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Ultra-high field MRI at 7T holds great potential but also presents significant challenges, often necessitating extensive calibration times to achieve spatially heterogeneous B1+/ΔB0 profiles. This talk explores the development of novel methodologies to address such challenges in cardiac and spinal cord imaging. It includes the creation of calibration-free parallel transmission techniques to eliminate conventional time-consuming calibration routines and covers broadband excitation to compensate for local ΔB0 variations or chemical shifts. Moreover, the presentation delves into respiration-related ΔB0 variations in mid- to lower spinal cord regions, providing essential insights for advancing spinal cord imaging techniques at ultra-high fields. [more]

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Abstract: Multi-echo gradient-echo (GRE) sequences are commonly used for anatomical imaging of the spinal cord because they provide excellent contrast between grey matter (GM), white matter (WM), and cerebrospinal fluid (CSF). One of their main limitations is the sensitivity to voluntary and involuntary motion, leading to ghosting artifacts and lower image quality even in compliant subjects. Time-varying B0 fields related to the breathing cycle contribute substantially to the artifact load in the spinal cord. Navigator readouts can be used to measure the intensity of the B0 fluctuations, allowing to demodulate the acquired signal before the image reconstruction. However, the standard navigator processing approach, developed for brain imaging, often fails in the spine, which can even exacerbate the artifacts. Therefore, there is a need for navigator processing specifically tailored to spinal cord imaging. In this study, we explore the effect of optimized processing pipelines for navigator-based correction on the image quality of a multi-echo GRE sequence acquired in the spinal cord at 3T. [more]

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Scrutiny of the cortical neuronal circuits underlying human visual perception typically involves the summarization of large-scale recordings of brain activity under different perceptual states, with the combination of various measurement modalities and modeling techniques being critical in revealing organizing principles. In this seminar, we'll delve into the relationship between anatomical structure and evolving patterns of neuronal functional connectivity across the early visual foveal cluster (V1-V2-V3). I will show how we can inform our understanding of visual perception through different recording modalities, combining high-resolution fMRI and laminar electrophysiology with computational modeling. I will present key findings on task-dependent modulation of directed interactions across visual cortical areas in humans and laminar distinctions in visual processing in Macaque, as well as touch on preliminary validation work. Finally, I look forward to discussing new advancements and techniques and to providing a clearer picture of neuronal circuit dynamics at the mesoscopic level. [more]

* Collaboration with Leipzig University / Open Science Network Leipzig * IT solutions task force wrap-up * Upcoming events [more]

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Niso, G., Botvinik-Nezer, R., Appelhoff, S., De La Vega, A., Esteban, O., Etzel, J. A., Finc, K., Ganz, M., Gau, R., Halchenko, Y. O., Herholz, P., Karakuzu, A., Keator, D. B., Markiewicz, C. J., Maumet, C., Pernet, C. R., Pestilli, F., Queder, N., Schmitt, T., … Rieger, J. W. (2022). Open and reproducible neuroimaging: From study inception to publication. NeuroImage, 263, 119623. https://doi.org/10.1016/j.neuroimage.2022.119623 [more]

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The brainstem is a crucial yet understudied structure of the human brain. Due to the technical difficulties of imaging deep brain structures, the cerebral cortex has long been the focus of in-vivo human imaging studies. Functional magnetic resonance imaging (fMRI) in particular has deepened our understanding of the cortex, including the presence of functionally specialized brain regions, intrinsic functional networks, and our understanding of higher-order cognitive processes. The brainstem’s role in what is now considered primarily cortical organization and function remains an open question. Here we employ a recently acquired 7T fMRI brainstem dataset, which underwent rigorous physiological noise correction and was delineated according to 58 brainstem nuclei, to study how functional activity in the brainstem aligns with cortical function. We identify a set of brainstem hubs that are maximally connected to the cortex, including the periaqueductal grey, the dorsal raphe, and the laterodorsal tegmental nucleus. Likewise, cortical regions that are maximally connected with the brainstem appear in anterior regions. We demonstrate that these brainstem and cortical hubs reflect both slow (fMRI) and fast (MEG) dynamics, including lag-1 temporal autocorrelation, signal variability, and MEG alpha power. Next, we cluster brainstem regions with respect to how they connect to the cortex and identify modules of brainstem nuclei that subserve familiar cortical functional activation patterns related to memory, social cognition, movement and sensation, and emotion. Using PET-derived cortical profiles for 18 neurotransmitter receptors and transporters we show that neuromodulatory systems are likely mediating the relationship between brainstem and cortical functional activity. Finally, we demonstrate that unimodal and transmodal cortical regions have distinct patterns of connectivity to the brainstem. Altogether, this study extends our perspective of cortical function---including dynamics, cognitive function, and the functional hierarchy---to the brainstem, demonstrating the importance of brainstem activity to cortical function. [more]

