Graduate School of Systemic Neurosciences - Digitale Hochschulschriften der LMU Archiv

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.

Age-related cognitive decline has been linked to a reduction in attentional resources that are assumed to result from alterations in the aging brain. A core ability that is subject to age-related decline is visual attention, which enables individuals to select the most important information for conscious processing and action. However, visual attention is considered a conglomerate of various functions and the specific components underlying age differences in performance remain little understood. The present PhD project aimed at dissociating age effects on several (sub-) components that concur in visual attention tasks within a neurocognitive approach. Established and theoretically grounded psychological paradigms that allow separating various attentional components were combined with event-related potentials (ERPs), which provide a temporally fine-graded dissociation of cognitive processes involved in a task. 1st Project The first project was designed to determine the origin(s) of age-related decline in visual search, a key paradigm of attention research. To pursue this goal on a micro-level, response time measures in a compound-search task, in which the target-defining feature of a pop-out target (color/shape) was dissociated from the response-defining feature (orientation), were coupled with lateralized ERPs. Several ERP components tracked the timing of processing stages involved in this task, these being (1) allocation of attention to the target, marked by the posterior-contralateral negativity (PCN), (2) target analyses in vSTM, marked by the sustained posterior-contralateral negativity (SPCN), (3) response selection, marked by the stimulus-locked lateralized readiness potential (LRP) and (4) response execution, marked by the response-locked LRP. Slowed response times (RT) in older participants were associated with age differences in all analyzed ERPs, indicating that behavioural slowing accrues across multiple stages within the information processing stream. Furthermore, v behavioral data and ERPs were analyzed with respect to age and carry-over effects from one trial to the next. The intertrial analyses revealed relatively automatic processes – such as dimension weighting facilitating the early stage of visual selection, and response weighting facilitating the late stage of response execution – to be preserved in older age. By contrast, more controlled processes – such as the flexible stimulus-response (S-R) (re-) mapping across trials on the intermediate stages of response selection - were particularly affected by aging. This indicates that besides general slowing, specific age decrements in executively controlled processes contribute to age-related decline in visual search. 2nd Project The second project explored neural markers of individual and age differences in attention parameters formally integrated in Bundesen’s computational Theory of Visual Attention (TVA). According to the model, two parameters of general visual attention capacity, perceptual processing speed C and visual short-term memory (vSTM) storage capacity K are defined and can be modeled mathematically independently for a particular individual. More recently, the neural interpretation of the model (NTVA) suggested that the two functions (at least partly) rely on distinct brain mechanisms. To test this assumption in an empirical approach, individual TVA-based estimates were derived in a standard TVA whole report task, and ERPs of the same participants were recorded in an adapted EEG-compatible version of the task. In the first study of the second project, we explored neurophysiological markers of interindividual differences in the two functions in younger participants. The results revealed distinct ERP correlates to be related to the parameters: Individuals with higher compared to lower processing speed C had significantly smaller posterior N1 amplitudes, suggesting that the rate of object categorization is associated with the efficiency of early visual processing. Individuals with higher compared to lower storage capacity showed stronger contralateral delay activity (CDA) over visual areas, indicating that the limit of vi vSTM relies on topographically-organized sustained activation within the visual system. These results can be regarded as direct neuroscientific evidence for central assumptions of the theoretical framework. In the second study of the second project, the same approach was pursued to investigate whether and how TVA attentional capacity parameters and their neural markers change with aging. First, the same ERP correlates of processing speed and storage capacity indexing individual differences in younger participants (i.e., the posterior N1 marked differences in processing speed C and the CDA marked differences in storage capacity K, respectively) were found to be valid also in the older group. In addition to this, two further components marked performance differences in the parameters exclusively within the older group: Older participants with lower processing speed showed smaller anterior N1 amplitudes relative to faster older and all younger participants, suggesting a selective loss of resources supporting early control of attentional guidance. Older participants with higher storage capacity exhibited a stronger right-central positivity than older participants with lower storage capacity and all younger participants. This pattern is indicative of compensatory recruitment of additional neural resources in high-functioning older individuals, presumably related to enhanced executive control fostering sustained activation of vSTM representations. Again, these findings strongly support the NTVA framework, proposing distinct neural mechanisms underlying processing speed and storage capacity. Furthermore, they show that distinct mechanisms of attentional control determine the two functions in older age.

