Search

Functional connectome alterations, including modular network organization, have been related to the experience of hallucinations. It remains to be determined whether individuals with hallucinations across the psychosis continuum exhibit similar alterations in modular brain network organization. This study assessed functional connectivity matrices of 465 individuals with and without hallucinations, including patients with schizophrenia and bipolar disorder, nonclinical individuals with hallucinations, and healthy controls. Modular brain network organization was examined at different scales of network resolution, including (1) global modularity measured as Qmax and Normalised Mutual Information (NMI) scores, and (2) within-and between-module connectivity. Global modular organization was not significantly altered across groups. However, alterations in within-and between-module connectivity were observed for higher-order cognitive (e.g., central-executive salience, memory, default mode), and sensory modules in patients with schizophrenia and nonclinical individuals with hallucinations relative to controls. Dissimilar patterns of altered within-and between-module connectivity were found bipolar disorder patients with hallucinations relative to controls, including the visual, default mode, and memory network, while connectivity patterns between visual, salience, and cognitive control modules were unaltered. Bipolar disorder patients without hallucinations did not show significant alterations relative to controls. This study provides evidence for alterations in the modular organization of the functional connectome in individuals prone to hallucinations, with schizophrenia patients and nonclinical individuals showing similar alterations in sensory and higher-order cognitive modules. Other higher-order cognitive modules were found to relate to hallucinations in bipolar disorder patients, suggesting differential neural mechanisms may underlie hallucinations across the psyc

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.

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.

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.

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.

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.

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.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

That trauma can play a significant role in the onset and maintenance of voice-hearing is one of the most striking and important developments in the recent study of psychosis. Yet the finding that trauma increases the risk for hallucination and for psychosis is quite different from the claim that trauma is necessary for either to occur. Trauma is often but not always associated with voice-hearing in populations with psychosis; voice-hearing is sometimes associated with willful training and cultivation in nonclinical populations. This article uses ethnographic data among other data to explore the possibility of multiple pathways to voice-hearing for clinical and nonclinical individuals whose voices are not due to known etiological factors such as drugs, sensory deprivation, epilepsy, and so forth. We suggest that trauma sometimes plays a major role in hallucinations, sometimes a minor role, and sometimes no role at all. Our work also finds seemingly distinct phenomenological patterns for voice-hearing, which may reflect the different salience of trauma for those who hear voices.

There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ.

BackgroundNeuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis.MethodsIn this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156.FindingsOur sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohen's d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06)

There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ.

BackgroundNeuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis.MethodsIn this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156.FindingsOur sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohen's d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06)

Background Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis. Methods In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156. Findings Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4–63 years). The volumes of the accumbens (Cohen's d=−0·15), amygdala (d=−0·19), caudate (d=−0·11), hippocampus (d=−0·11), putamen (d=−0·14), and intracranial volume (d=−0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohen's d=−0·19 vs −0·10), amygdala (d=−0·18 vs −0·14), caudate (d=−0·13 vs −0·07), hippocampus (d=−0·12 vs

There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ.

Background: Tourette Syndrome (TS) is a neurodevelopmental disorder with childhood-onset, with a typical decline in tic severity, as well as an increasing ability to suppress tics in late childhood and adolescence. These processes develop in parallel with general improvement of self-regulatory abilities, and performance monitoring during this age-span. Hence, changes in performance monitoring over time might provide insight into the regulation of tics in children and adolescents with TS. Method: We measured reaction time, reaction time variability, accuracy, and event-related potentials (ERP) in 17 children with TS, including 10 children with comorbid Attention-Deficit/Hyperactivity Disorder (ADHD), 24 children with ADHD, and 29 typically developing children, using a modified Eriksen Flanker task in two testing sessions administered on average 4.5 years apart. We then compared task performance, as well as ERP components across groups, and over time using regression models. Results: Task performance improved in all groups with age, and behavioral differences between children with TS and controls diminished at second assessment, while differences between controls and children with ADHD largely persisted. In terms of ERP, the early P3 developed earlier in children with TS compared with controls at the first assessment, but trajectories converged with maturation. ERP component amplitudes correlated with worst-ever tic scores. Conclusions: Merging trajectories between children with TS and controls are consistent with the development of compensatory self-regulation mechanisms during early adolescence, probably facilitating tic suppression, in contrast to children with ADHD. Correlations between ERP amplitudes and tic scores also support this notion.

