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BACKGROUND: A set of enduring conditions have been reported in the literature involving persistent sexual dysfunction after discontinuation of serotonin reuptake inhibiting antidepressants, 5 alpha-reductase inhibitors and isotretinoin.OBJECTIVE: To develop diagnostic criteria for post-SSRI sexual dysfunction (PSSD), persistent genital arousal disorder (PGAD) following serotonin reuptake inhibitors, post-finasteride syndrome (PFS) and post-retinoid sexual dysfunction (PRSD).METHODS: The original draft was designed using data from two published case series (Hogan et al., 2014 and Healy et al., 2018), which represent the largest public collections of data on these enduring conditions. It was further developed with the involvement of a multidisciplinary panel of experts.RESULTS: A set of criteria were agreed upon for each of the above conditions. Features of PSSD, PFS and PRSD commonly include decreased genital and orgasmic sensation, decreased sexual desire and erectile dysfunction. Ancillary non-sexual symptoms vary depending on the specific condition but can include emotional blunting and cognitive impairment. PGAD presents with an almost mirror image of unwanted sensations of genital arousal or irritability in the absence of sexual desire. A new term, post-SSRI asexuality, is introduced to describe a dampening of sexual interest and pleasure resulting from a pre-natal or pre-teen exposure to a serotonin reuptake inhibitor.CONCLUSIONS: These criteria will help in both clinical and research settings. As with all criteria, they will likely need modification in the light of developments.

Copy Number Variation (CNV) at the 1q21.1 locus is associated with a range of neurodevelopmental and psychiatric disorders in humans, including abnormalities in head size and motor deficits. Yet, the functional consequences of these CNVs (both deletion and duplication) on neuronal development remain unknown. To determine the impact of CNV at the 1q21.1 locus on neuronal development, we generated induced pluripotent stem cells from individuals harbouring 1q21.1 deletion or duplication and differentiated them into functional cortical neurons. We show that neurons with 1q21.1 deletion or duplication display reciprocal phenotype with respect to proliferation, differentiation potential, neuronal maturation, synaptic density and functional activity. Deletion of the 1q21.1 locus was also associated with an increased expression of lower cortical layer markers. This difference was conserved in the mouse model of 1q21.1 deletion, which displayed altered corticogenesis. Importantly, we show that neurons with 1q21.1 deletion and duplication are associated with differential expression of calcium channels and demonstrate that physiological deficits in neurons with 1q21.1 deletion or duplication can be pharmacologically modulated by targeting Ca2+ channel activity. These findings provide biological insight into the neuropathological mechanism underlying 1q21.1 associated brain disorder and indicate a potential target for therapeutic interventions.

BACKGROUND: Altered functional brain connectivity has been proposed as an intermediate phenotype between genetic risk loci and clinical expression of schizophrenia. Genetic high-risk groups of healthy subjects are particularly suited for the investigation of this proposition because they can be tested in the absence of medication or other secondary effects of schizophrenia. METHODS: Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data to reveal the reconfiguration of brain networks during a cognitive task. We recruited healthy carriers of common risk variants using the recall-by-genotype design. We assessed 197 individuals: 99 individuals (52 female, 47 male) with low polygenic risk scores (schizophrenia risk profile scores [SCZ-PRSs]) and 98 individuals (52 female, 46 male) with high SCZ-PRSs from both tails of the SCZ-PRS distribution from a genotyped population cohort, the Avon Longitudinal Study of Parents and Children (N = 8169). We compared groups both on conventional brain activation profiles, using the general linear model of the experiment, and on the neural flexibility index, which quantifies how frequent a brain region's community affiliation changes over experimental time. RESULTS: Behavioral performance and standard brain activation profiles did not differ significantly between groups. High SCZ-PRS was associated with reduced flexibility index and network modularity across n-back levels. The whole-brain flexibility index and that of the frontoparietal working memory network was associated with n-back performance. We identified a dynamic network phenotype related to high SCZ-PRS. CONCLUSIONS: Such neurophysiological markers can become important for the elucidation of biological mechanisms of schizophrenia and, particularly, the associated cognitive deficit.

Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen’s d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (NCASE = 50; NCONTROL = 125), a replication sample (NCASE = 23; NCONTROL = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (NHIGH-SCZ-PRS = 95; NLOW-SCZ-PRS = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: β = 0.62, P < 0.001; Study 2: β = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: β = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual’s patterns of structural brain-wide alterations.

Objective: 22q11.2 deletion syndrome (22q11DS) is among the strongest known genetic risk factors for schizophrenia. Previous studies have reported variable alterations in subcortical brain structures in 22q11DS. To better characterize subcortical alterations in 22q11DS, including modulating effects of clinical and genetic heterogeneity, the authors studied a large multicenter neuroimaging cohort from the ENIGMA 22q11.2 Deletion Syndrome Working Group. Methods: Subcortical structures were measured using harmonized protocols for gross volume and subcortical shape morphometry in 533 individualswith 22q11DS and 330matched healthy control subjects (age range, 6-56 years; 49% female). Results: Compared with the control group, the 22q11DS group showed lower intracranial volume (ICV) and thalamus, putamen, hippocampus, and amygdala volumes and greater lateral ventricle, caudate, and accumbens volumes (Cohen's d values, 20.90 to 0.93). Shape analysis revealed complex differences in the 22q11DS group across all structures. The larger A-D deletion was associated with more extensive shape alterations compared with the smaller A-B deletion. Participants with 22q11DS with psychosis showed lower ICV and hippocampus, amygdala, and thalamus volumes (Cohen's d values, 20.91 to 0.53) compared with participants with 22q11DS without psychosis. Shape analysis revealed lower thickness and surface area across subregions of these structures. Compared with subcortical findings from other neuropsychiatric disorders studied by the ENIGMA consortium, significant convergence was observed between participants with 22q11DS with psychosis and participants with schizophrenia, bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. Conclusions: In the largest neuroimaging study of 22q11DS to date, the authors found widespread alterations to subcortical brain structures, which were affected by deletion size and psychotic illness. Findings indicate significant overlap between 22q11DS-associated psychosis, idiopathic schizophrenia, and other severe neuropsychiatric illnesses.

BackgroundIt is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies.MethodsAssociations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes.ResultsThe schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses.ConclusionsOur study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.