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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 [more]

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Magnetic resonance (MR) imaging technologies provide unique capabilities to probe the mysteries of biological systems, and have enabled novel insights into anatomy, metabolism, and physiology in both health and disease. However, while MRI is decades old, is associated with multiple Nobel prizes (in physics, chemistry, and medicine), and has already revolutionized fields like medicine and neuroscience, current MRI methods are still very far from achieving the full potential of the MRI signal. In particular, traditional methods are based on classical sampling theory, and suffer from fundamental trade-offs between signal-to-noise ratio, spatial resolution, and data acquisition speed. These issues are exacerbated in high-dimensional applications, due to the curse of dimensionality. Our work addresses the limitations of traditional MR imaging using signal processing approaches that are enabled by modern computational capabilities. These approaches are possible because of certain "blessings of dimensionality," e.g., that high-dimensional data often possess unexpectedly simple structure that can be exploited to alleviate classical barriers to fast high-resolution imaging. This seminar will describe approaches we have developed that use novel constrained imaging models to guide the design of new MR data acquisition and image reconstruction methods, and enable substantial acceleration of both low-dimensional and high-dimensional MR imaging experiments. [more]

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Organized by the Open Science Initiative at the Max Planck Institute for Human Cognitive and Brain Sciences, this is a space to discuss various aspects related to open and reproducible research practices, from general issues to specific applications, presenting both enthusiastic and critical perspectives. [more]

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MRI signal generation is substantially influenced by factors such as water content, iron, myelin, and several other contributors. Iron levels can be directly assessed using mass spectrometry, while the quantitative impacts of myelin's structure and composition remain unknown to a certain extent and are often inferred from theoretical simulations. Additionally, MRI relaxation rates and susceptibility are sensitive to these tissue constituents, but their specificity is limited. In this context, post-mortem investigations utilizing complementary methods such as TEM, LA-ICP-MS, MALDI-MSI, CARS, and SAXS-TT provide unique insights for the validation and understanding of quantitative MRI parameters. However, in-situ post-mortem MRI has to accommodate for factors like variable temperature, deoxygenated blood, and perfusion. Furthermore, the process of formalin fixation introduces a significant confounder, often obstructing direct conclusions. In this presentation, I aim to summarize our work on translating post-mortem MRI findings to in-vivo conditions, outline the analytical methods used to assess brain tissue structure and composition, and discuss potential collaborations with the MPI CBS. [more]

Magnetic resonance imaging of the human spinal cord at 7 Tesla offers new opportunities to visualize structures with high spatial resolution and enhanced conspicuity, and to detect functional networks with greater sensitivity. Sub-millimeter in-plane fMRI acquisitions are desirable and achievable, but published studies have had modest temporal resolution (>2 sec). Using a custom-built 7T pTx spine coil, we demonstrate sub-second and sub-millimeter cervical cord fMRI for the first time. Employing a 3D multi-shot sequence with appropriate phase corrections and NORDIC denoising, our data demonstrate temporal signal-to-noise ratios comparable to those of supra-second protocols, and we replicate bilateral functional connectivity patterns previously published in the cord. Realizing sub-second and sub-millimeter spinal cord fMRI opens new avenues of discovery that echo what has been reported through high spatiotemporal resolution brain fMRI. [more]

Several Parallel Transmit (pTX), capable coils have become available at 7T in the last few years. With pTx comes the ability to shape the excitation field to our needs. However, while pTx applications have seen great uptake in brain and body imaging, their use for the spinal cord has been limited so far. In this talk, we will demonstrate the feasibility of designing and deploying Universal Pulses for the cervical spinal cord at 7T. We will also show the first results in subject-specific B1+ shimming for the c-spine, using a dedicated Shimming Toolbox developed in our lab. Both approaches allow us to improve the signal homogeneity and thus deliver better image contrast for high-field spinal cord imaging. Finally, we will demonstrate the utility of the Shimming Toolbox for dynamic B0 field corrections in the cervical spine at clinical field strengths. [more]

