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  • 1.
    Jönemo, Johan
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Akbar, Muhammad Usman
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Kämpe, Robin
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Hamilton, J. Paul
    Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Efficient Brain Age Prediction from 3D MRI Volumes Using 2D Projections2023In: Brain Sciences, ISSN 2076-3425, E-ISSN 2076-3425, Vol. 13, no 9, article id 1329Article in journal (Refereed)
    Abstract [en]

    Using 3D CNNs on high-resolution medical volumes is very computationally demanding, especially for large datasets like UK Biobank, which aims to scan 100,000 subjects. Here, we demonstrate that using 2D CNNs on a few 2D projections (representing mean and standard deviation across axial, sagittal and coronal slices) of 3D volumes leads to reasonable test accuracy (mean absolute error of about 3.5 years) when predicting age from brain volumes. Using our approach, one training epoch with 20,324 subjects takes 20–50 s using a single GPU, which is two orders of magnitude faster than a small 3D CNN. This speedup is explained by the fact that 3D brain volumes contain a lot of redundant information, which can be efficiently compressed using 2D projections. These results are important for researchers who do not have access to expensive GPU hardware for 3D CNNs.

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  • 2.
    Paul, Elisabeth R.
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience.
    Farmer, Madison
    Roosevelt University, Chicago, Illinois.
    Kämpe, Robin
    Linköping University, Department of Clinical and Experimental Medicine, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience.
    Cremers, Henk R.
    University of Amsterdam, Amsterdam, The Netherlands.
    Hamilton, Paul J.
    Linköping University, Department of Clinical and Experimental Medicine, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Functional Connectivity Between Extrastriate Body Area and Default Mode Network Predicts Depersonalization Symptoms in Major Depression: Findings From an A Priori Specified Multinetwork Comparison2019In: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, ISSN 2451-9022, Vol. 4, no 7, p. 627-635Article in journal (Refereed)
    Abstract [en]

    Background

    Depersonalization/derealization disorder is a dissociative disorder characterized by feelings of unreality and detachment from the self and surroundings. Depersonalization/derealization disorder is classified as a primary disorder, but depersonalization symptoms are frequently observed in mood and anxiety disorders. In the context of major depressive disorder (MDD), depersonalization symptoms are associated with greater depressive severity as indexed by treatment resistance, inpatient visits, and duration of depressive episodes. In the current investigation, we tested four network-based, neural-functional hypotheses of depersonalization in MDD. These hypotheses were framed in terms of functional relationships between 1) extrastriate body area and default mode network (DMN); 2) hippocampus and DMN; 3) medial prefrontal cortex and ventral striatum; and 4) posterior and anterior insular cortex.

    Methods

    We conducted functional magnetic resonance imaging during resting state on 28 female patients with MDD and 27 control subjects with no history of a psychiatric disorder. Functional connectivity between seed and target regions as specified by our network-level hypotheses was computed and correlated with scores on the Cambridge Depersonalization Scale. We used a conservative, unbiased bootstrapping procedure to test the significance of neural-behavioral correlations observed under each of the four models tested.

    Results

    Of the four neural-functional models of depersonalization symptoms tested, only the model proposing that reduced connectivity between the extrastriate body area and DMN predicts higher levels of depersonalization symptoms in MDD was confirmed.

    Conclusions

    Our results indicate that depersonalization/derealization disorder symptoms in patients with depression are related to reduced functional connectivity between brain regions that are proposed to support processing of body-related (extrastriate body area) and autobiographical (DMN) information.

  • 3.
    Paul, Elisabeth
    et al.
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Schwieler, Lilly
    Karolinska Inst, Sweden.
    Erhardt, Sophie
    Karolinska Inst, Sweden.
    Boda, Sandra
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Trepci, Ada
    Karolinska Inst, Sweden.
    Kämpe, Robin
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Asratian, Anna
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Cell Biology. Linköping University, Faculty of Medicine and Health Sciences.
    Holm, Lovisa
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Yngve, Adam
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Dantzer, Robert
    Univ Texas MD Anderson Canc Ctr, TX 77030 USA.
    Heilig, Markus
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping.
    Hamilton, Paul J.
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Samuelsson, Martin
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping.
    Peripheral and central kynurenine pathway abnormalities in major depression2022In: Brain, behavior, and immunity, ISSN 0889-1591, E-ISSN 1090-2139, Vol. 101, p. 136-145Article in journal (Refereed)
    Abstract [en]

