The role of the dentate gyrus and adult neurogenesis in hippocampal-basal ganglia associated behaviour

The ability of the brain to continually generate new neurons throughout life is one of the most intensely researched areas of modern neuroscience. While great advancements in understanding the biochemical mechanisms of adult neurogenesis have been made, there remain significant obstacles and gaps in connecting neurogenesis with behavioural and cognitive processes such as learning and memory. The purpose of the thesis was to examine by review and laboratory experimentation the role of the dentate gyrus and of adult neurogenesis within the hippocampus in the performance of cognitive tasks dependent on the hippocampal formation and hippocampal-basal ganglia interactions. Advancement in understanding the role of neurogenesis in these processes may assist in improving treatments for common brain injury and cognitive diseases that affect this region of the brain. Mild chronic stress reduced the acquisition rate of a stimulus-response task (p=0.043), but facilitated the acquisition of a discrimination between a small and a large reward (p=0.027). In locomotor activity assays, chronic stress did not shift the dose-response to methamphetamine. Analysis of 2,5-bromodeoxyuridine incorporation showed that, overall, chronic mild stress did not effect survival of neuronal progenitors . However, learning of the tasks had a positive influence on cell survival in stressed animals (p=0.038). Microinjections of colchicine produced significant lesions of the dentate gyrus and surrounding CA1-CA3 and neocortex. Damage to these regions impaired hippocampal-dependent reference memory (p=0.054) while preserving hippocampal independent simple discrimination learning. In a delay discounting procedure, the lesions did not induce impulsive-like behaviour when delay associated with a large reward was introduced. The experiments uphold a current theory that learning acts as a buffer to mitigate the negative effects of stress on neurogenesis

Significance-aware filtering for nonlinear acoustic echo cancellation

This article summarizes and extends the recently proposed concept of Significance-Aware (SA) filtering for nonlinear acoustic echo cancellation. The core idea of SA filtering is to decompose the estimation of the nonlinear echo path into beneficially interacting subsystems, each of which can be adapted with high computational efficiency. The previously proposed SA Hammerstein Group Models (SA-HGMs) decompose the nonlinear acoustic echo path into a direct-path part, modeled by a Hammerstein Group Model (HGM) and a complementary part, modeled by a very efficient Hammerstein model. In this article, we furthermore propose a novel Equalization-based SA (ESA) structure, where the echo path is equalized by a linear filter to allow for an estimation of the loudspeaker nonlinearities by very small and efficient models. Additionally, we provide a novel in-depth analysis of the computational complexity of the previously proposed SA and the novel ESA filters and compare both SA filtering approaches to each other, to adaptive HGMs, and to linear filters, where fast partitioned-block frequency-domain realizations of the competing filter structures are considered. Finally, the echo reduction performance of the proposed SA filtering approaches is verified using real recordings from a commercially available smartphone. Beyond the scope of previous publications on SA-HGMs, the ability of the SA filters to generalize for double-talk situations is explicitly considered as well. The low complexity as well as the good echo reduction performance of both SA filters illustrate the potential of SA filtering in practice