Graduate School of Systemic Neurosciences - Digitale Hochschulschriften der LMU

In this doctoral thesis, several aspects of information integration and learning in neural systems are investigated at the levels of single neurons, networks, and perception. In the first study presented here, we asked the question of how contextual, multiplicative interactions can be mediated in single neurons by the physiological mechanisms available in the brain. Multiplicative interactions are omnipresent in the nervous system and although a wealth of possible mechanisms were proposed over the last decades, the physiological origin of multiplicative interactions in the brain remains an open question. We investigated permissive gating as a possible multiplication mechanism. We proposed an integrate-and-fire model neuron that incorporates a permissive gating mechanism and investigated the model analytically and numerically due to its abilities to realize multiplication between two input streams. The applied gating mechanism realizes multiplicative interactions of firing rates on a wide range of parameters and thus provides a feasible model for the realization of multiplicative interactions on the single neuron level. In the second study we asked the question of how gaze-invariant representations of visual space can develop in a self-organizing network that incorporates the gating model neuron presented in the first study. To achieve a stable representation of our visual environment our brain needs to transform the representation of visual stimuli from a retina-centered coordinate system to a frame of reference that is independent of changes in gaze direction. In the network presented here, receptive fields and gain fields organized in overlayed topographic maps that reflected the spatio-temporal statistics of the training input stream. Topographic maps supported a gaze-invariant representation in an output layer when the network was trained with natural input statistics. Our results show that gaze-invariant representations of visual space can be learned in an unsupervised way by a biologically plausible network based on the spatio-temporal statistics of visual stimulation and eye position signals under natural viewing conditions. In the third study we investigated psychophysically the effect of a three day meditative Zen retreat on tactile abilities of the finger tips. Here, meditators strongly altered the statistics of their attentional focus by focussing sustained attention on their right index finger for hours. Our data shows that sustained sensory focussing on a particular body part, here the right index finger, significantly affects tactile acuity indicating that merely changing the statistics of the attentional focus without external stimulation or training can improve tactile acuity. In the view of activity-dependent plasticity that is outlined in this thesis, the main driving force for development and alterations of neural representations is nothing more than neural activity itself. Patterns of neural activity shape our brains during development and significant changes in the patterns of neural activity inevitably change mature neural representations. At the same time, the patterns of neural activity are formed by environmental sensory inputs as well as by contextual, multiplicative inputs like gaze-direction or by internally generated signals like the attentional focus. In this way, our environments as well as our inner mental states shape our neural representations and our perception at any time.

Most of the commonly used antidepressants block monoamine reuptake transporters to enhance serotonergic or noradrenergic neurotransmission. Effects besides or downstream of increased monoaminergic neurotransmission are poorly understood and yet presumably important for the drugs’ mode of action. In my PhD thesis I employed proteomics and metabolomics technologies combined with in silico analyses and identified cellular pathways affected by antidepressant drug treatment. DBA/2 mice were treated with paroxetine as a representative Selective Serotonin Reuptake Inhibitor (SSRI). Hippocampal protein levels were compared between chronic paroxetine- and vehicle-treated animals using in vivo 15N metabolic labeling combined with mass spectrometry. I also studied chronic changes in the hippocampus using unbiased metabolite profiling and the time course of metabolic changes with the help of a targeted polar metabolomics profiling platform. I identified profound alterations related to hippocampal energy metabolism. Glycolytic metabolite levels acutely increased while Krebs cycle metabolite levels decreased upon chronic treatment. Changes in energy metabolism were influenced by altered glycogen metabolism rather than by altered glycolytic or Krebs cycle enzyme levels. Increased energy levels were reflected by an increased ATP/ADP ratio and by increased ratios of high-to-low energy purines and pyrimidines. Paralleling the shift towards aerobic glycolysis upon paroxetine treatment I identified decreased levels of Krebs cycle and oxidative phosphorylation enzyme levels upon the antidepressant-like 15N isotope effect in high-anxiety behavior mice. In the course of my analyses I also identified GABA, galactose-6-phosphate and leucine as biomarker candidates for the assessment of chronic paroxetine treatment effects in the periphery and myo-inositol as biomarker candidate for an early assessment of chronic treatment effects. The identified antidepressant drug treatment affected molecular pathways and novel SSRI modes of action warrant consideration in antidepressant drug development efforts.