Mette Ødegaard Nielsen

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BACKGROUND Various schizophrenic symptoms are suggested to be linked to a dysfunction of the brain reward system. Several studies have found alterations in the reward processing in patients with schizophrenia; however, most previous findings might be confounded by medication effects. METHODS Thirty-one antipsychotic-naïve schizophrenia patients and 31(More)
BACKGROUND Psychotic symptoms are core clinical features of schizophrenia. We tested recent hypotheses proposing that psychotic, or positive, symptoms stem from irregularities in long-range white matter tracts projecting into the frontal cortex, and we predicted that selective dopamine D2/3 receptor blockade would restore white matter. METHODS Between(More)
IMPORTANCE Weight gain is a common and serious adverse effect of antipsychotic treatment. A variable individual predisposition to development of metabolic disturbances calls for predictive biological markers. OBJECTIVES To investigate whether attenuated striatal activity during reward anticipation is associated with amisulpride-induced weight change in(More)
One of best validated findings in schizophrenia research is the association between blockade of dopamine D2 receptors and the effects of antipsychotics on positive psychotic symptoms. The aim of the present study was to examine correlations between baseline striatal D(2/3) receptor binding potential (BP(p)) values and treatment outcome in a cohort of(More)
It has been suggested that patients with schizophrenia develop higher levels of oxidative stress, which may contribute to deteriorating mental illness. In order to examine oxidative stress in the early stages of severe mental illness, we examined the levels of systemic Deoxyribonucleic Acid (DNA) and Ribonucleic Acid (RNA) oxidation,(More)
Deficits in information processing and cognition are among the most robust findings in schizophrenia patients. Previous efforts to translate group-level deficits into clinically relevant and individualized information have, however, been non-successful, which is possibly explained by biologically different disease subgroups. We applied machine learning(More)
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