    Considerable data relate major depressive disorder (MDD) with aberrant immune system functioning. Pro inflammatory cytokines facilitate metabolism of tryptophan along the kynurenine pathway (KP) putatively resulting in reduced neuroprotective and increased neurotoxic KP metabolites in MDD, in addition to modulating metabolic and immune function. This central nervous system hypothesis has, however, only been tested in the periphery. Here, we measured KP-metabolite levels in both plasma and cerebrospinal fluid (CSF) of depressed patients (n = 63/36 respectively) and healthy controls (n = 48/33). Further, we assessed the relation between KP abnormalities and brain-structure volumes, as well as body mass index (BMI), an index of metabolic disturbance associated with atypical depression. Plasma levels of picolinic acid (PIC), the kynurenic/quinolinic acid ratio (KYNA/QUIN), and PIC/QUIN were lower in MDD, but QUIN levels were increased. In the CSF, we found lower PIC in MDD. Confirming previous work, MDD patients had lower hippocampal, and amygdalar volumes. Hippocampal and amygdalar volumes were correlated positively with plasma KYNA/QUIN ratio in MDD patients. BMI was increased in the MDD group relative to the control group. Moreover, BMI was inversely correlated with plasma and CSF PIC and PIC/QUIN, and positively correlated with plasma QUIN levels in MDD. Our results partially confirm previous peripheral KP findings and extend them to the CSF in MDD. We present the novel finding that abnormalities in KP metabolites are related to metabolic disturbances in depression, but the relation between KP metabolites and depression-associated brain atrophy might not be as direct as previously hypothesized.

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  • 4.
    Perini, Irene
    et al.
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience.
    Kämpe, Robin
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Arlestig, Theodor
    Linköping University, Department of Clinical and Experimental Medicine, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Hanna
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping.
    Löfberg, Andreas
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping.
    Pietrzak, Michal
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping.
    Zangen, Abraham
    Department of Life Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.
    Heilig, Markus
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Repetitive transcranial magnetic stimulation targeting the insular cortex for reduction of heavy drinking in treatment-seeking alcohol-dependent subjects: a randomized controlled trial2019In: Neuropsychopharmacology, ISSN 0893-133X, E-ISSN 1740-634X, Vol. 45, no 5, p. 842-850Article in journal (Refereed)
    Abstract [en]

    Insula responses to drug cues are correlated with cravings, and lesions in this area reduce nicotine seeking. Here, we investigated the potential efficacy of repetitive transcranial magnetic stimulation (rTMS) targeting the insula in alcohol addiction. Treatment-seeking alcohol-dependent patients (Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition; N = 56) participated in this double-blind, sham-controlled, randomized trial. Participants received 10 Hz rTMS or sham using an H8 coil, 5 days a week for 3 weeks. Stimulation targeted insular cortex and overlaying regions bilaterally, while excluding anterior prefrontal areas. Craving and self-reported as well as biomarker-based drinking measures were collected at baseline, during treatment, and through 12 weeks. Resting-state magnetic resonance imaging (rsMRI) data were collected before and after treatment. Task-based MRI was used to probe brain correlates of reward processing, affective responses, and alcohol following completion of treatment. A marked overall decrease in craving and drinking measures was observed during treatment, but did not differ between rTMS or sham stimulation. Both groups equally increased their alcohol use following completion of treatment and through the 12-week follow-up. Analysis using seeds in the insula identified differences in resting-state connectivity between active and sham groups at completion of treatment, potentially indicating an ability of treatment to modify insula function. However, while each task robustly replicated brain responses established in the literature, no effects of rTMS were found. Collectively, this study does not support efficacy of rTMS targeting the insula in alcohol addiction. 