Anyone who has climbed a mountain before knows that the perceived distance walked depends on more than just its physical length. This intriguing relationship between physical and experienced magnitudes has fascinated researchers across various disciplines for more than 200 years. Part of the enthusiasm is driven by the fact that, although magnitudes, as well as the sensory organs with which we measure them, differ in so many ways, there are unifying principles in behavior common to all types of magnitudes estimated. In this thesis, the general characteristics of human magnitude estimation are studied in the case of visual path integration. The aim is to clarify the role of a-priori knowledge on the estimate of magnitude and to provide a unifying mathematical framework that explains the behavior. In particular, we investigated human linear and angular displacement estimation in different experimental situations with varying experience-dependent and abstract a-priori knowledge. We find systematic behavioral characteristics that are omnipresent in magnitude estimation studies, like the range effect, the regression effect or scalar variability. These characteristics are explained by a general model that combines a logarithmic scaling of magnitudes according to the Weber-Fechner law with the concept of Bayesian inference. The model incorporates apriori knowledge about the stimulus and updates this knowledge on a trial-by-trial basis. The resulting iterative Bayesian estimation accounts for the aforementioned behavioral characteristics and provides a link between the two most well-known laws in psychophysics: the Weber-Fechner and Stevens’ powerlaw. This work provides substantial evidence that magnitude estimation is not purely driven by sensation but underlies perceptual estimation processes that exploit and incorporate different types of information sources, in particular short-term prior experience. The proposed mathematical framework is likely applicable to magnitude estimation across different modalities and consequently contributes to a unifying account of the behavior.

The visual and vestibular systems play one of the central roles in the perception of verticality, spatial orientation, maintenance of balance and distinguishing self-motion from motion of the environment. As the brain continuously and simultaneously receives an enormous quantity of information through their receptor organs, collaboration between these systems at different levels of information processing is crucial for the proper execution of the above mentioned functions. Psychophysical and neuroimaging research in humans has provided support for the concept of a reciprocal inhibitory visual-vestibular interaction, the functional significance of which lies in suppression of potential mismatch between incongruent sensory inputs delivered from the two systems. Functional magnetic resonance imaging (fMRI) enabled visualization of this interaction through detection of blood-oxygen-level-dependant (BOLD) signal increases or signal decreases in the visual and vestibular networks during unisensory stimulation. Specifically, visual stimulation related to the percept of self-motion, such as optokinetic stimulation, was shown to elicit BOLD signal increases in areas involved in visual processing along with BOLD signal decreases in areas involved in vestibular processing. Increasing age was shown to alter the morphological and functional properties of the sensory, motor and cognitive systems. Previous research has revealed that senescence associates with deterioration of both, visual and vestibular functions, as well as a change in the psychophysical measurements related to their interaction. However, the effects of age on the BOLD signal pattern reflecting the visual-vestibular interaction have not yet been investigated. Exploring these effects in healthy subjects could offer the possibility to detect early age-related changes in the cortical function occurring before a decline in behavioural measurements can be detected. Aside broadening the scientific knowledge on the physiological changes with age in the sensory systems and their interactions, such research would also help to better understand the pathophysiological processes underlying various visual and vestibular disorders investigated in neuroimaging studies. Therefore, the aim of this doctoral thesis was to explore how the BOLD signal related to the visualvestibular interaction during optokinetic nystagmus (OKN) changes with age in healthy subjects. It specifically aimed to investigate the age-related changes in the spatial and temporal patterns of the signal during unaltered oculomotor performance. In order to obtain information on the diverse effects of age, the changes in the mean of the BOLD signal, as well as the changes in its temporal variability were analyzed. For the purpose of differentiating between global and task-related changes with age, the alterations of the BOLD signal during OKN were compared to the alterations of the BOLD signal elicited by a pure visual and a pure motor task. In the frame of this work, we were able to show that significant age-related changes in the mean of the BOLD signal and in its temporal fluctuations occur prior to any measurable decline in OKN performance. The changes in the mean of the BOLD signal were taskspecific and possibly reflected age-related alterations in neurovascular coupling and neural processing related to OKN. They were found only in cortical and subcortical areas of the visual system. The changes in the temporal fluctuations of the BOLD signal were not specific for the OKN task, but rather region-specific, affecting mostly areas know to be part of the multimodal vestibular processing network.

