myelination and neurotransmitter synthesis. However, iron turns toxic and harmful when present in certain chemical forms and at high concentrations. Increased iron accumulation in age leads to faster brain decline, diminished cognitive abilities and increased risk of neurodegenerative diseases. Understanding these mechanisms and following iron trajectories both on the cellular and the whole brain level is key to an in-depth understanding of brain development, plasticity and aging. Magnetic Resonance Imaging (MRI) is the method of choice for in vivo studies of the iron distribution in the human brain. Relaxation rates and susceptibility measurements provide a wealth of information on both the quantity and distribution of iron. It can potentially access iron dispersion down to the cellular level and provide unique information on the iron chemistry. I propose an innovative approach that combines multimodal quantitative MRI at 3T and 7T with biophysical modeling informed by quantitative iron histology. Thereby, brain tissue composition and cellular iron distribution can be linked to quantitative MRI measures. Two applications are selected to demonstrate how knowledge on MR contrast mechanisms can be employed to create sensitive and specific biomarkers of cellular iron distribution. The first example is a study in superficial white matter, where iron is accumulated in oligodendrocytes and potentially in the short association fibres. It is shown that iron in superficial white matter is not homogeneously distributed across the brain, but accumulated in iron deposits in U-fibre-rich frontal, temporal and parietal association areas. This observation is assigned to higher fibre density or late myelination. In the second study, dopaminergic neurons in substantia nigra are mapped. This information is a first step towards a specific in vivo biomarker for the density of dopaminergic neurons and may therefore provide a future diagnostic for Parkinson’s disease. [mehr]

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Neuropsychological and fMRI evidence suggests that the ability to vividly remember our personal past, and imagine future scenarios, involves two closely connected regions: the hippocampus and ventromedial prefrontal cortex (vmPFC). Despite evidence of a direct anatomical connection from hippocampus to vmPFC, it is unknown whether hippocampal-vmPFC structural connectivity supports both past and future-oriented episodic thinking. I will report a novel association between white matter microstructure of the pre-commissural fornix and episodic past and future thinking. Thus, elucidating a potential anatomical mechanism by which direct hippocampal-to-vmPFC connectivity supports constructive episodic processing. These findings provide support for the idea of a ‘core’ network supporting both the re-construction of autobiographical events and the construction of hypothetical personal future events (Benoit & Schacter, 2015). This indicates that individual differences in structural connectivity are important for how richly people can “mentally roam at will over what has happened, as readily as over what might happen” (Tulving, 2002). Additionally, perhaps a common neurocognitive network supports the construction of event representations for autobiographical memory and online scene construction. I will report other work on the construction of internal scene representations and hippocampal subfield volumes. I hope to convince you of the value of zooming in with ultra-high-resolution imaging for precise anatomical characterisation, as well as zooming out to look at structural neuroanatomical networks and the importance of broader network understanding. [mehr]

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Humans have the ability to generate and experience thoughts and feelings that can be independent of instantaneous input from the environment. These integrative mental processes support adaptation to changing environmental demands, well-being, and, ultimately, survival. Such processes are enabled by the unique structural and functional network organization of the human brain. The goal of the Otto Hahn group is to investigate how (phylo-)genetic and environmental factors shape brain organization. In the current colloquium, I will present the framework of our research approach and show preliminary results of the current group members studying brain asymmetry, brain-body relationships, and the heritability of the hippocampal connectome. [mehr]

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When studying perception, the focus is typically on neural signals in the brain. However, bodily signals can also influence perception. The underlying mechanisms of such effects are poorly understood. In my talk, I will demonstrate how the heart influences perception. Specifically, we have recently identified two heart-related factors, heartbeat-evoked potentials (HEP) and cardiac-phase, both of which influence perception. In an EEG study, we investigated psychophysical and neural mechanisms underlying the influence of cardiac-phase and HEP on somatosensory detection. In a follow-up EEG study, we tested the replicability of these heartbeat-related effects in a modified experimental paradigm and further explored the neural sources of the HEP modulations associated with perception. Lastly, using simultaneous EEG-TMS, we investigated whether the effect of heartbeat-related factors might be due to general changes in excitability. Together, this talk will highlight how cardiac signals are integrated into our conscious perception of the world. [mehr]