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Magnetic fields are ubiquitous in nature and since a long time also in technology. Yet, there are many open questions, needs for research and emerging new applications. Standards need to be set or refined, and more accurate calibrations are required by industrial adopters of new technologies. A particular challenge and opportunity arise at the lowest end of the spectrum of magnetic fields. With demonstrated measurement sensitivities beyond the femtotesla (per root Hertz) scale, the neuronal activities of the brain following a peripheral nerve stimulus become detectable in a single trial, for example. While even the foundations of physics can be tested at the frontier of lowest metrological noise floors, a current trend is to make magnetic field measurement and imaging viable in application contexts beyond quantum physics laboratories. Here, we will discuss such developments in terms of sensor developments, measurement environments and key use cases. We will focus on atomic gas-based probes of stationary and slowly varying magnetic fields. With trapped ultracold gases, high resolution field mapping can be achieved with relevance to material developments such as indium tin oxide replacements for next-generation touch screens and solar panels. On the other hand, cells containing thermal atomic vapours can provide highest field sensitivities as part of optically pumped magnetometers with use in clinical neurology or current-density imaging in electric vehicle batteries. [more]

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Compulsive behavior is a common feature of both OCD and pathological gambling, despite their differing motivational contexts. This talk will explore the role of control and agency in the onset and perpetuation of compulsions in these two conditions. Specifically, I will examine how a single belief disturbance, such as a lack of trust in one's avoidance actions or an illusion of control, can trigger and maintain compulsions. Using computational models of cognition in conjunction with empirical data, I will demonstrate the direct link between this disturbance and the severity of compulsions. Overall, this talk will shed light on the importance of control and agency in understanding and treating compulsive behaviors across different contexts. [more]

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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. [more]

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My talk will overview new tools and resources to study the human brain across multiple space scales, and how these approaches can help to (i) understand the spatial layout of brain networks, (ii) associations between brain structure and function, (iii) as well as shifts in spatial patterns in both typical and atypical brain development. [more]

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Magnetic Resonance Fingerprinting (MRF) was introduced in 2013 as an approach for mapping multiple tissue properties simultaneously using MRI. This presentation will provide an overview of the MRF technique, with an emphasis on practical aspects of implementation, and describe how tissue property maps derived from MRF may be leveraged to provide additional information about structure and function in the brain and beyond. [more]

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Principles of neuroscience, notably as they relate to vision, invoke concepts of building blocks, opponency, representation, and agency (active vision). He will argue that these ideas have been productively developed using color as a model system, with roots in the earliest western theories of psychology dating to the ancient Greeks. In his talk, he will describe data from neurophysiology, functional brain imaging (fMRI and MEG), and psychophysics that aim to test the principles of neuroscience and to place them in a holistic framework of our broad goal to understand brain and behavior [more]

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We — the Open Science Initiative at MPI CBS — are happy to invite you to an info event on Thursday, June 16, 12:00—13:00 CET, in Room A400 (Wilhelm Wundt-Raum). With this event, we would like to give you an overview of our initiative and key topics of Open Science more broadly. This event is for everyone who: - Cares deeply about the rigor and transparency of our scientific workflows - Would like to get started implementing Open Science practices in their own research - Wants to connect with like-minded people to make our research even more trustworthy and collaborative We will start the meeting with a short presentation about our initiative, followed by time for questions from the audience and a small get-together where we can further talk about Open Science and other topics on a one-to-one basis (incl. snacks and drinks). The event is open to researchers from all career stages and does not require registration. We are very much looking forward to seeing you there! [more]

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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. [more]

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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. [more]

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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. [more]

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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. [more]

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. [more]

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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 [more]

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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. [more]

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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. [more]

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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. [more]

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

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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. [more]

*** 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. [more]

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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. [more]

