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- Lycke Brandt, Christine, et al.
(författare)
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Working memory networks and activation patterns in schizophrenia and bipolar disorder : comparison with healthy controls
- 2014
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Ingår i: British Journal of Psychiatry. - 0007-1250 .- 1472-1465. ; 204:4, s. 290-298
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Schizophrenia and bipolar disorder are severe mental disorders with overlapping genetic and clinical characteristics, including cognitive impairments. An important question is whether these disorders also have overlapping neuronal deficits.AIMS: To determine whether large-scale brain networks associated with working memory, as measured with functional magnetic resonance imaging (fMRI), are the same in both schizophrenia and bipolar disorder, and how they differ from those in healthy individuals.METHOD: Patients with schizophrenia (n = 100) and bipolar disorder (n = 100) and a healthy control group (n = 100) performed a 2-back working memory task while fMRI data were acquired. The imaging data were analysed using independent component analysis to extract large-scale networks of task-related activations.RESULTS: Similar working memory networks were activated in all groups. However, in three out of nine networks related to the experimental task there was a graded response difference in fMRI signal amplitudes, where patients with schizophrenia showed greater activation than those with bipolar disorder, who in turn showed more activation than healthy controls. Secondary analysis of the patient groups showed that these activation patterns were associated with history of psychosis and current elevated mood in bipolar disorder.CONCLUSIONS: The same brain networks were related to working memory in schizophrenia, bipolar disorder and controls. However, some key networks showed a graded hyperactivation in the two patient groups, in line with a continuum of neuronal abnormalities across psychotic disorders.
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- Brandt, Christine Lycke, et al.
(författare)
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Cognitive effort and schizophrenia modulate large-scale functional brain connectivity
- 2015
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Ingår i: Schizophrenia Bulletin. - 0586-7614 .- 1745-1701. ; 41:6, s. 1360-1369
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Tidskriftsartikel (refereegranskat)abstract
- Schizophrenia (SZ) is characterized by cognitive dysfunction and disorganized thought, in addition to hallucinations and delusions, and is regarded a disorder of brain connectivity. Recent efforts have been made to characterize the underlying brain network organization and interactions. However, to which degree connectivity alterations in SZ vary across different levels of cognitive effort is unknown. Utilizing independent component analysis (ICA) and methods for delineating functional connectivity measures from functional magnetic resonance imaging (fMRI) data, we investigated the effects of cognitive effort, SZ and their interactions on between-network functional connectivity during 2 levels of cognitive load in a large and well-characterized sample of SZ patients (n = 99) and healthy individuals (n = 143). Cognitive load influenced a majority of the functional connections, including but not limited to fronto-parietal and default-mode networks, reflecting both decreases and increases in between-network synchronization. Reduced connectivity in SZ was identified in 2 large-scale functional connections across load conditions, with a particular involvement of an insular network. The results document an important role of interactions between insular, default-mode, and visual networks in SZ pathophysiology. The interplay between brain networks was robustly modulated by cognitive effort, but the reduced functional connectivity in SZ, primarily related to an insular network, was independent of cognitive load, indicating a relatively general brain network-level dysfunction.
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| 3. |
- Tønnesen, Siren, et al.
(författare)
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Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder : A Multisample Diffusion Tensor Imaging Study
- 2020
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Ingår i: Biological Psychiatry. - : Elsevier BV. - 2451-9022 .- 2451-9030. ; 5:12, s. 1095-1103
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts.METHODS: We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results.RESULTS: Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics.CONCLUSIONS: Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.
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| 10. |
- Hugdahl, K, et al.
(författare)
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Dichotic-listening performance and intracarotid injections of amobarbital in children and adolescents. Preoperative and postoperative comparisons.
- 1997
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Ingår i: Archives of neurology. - 0003-9942. ; 54:12, s. 1494-500
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Dichotic listening (DL) to consonant-vowel syllables is frequently used in clinical and experimental studies of brain laterality. However, the paradigm of consonant-vowel syllables has not been thoroughly validated through a comparison with injections of amobarbital sodium (Amytal). OBJECTIVE: To validate the DL test for hemisphere dominance preoperatively vs postoperatively with the results from intracarotid injections of amobarbital (i.e., the Wada test) in epileptic children and adolescents. DESIGN AND MAIN OUTCOME MEASURES: Patients were tested with DL preoperatively and at 6-month follow-up. Correct reports in the DL tests were entered in a stepwise discriminant analysis for calculation of correct classification of hemisphere dominance with the results from the injections of amobarbital as the grouping variable. Correct reports from the right and left ears on the consonant-vowel DL test were compared preoperatively and postoperatively, separated for the subjects with regard to language dominance in the left and right hemispheres. SETTING: The Department of Pediatrics, Ostra Hospital, University of G?teborg, G?teborg, Sweden. PATIENTS: Thirteen children and adolescents between the ages of 10 and 19 years, who were surgically treated for resistant epilepsy, were included in the study. The operated area corresponded with morphological changes and functional dysfunctions according to findings from computed tomography, magnetic resonance imaging, single photon emission computed tomography, and electroencephalography. RESULTS: The results of the Wada tests revealed that 10 subjects had left hemisphere language dominance, with 3 subjects having right hemisphere language dominance. All 3 subjects with right hemisphere language dominance showed a left ear advantage on the DL test preoperatively and postoperatively, with 8 and 7 of the 10 subjects with left hemisphere dominance showing a right ear advantage, preoperatively and postoperatively, respectively. However, according to discriminant analysis, knowledge of the DL performance led to a correct classification according to the Wada test results in 12 (92%) of the 13 subjects. CONCLUSIONS: A quantitative classification procedure like discriminant analysis may be more sensitive when predicting hemisphere speech dominance from DL data than a qualitative procedure based on the ear advantage dichotomy. The ear advantage dichotomy may actually introduce arbitrary left-right categories that do not correspond to the actual clustering of the data.
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