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*** Zoom Link *** https://gwdg.zoom.us/j/82649211062 *** Interoception refers to the set of physiological and cognitive processes that are involved in determining the physiological condition of the body. Recently, the number of studies showing the extent to which interoceptive signals such as heartbeat modulate cognition and perception in the healthy and atypical human brain has markedly increased. This has been shown by measuring participants’ responses to sensory events that are locked to distinct phases of the cardiac cycle. These studies have shown that perception and cognition are modulated by the phase of the cardiac cycle in which the stimuli were presented. However, it is unclear how these results relate to our everyday interaction with the world where sensory inputs are not presented according to our cardiac cycle, but rather actively sampled at one’s own pace. Moreover, if the phase of the cardiac cycle is an important modulator of perception and cognition, as previously proposed, then the way in which we actively sample the world should be similarly modulated by the phase of the cardiac cycle. One possibility is that we sample the world in a way that is linked to our cardiac signal and in this way optimize the sampling of our sensory inputs. Here, I will talk about a series of studies designed to test this hypothesis and I will discuss these results in relation to current theoretical models of interoception. [mehr]

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What drives us to trust someone we just met? Did we eat spaghetti for lunch because we saw our colleague eat spaghetti? Do we become happier when we are nicer to our neighbors? How is our breakfast linked to our social interactions throughout the day? Research from different disciplines such as economics, psychology and neuroscience have attempted to investigate the motives and modulators of human decision making. Our decisions can be flexibly modulated by the different experiences we have in our daily lives. These modulations can occur through our social networks, through the impact of our own behavior on the social environment, but also simply by the food we have eaten. Here, I will present a series of recent studies from my lab in which we shed light on the psychological, neural and metabolic motives and modulators of human decision making. [mehr]

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In this presentation Dr Mumford will be discussing power in neuroimaging studies. More and more research is highlighting the fact that fMRI studies, especially those with hypotheses about individual differences, require large sample sizes to adequately power. What is the way forward? This talk will discuss how to run a proper power analysis and optimize efficiency for fMRI studies. Additionally, she will discuss how we need to adjust our expectations for future fMRI research. [mehr]

Synchronization of neural activity is a process that has been linked to various neurological diseases as well as to healthy neural information processing. Different cell populations at different brain regions seem to express specific neural synchronization patterns that support their normal function and that may undergo changes in neurological disorders. To understand the computations carried out by the brain, it is a core task to develop mathematical tools and descriptions that can link alterations in neural synchronization patterns to changes in neural structure. In this talk, I will present different lines of work that I carried out to contribute to this task. As a mathematical basis, I will introduce an exact mean-field model of a spiking neural network (SNN) that allows for direct descriptions of changes in macroscopic neural synchronization caused by alterations in the underlying model parameters. I will then analyze how different variations and extensions of the SNN model affect the mean-field description. To this end, I will use bifurcation theory to identify phase transitions between asynchronous and synchronized regimes in the mean-field model and test whether the mean-field equations provide an accurate description of neural synchronization processes in the SNN. Finally, I will present an application of these methods to the modeling of phase transitions in the external pallidum, a part of the basal ganglia that undergoes structural and functional changes in Parkinson’s disease. Again, I identify phase transitions between asynchronous and synchronized states in these circuits and discuss how these transitions could relate to parkinsonian oscillation generation. [mehr]

