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Bernstein Conference 2026
Annual conference of the Bernstein Network Computational Neuroscience, bringing together students, postdocs and PIs from around the world to meet and discuss new scientific discoveries in computational neuroscience. Satellite workshops Sep 28-29, main conference Sep 29-Oct 1 at Goethe University, Campus Westend, Frankfurt am Main.
Computational Mechanisms of Predictive Processing in Brains and Machines
Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding inspired deep network that has been widely used to model real-world biological vision systems. Using dynamic stimuli generated with our Spatiotemporal Style Transfer algorithm, we demonstrate that PredNet relies primarily on low-level spatiotemporal structure and remains insensitive to high-level content, revealing limits in its generalization capacity. Finally, I will discuss new recurrent vision models that integrate top-down feedback connections with intrinsic neural variability, uncovering a dual mechanism for robust sensory coding in which neural variability decorrelates unit responses, while top-down feedback stabilizes network dynamics. Together, these results outline how prediction error signaling and top-down feedback pathways shape adaptive sensory processing in biological and artificial systems.
Top-down control of neocortical threat memory
Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally-generated top-down information reflecting past experiences and current aims. Decades of work have elucidated how sensory neocortex processes physical stimulus features. In contrast, examining how memory-related-top-down information is encoded and integrated with bottom-up signals has long been challenging. Here, I will discuss our recent work pinpointing the outermost layer 1 of neocortex as a central hotspot for processing of experience-dependent top-down information threat during perception, one of the most fundamentally important forms of sensation.
Competing Rhythms: Understanding and Modulating Auditory Neural Entrainment
How the presynapse forms and functions”
Nervous system function relies on the polarized architecture of neurons, established by directional transport of pre- and postsynaptic cargoes. While delivery of postsynaptic components depends on the secretory pathway, the identity of the membrane compartment(s) that supply presynaptic active zone (AZ) and synaptic vesicle (SV) proteins is largely unknown. I will discuss our recent advances in our understanding of how key components of the presynaptic machinery for neurotransmitter release are transported and assembled focussing on our studies in genome-engineered human induced pluripotent stem cell-derived neurons. Specifically, I will focus on the composition and cell biological identity of the axonal transport vesicles that shuttle key components of neurotransmission to nascent synapses and on machinery for axonal transport and its control by signaling lipids. Our studies identify a crucial mechanism mediating the delivery of SV and active zone proteins to developing synapses and reveal connections to neurological disorders. In the second part of my talk, I will discuss how exocytosis and endocytosis are coupled to maintain presynaptic membrane homeostasis. I will present unpublished data regarding the role of membrane tension in the coupling of exocytosis and endocytosis at synapses. We have identified an endocytic BAR domain protein that is capable of sensing alterations in membrane tension caused by the exocytotic fusion of SVs to initiate compensatory endocytosis to restore plasma membrane area. Interference with this mechanism results in defects in the coupling of presynaptic exocytosis and SV recycling at human synapses.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany
Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.
Functional Plasticity in the Language Network – evidence from Neuroimaging and Neurostimulation
Efficient cognition requires flexible interactions between distributed neural networks in the human brain. These networks adapt to challenges by flexibly recruiting different regions and connections. In this talk, I will discuss how we study functional network plasticity and reorganization with combined neurostimulation and neuroimaging across the adult life span. I will argue that short-term plasticity enables flexible adaptation to challenges, via functional reorganization. My key hypothesis is that disruption of higher-level cognitive functions such as language can be compensated for by the recruitment of domain-general networks in our brain. Examples from healthy young brains illustrate how neurostimulation can be used to temporarily interfere with efficient processing, probing short-term network plasticity at the systems level. Examples from people with dyslexia help to better understand network disorders in the language domain and outline the potential of facilitatory neurostimulation for treatment. I will also discuss examples from aging brains where plasticity helps to compensate for loss of function. Finally, examples from lesioned brains after stroke provide insight into the brain’s potential for long-term reorganization and recovery of function. Collectively, these results challenge the view of a modular organization of the human brain and argue for a flexible redistribution of function via systems plasticity.
