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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.

Understanding the brain and its functions is achallenging undertaking. To facilitate this work, brain-inspiredtechnology may be used to examine cognitive phenomena to acertain extent, by replacing real biological brains with simulations.The aim of this project was to provide insights intohow different kinds of plasticity modulation affected long-termmemory recall through the use of a computational model. Aneural network was constructed based on the existing BayesianConfidence Propagation Neural Network (BCPNN) model andtrained with binary patterns representing memories acquiredover a lifetime. By varying network plasticity parameters forselected patterns and performing recall of “aging” memories,greater effects were observed in recall statistics for modulationearly in the lifetime in comparison with modulation of later ages.From the experiments conducted in this study it was possible toconclude that selective modulation of learning affected the longtermrecall of all memories in the simulation. / Att förstå hjärnan och alla dess funktionerär en stor utmaning. För att underlätta detta arbete kanhjärninspirerad teknologi i viss utsträckning användas för attstudera kognitiva fenomen, genom att ersätta biologiska hjärnormed simuleringar. Syftet med denna studie var att ge en insikt ihur olika typer av modulering av synaptisk plasticitet påverkadeett simulerat biologiskt långtidsminne genom användning av endatoriserad modell. Ett neuralt nätverk implementerat med eninlärningsregel av typen Bayesian Confidence Propagation NeuralNetwork (BCPNN) konstruerades och användes för att träna och återkalla binära mönster, representerande minnen förvärvadeunder en livstid. Nätverkets synaptiska plasticitet varierades underträning av utvalda mönster och därefter utfördes återkallningav “åldrade” minnen. Testerna påvisade effekt på nätverketsförmåga att korrekt återkalla lagrade minnen. Det visade sigäven att modulering utförd på tidiga simulerade åldrar jämförtmed modulering av senare åldrar under livstiden hade störrepåverkan på långtidsminnet. Från resultaten var det möjligtatt konstatera att selektiv plasticitetsmodulering under inlärningpåverkade nätverkets förmåga att korrekt återkalla samtligabinära mönster i simuleringen. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Research into the reminiscence bump aims to improve our understanding of how the memories formed during our adolescence and early adulthood subsequently influence our autobiographical recollections later in life. The purpose of this study was to investigate the temporal dynamics of autobiographical memory in a sample involving two different age groups of adult South African participants. The main objective of the research was to explore the participants’ memories for salient events and to determine whether these memories exhibit the typical reminiscence bump that has been found in autobiographical memory research. This sample consisted of two sets of cohorts, totalling 48 research participants. The first group comprised participants ranging between the ages of 40 and 59 years, and the second group involved participants ranging between the ages of 60 to 79 years. A convergent parallel mixed method approach was adopted in this study. Both quantitative and qualitative data, on the distribution, valence and life domain importance of the reminiscence bump, were collected through the lifeline interview method. The results confirmed that reminiscence bumps are reflected in the memories of both age groups between the ages of 10 and 30 years. Most life events recalled were of positive affect thus confirming the positivity bias in older adults. The family and home life domains were indicated as the most important life domains in the autobiographical memories of both groups. The main conclusion drawn from the study was that there was not a significant difference in the dynamics of the autobiographical memories between the two groups, as reflected in the temporal characteristics of their reminiscence bumps. Future research could further explore the patterns of memories, and researchers could in particular investigate the semantic and affective aspects of these autobiographical memories in more depth. / Psychology / M.A. (Psychology)