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A major goal in cognitive neuroscience is to reveal the nature of our mental and neural representations: how do we make sense of our sensory input, access our learned knowledge, and generate meaningful behavior? The visual modality offers a highly valuable avenue for addressing this goal, with the hope that the insights gained can be generalized to other sensory modalities and cognitive domains. In this talk, I will discuss recent work from the Vision and Computational Cognition group tackling the nature of mental and neural representations of real-world objects, bringing together large-scale crowdsourcing, densely-sampled multimodal neuroimaging data, and recent advances in artificial intelligence. By uncovering interpretable factors and dimensions underlying the processing of objects and by providing new analytical tools for large-scale datasets, our group aims at moving us much closer to understanding how visually-perceived objects are represented and yield flexible and adaptive behavior. [mehr]

Keywords: language processing; incremental comprehension // linguistic predictions, RSA; language disorders [mehr]

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Jixing Li is postdoctoral researcher in the Neuroscience of Language Lab (NeLLab) at NYU Abu Dhabi. Her research applies computational models to understand how the human brain represents and computes semantic and syntactic information during language comprehension. John Hale is Professor at the Linguistics Department, University of Georgia. His work centres on language comprehension using analysis tools from computational linguistics and corpus methods. [mehr]

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Susceptibility-weighted imaging is gaining momentum in brain MRI due to the linkage of multiple brain pathologies to local alterations of iron and myelin. Multiple methods have been proposed for susceptibility quantification, most prominently quantitative susceptibility mapping (QSM). Typically, QSM models do not consider the anisotropic character of susceptibility in white-matter (WM) regions, which results from the specific arrangement of myelin lipids surrounding the WM fiber bundles. This may lead to potential inaccuracies on the derived QSM maps. In susceptibility tensor imaging (STI), susceptibility is depicted as a second rank symmetric tensor, in a similar way as orientation-dependent diffusivity in diffusion tensor imaging (DTI). However, STI suffers from acquisition and processing issues, primarily due to the need for physical re-orientation of the sample inside the main magnetic field. Hence, while orientation-dependent QSM datasets achieving a high spatial resolution they are typically rather limited in terms of angular resolution. In our study, we try to tackle the acquisition issues, obtaining high angular susceptibility datasets in fixed brain tissue, along with corresponding high angular-resolution diffusion-weighted imaging. These datasets are further processed to compare the susceptibility and diffusion tensors and their eigen-analysis results, to assess the susceptibility maps derived by STI in comparison to those derived by QSM in different orientations, and finally, as an approach to use DTI information to inform QSM on orientation-dependence in local susceptibility estimation. Furthermore, the high angular data open the way for studies of the susceptibility orientation distributions beyond tensorial analysis limitations. [mehr]

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Songhee Kim is postdoctoral researcher at the Medical College of Wisconsin, with neurolinguistics and semantics as main areas of study. Her dissertation focused on the neural representation of event concept composition. Liina Pylkkänen is Professor of Linguistics and Psychology and Head of the Neurolinguistics Lab at New York University. Her research focus on the characterization of the brain mechanisms responsible for the semantic combinatorics of language and how they are intimately intertwined with computations building complex syntactic structures. [mehr]

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The Managing Director and the Equal Opportunity Officers are inviting everyone to the presentation of the Gender Equality Plan (GEP) 2021-2023. The information session (in English & German) will include the objectives and measures of the plan and give some tips regarding what is on offer from the institute and MPS to employees of any gender. Everyone is welcome to join and benefit from the opportunities offered and ask questions! [mehr]

The Managing Director and the Equal Opportunity Officers are inviting everyone to the presentation of the Gender Equality Plan (GEP) 2021-2023. The information session (in English & German) will include the objectives and measures of the plan and give some tips regarding what is on offer from the institute and MPS to employees of any gender. Everyone is welcome to join and benefit from the opportunities offered and ask questions! [mehr]