Single-neuron correlates of perception and memory in the human medial temporal lobe
The human medial temporal lobe contains neurons that respond selectively to the semantic contents of a presented stimulus. These "concept cells" may respond to very different pictures of a given person and even to their written or spoken name. Their response latency is far longer than necessary for object recognition, they follow subjective, conscious perception, and they are found in brain regions that are crucial for declarative memory formation. It has thus been hypothesized that they may represent the semantic "building blocks" of episodic memories. In this talk I will present data from single unit recordings in the hippocampus, entorhinal cortex, parahippocampal cortex, and amygdala during paradigms involving object recognition and conscious perception as well as encoding of episodic memories in order to characterize the role of concept cells in these cognitive functions.
Dark Matter in the Locus coeruleus - Neuromelanin in Health and Disease
Gene regulatory mechanisms of neocortex development and evolution
The neocortex is considered to be the seat of higher cognitive functions in humans. During its evolution, most notably in humans, the neocortex has undergone considerable expansion, which is reflected by an increase in the number of neurons. Neocortical neurons are generated during development by neural stem and progenitor cells. Epigenetic mechanisms play a pivotal role in orchestrating the behaviour of stem cells during development. We are interested in the mechanisms that regulate gene expression in neural stem cells, which have implications for our understanding of neocortex development and evolution, neural stem cell regulation and neurodevelopmental disorders.
Bernstein Conference 2024
Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. Bernstein Conference 2024, held in Frankfurt am Main, featured discussions, keynote lectures, and poster sessions, and has established itself as one of the most renowned conferences worldwide in this field.
Cerebrospinal fluid and the meninges : Understanding brain immunology from its borders
Update on vestibular, ocular motor and cerebellar disorders
Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities; Spatial filtering to enhance signal processing in invasive neurophysiology
On Thursday February 15th, we will host Victoria Peterson and Julian Neumann. Victoria will tell us about “Spatial filtering to enhance signal processing in invasive neurophysiology”. Besides his scientific presentation on “Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities”, Julian will give us a glimpse at the person behind the science. The talks will be followed by a shared discussion. Note: The talks will exceptionally be held at 10 ET / 4PM CET. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
The Brain Prize winner's webinar
In 2023, Michael Greenberg (Harvard, USA), Erin Schuman (Max Planck Institute for Brain Research, Germany) and Christine Holt (University of Cambridge, UK) were awarded The Brain Prize for their pioneering work on activity-dependent gene transcription and local mRNA translation. In this webinar, all 3 Brain Prize winners will present their work. Each speaker will present for 25 minutes and the webinar will conclude with an open discussion. The webinar will be moderated by Kelsey Martin from the Simons Foundation.
Use of brain imaging data to improve prescriptions of psychotropic drugs - Examples of ketamine in depression and antipsychotics in schizophrenia
The use of molecular imaging, particularly PET and SPECT, has significantly transformed the treatment of schizophrenia with antipsychotic drugs since the late 1980s. It has offered insights into the links between drug target engagement, clinical effects, and side effects. A therapeutic window for receptor occupancy is established for antipsychotics, yet there is a divergence of opinions regarding the importance of blood levels, with many downplaying their significance. As a result, the role of therapeutic drug monitoring (TDM) as a personalized therapy tool is often underrated. Since molecular imaging of antipsychotics has focused almost entirely on D2-like dopamine receptors and their potential to control positive symptoms, negative symptoms and cognitive deficits are hardly or not at all investigated. Alternative methods have been introduced, i.e. to investigate the correlation between approximated receptor occupancies from blood levels and cognitive measures. Within the domain of antidepressants, and specifically regarding ketamine's efficacy in depression treatment, there is limited comprehension of the association between plasma concentrations and target engagement. The measurement of AMPA receptors in the human brain has added a new level of comprehension regarding ketamine's antidepressant effects. To ensure precise prescription of psychotropic drugs, it is vital to have a nuanced understanding of how molecular and clinical effects interact. Clinician scientists are assigned with the task of integrating these indispensable pharmacological insights into practice, thereby ensuring a rational and effective approach to the treatment of mental health disorders, signaling a new era of personalized drug therapy mechanisms that promote neuronal plasticity not only under pathological conditions, but also in the healthy aging brain.