ENIGMA-CNV Working Group: van der Meer, Dennis; Sonderby, Ida E; Kaufmann, Tobias; Walters, G Bragi; Abdellaoui, Abdel; Ames, David; Amunts, Katrin; Andersson, Micael; Armstrong, Nicola J; Bernard, Manon; Blackburn, Nicholas B; Blangero, John; Boomsma, Dorret I; Brodaty, Henry; Brouwer, Rachel M; Bulow, Robin; Cahn, Wiepke; Calhoun, Vince D; Caspers, Svenja; Cavalleri, Gianpiero L; Ching, Christopher R K; Cichon, Sven; Ciufolini, Simone; Corvin, Aiden; Crespo-Facorro, Benedicto; Curran, Joanne E; Dalvie, Shareefa; Dazzan, Paola; de Geus, Eco J C; de Zubicaray, Greig I; de Zwarte, Sonja M C; Delanty, Norman; den Braber, Anouk; Desrivieres, Sylvane; Di Forti, Marta; Doherty, Joanne L; Donohoe, Gary; Ehrlich, Stefan; Eising, Else; Espeseth, Thomas; Fisher, Simon E; Fladby, Tormod; Frei, Oleksandr; Frouin, Vincent; Fukunaga, Masaki; Gareau, Thomas; Glahn, David C; Grabe, Hans J; Groenewold, Nynke A; Gustafsson, Omar; Haavik, Jan; Haberg, Asta K; Hashimoto, Ryota; Hehir-Kwa, Jayne Y; Hibar, Derrek P; Hillegers, Manon H J; Hoffmann, Per; Holleran, Laurena; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E; Ikeda, Masashi; Jacquemont, Sebastien; Jahanshad, Neda; Jockwitz, Christiane; Johansson, Stefan; Jonsson, Erik G; Kikuchi, Masataka; Knowles, Emma E M; Kwok, John B; Le Hellard, Stephanie; Linden, David E J; Liu, Jingyu; Lundervold, Arvid; Lundervold, Astri J; Martin, Nicholas G; Mather, Karen A; Mathias, Samuel R; McMahon, Katie L; McRae, Allan F; Medland, Sarah E; Moberget, Torgeir; Moreau, Clara; Morris, Derek W; Muhleisen, Thomas W; Murray, Robin M; Nordvik, Jan E; Nyberg, Lars; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Michael J; Paus, Tomas; Pausova, Zdenka; Peralta, Juan M; Pike, Bruce; Prieto, Carlos; Quinlan, Erin Burke; Reinbold, Celine S; Reis Marques, Tiago; Rucker, James J H; Sachdev, Perminder S; Sando, Sigrid B; Schofield, Peter R; Schork, Andrew J; Schumann, Gunter; Shin, Jean; Shumskaya, Elena; Silva, Ana I; Sisodiya, Sanjay M; Steen, Vidar M; Stein, Dan J; Strike, Lachlan T; Tamnes, Christian K; Teumer, Alexander; Thalamuthu, Anbupalam; Tordesillas-Gutierrez, Diana; Uhlmann, Anne; Ulfarsson, Magnus O; van 't Ent, Dennis; van den Bree, Marianne B M; Vassos, Evangelos; Wen, Wei; Wittfeld, Katharina; Wright, Margaret J; Zayats, Tetyana; Dale, Anders M; Djurovic, Srdjan; Agartz, Ingrid; Westlye, Lars T; Stefansson, Hreinn; Stefansson, Kari; Thompson, Paul M; Andreassen, Ole A., [Importance] Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities., [Objective] To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance., [Design, Setting, and Participants] In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019., [Main Outcomes and Measures] The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort., [Results] Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = −0.41; SE, 0.08; P = 4.9 × 10−8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10−7), and a smaller nucleus accumbens (Cohen d = −0.27; SE, 0.07; P = 7.3 × 10−5). There was also a significant negative dose response on cortical thickness (β = −0.24; SE, 0.05; P = 6.8 × 10−7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks., [Conclusions and Relevance] These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders., This study is supported in part by grants U54 EB20403, R01MH116147, and R56AG058854 from the National Institutes of Health, grant 609020 from the European Union Seventh Framework Programme, and grants 223273 and 276082 from the Research Council Norway. Part of this work was performed using the Service for Sensitive Data (TSD), which is developed and operated by the TSD Service Groupand owned by the University of Oslo.

Gamma oscillations (30–90 Hz) have been proposed as a signature of cortical visual information processing, particularly the balance between excitation and inhibition, and as a biomarker of neuropsychiatric diseases. Magnetoencephalography (MEG) provides highly reliable visual-induced gamma oscillation estimates, both at sensor and source level. Recent studies have reported a deficit of visual gamma activity in schizophrenia patients, in medication naive subjects, and high-risk clinical participants, but the genetic contribution to such a deficit has remained unresolved. Here, for the first time, we use a genetic risk score approach to assess the relationship between genetic risk for schizophrenia and visual gamma activity in a population-based sample drawn from a birth cohort. We compared visual gamma activity in a group (N = 104) with a high genetic risk profile score for schizophrenia (SCZ-PRS) to a group with low SCZ-PRS (N = 99). Source-reconstructed V1 activity was extracted using beamformer analysis applied to MEG recordings using individual MRI scans. No group differences were found in the induced gamma peak amplitude or peak frequency. However, a non-parametric statistical contrast of the response spectrum revealed more robust group differences in the amplitude of high-beta/gamma power across the frequency range, suggesting that overall spectral shape carries important biological information beyond the individual frequency peak. Our findings show that changes in gamma band activity correlate with liability to schizophrenia and suggest that the index changes to synaptic function and neuronal firing patterns that are of pathophysiological relevance rather than consequences of the disorder.

Polygenicity and pleiotropy are key properties of the genomic architecture of psychiatric disorders. An optimistic interpretation of polygenicity is that genomic variants converge on a limited set of mechanisms at some level from genes to behavior. Alternatively, convergence may be minimal or absent.We took advantage of brain connectivity, measured by resting-state functional MRI (rs- fMRI), as well as rare and common genomic variants to understand the effects of polygenicity and pleiotropy on large-scale brain networks, a distal step from genes to behavior. We processed ten rs-fMRI datasets including 32,988 individuals, to examine connectome-wide effects of 16 copy number variants (CNVs), 10 polygenic scores, 6 cognitive and brain morphometry traits, and 4 idiopathic psychiatric conditions.Although effect sizes of CNVs on connectivity were correlated to cognition and number of genes, increasing polygenicity was associated with decreasing effect sizes on connectivity. Accordingly, the effect sizes of polygenic scores on connectivity were 6-fold lower compared to CNVs. Despite this heterogeneity of connectivity profiles, multivariate analysis identified convergence of genetic risks and psychiatric disorders on the thalamus and the somatomotor network. Based on spatial correlations with transcriptomic data, we hypothesize that excitatory thalamic neurons may be primary contributors to brain alteration profiles shared across genetic risks and conditions. Finally, pleiotropy measured by genetic and transcriptomic correlations between 38 pairs of conditions/traits showed significant concordance with connectomic correlations, suggesting a substantial causal genetic component for shared connectivity.Such findings open avenues to delineate general mechanisms - amenable to intervention - across conditions and genetic risks.One sentence summaryEffects of rare and common genomic variants on brain functional connectivity shed light on the impact of polygenicity and pleiotropy in psychiatry.

Highlights • Randomized clinical trial with a novel self-neuromodulation training in PTSD. • Demonstration of feasibility of an fMRI-informed EEG model of Amygdala modulation (AmygEFP). • Individually-tailored trauma-related content as the training feedback interface. • Results showed reduction of PTSD symptoms following AmygEFP trauma-related feedback training., Background Amygdala activity dysregulation plays a central role in post-traumatic stress disorder (PTSD). Hence learning to self-regulate one's amygdala activity may facilitate recovery. PTSD is further characterized by abnormal contextual processing related to the traumatic memory. Therefore, provoking the personal traumatic narrative while training amygdala down-regulation could enhance clinical efficacy. We report the results of a randomized controlled trial (NCT02544971) of a novel self-neuromodulation procedure (i.e. NeuroFeedback) for PTSD, aimed at down-regulating limbic activity while receiving feedback from an auditory script of a personal traumatic narrative. To scale-up applicability, neural activity was probed by an fMRI-informed EEG model of amygdala activity, termed Amygdala Electrical Finger-Print (AmygEFP). Methods Fifty-nine adults meeting DSM-5 criteria for PTSD were randomized between three groups: Trauma-script feedback interface (Trauma-NF) or Neutral feedback interface (Neutral-NF), and a control group of No-NF (to control for spontaneous recovery). Before and immediately after 15 NF training sessions patients were blindly assessed for PTSD symptoms and underwent one session of amygdala fMRI-NF for transferability testing. Follow-up clinical assessment was performed at 3- and 6-months following NF treatment. Results Patients in both NF groups learned to volitionally down-regulate AmygEFP signal and demonstrated a greater reduction in PTSD symptoms and improved down-regulation of the amygdala during fMRI-NF, compared to the No-NF group. The Trauma-NF group presented the largest immediate clinical improvement. Conclusions This proof-of-concept study indicates the feasibility of the AmygEFP-NF process-driven as a scalable intervention for PTSD and illustrates its clinical potential. Further investigation is warranted to elucidate the contribution of AmygEFP-NF beyond exposure and placebo effects.

