Biologically relevant subgroups within the schizophrenia syndrome
In the present thesis, we aimed to explore the existence of biological subgroups within schizophrenia patients by using data from structural and functional brain connectivity as well as a genetic information. It includes five articles with sample sizes from 27 to 121 schizophrenia patients and 27 to...
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| Format: | doctoral thesis |
| Status: | Published version |
| Publication Date: | 2019 |
| Country: | España |
| Institution: | Universidad de Valladolid |
| Repository: | UVaDOC. Repositorio Documental de la Universidad de Valladolid |
| OAI Identifier: | oai:uvadoc.uva.es:10324/39211 |
| Online Access: | https://doi.org/10.35376/10324/39211 http://uvadoc.uva.es/handle/10324/39211 |
| Access Level: | Open access |
| Keyword: | Schizophrenia Esquizofrenia 2490 Neurociencias 2490.01 Neurofisiología 3211 Psiquiatría 2409 Genética |
| Summary: | In the present thesis, we aimed to explore the existence of biological subgroups within schizophrenia patients by using data from structural and functional brain connectivity as well as a genetic information. It includes five articles with sample sizes from 27 to 121 schizophrenia patients and 27 to 144 healthy controls. All patients were diagnosed according to DSM-IV or V criteria and their symptoms were scored using the Positive and Negative Syndrome Scale (PANSS). Structural connectivity was assessed in two different ways. Firstly, using structural magnetic resonance imaging (MRI) we extracted measures of cortical curvature. Secondly, diffusion magnetic resonance imaging (dMRI) was used to obtain values of streamline count and fractional anisotropy in white matter tracts connecting a priori selected regions. Functional connectivity was calculated using electroencephalography (EEG) recordings during the performance of an auditive odd-ball task, in which participants were instructed to respond to infrequent targets while ignoring other stimuli. Then, small-worldness (SWn) index, which quantifies the efficiency of the global electrical network, was calculated at two temporal windows: before and after the target stimulus onset (baseline/pre-stimulus and response window, respectively). We focused our study on the SWn difference between pre-stimulus and response windows as a measure of modulation efficiency. |
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