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This thesis investigates the development of early cognition in infancy using neural network models. Fundamental events in visual perception such as caused motion, occlusion, object permanence, tracking of moving objects behind occluders, object unity perception and sequence learning are modeled in a unifying computational framework while staying close to experimental data in developmental psychology of infancy. In the first project, the development of causality and occlusion perception in infancy is modeled using a simple, three-layered, recurrent network trained with error backpropagation to predict future inputs (Elman network). The model unifies two infant studies on causality and occlusion perception. Subsequently, in the second project, the established framework is extended to a larger prediction network that models the development of object unity, object permanence and occlusion perception in infancy. It is shown that these different phenomena can be unified into a single theoretical framework thereby explaining experimental data from 14 infant studies. The framework shows that these developmental phenomena can be explained by accurately representing and predicting statistical regularities in the visual environment. The models assume (1) different neuronal populations processing different motion directions of visual stimuli in the visual cortex of the newborn infant which are supported by neuroscientific evidence and (2) available learning algorithms that are guided by the goal of predicting future events. Specifically, the models demonstrate that no innate force notions, motion analysis modules, common motion detectors, specific perceptual rules or abilities to "reason" about entities which have been widely postulated in the developmental literature are necessary for the explanation of the discussed phenomena. Since the prediction of future events turned out to be fruitful for theoretical explanation of various developmental phenomena and a guideline for learning in infancy, the third model addresses the development of visual expectations themselves. A self-organising, fully recurrent neural network model that forms internal representations of input sequences and maps them onto eye movements is proposed. The reinforcement learning architecture (RLA) of the model learns to perform anticipatory eye movements as observed in a range of infant studies. The model suggests that the goal of maximizing the looking time at interesting stimuli guides infants' looking behavior thereby explaining the occurrence and development of anticipatory eye movements and reaction times. In contrast to classical neural network modelling approaches in the developmental literature, the model uses local learning rules and contains several biologically plausible elements like excitatory and inhibitory spiking neurons, spike-timing dependent plasticity (STDP), intrinsic plasticity (IP) and synaptic scaling. It is also novel from the technical point of view as it uses a dynamic recurrent reservoir shaped by various plasticity mechanisms and combines it with reinforcement learning. The model accounts for twelve experimental studies and predicts among others anticipatory behavior for arbitrary sequences and facilitated reacquisition of already learned sequences. All models emphasize the development of the perception of the discussed phenomena thereby addressing the questions of how and why this developmental change takes place - questions that are difficult to be assessed experimentally. Despite the diversity of the discussed phenomena all three projects rely on the same principle: the prediction of future events. This principle suggests that cognitive development in infancy may largely be guided by building internal models and representations of the visual environment and using those models to predict its future development.
Deferred imitations assess declarative memory in infants. Many cross-sectional and a few longitudinal studies revealed that, with development, infants learn faster,and retain more target actions over longer retention intervals. Longitudinal stabilities are modest and increase through the second year. To date, there are only few multivariate deferred imitation studies pointing to interactions between declarative memory, language and self-development. However, as these studies applied variable-centered data analysis approaches, the individual stance was not taken into account.Therefore, the present dissertation focuses on the explanation of inter-individual differences of deferred imitation through the second year. In the multivariate, longitudinal Frankfurt Memory Study (FRAMES), declarative memory (deferred imitation), non-declarative memory (train task), as well as cognitive, language, motor, social, emotional and body self-awareness development (Developmental Test for 6-month- to 6-year-olds, ET6-6) were assessed on three measurement occasions (12-, 18- and 24-month-olds). From a psychometric perspective, sound tests for the assessment of deferred imitation in the respective age groups were developed (Paper 1 & 2). Reliability analyses (Paper 3) indicated relatively high short-term-stability for the deferred imitation test (12-month-olds). The co-development of declarative and nondeclarative memory in 12- and 18-month-olds provided evidence for discriminative validity (Paper 4). Longitudinally, deferred imitation performance tremendously increased throughout the second year, and performance was moderately stable between 12 and 18 months and stability increased between 18 and 24 months. Using a person-centered analysis approach (relative difference scores; cluster analysis), developmental subgroups were extracted out of the total sample. These groups differed in terms of mean growth and stability. However, between the first and second measurement occasion, the groups did not differ with respect to motor, cognitive and language development (Paper 5). Using the data of three measurement occasions, subgroups were extracted showing significant differences with respect to language, motor and body self-awareness development (Paper 6). The results are discussed against the background of infancy development theories.