Pathological personality traits are an important inhibitor of social functioning and well-being. Individual human values also possess important connections to both personality and well-being, but the links between human values and pathological personality traits have not been directly examined. Across two studies (N = 478), we provide the first direct examination of these relations by employing linear and sinusoidal methodologies assessing relations between Schwartz's circular model of human values (Schwartz, 1992) and a series of personality measures, including the Personality Inventory for the DSM-5 (e.g., Callousness, Intimacy avoidance, Rigid perfectionism). Data for Study 1 was collected in Germany and data for Study 2 in the UK. Self-transcendence values buffer against several pathological personality traits that constrain psychological well-being (e.g., callousness). Conversely, self-enhancement values (which are motivationally opposite to self-transcendence values in Schwartz's circular model of human values) were positively associated with these personality traits. Several pathological personality traits were related to the 10 value types in a sinusoidal waveform that was consistent with Schwartz's circular model of human values. Findings were overall consistent across samples from both countries. The results help us move closer to distinguishing between different processes underpinning the associations between personality traits and human values.

BackgroundWhile genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. Despite this, few studies have investigated electrophysiological activity and connectivity in this high-risk group.MethodsMagnetoencephalography (MEG) was used to investigate resting-state cortical oscillatory patterns in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, IQ and neurodevelopmental symptoms.ResultsChildren with 22q11.2DS had atypical oscillatory activity and functional connectivity across multiple frequency bands. In the 22q11.2DS group, low frequency (alpha band) activity was positively associated with cognitive ability, while connectivity was negatively associated with ASD and ADHD symptoms. Frontal high frequency (gamma band) activity and connectivity were positively associated with ASD and ADHD symptoms respectively, while posterior gamma activity was negatively associated with ASD symptoms.ConclusionsThese findings highlight that haploinsufficiency at the 22q11.2 locus alters both local and long-range cortical circuitry, which could be a mechanism underlying neurodevelopmental vulnerability in this high risk group.

Background Impulsive and irritable behaviour have been reported in HD from the earliest clinical descriptions of the condition, and abnormalities on various measures of impulsive behaviour have been demonstrated. However these studies had small sample sizes, and did not account for potential confounding effects in the HD population such as IQ and medication. Furthermore, the links between impulsive and irritable behaviour in HD remain unclear. Aims Determine which cognitive mechanisms contribute to irritable behaviour in HD Determine which aspects of impulsive behaviour are seen in HD Methods/Techniques We recruited HD patients and familial controls from the South Wales HD Service and performed a battery of established and novel cognitive tasks, including questionnaire measures of impulsive behavour and irritability (UPPSP, Barrett Impulsivity Scale, PBAs and Snaith), motor inhibition (stop signal task), delay discounting (Kirby instrument) and cognitive impulsivity (Iowa Gambling task). We also performed tasks of provocation (a previously reported task, and a novel task) to determine the relative contributions of impaired inhibition and excessive response to provocation in mediating irritability in HD. Results We recruited 51 HD patients and 26 controls. We found differences in response to provocation and also impaired motor inhibition on the stop signal task in the HD population, even after correcting for relevant confounders such as IQ, medication, motor impairment and psychiatric comorbidity. However, only the response to provocation was associated with irritability in HD. The tasks of delay discounting, and cognitive impulsivity did not demonstrate any differences between HD patients and controls after controlling for relevant confounders. Conclusions Irritability in HD is mediated by excessive response to provocation rather than the known impairments in motor inhibition. Other aspects of impulsivity to contribute to impulsive behaviour in HD.

Background\ud Copy number variations at the 15q11.2 BP1-BP2 locus are present in 0.5%–1.0% of the population, and the deletion is associated with several neurodevelopmental disorders. Previously, we showed a reciprocal effect of 15q11.2 copy number variation on fractional anisotropy, with widespread increases in deletion carriers. We aim to expand these findings using a larger sample of participants (N = 29,166) and higher resolution imaging and by examining the implications for cognitive performance.\ud Methods\ud Diffusion tensor imaging measures from participants with no neurological or psychiatric diagnoses were obtained from the UK Biobank database. We compared 15q11.2 BP1-BP2 deletion (n = 102) and duplication (n = 113) carriers to a large cohort of control individuals with no neuropsychiatric copy number variants (n = 28,951). Additionally, we assessed how changes in white matter mediated the association between carrier status and cognitive performance.\ud Results\ud Deletion carriers showed increases in fractional anisotropy in the internal capsule and cingulum and decreases in the posterior thalamic radiation compared with both duplication carriers and control subjects (who had intermediate values). Compared with control subjects, deletion carriers had lower scores across cognitive tasks, which were partly influenced by white matter. Reduced fractional anisotropy in the posterior thalamic radiation partially contributed to worse cognitive performance in deletion carriers.\ud Conclusions\ud These results, together with our previous findings, provide convergent evidence for an effect of 15q11.2 BP1-BP2 on white matter microstructure, this being more pronounced in deletion carriers. Additionally, changes in white matter were found to partially mediate cognitive ability in deletion carriers, providing a link between white matter changes in 15q11.2 BP1-BP2 carriers and cognitive function.

Introduction: Alcohol dependence is one of the most common substance use disorders, and novel treatment options are urgently needed. Neurofeedback training (NFT) based on real-time functional magnetic resonance imaging (rtf­MRI) has emerged as an attractive candidate for add-on treatments in psychiatry, but its use in alcohol dependence has not been formally investigated in a clinical trial. We investigated the use of rtfMRI-based NFT to prevent relapse in alcohol dependence. Methods: Fifty-two alcohol-dependent patients from the UK who had completed a detoxification program were randomly assigned to a treatment group (receiving rtfMRI NFT in addition to standard care) or the control group (receiving standard care only). At baseline, alcohol consumption was assessed as the primary outcome measure and a variety of psychological, behavioral, and neural parameters as secondary outcome measures to determine feasibility and secondary training effects. Participants in the treatment group underwent 6 NFT sessions over 4 months and were trained to downregulate their brain activation in the salience network in the presence of alcohol stimuli and to upregulate frontal activation in response to pictures related to positive goals. Four, 8, and 12 months after baseline assessment, both groups were followed up with a battery of clinical and psychometric tests. Results: Primary outcome measures showed very low relapse rates for both groups. Analysis of neural secondary outcome measures indicated that the majority of patients modulated the salience system in the desired directions, by decreasing activity in response to alcohol stimuli and increasing activation in response to positive goals. The intervention had a good safety and acceptability profile. Conclusion: We demonstrated that rtfMRI-neurofeedback targeting hyperactivity of the salience network in response to alcohol cues is feasible in currently abstinent patients with alcohol dependence.

IntroductionIlluminating neurobiological mechanisms underlying the protective effect of recently discovered common genetic resilience variants for schizophrenia is crucial for more effective prevention efforts. Current models implicate adaptive neuroplastic changes in the visual system and their pro-cognitive effects as a schizophrenia resilience mechanism. We investigated whether common genetic resilience variants might affect brain structure in similar neural circuits.MethodUsing structural magnetic resonance imaging, we measured the impact of an established schizophrenia polygenic resilience score (PRSResilience) on cortical volume, thickness, and surface area in 101 healthy subjects and in a replication sample of 33,224 healthy subjects (UK Biobank).FindingWe observed a significant positive whole-brain correlation between PRSResilience and cortical volume in the right fusiform gyrus (FFG) (r=0.35; p=.0004). Post-hoc analyses in this cluster revealed an impact of PRSResilience on cortical surface area. The replication sample showed a positive correlation between PRSResilience and global cortical volume and surface area in the left FFG.ConclusionOur findings represent the first evidence of a neurobiological correlate of a genetic resilience factor for schizophrenia. They support the view that schizophrenia resilience emerges from strengthening neural circuits in the ventral visual pathway and an increased capacity for the disambiguation of social and non-social visual information. This may aid psychosocial functioning, ameliorate the detrimental effects of subtle perceptual and cognitive disturbances in at-risk individuals, and facilitate coping with the cognitive and psychosocial consequences of stressors. Our results thus provide a novel link between visual cognition, the vulnerability-stress concept and schizophrenia resilience models.