’Gain-field-like’ tuning behavior is characterized by a modulation of the neuronal response depending on a certain variable, without changing the actual receptive field characteristics in relation to another variable. Eye position gain fields were first observed in area 7a of the posterior parietal cortex (PPC), where visually responsive neurons are modulated by ocular position. Analysis of artificial neural networks has shown that this type of tuning function might comprise the neuronal substrate for coordinate transformations. In this work, neuronal activity in the dorsal medial superior temporal area (MSTd) has been analyzed with an focus on it’s involvement in oculomotor control. MSTd is part of the extrastriate visual cortex and located in the PPC. Lesion studies suggested a participation of this cortical area in the control of eye movements. Inactivation of MSTd severely impairs the optokinetic response (OKR), which is an reflex-like kind of eye movement that compensates for motion of the whole visual scene. Using a novel, information-theory based approach for neuronal data analysis, we were able to identify those visual and eye movement related signals which were most correlated to the mean rate of spiking activity in MSTd neurons during optokinetic stimulation. In a majority of neurons firing rate was non-linearly related to a combination of retinal image velocity and eye velocity. The observed neuronal latency relative to these signals is in line with a system-level model of OKR, where an efference copy of the motor command signal is used to generate an internal estimate of the head-centered stimulus velocity signal. Tuning functions were obtained by using a probabilistic approach. In most MSTd neurons these functions exhibited gain-field-like shapes, with eye velocity modulating the visual response in a multiplicative manner. Population analysis revealed a large diversity of tuning forms including asymmetric and non-separable functions. The distribution of gain fields was almost identical to the predictions from a neural network model trained to perform the summation of image and eye velocity. These findings therefore strongly support the hypothesis of MSTd’s participation in the OKR control system by implementing the transformation from retinal image velocity to an estimate of stimulus velocity. In this sense, eye velocity gain fields constitute an intermediate step in transforming the eye-centered to a head-centered visual motion signal.Another aspect that was addressed in this work was the comparison of the irregularity of MSTd spiking activity during optokinetic response with the behavior during pure visual stimulation. The goal of this study was an evaluation of potential neuronal mechanisms underlying the observed gain field behavior. We found that both inter- and intra-trial variability were decreased with increasing retinal image velocity, but increased with eye velocity. This observation argues against a symmetrical integration of driving and modulating inputs. Instead, we propose an architecture where multiplicative gain modulation is achieved by simultaneous increase of excitatory and inhibitory background synaptic input. A conductance-based single-compartment model neuron was able to reproduce realistic gain modulation and the observed stimulus-dependence of neural variability, at the same time. In summary, this work leads to improved knowledge about MSTd’s role in visuomotor transformation by analyzing various functional and mechanistic aspects of eye velocity gain fields on a systems-, network-, and neuronal level.