Quality of life after DBS; Non-motor effects of DBS and quality of life
It’s our pleasure to announce that we will host Haidar Dafsari and Günther Deuschl on September 28th at noon ET / 6PM CET. Haidar Dafsari, MD, is a researcher and lecturer at the University Hospital Cologne. Günther Deuschl, MD, PhD, is a professor at Kiel University. He was president of the International Movement Disorders Society (MDS) from 2011-2013, Editor in Chief of the journal Movement Disorders and has been awarded numerous high-class awards. Beside his scientific presentation, he will give us a glimpse at the “Person behind the science”.The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Sleep deprivation and the human brain: from brain physiology to cognition”
Sleep strongly affects synaptic strength, making it critical for cognition, especially learning and memory formation. Whether and how sleep deprivation modulates human brain physiology and cognition is poorly understood. Here we examined how overnight sleep deprivation vs overnight sufficient sleep affects (a) cortical excitability, measured by transcranial magnetic stimulation, (b) inducibility of long-term potentiation (LTP)- and long-term depression (LTD)-like plasticity via transcranial direct current stimulation (tDCS), and (c) learning, memory, and attention. We found that sleep deprivation increases cortical excitability due to enhanced glutamate-related cortical facilitation and decreases and/or reverses GABAergic cortical inhibition. Furthermore, tDCS-induced LTP-like plasticity (anodal) abolishes while the inhibitory LTD-like plasticity (cathodal) converts to excitatory LTP-like plasticity under sleep deprivation. This is associated with increased EEG theta oscillations due to sleep pressure. Motor learning, behavioral counterparts of plasticity, and working memory and attention, which rely on cortical excitability, are also impaired during sleep deprivation. Our study indicates that upscaled brain excitability and altered plasticity, due to sleep deprivation, are associated with impaired cognitive performance. Besides showing how brain physiology and cognition undergo changes (from neurophysiology to higher-order cognition) under sleep pressure, the findings have implications for variability and optimal application of noninvasive brain stimulation.
The Geometry of Decision-Making
Running, swimming, or flying through the world, animals are constantly making decisions while on the move—decisions that allow them to choose where to eat, where to hide, and with whom to associate. Despite this most studies have considered only on the outcome of, and time taken to make, decisions. Motion is, however, crucial in terms of how space is represented by organisms during spatial decision-making. Employing a range of new technologies, including automated tracking, computational reconstruction of sensory information, and immersive ‘holographic’ virtual reality (VR) for animals, experiments with fruit flies, locusts and zebrafish (representing aerial, terrestrial and aquatic locomotion, respectively), I will demonstrate that this time-varying representation results in the emergence of new and fundamental geometric principles that considerably impact decision-making. Specifically, we find that the brain spontaneously reduces multi-choice decisions into a series of abrupt (‘critical’) binary decisions in space-time, a process that repeats until only one option—the one ultimately selected by the individual—remains. Due to the critical nature of these transitions (and the corresponding increase in ‘susceptibility’) even noisy brains are extremely sensitive to very small differences between remaining options (e.g., a very small difference in neuronal activity being in “favor” of one option) near these locations in space-time. This mechanism facilitates highly effective decision-making, and is shown to be robust both to the number of options available, and to context, such as whether options are static (e.g. refuges) or mobile (e.g. other animals). In addition, we find evidence that the same geometric principles of decision-making occur across scales of biological organisation, from neural dynamics to animal collectives, suggesting they are fundamental features of spatiotemporal computation.
New mechanically-gated ion channels and tethers for touch
Precise spatio-temporal spike patterns in cortex and model
The cell assembly hypothesis postulates that groups of coordinated neurons form the basis of information processing. Here, we test this hypothesis by analyzing massively parallel spiking activity recorded in monkey motor cortex during a reach-to-grasp experiment for the presence of significant ms-precise spatio-temporal spike patterns (STPs). For this purpose, the parallel spike trains were analyzed for STPs by the SPADE method (Stella et al, 2019, Biosystems), which detects, counts and evaluates spike patterns for their significance by the use of surrogates (Stella et al, 2022 eNeuro). As a result we find STPs in 19/20 data sets (each of 15min) from two monkeys, but only a small fraction of the recorded neurons are involved in STPs. To consider the different behavioral states during the task, we analyzed the data in a quasi time-resolved analysis by dividing the data into behaviorally relevant time epochs. The STPs that occur in the various epochs are specific to behavioral context - in terms of neurons involved and temporal lags between the spikes of the STP. Furthermore we find, that the STPs often share individual neurons across epochs. Since we interprete the occurrence of a particular STP as the signature of a particular active cell assembly, our interpretation is that the neurons multiplex their cell assembly membership. In a related study, we model these findings by networks with embedded synfire chains (Kleinjohann et al, 2022, bioRxiv 2022.08.02.502431).