Copy number variants are amongst the most highly penetrant risk factors for psychopathology and neurodevelopmental deficits, but little information about the detailed clinical phenotype associated with particular variants is available. We present the largest study of the microdeletion and -duplication at the distal 1q21 locus, which has been associated with schizophrenia and intellectual disability, in order to investigate the range of psychiatric phenotypes. Clinical and cognitive data from 68 deletion and 55 duplication carriers were analysed with logistic regression analysis to compare frequencies of mental disorders between carrier groups and controls, and linear mixed models to compare quantitative phenotypes. Both children and adults with copy number variants at 1q21 had high frequencies of psychopathology. In the children, neurodevelopmental disorders were most prominent (56% for deletion, 68% for duplication carriers). Adults had increased prevalence of mood (35% for deletion [OR = 6.6 (95% CI: 1.4-40.1)], 55% for duplication carriers [8.3 (1.4-55.5)]) and anxiety disorders (24% [1.8 (0.4-8.4)] and 55% [10.0 (1.9-71.2)]). The adult group, which included mainly genetically affected parents of probands, had an IQ in the normal range. These results confirm high prevalence of neurodevelopmental disorders associated with CNVs at 1q21 but also reveal high prevalence of mood and anxiety disorders in a high-functioning adult group with these CNVs. Because carriers of neurodevelopmental CNVs who show relevant psychopathology but no major cognitive impairment are not currently routinely receiving clinical genetic services widening of genetic testing in psychiatry may be considered.

Background: Apathy is a deficit in goal‐directed behavior that significantly affects quality of life and function. It is common in Huntington's disease and other disorders affecting corticostriatal pathways. Deficits in processing of reward, altered effort, and executive dysfunction are associated with apathy in other disorders, but the cognitive processes leading to apathy in Huntington's disease remain largely unknown. A previously reported deficit in learning from losses in Huntington's disease raises the possibility of a hitherto unrecognized mechanism leading to apathy. This study's objective was to delineate the cognitive processes associated with apathy in HD. Methods: We tested 51 Huntington's disease participants and 26 controls on a battery of novel and established measures to assess the contribution to apathy in Huntington's disease of executive function, reward value, reward‐effort calculations, instrumental learning, and response to reward and loss. Results: Huntington's disase participants had deficits in instrumental learning with impaired response to loss, but no evidence to suggest altered reward‐related behavior or effort. We also saw an executive dysfunction contribution to apathy in Huntington's disease. Discussion: We report the novel finding that apathy in Huntington's disease is associated with blunted responses to losses and impaired instrumental learning. This association is consistent with the known early degeneration of the indirect pathway and amygdala involvement in apathy in Huntington's disease, but is previously unreported in any disorder. In keeping with the comparative preservation of the ventral striatum and orbitofrontal cortex in Huntington's disease, reward valuation and reward‐effort calculations did not contribute to apathy. © 2019 International Parkinson and Movement Disorder Society

BackgroundYoung people with 22q11.2 deletion syndrome (22q11.2DS) are at high risk for neurodevelopmental disorders. Sleep problems may play a role in this risk but their prevalence, nature and links to psychopathology and cognitive function remain undescribed in this population.MethodSleep problems, psychopathology, developmental coordination and cognitive function were assessed in 140 young people with 22q11.2DS (mean age = 10.1, s.d. = 2.46) and 65 unaffected sibling controls (mean age = 10.8, s.d.SD = 2.26). Primary carers completed questionnaires screening for the children's developmental coordination and autism spectrum disorder.ResultsSleep problems were identified in 60% of young people with 22q11.2DS compared to 23% of sibling controls (OR 5.00, p < 0.001). Two patterns best-described sleep problems in 22q11.2DS: restless sleep and insomnia. Restless sleep was linked to increased ADHD symptoms (OR 1.16, p < 0.001) and impaired executive function (OR 0.975, p = 0.013). Both patterns were associated with elevated symptoms of anxiety disorder (restless sleep: OR 1.10, p = 0.006 and insomnia: OR 1.07, p = 0.045) and developmental coordination disorder (OR 0.968, p = 0.0023, and OR 0.955, p = 0.009). The insomnia pattern was also linked to elevated conduct disorder symptoms (OR 1.53, p = 0.020).ConclusionsClinicians and carers should be aware that sleep problems are common in 22q11.2DS and index psychiatric risk, cognitive deficits and motor coordination problems. Future studies should explore the physiology of sleep and the links with the neurodevelopment in these young people.

Autism spectrum disorder is characterized by abnormal function in core social brain regions. Here, we demonstrate the feasibility of real-time functional magnetic resonance imaging volitional neurofeedback. Following up the demonstration of neuromodulation in healthy participants, in this repeated-measure design clinical trial, 15 autism spectrum disorder patients were enrolled in a 5-session training program of real-time functional magnetic resonance imaging neurofeedback targeting facial emotion expressions processing, using the posterior superior temporal sulcus as region-of-interest. Participants were able to modulate brain activity in this region-of-interest, over multiple sessions. Moreover, we identified the relevant clinical and neural effects, as documented by whole-brain neuroimaging results and neuropsychological measures, including emotion recognition of fear, immediately after the intervention and persisting after 6 months. Neuromodulation profiles demonstrated subject-specificity for happy, sad, and neutral facial expressions, an unsurprising variable pattern in autism spectrum disorder. Modulation occurred in negative or positive directions, even for neutral faces, in line with their often-perceived ambiguity in autism spectrum disorder. Striatal regions (associated with success/failure of neuromodulation), saliency (insula/anterior cingulate cortex), and emotional control (medial prefrontal cortex) networks were recruited during neuromodulation. Recruitment of the operant learning network is consistent with participants’ engagement. Compliance, immediate intervention benefits, and their persistence after 6 months pave the way for a future Phase IIb/III, randomized controlled clinical trial, with a larger sample that will allow to conclude on clinical benefits from neurofeedback training in autism spectrum disorder (NCT02440451). Lay abstract Neurofeedback is an emerging therapeutic approach in neuropsychiatric disorders. Its potential application in autism spectrum disorder remains to be tested. Here, we demonstrate the feasibility of real-time functional magnetic resonance imaging volitional neurofeedback in targeting social brain regions in autism spectrum disorder. In this clinical trial, autism spectrum disorder patients were enrolled in a program with five training sessions of neurofeedback. Participants were able to control their own brain activity in this social brain region, with positive clinical and neural effects. Larger, controlled, and blinded clinical studies will be required to confirm the benefits.

Background: Non-invasive neurofeedback training is currently explored as a potential add-on therapy to treat patients suffering from major depressive disorder, and first trials show promising clin-ical effects. The temporal evolution of therapeutic change, however, remains unclear. Methods: Profile of mood states (POMS) questionnaire ratings were collected immediately before and after five sessions of real-time fMRI neurofeedback training (rt-fMRI-NFT) in a randomised controlled trial (RCT). Data were analysed for within and between treatment sessions ef-fects. Results: Trajectories of mood profiles varied between subscales. Total mood disturbance and the subscales depression and tension showed both within and between treatment sessions ef-fects, although within-session effects were descriptively larger. Limitations: The sample size was relatively small owed to the current state of the rt-fMRI-NFT field. No data from a sham-neurofeedback control group was available. Conclusions: The presented data provides a better understanding of when changes in mood states occur. The POMS questionnaire allows monitoring rapid and slowly evolving changes in mood states and can thus inform future study designs for neuromodulation and psychological in-terventions for mental disorders.

