Interacting bosons and fermions in three-dimensional optical lattice potentials

This thesis reports on the realization, characterization and analysis of ultracold bosonic and fermionic atoms in three-dimensional optical lattice potentials. Ultracold quantum gases in optical lattices can be regarded as ideal model systems to investigate quantum many-body physics. In this work interacting ensembles of bosonic 87Rb and fermionic 40K atoms are employed to study equilibrium phases and nonequilibrium dynamics. The investigations are enabled by a versatile experimental setup, whose core feature is a blue-detuned optical lattice that is combined with Feshbach resonances and a red-detuned dipole trap to allow for independent control of tunneling, interactions and external confinement. The Fermi-Hubbard model, which plays a central role in the theoretical description of strongly correlated electrons, is experimentally realized by loading interacting fermionic spin mixtures into the optical lattice. Using phase-contrast imaging the in-situ size of the atomic density distribution is measured, which allows to extract the global compressibility of the many-body state as a function of interaction and external confinement. Thereby, metallic and insulating phases are clearly identified. At strongly repulsive interaction, a vanishing compressibility and suppression of doubly occupied lattice sites signal the emergence of a fermionic Mott insulator. In a second series of experiments interaction effects in bosonic lattice quantum gases are analyzed. Typically, interactions between microscopic particles are described as two-body interactions. As such they are also contained in the single-band Bose-Hubbard model. However, our measurements demonstrate the presence of multi-body interactions that effectively emerge via virtual transitions of atoms to higher lattice bands. These findings are enabled by the development of a novel atom optical measurement technique: In quantum phase revival spectroscopy periodic collapse and revival dynamics of the bosonic matter wave field are induced. The frequencies of the dynamics are directly related to the on-site interaction energies of atomic Fock states and can be read out with high precision. The third part of this work deals with mixtures of bosons and fermions in optical lattices, in which the interspecies interactions are accurately controlled by means of a Feshbach resonance. Studies of the equilibrium phases show that the bosonic superfluid to Mott insulator transition is shifted towards lower lattice depths when bosons and fermions interact attractively. This observation is further analyzed by applying quantum phase revival spectroscopy to few-body systems consisting of a single fermion and a coherent bosonic field on individual lattice sites. In addition to the direct measurement of Bose-Fermi interaction energies, Bose-Bose interactions are proven to be modified by the presence of a fermion. This renormalization of bosonic interaction energies can explain the shift of the Mott insulator transition. The experiments of this thesis lay important foundations for future studies of quantum magnetism with fermionic spin mixtures as well as for the realization of complex quantum phases with Bose-Fermi mixtures. They furthermore point towards physics that reaches beyond the single-band Hubbard model.

Simulating event related potentials in tasks involving conflict resolution: a neural network

In this thesis, the main Executive Control theories are exposed. Methods typical of Cognitive and Computational Neuroscience are introduced and the role of behavioural tasks involving conflict resolution in the response elaboration, after the presentation of a stimulus to the subject, are highlighted. In particular, the Eriksen Flanker Task and its variants are discussed. Behavioural data, from scientific literature, are illustrated in terms of response times and error rates. During experimental behavioural tasks, EEG is registered simultaneously. Thanks to this, event related potential, related with the current task, can be studied. Different theories regarding relevant event related potential in this field - such as N2, fERN (feedback Error Related Negativity) and ERN (Error Related Negativity) – are introduced. The aim of this thesis is to understand and simulate processes regarding Executive Control, including performance improvement, error detection mechanisms, post error adjustments and the role of selective attention, with the help of an original neural network model. The network described here has been built with the purpose to simulate behavioural results of a four choice Eriksen Flanker Task. Model results show that the neural network can simulate response times, error rates and event related potentials quite well. Finally, results are compared with behavioural data and discussed in light of the mentioned Executive Control theories. Future perspective for this new model are outlined.

Velocity recovery cycles of human muscle action potentials in chronic renal failure

To test the hypothesis that muscle fibers are depolarized in patients with chronic renal failure, by measuring velocity recovery cycles of muscle action potentials as indicators of muscle membrane potential.

A method to measure the distribution of latencies of motor evoked potentials in man

To measure the intra-individual distribution of the latencies of motor evoked potentials (MepL) using transcranial magnetic stimulation.