  • 5.
    Takamiya, Akihiro
    et al.
    Keio Univ, Japan; Katholieke Univ Leuven, Belgium.
    Dols, Annemiek
    GGZ InGeest Specialized Mental Hlth Care, Netherlands; Vrije Univ Amsterdam, Netherlands.
    Emsell, Louise
    Katholieke Univ Leuven, Belgium.
    Abbott, Christopher
    Univ New Mexico, NM 87131 USA.
    Yrondi, Antoine
    Univ Toulouse, France.
    Mas, Carles Soriano
    Bellvitge Biomed Res Inst IDIBELL, Spain; Carlos III Hlth Inst, Spain; Univ Autonoma Barcelona, Spain.
    Jorgensen, Martin Balslev
    Psychiat Ctr Copenhagen, Denmark; Univ Copenhagen, Denmark.
    Nordanskog, Pia
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Psykiatricentrum, Psykiatriska kliniken i Linköping.
    Rhebergen, Didi
    GGZ Centraal, Netherlands.
    van Exel, Eric
    GGZ InGeest Specialized Mental Hlth Care, Netherlands; Vrije Univ Amsterdam, Netherlands.
    Oudega, Mardien L.
    GGZ InGeest Specialized Mental Hlth Care, Netherlands; Vrije Univ Amsterdam, Netherlands.
    Bouckaert, Filip
    Katholieke Univ Leuven, Belgium.
    Vandenbulcke, Mathieu
    Katholieke Univ Leuven, Belgium.
    Sienaert, Pascal
    Katholieke Univ Leuven, Belgium.
    Peran, Patrice
    Univ Toulouse, France.
    Cano, Marta
    Carlos III Hlth Inst, Spain; Univ Autonoma Barcelona, Spain; Parc Tauli Univ Hosp, Spain.
    Cardoner, Narcis
    Parc Tauli Univ Hosp, Spain.
    Jorgensen, Anders
    Psychiat Ctr Copenhagen, Denmark; Univ Copenhagen, Denmark.
    Paulson, Olaf B.
    Rigshosp, Denmark.
    Hamilton, Paul J.
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Kämpe, Robin
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Bruin, Willem
    Amsterdam UMC, Netherlands.
    Bartsch, Hauke
    Haukeland Hosp, Norway; Haukeland Hosp, Norway; Univ Bergen, Norway.
    Ousdal, Olga Therese
    Haukeland Hosp, Norway; Univ Bergen, Norway.
    Kessler, Ute
    Univ Bergen, Norway; Haukeland Hosp, Norway.
    van Wingen, Guido
    Amsterdam UMC, Netherlands.
    Oltedal, Leif
    Haukeland Hosp, Norway; Univ Bergen, Norway.
    Kishimoto, Taishiro
    Keio Univ, Japan.
    Neural Substrates of Psychotic Depression: Findings From the Global ECT-MRI Research Collaboration2022In: Schizophrenia Bulletin, ISSN 0586-7614, E-ISSN 1745-1701, Vol. 48, no 2, p. 514-523Article in journal (Refereed)
    Abstract [en]

    Psychotic major depression (PMD) is hypothesized to be a distinct clinical entity from nonpsychotic major depression (NPMD). However, neurobiological evidence supporting this notion is scarce. The aim of this study is to identify gray matter volume (GMV) differences between PMD and NPMD and their longitudinal change following electroconvulsive therapy (ECT). Structural magnetic resonance imaging (MRI) data from 8 independent sites in the Global ECT-MRI Research Collaboration (GEMRIC) database (n = 108; 56 PMD and 52 NPMD; mean age 71.7 in PMD and 70.2 in NPMD) were analyzed. All participants underwent MRI before and after ECT. First, cross-sectional whole-brain voxel-wise GMV comparisons between PMD and NPMD were conducted at both time points. Second, in a flexible factorial model, a main effect of time and a group-by-time interaction were examined to identify longitudinal effects of ECT on GMV and longitudinal differential effects of ECT between PMD and NPMD, respectively. Compared with NPMD, PMD showed lower GMV in the prefrontal, temporal and parietal cortex before ECT; PMD showed lower GMV in the medial prefrontal cortex (MPFC) after ECT. Although there was a significant main effect of time on GMV in several brain regions in both PMD and NPMD, there was no significant group-by-time interaction. Lower GMV in the MPFC was consistently identified in PMD, suggesting this may be a trait-like neural substrate of PMD. Longitudinal effect of ECT on GMV may not explain superior ECT response in PMD, and further investigation is needed.

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