The strongly recurrent regime of cortical networks
Modern electrophysiological recordings simultaneously capture single-unit spiking activities of hundreds of neurons. These neurons exhibit highly complex coordination patterns. Where does this complexity stem from? One candidate is the ubiquitous heterogeneity in connectivity of local neural circuits. Studying neural network dynamics in the linearized regime and using tools from statistical field theory of disordered systems, we derive relations between structure and dynamics that are readily applicable to subsampled recordings of neural circuits: Measuring the statistics of pairwise covariances allows us to infer statistical properties of the underlying connectivity. Applying our results to spontaneous activity of macaque motor cortex, we find that the underlying network operates in a strongly recurrent regime. In this regime, network connectivity is highly heterogeneous, as quantified by a large radius of bulk connectivity eigenvalues. Being close to the point of linear instability, this dynamical regime predicts a rich correlation structure, a large dynamical repertoire, long-range interaction patterns, relatively low dimensionality and a sensitive control of neuronal coordination. These predictions are verified in analyses of spontaneous activity of macaque motor cortex and mouse visual cortex. Finally, we show that even microscopic features of connectivity, such as connection motifs, systematically scale up to determine the global organization of activity in neural circuits.
Behavioural Basis of Subjective Time Distortions
Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, duration, and distance in time of two sequentially-organized events—standard S, with constant duration, and comparison C, with duration varying trial-by-trial—are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer inter-stimulus interval (ISI) helps to counteract such serial distortion effect only when the constant S is in the first position, but not if the unpredictable C is in the first position. These results imply the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. Our results clarify the mechanisms generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, something akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones.
25 years of DBS beyond movement disorders: what challenges are we facing?; Directional DBS targeting of different nuclei in the thalamus for the treatment of pain
On Thursday, 23rd of February, we will host Veerle Visser-Vandewalle and Marie Krüger. Marie Krüger, MD, is is currently leading the stereotactic surgery unit in St. Gallen but is on her move to join the team at UCL / Queensquare London. She will discuss “Directional DBS targeting of different nuclei in the thalamus for the treatment of pain”. Veerle Visser-Vandewalle, MD, PhD, is the Head of the Department of Stereotactic and Functional Neurosurgery at University Hospital of Cologne. Beside his scientific presentation on “25 years of DBS beyond movement disorders: what challenges are we facing?”, she will also give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Beta oscillations in the basal ganglia: Past, Present and Future; Oscillatory signatures of motor symptoms across movement disorders
On Wednesday, January 25th, at noon ET / 6PM CET, we will host Roxanne Lofredi and Hagai Bergman. Roxanne Lofredi, MD, is a research fellow in the Movement Disorders and Neuromodulation Unit at Charité Universitätsmedizin Berlin. Hagai Bergman, MD, PhD, is a Professor of Physiology in the Edmond and Lily Safra Center for Brain Research and Faculty of Medicine at the Hebrew University of Jerusalem, and is Simone and Bernard Guttman Chair in Brain Research. Beside his scientific presentation on “Beta oscillations in the basal ganglia: Past, Present and Future”, he will also give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Dynamical System Theory and Mean Field Approximation
Talk & Tutorial
Critical periods of plasticity in adult-born neurons
Physiomic Analysis of the Human L2&3 Pyramidal Neuron Network
Talk & Tutorial
Aligned and Oblique Dynamics in Recurrent Neural Networks
Talk & Tutorial
Radiopharmaceutical evaluation of novel bifunctional chelators and bioconjugates for tumour imaging and therapy
Bispidines (3,7-diazabicyclo[3.3.1]nonane) and their derivatives act as bifunctional chelators (BFC), combining the advantages of multidentate macrocyclic and acyclic ligands e.g. high kinetic inertness, rapid radiolabelling under mild conditions. This bicyclic chelator system shows a great diversity in terms of its denticity and type of functional groups, yielding a wide range of multidentate ligands that can bind a variety of different metal ions. In addition, they allow a facile functionalisation of targeting molecules such as peptides, peptidomimetics, and bispecic antibodies. Herein, examples of various bispidine complexes labelled with [64Cu]Cu2+, [111In]In3+, [ 177Lu]Lu3+ or [ 225Ac]Ac3+ will be presented which provide a picture of how different substituents inuence the coordination mode. Target-specic radiolabelled bispidine-based conjugates (e.g. peptides, antibody fragments, antibodies) investigated in vivo by positron emission or single-photon emission computed tomography will be presented and discussed in terms of their suitability for nuclear medicine applications.