Copy Number Variation (CNV) at the 1q21.1 locus is associated with a range of neurodevelopmental and psychiatric disorders in humans, including abnormalities in head size and motor deficits. Yet, the functional consequences of these CNVs (both deletion and duplication) on neuronal development remain unknown. To determine the impact of CNV at the 1q21.1 locus on neuronal development, we generated induced pluripotent stem cells from individuals harbouring 1q21.1 deletion or duplication and differentiated them into functional cortical neurons. We show that neurons with 1q21.1 deletion or duplication display reciprocal phenotype with respect to proliferation, differentiation potential, neuronal maturation, synaptic density, and functional activity. Deletion of the 1q21.1 locus was also associated with an increased expression of lower cortical layer markers. This difference was conserved in the mouse model of 1q21.1 deletion, which displayed altered corticogenesis. Importantly, we show that neurons with 1q21.1 deletion and duplication are associated with differential expression of calcium channels and demonstrate that physiological deficits in neurons with 1q21.1 deletion or duplication can be pharmacologically modulated by targeting Ca2+ channel activity. These findings provide biological insight into the neuropathological mechanism underlying 1q21.1 associated brain disorder and indicate a potential target for therapeutic interventions.

Copy number variants are amongst the most highly penetrant risk factors for psychopathology and neurodevelopmental deficits, but little information about the detailed clinical phenotype associated with particular variants is available. We present the largest study of the microdeletion and -duplication at the distal 1q21 locus, which has been associated with schizophrenia and intellectual disability, in order to investigate the range of psychiatric phenotypes. Clinical and cognitive data from 68 deletion and 55 duplication carriers were analysed with logistic regression analysis to compare frequencies of mental disorders between carrier groups and controls, and linear mixed models to compare quantitative phenotypes. Both children and adults with copy number variants at 1q21 had high frequencies of psychopathology. In the children, neurodevelopmental disorders were most prominent (56% for deletion, 68% for duplication carriers). Adults had increased prevalence of mood (35% for deletion [OR = 6.6 (95% CI: 1.4–40.1)], 55% for duplication carriers [8.3 (1.4–55.5)]) and anxiety disorders (24% [1.8 (0.4–8.4)] and 55% [10.0 (1.9–71.2)]). The adult group, which included mainly genetically affected parents of probands, had an IQ in the normal range. These results confirm high prevalence of neurodevelopmental disorders associated with CNVs at 1q21 but also reveal high prevalence of mood and anxiety disorders in a high-functioning adult group with these CNVs. Because carriers of neurodevelopmental CNVs who show relevant psychopathology but no major cognitive impairment are not currently routinely receiving clinical genetic services widening of genetic testing in psychiatry may be considered.