Auditory evoked potentials are tools widely used to assess auditory cortex functions in clinical context. However, in cochlear implant users, electrophysiological measures are challenging due to implant-created artefacts in the EEG. Here, we used independent component analysis to reduce cochlear implant-related artefacts in event-related EEGs of cochlear implant users (n = 12), which allowed detailed spatio-temporal evaluation of auditory evoked potentials by means of dipole source analysis. The present study examined hemispheric asymmetries of auditory evoked potentials to musical sounds in cochlear implant users to evaluate the effect of this type of implantation on neuronal activity. In particular, implant users were presented with two dyadic tonal intervals in an active oddball design and in a passive listening condition. Principally, the results show that independent component analysis is an efficient approach that enables the study of neurophysiological mechanisms of restored auditory function in cochlear implant users. Moreover, our data indicate altered hemispheric asymmetries for dyadic tone processing in implant users compared with listeners with normal hearing (n = 12). We conclude that the evaluation of auditory evoked potentials are of major relevance to understanding auditory cortex function after cochlear implantation and could be of substantial clinical value by indicating the maturation/reorganization of the auditory system after implantation

Background: Tourette Syndrome (TS) is a neurodevelopmental disorder with childhood-onset, with a typical decline in tic severity, as well as an increasing ability to suppress tics in late childhood and adolescence. These processes develop in parallel with general improvement of self-regulatory abilities, and performance monitoring during this age-span. Hence, changes in performance monitoring over time might provide insight into the regulation of tics in children and adolescents with TS. Method: We measured reaction time, reaction time variability, accuracy, and event-related potentials (ERP) in 17 children with TS, including 10 children with comorbid Attention-Deficit/Hyperactivity Disorder (ADHD), 24 children with ADHD, and 29 typically developing children, using a modified Eriksen Flanker task in two testing sessions administered on average 4.5 years apart. We then compared task performance, as well as ERP components across groups, and over time using regression models. Results: Task performance improved in all groups with age, and behavioral differences between children with TS and controls diminished at second assessment, while differences between controls and children with ADHD largely persisted. In terms of ERP, the early P3 developed earlier in children with TS compared with controls at the first assessment, but trajectories converged with maturation. ERP component amplitudes correlated with worst-ever tic scores. Conclusions: Merging trajectories between children with TS and controls are consistent with the development of compensatory self-regulation mechanisms during early adolescence, probably facilitating tic suppression, in contrast to children with ADHD. Correlations between ERP amplitudes and tic scores also support this notion.

BACKGROUND: We examined the blood-oxygen level-dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD).METHODS: We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8-12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations.RESULTS: We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN.LIMITATIONS: Our study was limited by the modest sample size and imperfect matching across groups.CONCLUSION: Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD.

BACKGROUND: Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder and its impact on cognitive development needs further study. Evidence from neuropsychological, neuroimaging and electrophysiological studies suggests that the decline in tic severity and the ability to suppress tics relate to the development of self-regulatory functions in late childhood and adolescence. Hence, tasks measuring performance monitoring might provide insight into the regulation of tics in children with TS.METHOD: Twenty-five children with TS, including 14 with comorbid Attention-deficit/ hyperactivity disorder (ADHD), 39 children with ADHD and 35 typically developing children aged 8-12 years were tested with a modified Eriksen-Flanker task during a 34-channel electroencephalography (EEG) recording. Task performance, as well as stimulus-locked and response-locked event-related potentials (ERP) were analyzed and compared across groups.RESULTS: Participants did not differ in their behavioral performance. Children with TS showed higher amplitudes of an early P3 component of the stimulus-locked ERPs in ensemble averages and in separate trial outcomes, suggesting heightened orienting and/or attention during stimulus evaluation. In response-locked averages, children with TS had a slightly higher positive complex before the motor response, likely also reflecting a late P3. Groups did not differ in post-response components, particularly in the error-related negativity (ERN) and error-related positivity (Pe).CONCLUSIONS: These findings suggest that children with TS may employ additional attentional resources as a compensatory mechanism to maintain equal behavioral performance.