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The aims of the meeting are: - Networking of all MPIs on sustainability - Exchange on and mutual support for various projects (setting up and organizing a sustainability group, exchanging ideas on measures, implementing measures, events on sustainability) - Election of the steering committee of the sustainability network - Climate Change of Mind: How can science drive the change towards more sustainable behaviour? How to communicate effectively and convincingly about climate change and sustainability? - Establishing a climate-friendly way of organizing scientific conferences virtually and interactively * For whom? All affiliates of the Max Planck Society with an interest in sustainability are invited. We would also be pleased if at least one representative from the existing sustainability groups would attend the meeting to share expertise and current projects. When registering, please also indicate whether you would be willing to give a one-hour workshop on a topic you (and your sustainability group) have already dealt with in order to share knowledge and experience. * When and where? On 26.5.20 from 1.30 pm to about 7:30 pm and on 27.5.20 from 1:30 pm to about 7:30 pm. Access to the virtual conference rooms and other platforms will be announced in a separate mail as soon as possible. * Costs The participation in the virtual meeting is of course free of charge. * Registration Please register by April 30th 2020 under the following link: https://survey3.gwdg.de/index.php?r=survey/index&sid=579528&lang=de * Election of the steering committee Interested parties can stand for election until May 26, 5 pm. The presentation of the candidates takes place at about 7 p,. All representatives of the local sustainability groups are entitled to vote. If you are a representative of your local sustainability group, please be sure to take part in the online election (from 26 May, 7:30 pm to 27 May, 12 noon). * Music We would like to weave in some small music contributions after certain items on the agenda so that also some personal notes mix into the virtual conference . If you would like to add a contribution of about 3 minutes please send as an e-mail beforehand. *Please note: All times and dates refer to Central European Summer Time. * Questions? If you have further questions, please contact us, the Green Team of the MPI CBS and the local organization team, at: green-team@cbs.mpg.de [more]

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Exposure to childhood adversity is common and associated with a host of negative developmental outcomes as well as differences in neural structure and function. It is commonly posited that these social experiences “get under the skin” in early childhood, increasing long-term risk through disruptions to biology. In this talk I propose a novel approach to studying the link between adversity, brain development, and risk for psychopathology, the dimensional model of adversity and psychopathology (DMAP). In this model we propose that adversity exposure can be defined according to different dimensions which we expect to impact health and well-being through different neural substrates. Whereas we expect deprivation to primarily disrupt function and structure of lateral association cortex (e.g., dorsolateral prefrontal cortex and superior parietal cortex) and thus complex cognitive processing such as executive functioning. In contrast, we expect threat to alter structure and function of subcortical structures such as the hippocampus and amygdala and midline regions associated with emotion regulation such as the ventral medial prefrontal cortex and thus, associated emotion reactivity and automatic regulation processes. In a series of studies I test the basic tenants of the DMAP concluding that initial evidence, using both a priori hypothesis testing and data-driven approaches is consistent with the proposed model. I conclude by describing future work addressing multiple dimensions of adversity and potential adjustments to the model. [more]

Learning often takes place in environments, in which it is impossible to exactly know current and future outcomes. To successfully behave in such uncertain environments, humans have to learn appropriate beliefs from past experiences that can be used to predict desirable and undesirable outcomes. Drawing on optimal inference models and behavioural learning tasks, I will illustrate how learning under uncertainty should be regulated from a normative perspective and how learning deficits may emerge from deviations from these computations. I will show how human participants learn in the face of perceptual uncertainty and to which extent the ability to adjust learning in dynamically changing environments differs between age groups across the lifespan. Moreover, I will explore the possibility that the intricate computations to optimally adjust learning may often be simplified by resorting to heuristic strategies that are guided by previous choices. Finally, I will discuss some future directions that follow from these results. [more]