Der geschäftsführende Direktor und die Gleichstellungsbeauftragten laden alle Mitarbeiter*innen zur Präsentation des Gleichstellungsplans 2021-2023 ein. Die Informationsveranstaltung (in Englisch & Deutsch) wird die Ziele und Maßnahmen des Plans vorstellen und Tipps geben, was das Institut und die MPG für Mitarbeiter*innen jeden Geschlechts zu bieten hat. Jeder ist herzlich eingeladen, teilzunehmen und von den angebotenen Möglichkeiten zu profitieren und Fragen zu stellen! [mehr]

Molly Flaherty is Assistant Professor in the Department of Psychology at Davidson College. In her research, she seeks to better understand the developing human mind by closely examining the structure of language. Her work explores the emergence of linguistic structure in one of the youngest languages known to science: Nicaraguan Sign Language (NSL). Susan Goldin-Meadow is Professor in the Department of Psychology at the University of Chicago. Her main research interests include language development and creation, and the role of gesture in communicating, thinking, and learning. [mehr]

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Rie Asano is a post-doctoral researcher at the Institute of Musicology in Cologne, Germany. Her research focuses on syntax in language, music, and action, as well as the relationship between linguistic syntactic processing and musical rhythm, and computational evolutionary neuroscience. Cedric Boeckx is Professor at the Catalan Institute for Research & Advanced Studies, University of Barcelona. His current research focuses on the neurobiological foundations of the human language faculty, with special emphasis on evolutionary issues. Keywords: language evolution // emergence of language; speech processing; vocal learning [mehr]

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Interest in disorders of later life have grown in proportion with the increase of this population group in many societies. We are accustomed to see age as a confounder, so attempts to pinpoint group difference while adjusting for age effects often result in the removal of differences that may be crucial to understanding the aging process. In addition, age reflects between-subject variation (particularly in cross-sectional studies), as well as within-subject changes over time in repeat measures designs. Both are relevant clinically, as the importance of education or IQ for dementia diagnosis and the gradual development of vascular and cognitive risks in mid-life for accelerated ageing demonstrate. I will try to illustrate these issues with studies from UK Biobank and the EU Lifebrain Consortium, covering concepts such as brain-, cognitive age and -reserve, and the role of the natural history and life-time course of depression in its relation to biomarkers and putative aetiologies. [mehr]

Stephan Meylan is a Postdoctoral Fellow in the Computational Psycholinguistics Lab in the Department of Brain and Cognitive Sciences at MIT and a Postdoctoral Associate in the Bergelson Lab in the Department of Psychology and Neuroscience at Duke University. He studies the relationship of language processing and language development—with a focus on the emergence of combinatorial morphosyntax— using a combination of computational models, corpus studies, and in-lab experiments. Roger Levy is an Associate Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT). His research focuses on theoretical and applied questions in the processing and acquisition of natural language, employing computational modeling, psycholinguistic experimentation, and analysis of large naturalistic language datasets. [mehr]

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Quantitative MRI offers the potential to characterize human brain microstructure. Mapping of several MR parameters can be efficiently done using the multi-parameter mapping (MPM) protocol, which allows for quantification of PD, R2*, R1 and MT contrasts, reflecting respectively water content, iron concentration, myelin and macromolecular content. Even small improvements in the reliability of parameter maps are relevant in the context of quantifying myelination changes (for example in disease), which are typically in the order of a couple of percent. Therefore, we investigated correction of physiological artifacts caused by breathing and head motion, which are especially prominent at 7T and in long high resolution acquisitions, and applied the corrections in an elderly cohort including Alzheimer patients. Additionally, we modified the MPM protocol to measure an inhomogenous MT (ihMT) metric that has been shown to have higher specificity to myelin than simple MT contrast, and optimized the measurement protocol at our 3T scanners. [mehr]

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Giulio Degano is Postdoctoral Researcher in the Brain and Language Lab, University of Geneva. His research interests include the perception of naturalistic stimuli such as speech and music, and multisensory integration. Narly Golestani is Associate Professor at the University of Geneva and the University of Vienna. Her research focuses on the neural bases of auditory and language processing, using a range of neuroimaging techniques to study questions on language learning, multilingualism and individual differences. [mehr]