BackgroundMajor depression can be a serious and debilitating condition. For some patients in a treatment resistant depressive episode, electroconvulsive treatment (ECT) is the only treatment that is effective. Although ECT has shown efficacy in randomized controlled trials, the treatment is still controversial and stigmatized. This can in part be attributed to our lack of knowledge of the mechanisms of action. Some reports also suggest potential harmful effects of ECT treatment and memory related side effects have been documented.Methods/designThe present study will apply state of the art radiology through advanced magnetic resonance imaging (MRI) techniques to investigate structural and functional brain effects of ECT. As a multi-disciplinary collaboration, imaging findings will be correlated to psychiatric response parameters, neuropsychological functioning as well as neurochemical and genetic biomarkers that can elucidate the underlying mechanisms. The aim is to document both treatment effects and potential harmful effects of ECT.Samplen = 40 patients in a major depressive episode (bipolar and major depressive disorder). Two control groups with n = 15 in each group: age and gender matched healthy volunteers not receiving ECT and patients undergoing electrical cardioversion (ECV) for atrial fibrillation (AF). Observation time: six months.DiscussionThe study will contribute to our understanding of the pathophysiology of major depression as well as mechanisms of action for the most effective treatment for the disorder; ECT.

BackgroundMajor depression can be a serious and debilitating condition. For some patients in a treatment resistant depressive episode, electroconvulsive treatment (ECT) is the only treatment that is effective. Although ECT has shown efficacy in randomized controlled trials, the treatment is still controversial and stigmatized. This can in part be attributed to our lack of knowledge of the mechanisms of action. Some reports also suggest potential harmful effects of ECT treatment and memory related side effects have been documented.Methods/designThe present study will apply state of the art radiology through advanced magnetic resonance imaging (MRI) techniques to investigate structural and functional brain effects of ECT. As a multi-disciplinary collaboration, imaging findings will be correlated to psychiatric response parameters, neuropsychological functioning as well as neurochemical and genetic biomarkers that can elucidate the underlying mechanisms. The aim is to document both treatment effects and potential harmful effects of ECT.Samplen = 40 patients in a major depressive episode (bipolar and major depressive disorder). Two control groups with n = 15 in each group: age and gender matched healthy volunteers not receiving ECT and patients undergoing electrical cardioversion (ECV) for atrial fibrillation (AF). Observation time: six months.DiscussionThe study will contribute to our understanding of the pathophysiology of major depression as well as mechanisms of action for the most effective treatment for the disorder; ECT.

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.

Developmental dyslexia is a common reading disorder that negatively impacts an individual's ability to achieve literacy. Although the brain network involved in reading and its dysfunction in dyslexia has been well studied, it is unknown whether dyslexia is caused by structural abnormalities in the reading network itself or in the lower-level networks that provide input to the reading network. In this study, we acquired structural magnetic resonance imaging scans longitudinally from 27 Norwegian children from before formal literacy training began until after dyslexia was diagnosed. Thus, we were able to determine that the primary neuroanatomical abnormalities that precede dyslexia are not in the reading network itself, but rather in lower-level areas responsible for auditory and visual processing and core executive functions. Abnormalities in the reading network itself were only observed at age 11, after children had learned how to read. The findings suggest that abnormalities in the reading network are the consequence of having different reading experiences, rather than dyslexia per se, whereas the neuroanatomical precursors are predominantly in primary sensory cortices.