Setting network states via the dynamics of action potential generation
To understand neural computation and the dynamics in the brain, we usually focus on the connectivity among neurons. In contrast, the properties of single neurons are often thought to be negligible, at least as far as the activity of networks is concerned. In this talk, I will contradict this notion and demonstrate how the biophysics of action-potential generation can have a decisive impact on network behaviour. Our recent theoretical work shows that, among regularly firing neurons, the somewhat unattended homoclinic type (characterized by a spike onset via a saddle homoclinic orbit bifurcation) particularly stands out: First, spikes of this type foster specific network states - synchronization in inhibitory and splayed-out/frustrated states in excitatory networks. Second, homoclinic spikes can easily be induced by changes in a variety of physiological parameters (like temperature, extracellular potassium, or dendritic morphology). As a consequence, such parameter changes can even induce switches in network states, solely based on a modification of cellular voltage dynamics. I will provide first experimental evidence and discuss functional consequences of homoclinic spikes for the design of efficient pattern-generating motor circuits in insects as well as for mammalian pathologies like febrile seizures. Our analysis predicts an interesting role for homoclinic action potentials as an integral part of brain dynamics in both health and disease.
Drifting assemblies for persistent memory: Neuron transitions and unsupervised compensation
Change is ubiquitous in living beings. In particular, the connectome and neural representations can change. Nevertheless behaviors and memories often persist over long times. In a standard model, associative memories are represented by assemblies of strongly interconnected neurons. For faithful storage these assemblies are assumed to consist of the same neurons over time. We propose a contrasting memory model with complete temporal remodeling of assemblies, based on experimentally observed changes of synapses and neural representations. The assemblies drift freely as noisy autonomous network activity or spontaneous synaptic turnover induce neuron exchange. The exchange can be described analytically by reduced, random walk models derived from spiking neural network dynamics or from first principles. The gradual exchange allows activity-dependent and homeostatic plasticity to conserve the representational structure and keep inputs, outputs and assemblies consistent. This leads to persistent memory. Our findings explain recent experimental results on temporal evolution of fear memory representations and suggest that memory systems need to be understood in their completeness as individual parts may constantly change.
Pro-regenerative functions of microglia in demyelinating diseases
Our goal is to understand why myelin repair fails in multiple sclerosis and to develop regenerative medicines for the nervous system. A central obstacle for progress in this area has been the complex biology underlying the response to CNS injury. Acute CNS damage is followed by a multicellular response that encompasses different cell types and spans different scales. Currently, we do not understand which factors determines lesion recovery. Failure of inflammation to resolve is a key underlying reason of poor regeneration, and one focus is therefore on the biology of microglia during de- and remyelination, and their cross talk to other cells, in particular oligodendrocytes and the progenitor cells. In addition, we are exploring the link between lipid metabolism and inflammation, and its role in the regulation of regeneration. I will report about our recent progress in our understanding of how microglia promote regeneration in the CNS.
Translation at the Synapse
Translation at the Synapse
The complex morphology of neurons, with synapses located hundreds of microns from the cell body, necessitates the localization of important cell biological machines, including ribosomes, within dendrites and axons. Local translation of mRNAs is important for the function and plasticity of synapses. Using advanced sequencing and imaging techniques we have updated our understanding of the local transcriptome and identified the local translatome- identifying over 800 transcripts for which local translation is the dominant source of protein. In addition, we have explored the unique mechanisms neurons use to meet protein demands at synapses, identifying surprising features of neuronal and synaptic protein synthesis.
Heterogeneity and non-random connectivity in reservoir computing
Reservoir computing is a promising framework to study cortical computation, as it is based on continuous, online processing and the requirements and operating principles are compatible with cortical circuit dynamics. However, the framework has issues that limit its scope as a generic model for cortical processing. The most obvious of these is that, in traditional models, learning is restricted to the output projections and takes place in a fully supervised manner. If such an output layer is interpreted at face value as downstream computation, this is biologically questionable. If it is interpreted merely as a demonstration that the network can accurately represent the information, this immediately raises the question of what would be biologically plausible mechanisms for transmitting the information represented by a reservoir and incorporating it in downstream computations. Another major issue is that we have as yet only modest insight into how the structural and dynamical features of a network influence its computational capacity, which is necessary not only for gaining an understanding of those features in biological brains, but also for exploiting reservoir computing as a neuromorphic application. In this talk, I will first demonstrate a method for quantifying the representational capacity of reservoirs without training them on tasks. Based on this technique, which allows systematic comparison of systems, I then present our recent work towards understanding the roles of heterogeneity and connectivity patterns in enhancing both the computational properties of a network and its ability to reliably transmit to downstream networks. Finally, I will give a brief taster of our current efforts to apply the reservoir computing framework to magnetic systems as an approach to neuromorphic computing.
