Human capability to recall episodic memories depends on how much time has passed since the memory was encoded. This dependency is described by a memory retrieval curve that reflects an interesting phenomenon referred to as a reminiscence bump - a tendency for older people to recall more memories formed during their young adulthood than in other periods of life. This phenomenon can be modelled with an attractor neural network, for example, the firing-rate Bayesian Confidence Propagation Neural Network (BCPNN) with incremental learning. In this work, the mechanisms underlying the reminiscence bump in the neural network model are systematically studied. The effects of synaptic plasticity, network architecture and other relevant parameters on the characteristics of the reminiscence bump are systematically investigated. The most influential factors turn out to be the magnitude of dopamine-linked plasticity at birth and the time constant of exponential plasticity decay with age that set the position of the bump. The other parameters mainly influence the general amplitude of the lifespan retrieval curve. Furthermore, the recency phenomenon, i.e. the tendency to remember the most recent memories, can also be parameterized by adding a constant to the exponentially decaying plasticity function representing the decrease in the level of dopamine neurotransmitters. / Människans förmåga att återkalla episodiska minnen beror på hur lång tid som gått sedan minnena inkodades. Detta beroende beskrivs av en sk glömskekurva vilken uppvisar ett intressant fenomen som kallas ”reminiscence bump”. Detta är en tendens hos äldre att återkalla fler minnen från ungdoms- och tidiga vuxenår än från andra perioder i livet. Detta fenomen kan modelleras med ett neuralt nätverk, sk attraktornät, t ex ett icke spikande Bayesian Confidence Propagation Neural Network (BCPNN) med inkrementell inlärning. I detta arbete studeras systematiskt mekanismerna bakom ”reminiscence bump” med hjälp av denna neuronnätsmodell. Exempelvis belyses betydelsen av synaptisk plasticitet, nätverksarkitektur och andra relavanta parameterar för uppkomsten av och karaktären hos detta fenomen. De mest inflytelserika faktorerna för bumpens position befanns var initial dopaminberoende plasticitet vid födseln samt tidskonstanten för plasticitetens avtagande med åldern. De andra parametrarna påverkade huvudsakligen den generella amplituden hos kurvan för ihågkomst under livet. Dessutom kan den s k nysseffekten (”recency effect”), dvs tendensen att bäst komma ihåg saker som hänt nyligen, också parametriseras av en konstant adderad till den annars exponentiellt avtagande plasticiteten, som kan representera densiteten av dopaminreceptorer.

The aim of this study was to examine the validity and feasibility of sentence transcription testing (STT) for the purpose of examining the interplay between verbal working memory and central processing. The general area of interest is to understand working memory as a dynamic system that involves the management and integration of information from several temporal distances. Due to the world-wide conditions at the time this study was conducted (2020), the testing was online and computerized, which severely limited the controllability of the procedure leading to a high amount of exclusions and dubious results. The testing of 17 subjects, 9 females, 8 males with the average age of 30.5 (SD = 9.5) yielded mixed results, excluding gender, impulsivity and age as likely factors for the variance. Following these results, a post hoc analysis was added to interpret if transcription data has validity as a tool for observing effects of interference on memory recall and the task at hand. This analysis did reveal patterns that reinforce the view of language processing as a multimodal task. The type of errors seems to follow tendencies of primacy, recency and availability, as well as proactive and retroactive interference. These tendencies of memory recall seem to work in unison or is a manifestation of syntactic, lexical, and presumably semantic processing and can be used to measure individual differences in language processing and the tendency to linguistically “fill in the gaps”. The variation seen within the sample does make transcription testing appealing for further studies. The main variance within the sample can be described as replacing words with other previously attended to information, and or forgetting words during transcription. These tendencies, might reveal properties about the interaction between executive function (EF) and verbal working memory (V-WM) as a source of individual difference. However, more validation studies are proposed for weaving out factors that might skew the results in this type of testing and modelling.

This master thesis deals with design and implementation of betting agent. It covers issues such as theoretical background of an online betting, probability and statistics. In its first part it is focused on data mining and explains the principle of knowledge mining form data warehouses and certain methods suitable for different types of tasks. Second, it is concerned with neural networks and algorithm of back-propagation. All the findings are demonstrated on and supported by graphs and histograms of data analysis, made via SAS Enterprise Miner program. In conclusion, the thesis summarizes all the results and offers specific methods of extension of the agent.