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The Max Planck Research Group: Adaptive Memory examines how we edit memories of our past and how we use our memories for the simulation of hypothetical events. In this colloquium, we will showcase some of our recent work in these two areas. Ann-Kirstin Meyer will first present evidence that memory suppression causes inhibitory after effects on declarative, affective, and neural memory representations. Roland Benoit will then turn to our recent observation that we learn from simulated experiences much the same way as we learn from real experiences. [mehr]

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Bingjiang Lyu is Postdoctoral Researcher at the University of Cambridge. His research interests lie in the cortical mechanisms and dynamics involved in language comprehension using EEG/MEG and fMRI. He is currently working on how the incremental processing of speech is affected by contextual information embedded in sentences. Lorraine Tyler is Professor the Department of Psychology, University of Cambridge. Her research combines cognitive models with multi-modal imaging to understand the neurobiological substrate for language functions. [mehr]

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Neural activity is remarkably variable: Even for the very same stimulus, the brain´s response can differ from moment to moment. Although it has been hypothesized that changes of the system´s excitability may account for this variability, the underlying dynamics that link instantaneous brain state and stimulus processing remain poorly understood. Therefore, we studied the spatiotemporal organization of cortical excitability in a series of three somatosensory stimulation paradigms in humans, examining the interplay between pre-stimulus oscillatory state and short-latency somatosensory evoked potentials in the EEG, as well as their association with the consciously accessible stimulus percept. We found that these dynamics of excitability are (i) temporally structured in a special way (long-range temporal dependencies), (ii) linked to the perceived stimulus intensity already via first cortical responses, and (iii) organized with spatially confined, somatotopic patterns. Taken together, these findings may reflect a delicate balance between robustness and flexibility of neural responses to sensory stimuli, enabling the brain to adaptively change the neural encoding of even low-level stimulus features, such as the stimulus´ intensity. [mehr]

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Under what conditions will a neural network train, and under what conditions will it train well? Years of experimentation have led the community to develop a fairly robust recipe book for training deep nets on common tasks, and a series of slightly delayed efforts have built up a reasonably deep understanding of the mechanisms underlying the success of these techniques. In this talk, I’ll discuss our recent work on understanding and improving signal propagation in deep neural networks, with a focus on the process by which one might discover and visualize quantities of interest, use that knowledge to ground the development of new techniques in empirical understanding, and maybe land an ImageNet SOTA or two in the process. [mehr]

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When navigating physical and virtual environments, the human brain processes spatial information using allocentric representations such as cognitive maps, that reflect spatial relations between locations in a world-centred, viewpoint independent manner (e.g., object X is between object Y and Z, or object X is further north than object Z) - and egocentric representations such as image spaces, that focus on self-centred, viewpoint dependent information (e.g., object X is on my left). Converging evidence across different fields of neuroscience has shown that allocentric representations are mostly supported by the medial temporal lobe and the hippocampal formation, while egocentric representations seem to be linked to the activity of parietal cortex. In recent years, the representational mechanisms and coding schemes typical of allocentric representations in the hippocampal formation have been observed also when human participants process conceptual knowledge, “mentally navigating” 2D feature spaces that bear little, if any, similarity with the physical world. This led to the proposal that allocentric cognitive mapping might serve a more general purpose than spatial navigation, representing mutual relations between items or “states” in memory, be them spatial locations or abstract concepts. In this talk I will present an fMRI study on goal-directed conceptual navigation aiming at testing the hypothesis that the same thing might happen in the parietal system, which might follow egocentric-like schema that link the representation of conceptual goals to our current stimulation (aka “the self”). I will present the analytical approach we are currently following, as well as preliminary (N=30) results of ongoing analyses that potentially support our hypothesis. [mehr]