Melatonin in the field: weekly, seasonal and light-dependent variations
Laboratory studies have shown that meaningful changes in light exposure lead to phase shifts in melatonin rhythm. In natural settings, however, light is a very complex signal. How melatonin responds to weekly- and seasonal-dependent variations in light exposure is still poorly understood. In this talk I will present results from a series of observational and intervention studies on the relationship between melatonin and light exposure in the field.
ISYNC: International SynAGE Conference on Healthy Ageing
The SynAGE committee members are thrilled to host ISYNC, the International SynAGE conference on healthy ageing, on 28-30 March 2022 in Magdeburg, Germany. This conference has been entirely organised from young scientists of the SynAGE research training group RTG 2413 (www.synage.de) and represents a unique occasion for researchers from all over the world to bring together and join great talks and sessions with us and our guests. A constantly updated list of our speakers can be found on the conference webpage: www.isync-md.de. During the conference, attendees will have access to a range of symposia which will deal with Glia, Biomarkers and Immunoresponses during ageing to neurodegeneration brain integrity and cognitive function in health and diseases. Moreover, the conference will offer social events especially for young researchers and the possibility to network together in a beautiful and suggestive location where our conference will take place: the Johanniskirche. The event will be happening in person, but due to the current pandemic situation and restrictions we are planning the conference as a hybrid event with lots of technical support to ensure that every participant can follow the talks and take part in the scientific discussions. The registration to our ISYNC conference is free of charge. However, the number of people attending the conference in person is restricted to 100. Afterwards, registrations will be accepted for joining virtually only. The registration is open until 15.02.2022. Especially for PhD and MD Students: Check our available Travel Grants, Poster Prize and SynAGE Award Dinner: https://www.isync-md.de/index.php/phd-md-specials/ If you need any further information don’t hesitate to contact us via email: contact@synage.de. We are looking forward to meet you in 2022 in Magdeburg to discuss about our research and ideas and bless together science. Your ISYNC organization Committee
Neural stem cells, human-specific genes, and neocortex expansion in development and human evolution
Attention to visual motion: shaping sensation into perception
Evolution has endowed primates, including humans, with a powerful visual system, seemingly providing us with a detailed perception of our surroundings. But in reality the underlying process is one of active filtering, enhancement and reshaping. For visual motion perception, the dorsal pathway in primate visual cortex and in particular area MT/V5 is considered to be of critical importance. Combining physiological and psychophysical approaches we have used the processing and perception of visual motion and area MT/V5 as a model for the interaction of sensory (bottom-up) signals with cognitive (top-down) modulatory influences that characterizes visual perception. Our findings document how this interaction enables visual cortex to actively generate a neural representation of the environment that combines the high-performance sensory periphery with selective modulatory influences for producing an “integrated saliency map’ of the environment.
How does a neuron decide when and where to make a synapse?
Precise synaptic connectivity is a prerequisite for the function of neural circuits, yet individual neurons, taken out of their developmental context, readily form unspecific synapses. How does genetically encoded brain wiring deal with this apparent contradiction? Brain wiring is a developmental growth process that is not only characterized by precision, but also flexibility and robustness. As in any other growth process, cellular interactions are restricted in space and time. Correspondingly, molecular and cellular interactions are restricted to those that 'get to see' each other during development. This seminar will explore the question how neurons decide when and where to make synapses using the Drosophila visual system as a model. New findings reveal that pattern formation during growth and the kinetics of live neuronal interactions restrict synapse formation and partner choice for neurons that are not otherwise prevented from making incorrect synapses in this system. For example, cell biological mechanisms like autophagy as well as developmental temperature restrict inappropriate partner choice through a process of kinetic exclusion that critically contributes to wiring specificity. The seminar will explore these and other neuronal strategies when and where to make synapses during developmental growth that contribute to precise, flexible and robust outcomes in brain wiring.