ENIGMA-CNV working group., Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function., 1000BRAINS: The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 945539 (Human Brain Project SGA3; Amunts, Caspers, Cichon). Brainscale: The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret I. Boomsma), 51.02.060 (Hilleke E. Hulshoff Pol), 668.772 (Dorret I. Boomsma and Hilleke E. Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret I. Boomsma), the European Research Council (ERC-230374) (Dorret I. Boomsma), High Potential Grant Utrecht University (Hilleke E.Hulshoff Pol) and NWO Brain and Cognition 433-09-220 (Hilleke E.Hulshoff Pol). Betula: The Betula study was funded by the Knut and Alice Wallenberg (KAW) foundation (Nyberg). The Freesurfer segmentations on the Betula sample were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N (in Umeå, Sweden), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers from the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud University Medical Centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received support from the participating departments and centres and from external grants, that is, the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland and the Netherlands Organization for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 602450 (IMAGEMEND), 278948 (TACTICS) and 602805 (Aggressotype), as well as from the European Community’s Horizon 2020 programme under grant agreement no. 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. deCODE genetics: deCODE genetics acknowledges support from the Innovative Medicines Initiative Joint Undertaking under grant agreement nos. 115008 (NEWMEDS) and 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007-2013), EU-FP7-funded grant agreement no. 602450 (IMAGEMEND) and EU-funded FP7-People-2011-IAPP grant agreement no. 286213 (PsychDPC). Dublin: This work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and grant SFI08/IN.1/B1916-Corvin to Aidan C. Corvin). ECHO-DEFINE: The ECHO study acknowledges funding from a Medical Research Council (MRC) Centre Grant to Michael J. Owen (G0801418), the Wellcome Trust (Institutional Strategic Support Fund (ISSF) to van den Bree and Clinical Research Training Fellowship to Joanne L. Doherty), the Waterloo Foundation (WF 918-1234 to van den Bree), the Baily Thomas Charitable Fund (2315/1 to van den Bree), National Institute of Mental Health (NIMH 5UO1MH101724 to van den Bree and Michael J. Owen), the IMAGINE-2 study (funded by the MRC (MR/T033045/1) to van den Bree, Jeremy Hall and Michael J. Owen), the IMAGINE-ID study (funded by MRC (MR/N022572/1) to Jeremy Hall, van den Bree and Owen). The DEFINE study was supported by a Wellcome Trust Strategic Award (100202/Z/12/Z) to Michael J. Owen. ENIGMA: ENIGMA is supported in part by NIH grants U54 EB20403, R01MH116147 and R56AG058854. NIA T32AG058507; NIH/NIMH 5T32MH073526. EPIGEN-Dublin: The EPIGEN-Dublin cohort was supported by a Science Foundation Ireland Research Frontiers Programme award (08/RFP/GEN1538). EPIGEN-UK (Sisodiya): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner. GAP: This work was supported by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. GOBS: The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111 and R01 MH083824, with work conducted in part in facilities constructed under the support of NIH grant C06 RR020547. GSP: Data were in part provided by the Brain Genomics Superstruct Project (GSP) of Harvard University and Massachusetts General Hospital (MGH) (Principal Investigators: Randy Buckner, Jordan Smoller and Joshua Roffman), with support from the Center for Brain Science Neuroinformatics Research Group, Athinoula A. Martinos Center for Biomedical Imaging, Center for Genomic Medicine and Stanley Center for Psychiatric Research. Twenty individual investigators at Harvard and MGH generously contributed data to the overall project. We would like to thank Randy Buckner for insightful comments and feedback on this work. HUBIN: The HUBIN study was financed by the Swedish Research Council (K2010-62X-15078-07-2, K2012-61X-15078-09-3, 521-2014-3487 K2015-62X-15077-12-3, 2017-00949), the regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet. HUNT: The HUNT study is a collaboration between HUNT Research Centre (Faculty of Medicine and Movement Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), Human Brain Project (HBP SGA 2, 785907),the FP7 projects IMAGEMEND(602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EUAIMS (115300-2), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152, 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL 01EE1406A, 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants, SM 80/7-2, SFB 940/2), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, ANR-12-SAMA-0004), the Eranet Neuron (ANR-18-NEUR00002-01), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1) and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. Lifespan: The study is funded by the Research Council of Norway (230345, 288083 and 223273). NCNG: NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the Research Council of Norway, to le Hellard, Steen and Espeseth. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to Arvid Lundervold, Grant 911397 and 911687 to Astri Johansen Lundervold). NTR: The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organisation for Health Research and Development (ZonMW) grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004,463-06-001, 451-04-034, 400-05-717, Addiction-31160008, 016-115-035, 481-08-011, 056-32-010, Middelgroot-911-09-032, OCW_NWO Gravity programme—024.001.003, NWO-Groot 480-15-001/674, Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007 and 184.033.111); Spinozapremie (NWO-56-464-14192), KNAW Academy Professor Award (PAH/6635) and University Research Fellow grant (URF) to Dorret I. Boomsma; Amsterdam Public Health research institute (former EMGO+), Neuroscience Amsterdam research institute (former NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Programme (FP7- HEALTH-F4-2007-2013, grant 01413: ENGAGE and grant 602768: ACTION); the European Research Council (ERC Starting 284167, ERC Consolidator 771057, ERC Advanced 230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the National Institutes of Health (NIH, R01D0042157-01A1, R01MH58799-03, MH081802, DA018673, R01 DK092127-04, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by NWO through grant 2018/EW/00408559, BiG Grid, the Dutch e-Science Grid and SURFSARA. OATS: The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Ageing Well, Ageing Productively Programme (ID No. 401162) and NHMRC Project Grants (ID Nos. 1045325 and 1085606). This research was facilitated through Twins Research Australia, a national resource in part supported by an NHMRC Centre for Research Excellence Grant (ID No.: 1079102). We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organization Flagship Collaboration Fund Grant. Osaka: Osaka study was supported by the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS: Grant Number JP18dm0207006), Brain/MINDS& beyond studies (Grant Number JP20dm0307002) and Health and Labour Sciences Research Grants for Comprehensive Research on Persons with Disabilities (Grant Number JP20dk0307081) from the Japan Agency for Medical Research and Development (AMED), Grants-in-Aid for Scientific Research (KAKENHI; Grant Numbers JP25293250 and JP16H05375). Some computations were performed at the Research Center for Computational Science, Okazaki, Japan. PAFIP: The PAFIP study was supported by Instituto de Salud Carlos III, FIS 00/3095, 01/3129, PI020499, PI060507, PI10/00183, the SENY Fundació Research Grant CI2005-0308007 and the FundaciónMarqués de Valdecilla API07/011. Biological samples from our cohort were stored at the Valdecilla Biobank and genotyping services were conducted at the Spanish ‘Centro Nacional de Genotipado’ (CEGEN-ISCIII). MCIC/COBRE: The study is funded by the National Institutes of Health studies R01EB006841, P20GM103472 and P30GM122734 and Department of Energy DE-FG02-99ER62764. PING: Data collection and sharing for the Paediatric Imaging, Neurocognition and Genetics (PING) Study (National Institutes of Health Grant RC2DA029475) were funded by the National Institute on Drug Abuse and the Eunice Kennedy Shriver National Institute of Child Health & Human Development. A full list of PING investigators is at http://pingstudy.ucsd.edu/investigators.html. QTIM: The QTIM study was supported by the National Institute of Child Health and Human Development (R01 HD050735) and the National Health and Medical Research Council (NHMRC 486682, 1009064), Australia. Genotyping was supported by NHMRC (389875). Medland is supported in part by an NHMRC fellowship (APP1103623). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide single-nucleotide polymorphism typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. StrokeMRI: StrokeMRI was supported by the Norwegian ExtraFoundation for Health and Rehabilitation(2015/FO5146), the Research Council of Norway (249795, 262372), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Department of Psychology, University of Oslo. Sydney MAS: The Sydney Memory and Aging Study (Sydney MAS) is funded by National and HealthMedical Research Council (NHMRC) Programme and Project Grants (ID350833, ID568969 and ID109308). We also thank the Sydney MAS participants and the Research Team. SYS: The SYS Study is supported by Canadian Institutes of Health Research. TOP: Centre of Excellence: RCN #23273 and RCN #226971. Part of this work was performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT) (tsd-drift@usit.uio.no). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7-PEOPLE-2013-COFUND) under grant agreement no. 609020—Scientia Fellows; the Research Council of Norway (RCN) #276082—A lifespan perspective on mental illness: toward precision medicine using multimodal brain imaging and genetics. Ida E. Sønderby and Rune Bøen are supported by South-Eastern Norway Regional Health Authority (#2020060). Ida E. Sønderby and Ole A. Andreassen have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement no. 847776 (CoMorMent project) and the KG Jebsen Foundation (SKGJ-MED-021). UCLA_UMCU: The UCLA_UMCU cohort comprises of six studies which were supported by National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) (20244 to Prof. Hillegers), The Netherlands Organisation for Health Research and Development (ZonMw) (908-02-123 to Prof. Hulshoff Pol), and Netherlands Organisation for Scientific Research (NWO 9120818 and NWO-VIDI 917-46-370 to Prof. Hulshoff Pol). The GROUP study was funded through the Geestkracht programme of the Dutch Health Research Council (ZonMw, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly and Janssen Cilag) and universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ inGeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord-Holland-Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia Psycho-medical Center, The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh, voor Geestelijke Gezondheid, Mondriaan, Virenzeriagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-JozefKortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions: Altrecht, GGZ Centraal and Delta.). UK Biobank: This work made use of data sharing from UK Biobank (under project code 27412). Others: Work by Pierre Vanderhaeghen was funded by Grants of the European Research Council (ERC Adv Grant GENDEVOCORTEX), the EOS Programme, the Belgian FWO, the AXA Research Fund and the Belgian Queen Elizabeth Foundation. Ikuo K. Suzuki was supported by a postdoctoral fellowship of the FRS/FNRS.

Major depressive disorder (MDD) is the leading cause of disability worldwide. Neurofeedback training has been suggested as a potential additional treatment option for MDD patients not reaching remission from standard care (i.e., psychopharmacology and psychotherapy). Here we systematically reviewed neurofeedback studies employing electroencephalography, or functional magnetic resonance-based protocols in depressive patients. Of 585 initially screened studies, 24 were included in our final sample (N = 480 patients in experimental and N = 194 in the control groups completing the primary endpoint). We evaluated the clinical efficacy across studies and attempted to group studies according to the control condition categories currently used in the field that affect clinical outcomes in group comparisons. In most studies, MDD patients showed symptom improvement superior to the control group(s). However, most articles did not comply with the most stringent study quality and reporting practices. We conclude with recommendations on best practices for experimental designs and reporting standards for neurofeedback training.

The impact of human values on our choices depends on their nature. Self-Transcendence values motivate us to act for the benefit of others and care for the environment. Self-Enhancement values motivate us to act for our benefit. The present study examines differences in the neural processes underlying these two value domains. Extending our previous research, we used fMRI to explore first of all neural correlates of Self-Transcendence vs Self-Enhancement values, with a particular focus on the putative role of the medial prefrontal cortex (MPFC), which has been linked to a self-transcendent mind-set. Additionally, we investigated the neural basis of Openness to Change vs Conservation values. We asked participants to reflect on and rate values as guiding principles in their lives while undergoing fMRI. Mental processing of Self-Transcendence values was associated with higher brain activity in the dorsomedial (BA9, BA8) and ventromedial (BA10) prefrontal cortices, as compared to Self-Enhancement values. The former involved activation and the latter deactivation of those regions. We did not detect differences in brain activation between Openness to Change vs Conservation values. Self-Transcendence values thus shared brain regions with social processes that have previously been linked to a self-transcendent mind-set, and the "core self" representation.

Developments in neuroscience can have major implications both for jurisprudence and for the legal decision-making in individual cases. This chapter focuses on the current role of neuroscience in the evaluation of individual cases, including the determination of actus reus and mens rea, liability, punishment and prevention of re-offending. I argue that findings of neuroscience can play a major role in all these steps although often classical psychological or psychiatric methods will be even more important. I also urge caution against expecting too much from neuroscience and argue that the question whether to adopt a retributivist or a consequentialist stance is a philosophical one, and not one that neuroscience can answer.