Neurofascin (NF) is a cell-adhesion molecule that is found at the nodes of Ranvier. The 186 kDa isoform of neurofascin (NF186) is expressed on the axon in the exposed node, and the 155 kDa isoform (NF155) is expressed on myelinating glia at the paranode. NF186 is essential for clustering of sodium channels to the nodes while NF155 is needed for close paranodal interactions between myelinating glia and axons. The neurofascins are found in both the peripheral and central nervous system (PNS and CNS). NF-specific autoantibodies were identified in serum of multiple sclerosis (MS) patients using a proteomics approach with two-dimensional Western blotting of human myelin glycoproteins. A monoclonal antibody (mAb) specific for NF was shown to induce axonal injury in an animal model of MS, experimental autoimmune encephalomyelitis. This indicated that NF is a relevant autoantibody target in patients with inflammatory diseases of the nervous system (central and peripheral), but actual abundance of anti-NF autoantibodies is unknown. The objectives of the thesis were the following: 1) Develop assays to detect autoantibodies against human NF. 2) Determine the prevalence in patients with MS and with inflammatory diseases of the PNS. 3) Characterize the reactivity by immunoglobulin isotyping, serial dilution, epitope mapping, and staining of nodal structures in tissue sections. 4) Affinity purify anti-NF antibodies from plasma exchange material. 5) Determine possible in vivo effects of anti-NF antibodies in the PNS using a neuritis animal model. First, we expressed the complete human NF155 and NF186 on the surface of stable human cell lines, produced the complete extracellular portion of the NFs in HEK293 cells, and expressed truncated variants of the NFs in E. coli. With these reagents, we set up three antibody detection assays: cell-based assay by flow cytometry, ELISA, and Western blot. These assays were validated using NF-specific monoclonal and polyclonal antibodies, and optimized with a test cohort of serum samples. We screened 687 serum and 48 plasma exchange samples from patients with MS (n = 233), inflammatory diseases in the PNS (n = 294), and controls (n = 208). From serum analysis, we observed low prevalence of anti-NF reactivity (3%) by flow cytometry and/or ELISA despite broad reactivity in almost half of the serum samples analyzed by Western blot. Reactivity observed by flow cytometry and by ELISA were congruent only in the patients with the highest reactivities. The anti-NF antibodies were NF-isoform specific, mainly IgG subclasses, and at high titres in some cases. Using truncated variants of NF fused to super green fluorescence protein (sGFP), we showed that reactivity of anti-NF Abs was largely directed towards the membrane proximal extracellular domains that are unique to each isoform, while the membrane distal immunoglobulin-like domains and fibronectin domains were not recognized. A small proportion (3%; 8/254) of patients with GBS and CIDP showed reactivity to human NF by ELISA. A few showed a particularly high reactivity (up to 1:10 000 dilution) to NF. Two CIDP patients showed a particularly high (up to 1:10 000 dilution) anti-NF155 reactivity by FACS and ELISA, recognized paranodes in tissue sections, and exhibited dominant IgG4 subclass usage. Another CIDP patient who benefited from plasma exchange had a persistent anti-NF155 reactivity by ELISA in serum, and after affinity purification, anti-NF186 and -NF155 reactivity by FACS and ELISA were detected in addition. These antibodies were mainly IgG3, with minor contribution of IgM and IgA. To investigate possible functions of anti-NF antibodies in inflammatory PNS diseases, we injected two different monoclonal antibodies (mAbs) into a P2-peptide induced experimental autoimmune neuritis (EAN) animal model at disease onset. We found that while the anti-NF mAbs prolonged and exacerbated clinical disease in these animals, they could not induce disease on their own. We detected NF-reactivity in a small proportion of MS samples (3%; 7/225) by ELISA and flow cytometry. We obtained follow-up material from two NF-reactive patients and saw a persistent NF reactivity in one of them. To increase detection sensitivity, we affinity purified anti-NF antibodies from plasma exchange material of patients with MS (n = 8). IgG, IgM, and IgA were isolated from most of the samples; they were found to recognize NF155 and to a lower extent NF186 by ELISA and in a few also by flow cytometry. This indicates that low levels of anti-NF antibodies exist in a proportion of MS patients. In conclusion, 3% of serum samples from patients with PNS inflammatory neuropathies (GBS and CIDP) showed reactivity by ELISA and none of the controls. In an animal model of autoimmune peripheral nerve inflammation, we showed, using two anti-NF mAbs, that antibody targeting of NF can enhance and prolong disease course. This suggests that antibodies to NF may be relevant for a small group of patients with peripheral inflammatory neuropathies. In MS patients, 3% showed anti-NF reactivity by flow cytometry and ELISA. Furthermore, low levels of anti-NF antibodies that could be detected by ELISA and flow cytometry after affinity purification were additionally found in some MS patient samples that were unreactive by serum screening. This raises the possibility that low levels of antibodies to NF are present in some MS patients and may contribute to the pathogenesis of this chronic disease.