Keeping the balance- A role for the insular cortex in emotion homeostasis
Neuronal RNA signatures: Regulation and Function
Neurons are uniquely complex cells characterized by the expression of RNA sequences that are found in no other cell type: neuron-specific mRNA splice isoforms, circular RNAs, microRNAs, and ultra-long 3’UTRs. Although relatively little is known about how these neuronal RNA signatures control neuronal development and function, the importance of RNA-directed regulation in the brain is exemplified by its implication in neurological diseases. Our goal is to gain mechanistic and functional insight of the neuron-specific RNA landscape that drives neural function in health and disease.
Nonlinear spatial integration in retinal bipolar cells shapes the encoding of artificial and natural stimuli
Vision begins in the eye, and what the “retina tells the brain” is a major interest in visual neuroscience. To deduce what the retina encodes (“tells”), computational models are essential. The most important models in the retina currently aim to understand the responses of the retinal output neurons – the ganglion cells. Typically, these models make simplifying assumptions about the neurons in the retinal network upstream of ganglion cells. One important assumption is linear spatial integration. In this talk, I first define what it means for a neuron to be spatially linear or nonlinear and how we can experimentally measure these phenomena. Next, I introduce the neurons upstream to retinal ganglion cells, with focus on bipolar cells, which are the connecting elements between the photoreceptors (input to the retinal network) and the ganglion cells (output). This pivotal position makes bipolar cells an interesting target to study the assumption of linear spatial integration, yet due to their location buried in the middle of the retina it is challenging to measure their neural activity. Here, I present bipolar cell data where I ask whether the spatial linearity holds under artificial and natural visual stimuli. Through diverse analyses and computational models, I show that bipolar cells are more complex than previously thought and that they can already act as nonlinear processing elements at the level of their somatic membrane potential. Furthermore, through pharmacology and current measurements, I illustrate that the observed spatial nonlinearity arises at the excitatory inputs to bipolar cells. In the final part of my talk, I address the functional relevance of the nonlinearities in bipolar cells through combined recordings of bipolar and ganglion cells and I show that the nonlinearities in bipolar cells provide high spatial sensitivity to downstream ganglion cells. Overall, I demonstrate that simple linear assumptions do not always apply and more complex models are needed to describe what the retina “tells” the brain.
Brain circuit dynamics in Action and Sleep
Our group focuses on brain computation, physiology and evolution, with a particular focus on network dynamics, sleep (evolution and mechanistic underpinnings), cortical computation (through the study of ancestral cortices), and sensorimotor processing. This talk will describe our recent results on the remarkable camouflage behavior of cuttlefish (action) and on brain activity in REM and NonREM in lizards (sleep). Both topics will focus on aspects of circuit dynamics.
Brain circuit dynamics in Action and Sleep
Our group focuses on brain computation, physiology and evolution, with a particular focus on network dynamics, sleep (evolution and mechanistic underpinnings), cortical computation (through the study of ancestral cortices), and sensorimotor processing. This talk will describe our recent results on the remarkable camouflage behavior of cuttlefish (action) and on brain activity in REM and NonREM in lizards (sleep). Both topics will focus on aspects of circuit dynamics.
Spontaneous activity competes with externally evoked responses in sensory cortex
The interaction between spontaneously and externally evoked neuronal activity is fundamental for a functional brain. Increasing evidence suggests that bursts of high-power oscillations in the 15-30 Hz beta-band represent activation of resting state networks and can mask perception of external cues. Yet demonstration of the effect of beta power modulation on perception in real-time is missing, and little is known about the underlying mechanism. In this talk I will present the methods we developed to fill this gap together with our recent results. We used a closed-loop stimulus-intensity adjustment system based on online burst-occupancy analyses in rats involved in a forepaw vibrotactile detection task. We found that the masking influence of burst-occupancy on perception can be counterbalanced in real-time by adjusting the vibration amplitude. Offline analysis of firing-rates and local field potentials across cortical layers and frequency bands confirmed that beta-power in the somatosensory cortex anticorrelated with sensory evoked responses. Mechanistically, bursts in all bands were accompanied by transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction of firing-rate. Our closed loop approach reveals that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.