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What motivates us to do what we do? And why is it so incredibly difficult to do the right thing, even when we (think we) set our minds to it? Successful behavioural change is still a major challenge for people, both in clinical and non-clinical settings. This lack of flexibility, which often results in maladaptive behaviour of some kind, is what fascinates me and what broadly has been driving my research interest in real-world habits. In this talk, I would like to give you a concise overview of some of the studies I worked on regarding people’s ability to adjust to changes in learnt responses and reward probabilities (reversal learning, two-step task, outcome devaluation) in different target populations (e.g., disordered gambling, diet-induced obesity). Dopamine will be a red thread throughout the talk. Finally, I will discuss the idea that adaptive flexibility requires sufficient stability, and that it may be worth reconsidering the traditional dichotomous thinking in behavioural control research. [mehr]

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The loss of dopaminergic neurons in the substantia nigra leads to the primary motor symptoms of Parkinson’s disease but starts more than ten years before diagnosis. Dopaminergic neurons contain iron in the pigment neuromelanin. Thus, iron-sensitive MRI promises to map these neurons and their loss. However, the exact mechanisms of MRI contrast in the substantia nigra are not well understood, hindering the development of robust biomarkers. We propose and validate a biophysical model of iron-induced transverse MRI relaxation in the substantia nigra, combining quantitative 3D iron histology with ultra-high-field and -resolution post mortem MRI. We quantify a missing but central parameter of this model, the susceptibility of neuromelanin-bound iron, using quantitative susceptibility mapping at cellular resolution. We demonstrate that iron in dopaminergic neurons, although being only a tiny fraction of all tissue iron, contributes predominantly to iron-induced effective transverse relaxation rate R2* and propose biomarkers of this iron pool. We leverage our understanding of iron-induced transverse relaxation to revisit the interpretation of a potent diagnostic marker of Parkinson’s, the swallow tail sign. Our results provide directions for developing biomarkers for early detection of dopaminergic neuron depletion in Parkinson’s disease. [mehr]

Encoding new memories not only takes place simultaneously with occurring events but also against the backdrop of a rich library of information acquired through one’s life. Previous studies show that prior knowledge (e.g. schemas) strengthens the encoding and accelerates the recall of new memories that are both in agreement with (congruent), or in opposition (incongruent) to that previous knowledge. The contradictions between these two lines of research have not been resolved yet. A third suggestion of how prior knowledge influences memory comes from a recent framework, SLIMM (van Kesteren et al., 2012), which postulates that learning shows a non-linear, U-shaped function with degrees of congruency to prior information. However, the SLIMM model remains under scrutiny as not all of its hypotheses have been successfully tested yet. Furthermore, the neural underpinnings of such learning processes remain unknown. While the SLIMM model predicts a trade-off between the mPFC and MTL structures for congruent and incongruent effects respectively, other models predict an essential role of MTL structures in encoding congruent information. In this PhD project, we aim to use behavioural methods as well as neuroimaging techniques (fMRI) in order to understand whether and how prior knowledge structures enhance the encoding and retrieval of new events. Using a novel spatial schema paradigm, we will compare three conditions with varying degrees of congruency to previous knowledge in order to test the three seemingly contradictory patterns of findings in the literature. Additionally, we will use fMRI to directly compare learning systems in the brain that support learning under certain (congruent) and uncertain (incongruent) conditions. This will allow us to offer a refined neuroscientific model of how brain networks interact to successfully integrate new information with previous knowledge schemas. Importantly, to the best of our knowledge, we will be the first to use a machine learning classifier to decode schemas in the brain by investigating which brain networks are responsible for representing knowledge structures and integrating new learning into them. Understanding how learning is influenced by previous knowledge bear implications for improving clinical conditions, educational methods and machine learning techniques. [mehr]

