Investigations of effective connectivity in small and large scale neural networks

The correct signal processing of neuronal signals requires coordination of different groups of neurons. To achieve this there has to be a connection between those neurons. This connection and especially the strength of the connection is not known a priori and can only be measured directly in rare cases. In this thesis I present three publications (Rosjat et al., 2014; Toth et al., 2015; Popovych et al., under review) and the results from two additional studies focussing on the analysis of couplings in experimental measured neuronal activities. The publications can be divided into investigations of intrinsic, as well as extrinsic intra- and intersegmental connections in the stick insect Carausius morosus and into analysis and mathematical modeling of couplings from EEG-measurements of the human brain while subjects were performing different tasks. In both parts I made use of mathematical models to build hypotheses about so far unknown coupling mechanisms. The first study deals with connectivity changes in the thalamo-cortical loop caused by schizophrenia (Rosjat et al., 2014). To build a mathematical model consisting of neural populations representing the thalamus and the auditory cortex we made use of published EEG-data, which were collected while subjects performed a double-click paradigm. The individual populations comprised a large number of phase oscillators with continuously distributed natural frequencies. Applying reduction methods by Pikovsky and Rosenblum, Ott and Antonsen together with the reduction method by Watanabe and Strogatz we investigated the influences of the bidirectional connections between the brain areas on the synchronization of the neuronal populations. The model was able to replicate the experimental data adequately. We observed that the coupling strength from the thalamic region to the cortical region mainly affected the duration of synchrony while the feedback to the thalamic region had a bigger effect on the strength of synchrony. This led to the hypothesis that the back coupling to the thalamic region might be reduced in schizophrenia patients. The second study will show an analysis of intersegmental couplings in the protractorretractor system of the pro- and mesothoracic ganglion of the stick insect Carausius morosus using mathematical models based on experimental data (Toth et al., 2015). We made use of phase-response curves that were calculated experimentally on the one hand and simulated by mathematical models on the other hand to determine the nature and the strength of their connection. We showed that connections on both sides from the prothoracic to the mesothoracic network were necessary to achieve a good agreement with the experimental phase-response curves. Additionally, it was found that the strength of the excitatory connection played a key role, while the strength of the inhibitory connection did not have a big influence on the shape of the phase-response curves. The third study deals with the identification of a neuronal marker of movement execution (Popovych et al., under review). In this work we investigated the influence of internally and externally triggered movement on the phase synchronization in the motor system. We tested the signals, that were recorded from electrodes lying above the motor cortex, in the phase space including the major frequency bands (delta-, theta-, alpha-, beta- and low gamma-frequencies) for inter-trial phase synchrony. The study revealed a strong lateralized phase synchronization in the lower frequency bands (delta and theta) in the electrodes above the contralateral primary motor cortex independent of the hand performing and the cue triggering the movement. The results suggest that this phase synchronization could serve as an electrophysiological marker of movement execution additionally to the well established event-related desynchronization and event-related synchronization that are based on the amplitude changes in alpha- and beta- frequency bands.