Exploring aspects of memory in healthy ageing and following stroke

Memory is critical for everyday functioning. Remembering an event with rich detail requires the ability to remember the temporal order of occurrences within the event and spatial locations associated with it. But it remains unclear whether it also requires memory for the perspective from which we encoded the event, whether these three aspects of memory are affected following stroke, and which are the key brain regions upon which they rely. These questions are explored in this thesis. In the first study presented here, I examined young and elderly healthy subjects with an autobiographical memory interview and a 2D spatial memory task assessing self-perspective, and found no correlation between performance on these tasks. In the second experimental study, by assessing stroke patients on a 3D spatio-temporal memory task, I found that damage to the right intraparietal sulcus was associated with poorer memory for temporal order. However, voxelwise analyses detected no association between parietal lobe regions and accuracy in the egocentric condition of this task, or between medial temporal lobe regions and accuracy in the allocentric condition, one possible reason being that performance was near ceiling. In the third experimental study, by assessing a considerably larger group of stroke patients on a spatial memory task, I found that, as a group, patients performed worse than healthy controls, and performance was correlated with an activities of daily living scale. A spatial memory network was identified in right (but not left) hemisphere stroke patients. These findings provide evidence that spatial memory impairment is common after stroke, highlight its potential functional relevance, and increase our understanding of which regions are critical for remembering temporal order and spatial information. Furthermore, they suggest a dissociation between the mechanisms underpinning recall of 2D scenes over relatively short intervals versus remembering of real-life events across periods of many years.Open Acces

Model-based testing for space-time interaction using point processes: An application to psychiatric hospital admissions in an urban area

Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space-time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic-epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space-time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007-2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases.Comment: 21 pages including 4 figures and 5 tables; methods are implemented in the R package surveillance (https://CRAN.R-project.org/package=surveillance

Rupture cascades in a discrete element model of a porous sedimentary rock

We investigate the scaling properties of the sources of crackling noise in a fully-dynamic numerical model of sedimentary rocks subject to uniaxial compression. The model is initiated by filling a cylindrical container with randomly-sized spherical particles which are then connected by breakable beams. Loading at a constant strain rate the cohesive elements fail and the resulting stress transfer produces sudden bursts of correlated failures, directly analogous to the sources of acoustic emissions in real experiments. The source size, energy, and duration can all be quantified for an individual event, and the population analyzed for their scaling properties, including the distribution of waiting times between consecutive events. Despite the non-stationary loading, the results are all characterized by power law distributions over a broad range of scales in agreement with experiments. As failure is approached temporal correlation of events emerge accompanied by spatial clustering.Comment: 5 pages, 4 figure

Nano-optomechanical measurement in the photon counting regime

Optically measuring in the photon counting regime is a recurrent challenge in modern physics and a guarantee to develop weakly invasive probes. Here we investigate this idea on a hybrid nano-optomechanical system composed of a nanowire hybridized to a single Nitrogen-Vacancy (NV) defect. The vibrations of the nanoresonator grant a spatial degree of freedom to the quantum emitter and the photon emission event can now vary in space and time. We investigate how the nanomotion is encoded on the detected photon statistics and explore their spatio-temporal correlation properties. This allows a quantitative measurement of the vibrations of the nanomechanical oscillator at unprecedentedly low light intensities in the photon counting regime when less than one photon is detected per oscillation period, where standard detectors are dark-noise-limited. These results have implications for probing weakly interacting nanoresonators, for low temperature experiments and for investigating single moving markers

Correlation-based Cross-layer Communication in Wireless Sensor Networks

Wireless sensor networks (WSN) are event based systems that rely on the collective effort of densely deployed sensor nodes continuously observing a physical phenomenon. The spatio-temporal correlation between the sensor observations and the cross-layer design advantages are significant and unique to the design of WSN. Due to the high density in the network topology, sensor observations are highly correlated in the space domain. Furthermore, the nature of the energy-radiating physical phenomenon constitutes the temporal correlation between each consecutive observation of a sensor node. This unique characteristic of WSN can be exploited through a cross-layer design of communication functionalities to improve energy efficiency of the network. In this thesis, several key elements are investigated to capture and exploit the correlation in the WSN for the realization of advanced efficient communication protocols. A theoretical framework is developed to capture the spatial and temporal correlations in WSN and to enable the development of efficient communication protocols. Based on this framework, spatial Correlation-based Collaborative Medium Access Control (CC-MAC) protocol is described, which exploits the spatial correlation in the WSN in order to achieve efficient medium access. Furthermore, the cross-layer module (XLM), which melts common protocol layer functionalities into a cross-layer module for resource-constrained sensor nodes, is developed. The cross-layer analysis of error control in WSN is then presented to enable a comprehensive comparison of error control schemes for WSN. Finally, the cross-layer packet size optimization framework is described.Ph.D.Committee Chair: Ian F. Akyildiz; Committee Member: Douglas M. Blough; Committee Member: Mostafa Ammar; Committee Member: Raghupathy Sivakumar; Committee Member: Ye (Geoffrey) L