Although rtfMRI-neurofeedback is a relatively young field, it has developed rapidly over its 20-year history. We broadly divide the history of the field into three phases. First, an early phase of methods development and exploratory studies conducted by a small number of research groups. Second, a phase of widening interest among the international neuroscience community, with an increasing number of studies into neural and behavioral effects of neurofeedback and the first clinical pilot studies. Third, beginning around 2012, a phase marked by the emergence of an international research community, as well as further technological development and growing interest from the clinical research community. We provide a selective review of this history based on our perspective and provide context, both in terms of developments of MR technology and analysis tools but also in terms of the wider scientific trends such as open science and an increasing focus on standardization and replicability.

22q11.2 deletion syndrome (22q11DS)—a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22—is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6–52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen’s d’s ranging from −0.9 to −1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers. Sin financiación 15.992 JCR (2020) Q1, 10/295 Biochemistry & Molecular Biology 5.071 SJR (2020) Q1, 5/85 Cellular and Molecular Neuroscience No data IDR 2020 UEM

Rare copy number variants associated with increased risk for neurodevelopmental and psychiatric disorders (referred to as ND-CNVs) are characterized by heterogeneous phenotypes thought to share a considerable degree of overlap. Altered neural integration has often been linked to psychopathology and is a candidate marker for potential convergent mechanisms through which ND-CNVs modify risk; however, the rarity of ND-CNVs means that few studies have assessed their neural correlates. Here, we used magnetoencephalography (MEG) to investigate resting-state oscillatory connectivity in a cohort of 42 adults with ND-CNVs, including deletions or duplications at 22q11.2, 15q11.2, 15q13.3, 16p11.2, 17q12, 1q21.1, 3q29, and 2p16.3, and 42 controls. We observed decreased connectivity between occipital, temporal, and parietal areas in participants with ND-CNVs. This pattern was common across genotypes and not exclusively characteristic of 22q11.2 deletions, which were present in a third of our cohort. Furthermore, a data-driven graph theory framework enabled us to successfully distinguish participants with ND-CNVs from unaffected controls using differences in node centrality and network segregation. Together, our results point to alterations in electrophysiological connectivity as a putative common mechanism through which genetic factors confer increased risk for neurodevelopmental and psychiatric disorders.

BackgroundCopy-number variations at the 15q11.2 BP1-BP2 locus are present in 0.5 to 1.0% of the population, and the deletion is associated with a range of neurodevelopmental disorders. Previously, we showed a reciprocal effect of 15q11.2 copy-number variation on fractional anisotropy, with widespread increases in deletion carriers. We aim to replicate and expand these findings, using a larger sample of participants (n=30,930), higher resolution imaging, and examining the implications for cognitive performance.MethodsDiffusion tensor imaging measures from participants with no neurological/psychiatric diagnoses were obtained from the UK Biobank database. We compared 15q11.2 BP1-BP2 deletion (n=103) and duplication (n=119) carriers to a large cohort of control individuals with no neuropsychiatric copy-number variants (n=29,870). Additionally, we assessed how changes in white matter mediated the association between carrier status and cognitive performance.ResultsDeletion carriers showed increases in fractional anisotropy in the internal capsule and cingulum, and decreases in the posterior thalamic radiation, compared to both duplication carriers and controls (who had intermediate values). Deletion carriers had lower scores across cognitive tasks compared to controls, which were mildly influenced by white matter alterations. Reduced fractional anisotropy in the posterior thalamic radiation partially contributed to worse cognitive performance in deletion carriers.ConclusionsThis study, together with our previous findings, provides convergent evidence for a dosage-dependent effect of 15q11.2 BP1-BP2 on white matter microstructure. Additionally, changes in white matter were found to partially mediate cognitive ability in deletion carriers, providing a link between white matter changes in 15q11.2 BP1-BP2 carriers and cognitive function.

Neuronal cell death and loss of synapses are hallmarks of the pathology of Alzheimer disease (AD). The incidence of AD increases with age, and both regional and global brain atrophies have been identified as pathological correlates. Thus, AD can, in many respects, be regarded as a paradigmatic neurodegenerative disorder. However, disrupted function of the presenilin genes, the most common cause of early-onset familial AD (FAD), can also affect brain development, including early processes of neuronal migration and morphogenesis.(1)

The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen’s d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = −1.01/−1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia.

An amendment to this paper has been published and can be accessed via the original article.

OBJECTIVE: The authors investigated the incidence, course, and outcome of psychotic experiences from childhood through early adulthood in the general population and examined prediction of psychotic disorder. METHODS: This was a population-based cohort study using the semistructured Psychosis-Like Symptoms Interview at ages 12, 18, and 24 (N=7,900 with any data). Incidence rates were estimated using flexible parametric modeling, and positive predictive values (PPVs), sensitivity, specificity, and area under the curve were estimated for prediction. RESULTS: The incidence rate of psychotic experiences increased between ages 13 and 24, peaking during late adolescence. Of 3,866 participants interviewed at age 24, 313 (8.1%, 95% CI=7.2, 9.0) had a definite psychotic experience since age 12. A total of 109 individuals (2.8%) met criteria for a psychotic disorder up to age 24, of whom 70% had sought professional help. Prediction of current psychotic disorder at age 24 (N=47, 1.2%), by both self-report and interviewer-rated measures of psychotic experiences at age 18 (PPVs, 2.9% and 10.0%, respectively), was improved by incorporating information on frequency and distress (PPVs, 13.3% and 20.0%, respectively), although sensitivities were low. The PPV of an at-risk mental state at age 18 predicting incident disorder at ages 18-24 was 21.1% (95% CI=6.1, 45.6) (sensitivity, 14.3%, 95% CI=4.0, 32.7). CONCLUSIONS: The study results show a peak in incidence of psychotic experiences during late adolescence as well as an unmet need for care in young people with psychotic disorders. Because of the low sensitivity, targeting individuals in non-help-seeking samples based only on more severe symptom cutoff thresholds will likely have little impact on population levels of first-episode psychosis.

Large effect-size mutations such as copy number variants (CNVs) have the potential to provide key insights into the underlying biological mechanisms linking deleterious genetic variants to brain architecture and neuropsychiatric disorders. To date, the effect of CNVs on functional brain connectivity remains mostly unstudied, and findings are derived from analyses conducted one mutation at a time. The lack of systematic cross-CNV comparisons hinders our understanding of any potential general mechanisms linking CNVs to effects on brain organization. We performed connectome-wide analyses using resting-state functional MRI data from 436 carriers of neuropsychiatric CNVs at the 1q21.1, 15q11.2, 16p11.2, 22q11.2 loci, and 4 neutral-effect CNVs, 66 carriers of scarcer neuropsychiatric CNVs, 756 individuals with idiopathic autism spectrum disorder (ASD), schizophrenia, attention deficit hyperactivity disorder, and 5,377 controls. Neuropsychiatric CNVs showed global shifts of mean connectivity. The effect size of CNVs on relative connectivity (adjusted for the mean) was correlated with the known level of neuropsychiatric risk conferred by CNVs. We reported architecture similarities between individuals with idiopathic psychiatric conditions and high-risk neuropsychiatric-CNVs, predominantly in the thalamus, the posterior cingulate cortex, and the anterior insula. We identified a linear relationship between connectivity and intolerance to haploinsufficiency measured for all genes encompassed by CNVs across 18 loci. This profile involved the thalamus, the basal ganglia, somatomotor and frontoparietal networks and was correlated with lower general intelligence and higher autism severity scores. An exploratory factor analysis confirmed the contribution of these regions to three latent components shared across CNVs and neuropsychiatric disorders. We posit that deleting genes intolerant to haploinsufficiency reorganize connectivity along general dimensions irrespective of where deletions occur in the genome. This haploinsufficiency brain signature opens new avenues to understand polygenicity in psychiatric conditions and the pleiotropic effect of CNVs on cognition and risk for neuropsychiatric disorders.