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A considerable body of work over the last 10 years combining non-invasive electrophysiology (electroencephalography/magnetoencephalography) in patient populations with preclinical research has contributed to the conceptualization of schizophrenia as a disorder associated with aberrant neural dynamics and disturbances in excitation/inhibition (E/I) balance parameters. Specifically, I will propose that recent technological and analytic advances in MEG provide novel opportunities to address these fundamental questions as well as establish important links with translational research. We have carried out several studies which have tested the importance of neural oscillations in the pathophysiology of schizophrenia through a combination of MEG-measurements in ScZ-patients and pharmacological manipulations in healthy volunteers which target the NMDA-receptor. These results highlight a pronounced impairment in high-frequency activity in both chronic and unmedicated patients which could provide novel insights into basic circuit mechanisms underlying cognitive and perceptual dysfunctions. However, acute Ketamine only partly recreates abnormalities observed in both resting-state and task-related neural oscillations in ScZ, suggesting potentially shortcoming of this pharmacological model for capturing large-scale network dysfunctions. Our recent work has employed MEG to develop a biomarker for early detection and diagnosis of ScZ. We have obtained MEG- and MRS-data from 125 participants meeting clinical high-risk criteria (CHR), 90 controls and 30 FEP-patients. We found marked changes in the synchrony of gamma-band oscillations in visual and auditory cortices during sensory processing which predicted clinical outcomes. In addition, CHR-participants were characterized by elevated broad-band gamma-band activity at rest which correlated with increased glutamate levels. Together, these findings highlight the potential of MEG-based biomarkers for the early diagnosis of ScZ in at-risk populations. [more]

Various psychological disorders are characterized by pronounced cognitive biases, including biased orienting of attention to certain stimuli, distorted expectation of the likelihood to encounter specific objects, biased interpretation of ambiguous information and biased perception. Although these biases are common in psychopathology, most of the studies so far focused on one bias by employing traditional analysis methods. Therefore, little is known about the correlational and causal relations between different biases and about combined patterns that may characterize certain disorders. In this talk, I will discuss recent behavioral, fMRI and autonomic data showing links between biases, as well as modulation of biased emotional processing in different populations. Moreover, by employing machine-learning based analysis, we managed to specify specific behavioral patterns that characterize anxiety vs. depression, two disorders that share many characteristics and show high comorbidity. Finally, I will discuss recent evidence for abnormalities in the blood pressure reaction to aversive pictures among individuals with pre- hypertension, a population that is usually not studied in the context of psychological reactions. Taken together, these findings suggest new strategies to explore and treat maladaptive behaviors that have fundamental implications on the patients’ life. [more]

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Multisensory integration does not only recruit higher-level association cortex, but also primary sensory cortices like A1 (auditory), S1 (somatosensory), and V1 (visual). The underlying anatomical pathways, which might preferentially serve short-latency integration processes, include direct thalamocortical and corticocortical connections across the senses. We investigated how these multisensory connections develop over the individual’s lifespan and how early sensory deprivation alters them. Using tracer injections into A1, S1, and V1 of a rodent model (Mongolian gerbil) we could show that multisensory thalamocortical connections emerge before corticocortical connections but mostly disappear towards the end of the critical sensory period. Early auditory, somatosensory, or visual deprivation increases multisensory connections via axonal reorganization processes mediated by non-lemniscal thalamic nuclei and the primary areas themselves. Functional imaging reveals a mostly reduced stimulus-induced activity but a higher functional connectivity specifically between primary areas in deprived animals. In adult animals, primary sensory cortices receive substantial inputs from thalamic nuclei and cortical areas of non-matched sensory modalities. In very old animals, these multisensory connections strongly decrease in number or vanish entirely. This is likely due to a retraction of the projection neuron axonal branches and is accompanied by changes in anatomical correlates of inhibition and excitation in the sensory thalamus and cortex. Together, we show that during early development, intracortical multisensory connections are formed as a consequence of sensory driven multisensory thalamocortical activity and that during aging, multisensory processing is probably shifted from primary cortices towards other sensory brain areas. [more]

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Today only seven percent of the subcortical structures listed by the Federative Community on Anatomical Terminology (FCAT, 1998) are depicted in available standard MRI-atlases (Forstmann et al., 2016). As a consequence, the remaining 423 subcortical structures cannot be studied using automated analysis protocols available for MRI and therefore require trained anatomists for the study of subcortical brain areas: The human subcortex is notoriously difficult to visualize and analyze with functional magnetic resonance imaging. In this talk, exciting technical advances are presented that allow charting terra incognita; the human subcortex. Closing the knowledge-gap of the human subcortex has already resulted in the re-evaluation of prominent models in the cognitive neurosciences such as the functional role of cortico-basal ganglia loops in decision-making. I will discuss the emerging possibilities of novel human neuroanatomical approaches and directions for the incorporation of these data within the field of model-based cognitive neuroscience. [more]