P.2.049 - Fronto-parietal connectivity and its relation to frontal glutamate in patients suffering from schizophrenia

Abstract

Cognitive deficits like working memory impairment in schizophrenia are of great importance for clinical outcome, but the underlying neurobiology is not fully understood. During working memory (WM) altered connectivity patterns in the fronto-parietal network are present in patients suffering from schizophrenia [1–3]. One candidate biochemical marker for the integrity of connectivity is glutamate [4]. Here we tested for group differences in fronto-parietal connectivity and it’s relation to possible glutamatergic influences. During a functional magnetic resonance imaging (fMRI) scan, a sample of 42 medicated patients (SZ) and 41 age and gender matched healthy controls (HC) were asked to perform a numeric n-back working memory task, which consisted of two conditions “2-back” and “0-back”. FMRI was conducted on a 3T Siemens Trio scanner with a 12 channel head coil using gradient-echo echo-planar imaging. Data were further preprocessed using the statistical parametric mapping (SPM 8; Welcome Department of Imaging Neuroscience, London, UK; htt://www.fil.ion.ucl.ac.uk/spm) in MATLAB 2009b. We performed dynamic causal modeling [5] (DCM) on a model space comprising regions of interest for a visual input, parietal (PC) and dorsolateral prefrontal cortex (DLPFC). We calculated Bayesian model averages to obtain weighted connectivity parameters. One-sample t-tests were calculated on parameters for PC->DLPFC and DLPFC->PC connectivity within each group in order to evaluate modulatory effects of working memory on the executive network. Glutamate levels were measured in left DLPFC using magnetic resonance spectroscopy. We used LCmodel (Linear Combination of Model spectra, a commercial spectral fitting package) to estimate local glutamate concentration. Absolute glutamate concentrations were adjusted for grey and white matter volume. We performed group comparisons (two-sample t-test) on connectivity parameters as well as on glutamate levels. Due to non-normality two-sided Spearman correlation analysis were calculated between connectivity parameters and glutamate levels. Working memory dependent connectivity effects (between PC and DLPFC) could be observed in the left hemisphere on backward connections (PC->DLPFC, HC: t=2.77, p=0.008; SZ: t=2.62, p=0.012), whereas no significant working memory effects were present on DLPFC->PC connectivity. We found no group difference in fronto-parietal connectivity parameters and no difference in glutamate levels. Nonetheless numerically controls show higher glutamate levels as compared to patients. To explore possible effects of local Glutamate levels on working memory dependent connectivity, we correlated parameters for PC->DLPFC connectivity (where we found significant working memory dependent effects) with glutamate levels. We found a significant negative association between parieto-frontal connectivity and glutamate in DLPFC in patients (rho=-0.47, p=0.0035). Controls did not show any significant association (rho=-0.12, p=0.53). Comparing correlation coefficients, we found a trend-wise significant difference between groups (z=1.55, p=0.06). Although our data neither showed a difference in connectivity nor in glutamate levels, our findings suggest that glutamate is differentially related to working memory dependent connectivity from parietal to frontal areas in patients as compared to controls.