In recent years, the Max Planck Research Group: Adaptive Memory has examined how we use our general knowledge about the world for the recollection of the past and the simulation of the future. In this colloquium, we will showcase some of our recent work-in-progress. Heidrun Schultz will first examine how we use our pre-existing knowledge to augment the retrieval of specific episodic memories. Towards this end, she gauges how information pertaining to pre-existing knowledge is represented in the medial temporal lobes versus prefrontal cortex. Mark Lauckner will then highlight the contribution of memory schemas to episodic memory and future simulation. This work combines natural language processing of a large data set with examinations of patients with focal brain lesions. Finally, Aroma Dabas will demonstrate that we learn from simulated experiences much the same way as we learn from real experiences. Specifically, she will show that simulation-based learning is governed by the same computational algorithm and implemented by a similar neural mechanism. [mehr]

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Please join using this link: https://zoom.us/j/8868284415?pwd=ZkkweVNqaUxGMVNCcCtLQnNCeEVWUT09 [mehr]

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Please join using this link: https://zoom.us/j/8868284415?pwd=NmpZRjZsRnRvU0NJMDBTUERzc2x0Zz09 (passcode: skeidelab) [mehr]

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Researchers in psychiatry and neuroscience are increasingly recognizing the importance of gut-brain communication in mental health. Based on a foundation of animal studies demonstrating the vital role for microbiota-brain communication in brain development, behavior, and brain function over the life span, clinical studies have started to consider the microbiome in psychiatric disorders. Work to date by our group and others suggest that microbiota-immune-brain signaling is an important pathway that infuences brain structure, gene expression of stress-related and plasticity-related genes, stress-reactivity, and behaviour. Ongoing work in our lab is interested in determining the importance of peripheral T cells in the maturation of the microbiome, microbe and host metabolism, and neurodevelopment. The composition, diversity and function of commensal microbes is influenced by genetic, lifestyle, and environmental factors. Our increasing knowledge on pathways and involved mediators along the gut-brain axis has revolutionized our understanding of brain-body interaction. Intestinal bacteria act along the gut-brain axis in part by modifying the immune response. On the other side, bacteria produce neuroactive mediators and can modulate neuronal function, plasticity and behavior. Our recent research has focused on the bidirectional communication between microbiota and T cells in mouse models and in clinical popupations. This presentation will highlight this work in the context of recent developments linking microbiota to behaviour and brain function. Understanding the influence of microbiota-brain axis on brain function and behaviour is essential to understanding how host-microbe interactions are essential regulators of both physical and mental health. Understanding the basis of these differences, their functional impact, and mapping them to clinical symptoms, severity, and host biology is the next step in this fast-moving area of research. Moveover, the opportunity to harness our knowledge of the microbiome to develop novel therapies and to improve outcomes in psychiatry will be discussed. [mehr]

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Please join using this link: https://zoom.us/j/95065830000 [mehr]

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Due to technical difficulties on the original day of the lecture, the talk has been postponed and will now take place on 27 September. Join online: https://zoom.us/j/95065830000 [mehr]

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Please join online: https://zoom.us/j/8868284415?pwd=NmpZRjZsRnRvU0NJMDBTUERzc2x0Zz09 [mehr]

Please join online: https://zoom.us/j/93526030034?pwd=ZkJnYlFVOEthU2lDeE5nVmV6TlZLZz09 (Meeting ID: 935 2603 0034 / Passcode: 250171) [mehr]

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Please join online: https://zoom.us/j/93526030034?pwd=ZkJnYlFVOEthU2lDeE5nVmV6TlZLZz09 (Meeting ID: 935 2603 0034 / Passcode: 250171) [mehr]

Please join online: https://zoom.us/j/93526030034?pwd=ZkJnYlFVOEthU2lDeE5nVmV6TlZLZz09 (Meeting ID: 935 2603 0034 / Passcode: 250171) [mehr]

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Please join online: https://zoom.us/j/91383057579?pwd=RDJQNkllaEJRYTV3VTlJTHprSjZodz09 / Passcode: skeidelab [mehr]