Homeostatic structural plasticity of neuronal connectivity triggered by optogenetic stimulation
Ever since Bliss and Lømo discovered the phenomenon of long-term potentiation (LTP) in rabbit dentate gyrus in the 1960s, Hebb’s rule—neurons that fire together wire together—gained popularity to explain learning and memory. Accumulating evidence, however, suggests that neural activity is homeostatically regulated. Homeostatic mechanisms are mostly interpreted to stabilize network dynamics. However, recent theoretical work has shown that linking the activity of a neuron to its connectivity within the network provides a robust alternative implementation of Hebb’s rule, although entirely based on negative feedback. In this setting, both natural and artificial stimulation of neurons can robustly trigger network rewiring. We used computational models of plastic networks to simulate the complex temporal dynamics of network rewiring in response to external stimuli. In parallel, we performed optogenetic stimulation experiments in the mouse anterior cingulate cortex (ACC) and subsequently analyzed the temporal profile of morphological changes in the stimulated tissue. Our results suggest that the new theoretical framework combining neural activity homeostasis and structural plasticity provides a consistent explanation of our experimental observations.
Clinical Outcome Assessments in Ataxias
Organization and Computation in Neural Circuits
Representation transfer and signal denoising through topographic modularity
To prevail in a dynamic and noisy environment, the brain must create reliable and meaningful representations from sensory inputs that are often ambiguous or corrupt. Since only information that permeates the cortical hierarchy can influence sensory perception and decision-making, it is critical that noisy external stimuli are encoded and propagated through different processing stages with minimal signal degradation. Here we hypothesize that stimulus-specific pathways akin to cortical topographic maps may provide the structural scaffold for such signal routing. We investigate whether the feature-specific pathways within such maps, characterized by the preservation of the relative organization of cells between distinct populations, can guide and route stimulus information throughout the system while retaining representational fidelity. We demonstrate that, in a large modular circuit of spiking neurons comprising multiple sub-networks, topographic projections are not only necessary for accurate propagation of stimulus representations, but can also help the system reduce sensory and intrinsic noise. Moreover, by regulating the effective connectivity and local E/I balance, modular topographic precision enables the system to gradually improve its internal representations and increase signal-to-noise ratio as the input signal passes through the network. Such a denoising function arises beyond a critical transition point in the sharpness of the feed-forward projections, and is characterized by the emergence of inhibition-dominated regimes where population responses along stimulated maps are amplified and others are weakened. Our results indicate that this is a generalizable and robust structural effect, largely independent of the underlying model specificities. Using mean-field approximations, we gain deeper insight into the mechanisms responsible for the qualitative changes in the system’s behavior and show that these depend only on the modular topographic connectivity and stimulus intensity. The general dynamical principle revealed by the theoretical predictions suggest that such a denoising property may be a universal, system-agnostic feature of topographic maps, and may lead to a wide range of behaviorally relevant regimes observed under various experimental conditions: maintaining stable representations of multiple stimuli across cortical circuits; amplifying certain features while suppressing others (winner-take-all circuits); and endow circuits with metastable dynamics (winnerless competition), assumed to be fundamental in a variety of tasks.
An optimal population code for global motion estimation in local direction-selective cells
Neuronal computations are matched to optimally encode the sensory information that is available and relevant for the animal. However, the physical distribution of sensory information is often shaped by the animal’s own behavior. One prominent example is the encoding of optic flow fields that are generated during self-motion of the animal and will therefore depend on the type of locomotion. How evolution has matched computational resources to the behavioral constraints of an animal is not known. Here we use in vivo two photon imaging to record from a population of >3.500 local-direction selective cells. Our data show that the local direction-selective T4/T5 neurons in Drosophila form a population code that is matched to represent optic flow fields generated during translational and rotational self-motion of the fly. This coding principle for optic flow is reminiscent to the population code of local direction-selective ganglion cells in the mouse retina, where four direction-selective ganglion cells encode four different axes of self-motion encountered during walking (Sabbah et al., 2017). However, in flies we find six different subtypes of T4 and T5 cells that, at the population level, represent six axes of self-motion of the fly. The four uniformly tuned T4/T5 subtypes described previously represent a local snapshot (Maisak et al. 2013). The encoding of six types of optic flow in the fly as compared to four types of optic flow in mice might be matched to the high degrees of freedom encountered during flight. Thus, a population code for optic flow appears to be a general coding principle of visual systems, resulting from convergent evolution, but matching the individual ethological constraints of the animal.
Fundamentals of PyTorch: Building a Model Step-by-Step
In this workshop you'll learn the fundamentals of PyTorch using an incremental, from-first-principles approach. We'll start with tensors, autograd, and the dynamic computation graph, and then move on to developing and training a simple model using PyTorch's model classes, datasets, data loaders, optimizers, and more. You should be comfortable using Python, Jupyter notebooks, Google Colab, Numpy and, preferably, object oriented programming.