Sleep restriction attenuates amplitudes and attentional modulation of pain-related evoked potentials, but augments pain ratings in healthy volunteers

The experiment investigated the impact of sleep restriction on pain perception and related evoked potential correlates (laser-evoked potentials, LEPs). Ten healthy subjects with good sleep quality were investigated in the morning twice, once after habitual sleep and once after partial sleep restriction. Additionally, we studied the impact of attentional focussing on pain and LEPs by directing attention to (intensity discrimination) or away from the stimulus (mental arithmetic). Laser stimuli directed to the hand dorsum were rated as 30% more painful after sleep restriction (49+/-7 mm) than after a night of habitual sleep (38+/-7 mm). A significant interaction between attentional focus and sleep condition suggested that attentional focusing was less distinctive under sleep restriction. Intensity discrimination was preserved. In contrast, the amplitude of the early parasylvian N1 of LEPs was significantly smaller after a night of partial sleep restriction (-36%, p<0.05). Likewise, the amplitude of the vertex N2-P2 was significantly reduced (-34%, p<0.01); also attentional modulation of the N2-P2 was reduced. Thus, objective (LEPs) and subjective (pain ratings) parameters of nociceptive processing were differentially modulated by partial sleep restriction. We propose, that sleep reduction leads to an impairment of activation in the ascending pathway (leading to reduced LEPs). In contradistinction, pain perception was boosted, which we attribute to lack of pain control distinct from classical descending inhibition, and thus not affecting the projection pathway. Sleep-restricted subjects exhibit reduced attentional modulation of pain stimuli and may thus have difficulties to readily attend to or disengage from pain.

Velocity recovery cycles of human muscle action potentials: Repeatability and variability

Velocity recovery cycles (VRCs) of human muscle action potentials have been proposed as a new technique for assessing muscle membrane function in myopathies. This study was undertaken to determine the variability and repeatability of VRC measures such as supernormality, to help guide future clinical use of the method.

Microneurography in rats: a minimally invasive method to record single C-fiber action potentials from peripheral nerves in vivo

Microneurography is a method suitable for recording intraneural single or multiunit action potentials in conscious subjects. Microneurography has rarely been applied to animal experiments, where more invasive methods, like the teased fiber recording technique, are widely used. We have tested the feasibility of microneurographic recordings from the peripheral nerves of rats. Tungsten microelectrodes were inserted into the sciatic nerve at mid-thigh level. Single or multiunit action potentials evoked by regular electrical stimulation were recorded, digitized and displayed as a raster plot of latencies. The method allows unambiguous recording and recognition of single C-fiber action potentials from an in vivo preparation, with minimal disruption of the nerve being recorded. Multiple C-fibers can be recorded simultaneously for several hours, and if the animal is allowed to recover, repeated recording sessions can be obtained from the same nerve at the same level over a period of weeks or months. Also, single C units can be functionally identified by their changes in latency to natural stimuli, and insensitive units can be recognized as 'silent' nociceptors or sympathetic efferents by their distinctive profiles of activity-dependent slowing during repetitive electrical stimulation, or by the effect on spontaneous efferent activity of a proximal anesthetic block. Moreover, information about the biophysical properties of C axons can be obtained from their latency recovery cycles. Finally, we show that this preparation is potentially suitable for the study of C-fiber behavior in models of neuropathies and nerve lesions, both under resting conditions and in response to drug administration.

Femur Specific Polyaffine Model to Regularize the Log-Domain Demons Registration

Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.

Geometry-Aware Multiscale Image Registration via OBBTree-Based Polyaffine Log-Demons

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

Managing a World Heritage Site: Potentials and limitations of transdisciplinary approaches

Balancing the frequently conflicting priorities of conservation and economic development poses a challenge to management of the Swiss Alps Jungfrau- Aletsch World Heritage Site (WHS). This is a complex societal problem that calls for a knowledge-based solution. This in turn requires a transdisciplinary research framework in which problems are defined and solved cooperatively by actors from the scientific community and the life-world. In this article we re-examine studies carried out in the region of the Swiss Alps Jungfrau-Aletsch WHS, covering three key issues prevalent in transdisciplinary settings: integration of stakeholders into participatory processes; perceptions and positions; and negotiability and implementation. In the case of the Swiss Alps Jungfrau-Aletsch WHS the transdisciplinary setting created a situation of mutual learning among stakeholders from different levels and backgrounds. However, the studies showed that the benefits of such processes of mutual learning are continuously at risk of being diminished by the power play inherent in participatory approaches.

The importance of ship log data: reconstructing North Atlantic, European and Mediterranean sea level pressure fields back to 1750

Local to regional climate anomalies are to a large extent determined by the state of the atmospheric circulation. The knowledge of large-scale sea level pressure (SLP) variations in former times is therefore crucial when addressing past climate changes across Europe and the Mediterranean. However, currently available SLP reconstructions lack data from the ocean, particularly in the pre-1850 period. Here we present a new statistically-derived 5° × 5° resolved gridded seasonal SLP dataset covering the eastern North Atlantic, Europe and the Mediterranean area (40°W–50°E; 20°N–70°N) back to 1750 using terrestrial instrumental pressure series and marine wind information from ship logbooks. For the period 1750–1850, the new SLP reconstruction provides a more accurate representation of the strength of the winter westerlies as well as the location and variability of the Azores High than currently available multiproxy pressure field reconstructions. These findings strongly support the potential of ship logbooks as an important source to determine past circulation variations especially for the pre-1850 period. This new dataset can be further used for dynamical studies relating large-scale atmospheric circulation to temperature and precipitation variability over the Mediterranean and Eurasia, for the comparison with outputs from GCMs as well as for detection and attribution studies.