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The pathophysiology of schizophrenia is still poorly understood. Investigating the neurophysiological correlates of cognitive dysfunction with functional neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is widely considered to be a possible solution for this problem. Working memory impairment is one of the most prominent cognitive impairments found in schizophrenia. Working memory can be divided into a number of component processes, encoding, maintenance and retrieval. They appear to be differentially affected in schizophrenia, but little is known about the neurophysiological disturbances which contribute to deficits in these component processes. The aim of this dissertation was to elucidate the neurophysiological underpinnings of the component processes of working memory and their disturbance in schizophrenia. In the first study the the neurophysiological substrates of visual working memory capacity limitations were investigated during encoding, maintenance and retrieval in 12 healthy subjects using event-related fMRI. Subjects had to encode up to four abstract visual shapes and maintain them in working memory for 12 seconds. Afterwards a test stimulus was presented, which matched one of the previously shown shapes in fifty percent of the trials. A bilateral inverted U-shape pattern of BOLD activity with increasing memory load in areas closely linked with selective attention, i.e. the frontal eye fields and areas around the intraparietal sulcus, was observed already during encoding. The increase of the number of stored items from memory load three to memory load four in these regions was negatively correlated with the increase of BOLD activity from memory load three to memory load four. These results point to a crucial role of attentional processes for the limited capacity of working memory. In the second study, the contribution of early perceptual processing deficits during encoding and retrieval to working memory dysfunction was investigated in 17 patients with schizophrenia and 17 healthy control subjects using EEG and event-related fMRI. A slightly modified version of the working memory task used in the fist study was employed. Participants only had to encode and maintain up to three items. In patients the amplitude of the P1 event-related potential was significantly reduced already during encoding in all memory load conditions. Similarly, BOLD activity in early visual areas known to generate the P1 was significantly reduced in patients. In controls, a stronger P1 amplitude increase with increasing memory load predicted better performance. These findings indicate that in addition to later memory related processing stages early visual processing is disturbed in schizophrenia and contributes to working memory dysfunction by impairing the encoding of information. In the third study, which was based on the same data set as the second study, cortical activity and functional connectivity in 17 patients with schizophrenia and 17 to healthy control subjects during the working memory encoding, maintenance and retrieval was investigated using event-related fMRI. Patients had reduced working memory capacity. During encoding activation in the left ventrolateral prefrontal cortex and extrastriate visual cortex was reduced in patients but positively correlated with working memory capacity in controls. During early maintenance patients switched from hyper- to hypoactivation with increasing memory load in a fronto-parietal network which included left dorsolateral prefrontal cortex. During retrieval right ventrolateral prefrontal hyperactivation was correlated with encoding-related hypoactivation of left ventrolateral prefrontal cortex in patients. Cortical dysfunction in patients during encoding and retrieval was accompanied by abnormal functional connectivity between fronto-parietal and visual areas. These findings indicate a primary encoding deficit in patients caused by a dysfunction of prefrontal and visual areas. The findings of these studies suggest that isolating the component processes of working memory leads to more specific markers of cortical dysfunction in schizophrenia, which had been obscured in previous studies. This approach may help to identify more reliable biomarkers and endophenotypes of schizophrenia.
This dissertation connects two independent fields of theoretical neuroscience: on the one hand, the self-organization of topographic connectivity patterns, and on the other hand, invariant object recognition, that is the recognition of objects independently of their various possible retinal representations (for example due to translations or scalings). The topographic representation is used in the presented approach, as a coordinate system, which then allows for the implementation of invariance transformations. Hence this study shows, that it is possible that the brain self-organizes before birth, so that it is able to invariantly recognize objects immediately after birth. Besides the core hypothesis that links prenatal work with object recognition, advancements in both fields themselves are also presented. In the beginning of the thesis, a novel analytically solvable probabilistic generative model for topographic maps is introduced. And at the end of the thesis, a model that integrates classical feature-based ideas with the normalization-based approach is presented. This bilinear model makes use of sparseness as well as slowness to implement "optimal" topographic representations. It is therefore a good candidate for hierarchical processing in the brain and for future research.
The dissertation deals with the general problem of how the brain can establish correspondences between neural patterns stored in different cortical areas. Although an important capability in many cognitive areas like language understanding, abstract reasoning, or motor control, this thesis concentrates on invariant object recognition as application of correspondence finding. One part of the work presents a correspondence-based, neurally plausible system for face recognition. Other parts address the question of visual information routing over several stages by proposing optimal architectures for such routing ('switchyards') and deriving ontogenetic mechanisms for the growth of switchyards. Finally, the idea of multi-stage routing is united with the object recognition system introduced before, making suggestions of how the so far distinct feature-based and correspondence-based approaches to object recognition could be reconciled.