ERC FUNDED PROJECTS

4D reconstruction, the camera-based dense dynamic scene reconstruction, is a grand challenge in computer graphics and computer vision. Despite great progress, 4D capturing the complex, diverse real world outside a studio is still far from feasible. 4DRepLy builds a new generation of high-fidelity 4D reconstruction (4DRecon) methods. They will be the first to efficiently capture all types of deformable objects (humans and other types) in crowded real world scenes with a single color or depth camera. They capture space-time coherent deforming geometry, motion, high-frequency reflectance and illumination at unprecedented detail, and will be the first to handle difficult occlusions, topology changes and large groups of interacting objects. They automatically adapt to new scene types, yet deliver models with meaningful, interpretable parameters. This requires far reaching contributions: First, we develop groundbreaking new plasticity-enhanced model-based 4D reconstruction methods that automatically adapt to new scenes. Second, we develop radically new machine learning-based dense 4D reconstruction methods. Third, these model- and learning-based methods are combined in two revolutionary new classes of 4DRecon methods: 1) advanced fusion-based methods and 2) methods with deep architectural integration. Both, 1) and 2), are automatically designed in the 4D Real World Reconstruction Loop, a revolutionary new design paradigm in which 4DRecon methods refine and adapt themselves while continuously processing unlabeled real world input. This overcomes the previously unbreakable scalability barrier to real world scene diversity, complexity and generality. This paradigm shift opens up a new research direction in graphics and vision and has far reaching relevance across many scientific fields. It enables new applications of profound social pervasion and significant economic impact, e.g., for visual media and virtual/augmented reality, and for future autonomous and robotic systems.

1 977 000 €

Start date: 2018-09-01, End date: 2023-08-31

Mammalian organisms possess the remarkable ability to maintain internal body temperature (Tcore) within a narrow range close to 37°C despite wide environmental temperature variations. The brain’s neural “thermostat” is made up by central circuits in the hypothalamic preoptic area (POA), which orchestrate peripheral thermoregulatory responses to maintain Tcore. Thermogenesis requires metabolic fuel, suggesting intricate connections between the thermoregulatory centre and hypothalamic circuits controlling energy balance. How the POA detects and integrates temperature and metabolic information to achieve thermal balance is largely unknown. A major question is whether this circuitry could be harnessed therapeutically to treat obesity. We have recently identified the first known molecular temperature sensor in thermoregulatory neurons of the POA, transient receptor potential melastatin 2 (TRPM2), a thermo-sensitive ion channel. I aim to use TRPM2 as a molecular marker to gain access to and probe the function of thermoregulatory neurons in vivo. I propose a multidisciplinary approach, combining local, in vivo POA temperature stimulation with optogenetic circuit-mapping to uncover the molecular and cellular logic of the hypothalamic thermoregulatory centre and to assess its medical potential to counteract metabolic syndrome. Acclimation is a beneficial adaptive process that fortifies thermal responses upon environmental temperature challenges. Thermoregulatory neuron plasticity is thought to mediate acclimation. Conversely, maladaptive thermoregulatory changes affect obesity. The cell-type-specific neuronal plasticity mechanisms underlying these changes within the POA, however, are unknown. Using ex-vivo slice electrophysiology and in vivo imaging, I propose to characterize acclimation- and obesity-induced plasticity of thermoregulatory neurons. Ultimately, I aim to manipulate thermoregulatory neuron plasticity to test its potential counter-balancing effect on obesity.

1 902 500 €

Start date: 2018-09-01, End date: 2023-08-31

Sensory perception involves the discrimination and binding of multiple modalities of sensory input. This is especially evident in the somatosensory system where different modalities of sensory input, including thermal and mechanosensory, are combined to generate a unified percept. The neural mechanisms of multisensory binding are unknown, in part because sensory perception is typically studied within a single modality in a single brain region. I propose a multi-level approach to investigate thermo-tactile processing in the mouse forepaw system from the primary sensory afferent neurons to thalamo-cortical circuits and behaviour. The mouse forepaw system is the ideal system to investigate multisensory binding as the sensory afferent neurons are well investigated, cell type-specific lines are available, in vivo optogenetic manipulation is possible both in sensory afferent neurons and central circuits and we have developed high-resolution somatosensory perception behaviours. We have previously shown that mouse primary somatosensory forepaw cortical neurons respond to both tactile and thermal stimuli and are required for non-noxious cooling perception. With multimodal neurons how, then, is it possible to both discriminate and bind thermal and tactile stimuli? I propose 3 objectives to address this question. We will first, perform functional mapping of the thermal and tactile pathways to cortex; second, investigate the neural mechanisms of thermo-tactile discrimination in behaving mice; and third, compare neural processing during two thermo-tactile binding tasks, the first using passively applied stimuli, and the second, active manipulation of thermal objects. At each stage we will perform cell type-specific neural recordings and causal optogenetic manipulations in awake and behaving mice. Our multi-level approach will provide a comprehensive investigation into how the brain performs multisensory perceptual binding: a fundamental yet unsolved problem in neuroscience.

1 999 877 €

Start date: 2016-09-01, End date: 2021-08-31

The goal of this project is to demonstrate that novel aspects of the molecular basis of Darwinian adaptation can be discovered if the polygenic basis of adaptation is taken into account. This project will use the genome-wide distribution of cis-regulatory variants to discover the molecular pathways that are optimized during adaptation via accumulation of small effect mutations. Current approaches include scans for outlier genes with strong population genetics signatures of selection, or large effect QTL associating with fitness. They can only reveal a small subset of the molecular changes recruited along adaptive paths. Here, instead, the distribution of small effect mutations will be used to make inferences on the targets of polygenic adaptation across divergent populations in each of the two closely related species, A. thaliana and A. lyrata. These species are both found at diverse latitudes and show sign of local adaptation to climatic differences. Mutations affecting cis-regulation will be identified in leaves of plants exposed to various temperature regimes triggering phenotypic responses of adaptive relevance. Their distribution in clusters of functionally connected genes will be quantified. The phylogeographic differences in the distribution of the mutations will be used to disentangle neutral from adaptive clusters of functionally connected genes in each of the two species. This project will identify the molecular pathways subjected collectively to natural selection and provide a completely novel view on adaptive landscapes. It will further examine whether local adaptation occurs by convergent evolution of molecular systems in plants. This approach has the potential to find broad applications in ecology and agriculture.

1 683 120 €

Start date: 2015-09-01, End date: 2021-02-28