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.

We studied the effects of training on auditory attention in healthy adults with a speech perception task involving dichotically presented syllables. Training involved bottom-up manipulation (facilitating responses from the harder-to-report left ear through a decrease of right-ear stimulus intensity), top-down manipulation (focusing attention on the left-ear stimuli through instruction), or their combination. The results showed significant training-related effects for top-down training. These effects were evident as higher overall accuracy rates in the forced-left dichotic listening (DL) condition that sets demands on attentional control, as well as a response shift toward left-sided reports in the standard DL task. Moreover, a transfer effect was observed in an untrained auditory-spatial attention task involving bilateral stimulation where top-down training led to a relatively stronger focus on left-sided stimuli. Our results indicate that training of attentional control can modulate the allocation of attention in the auditory space in adults. Malleability of auditory attention in healthy adults raises the issue of potential training gains in individuals with attentional deficits.

We studied the effects of training on auditory attention in healthy adults with a speech perception task involving dichotically presented syllables. Training involved bottom-up manipulation (facilitating responses from the harder-to-report left ear through a decrease of right-ear stimulus intensity), top-down manipulation (focusing attention on the left-ear stimuli through instruction), or their combination. The results showed significant training-related effects for top-down training. These effects were evident as higher overall accuracy rates in the forced-left dichotic listening (DL) condition that sets demands on attentional control, as well as a response shift toward left-sided reports in the standard DL task. Moreover, a transfer effect was observed in an untrained auditory-spatial attention task involving bilateral stimulation where top-down training led to a relatively stronger focus on left-sided stimuli. Our results indicate that training of attentional control can modulate the allocation of attention in the auditory space in adults. Malleability of auditory attention in healthy adults raises the issue of potential training gains in individuals with attentional deficits.

The objective of the present study was to investigate the microstructure and the macrostructure of the corpus callosum (CC) in adults with Attention-Deficit/Hyperactivity Disorder (ADHD) by means of magnetic resonance imaging (MRI). Twenty-nine participants with ADHD and 37 controls were included from the Norwegian ADHD project in Bergen. We measured the fractional anisotropy (FA) values, as well as the size of different subdivisions of the CC, using diffusion tensor imaging (DTI) and anatomical MRI. The isthmus/splenium part of the CC in the ADHD group showed reduced FA values compared to the control group, whereas the size of the CC did not differ across groups. Our findings thus demonstrate a divergence between microstructural and macrostructural measures in the CC of adults with ADHD. This contrasts with findings in children demonstrating callosal abnormalities in both microstructure and macrostructure. Our results may indicate that adults with ADHD in part have succeeded in passing by an earlier developmental delay of the CC, resulting in a normalization of callosal macrostructure into adulthood. However, microstructural differences are still present in adults, which may point to an abnormal lateralization in adults with ADHD, or could be a sign of a persisting impairment.

The objective of the present study was to investigate the microstructure and the macrostructure of the corpus callosum (CC) in adults with Attention-Deficit/Hyperactivity Disorder (ADHD) by means of magnetic resonance imaging (MRI). Twenty-nine participants with ADHD and 37 controls were included from the Norwegian ADHD project in Bergen. We measured the fractional anisotropy (FA) values, as well as the size of different subdivisions of the CC, using diffusion tensor imaging (DTI) and anatomical MRI. The isthmus/splenium part of the CC in the ADHD group showed reduced FA values compared to the control group, whereas the size of the CC did not differ across groups. Our findings thus demonstrate a divergence between microstructural and macrostructural measures in the CC of adults with ADHD. This contrasts with findings in children demonstrating callosal abnormalities in both microstructure and macrostructure. Our results may indicate that adults with ADHD in part have succeeded in passing by an earlier developmental delay of the CC, resulting in a normalization of callosal macrostructure into adulthood. However, microstructural differences are still present in adults, which may point to an abnormal lateralization in adults with ADHD, or could be a sign of a persisting impairment.