Neurofeedback is going through a renaissance. Advances in brain imaging and computing have renewed efforts to modify brain activity and behaviour using this technique. Here, over 80 neurofeedback researchers present a consensus-derived checklist – CRED-nf – for reporting and experimental design standards in the field., Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

IntroductionThe thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remains unknown. Our ability to identify causal genetic variants can be improved by employing better delineated, less noisy brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, i.e. lower polygenicity and higher discoverability.MethodsUsing Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area. We further determined the polygenicity and discoverability of regional cortical measures from five often-employed parcellation schemes. We made use of UK Biobank data from 31,312 healthy White European individuals (mean age 55.5, standard deviation (SD) 7.4, 52.1% female).ResultsContrary to previous reports, we found large genetic overlap between total surface area and mean thickness, sharing 4427 out of 7150 causal variants. Regional surface area was more discoverable (p=4.1×10−6) and less polygenic (p=.007) than regional thickness measures. We further found that genetically-informed and less granular parcellation schemes had highest discoverability, with no differences in polygenicity.ConclusionsThese findings may serve as a roadmap for improved future GWAS studies; Knowledge of which measures or parcellations are most discoverable, as well as the genetic overlap between these measures, may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

22q11.2 Deletion Syndrome (22q11.2DS) is associated with high risk of psychiatric disorders and cognitive impairment. It remains unclear to what extent key cognitive skills are associated with psychopathology, and whether cognition is stable over time in 22q11.2DS. 236 children, adolescents and adults with 22q11.2DS and 106 typically developing controls were recruited from three sites across Europe. Measures of IQ, processing speed, sustained attention, spatial working memory and psychiatric assessments were completed. Cognitive performance in individuals was calculated relative to controls in different age groups (children (6-9 years), adolescents (10-17 years), adults (18+ years)). Individuals with 22q11.2DS exhibited cognitive impairment and higher rates of psychiatric disorders compared to typically developing controls. Presence of Autism Spectrum Disorder symptoms was associated with greater deficits in processing speed, sustained attention and working memory in adolescents but not children. Attention deficit hyperactivity disorder in children and adolescents and psychotic disorder in adulthood was associated with sustained attention impairment. Processing speed and working memory were more impaired in children and adults with 22q11.2DS respectively, whereas the deficit in sustained attention was present from childhood and remained static over developmental stages. Psychopathology was associated with cognitive profile of individuals with 22q11.2DS in an age-specific and domain-specific manner. Furthermore, magnitude of cognitive impairment differed by developmental stage in 22q11.2DS and the pattern differed by domain. ispartof: TRANSLATIONAL PSYCHIATRY vol:10 issue:1 ispartof: location:United States status: published

Neurofeedback is emerging as an attractive new tool for psycho-physiological interventions in psychiatry. Over the past decade, progress has been made, particularly in the development and evaluation of neurofeedback protocols that use the blood oxygenation-dependent (BOLD) signal measured with functional magnetic resonance imaging (fMRI) as a target measure of brain activation. This chapter reviews the principles of neurofeedback training, with a focus on fMRI-protocols and the state of development of clinical applications in psychiatry and neurorehabilitation. In the context of this book, it is argued that neurofeedback can be regarded as a paradigmatic personalized therapy because it uses personalized neural targets, personalized stimulus material, and personalized homework or other adjunct elements. One challenge for future research will be to develop integrated treatment approaches that combine neurofeedback with psychological and behavioral interventions, and to evaluate them in randomized controlled trials.

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research. ENIGMA MDD work is supported by NIH grants U54 EB020403 (Thompson), R01 MH116147 (Thompson), and R01 MH117601 (Jahanshad & Schmaal). LS was supported by an NHMRC Career Development Fellowship (1140764). AFFDIS cohort: this study was funded by the University Medical Center Goettingen (UMG Startfoerderung) and the research team is supported by German Federal Ministry of Education and Research (Bundesministerium fuer Bildung und Forschung, BMBF: 01 ZX 1507, “PreNeSt - e:Med”). Barcelona cohort: MJP is funded by the Ministerio de Ciencia e Innovación of the Spanish Government and by the Instituto de Salud Carlos III through a ‘Miguel Servet’ research contract (CP16–0020); National Research Plan (Plan Estatal de I + D + I 2016–2019); and co-financed by the European Regional Development Fund (ERDF). BRC DeCC cohort: CHYF is supported by NIHR BRC. Calgary cohort: supported by Canadian Institutes for Health Research, Branch Out Neurological Foundation. Cardiff cohort: supported by the Medical Research Council (grant G 1100629) and the National Center for Mental Health (NCMH), funded by Health Research Wales (HS/14/20). CLING cohort: this study was partially supported by the Deutsche Forschungsgemeinschaft (DFG) via grants to OG (GR1950/5–1 and GR1950/10–1). CODE cohort: Henrik Walter is supported by a grant of the Deutsche Forschungsgemeinschaft (WA 1539/4–1). The CODE cohort was collected from studies funded by Lundbeck and the German Research Foundation (WA 1539/4–1, SCHN 1205/3–1, SCHR443/11–1). DIP-Groningen cohort: this study was supported by the Gratama Foundation, the Netherlands (2012/35 to NG). Edinburgh cohort: The research leading to these results was supported by IMAGEMEND, which received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 602450. This paper reflects only the author’s views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award 104036/Z/14/Z. FOR2107-Marburg cohort: funded by the German Research Foundation (DFG, grant FOR2107 KR 3822/7–2 to AK; FOR2107 KI 588/14–2 to TK and FOR2107 JA 1890/7–2 to AJ). Houston cohorts: supported in part by NIMH grant R01 085667 and the Dunn Research Foundation. JCS is supported by the Pat Rutherford, Jr. Endowed Chair in Psychiatry. IMH Study cohort: supported by funding from NHG (SIG/15012) and NMRC CISSP (2018). Melbourne cohort: funded by National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (Principal Investigator BJH) and 1024570 (Principal Investigator CGD). Minnesota cohort: the study was funded by the National Institute of Mental Health (K23MH090421; Dr. Cullen) and Biotechnology Research Center (P41 RR008079; Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. Münster cohort: funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5–1 and DA1151/5–2 to UD; SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). NESDA cohort: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10–000–1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. Pharmo cohort: supported by ERA-NET PRIOMEDCHILD FP 6 (EU) grant 11.32050.26. PSYABM-NORMENT: supported by the Research Council of Norway (project number 229135). The South East Norway Health Authority Research Funding (project number 2015052). The Department of Psychology, University of Oslo, Norway. San Francisco cohort: supported by NIH/NCCIH 1R61AT009864–01A1. NIMH R01MH085734. SHIP and SHIP-trend cohorts: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. Stanford cohorts: this work was supported by NIH grant R37 MH101495. The BiDirect Study was supported by grants from the German Federal Ministry of Education and Research (BMBF; grants FKZ-01ER0816 and FKZ-01ER1506). MDS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. TCH is supported by NIMH grant 5K01MH117442. EJWVS, JL, and TFB are supported by European Research Council grant no. ERC-ADG-2014–671084 INSOMNIA. TFB is supported by a VU University Amsterdam University Research Fellowship 2016–2017. JL is supported by a VU University Amsterdam University Research Fellowship 2017–2018.

Highlights • Standardization of fMRI neurofeedback methods and results reporting is imperative. • Currently available reports of crucial measures are limited. • Past clinical fMRI neurofeedback studies could detect medium and big effect sizes. • Studies are limited by small sample sizes in different disorders., Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting.

BackgroundA core principle of creating a scientific evidence base is that results can be replicated in independent experiments and in health intervention research. The TIDieR (Template for Intervention Description and Replication) checklist has been developed to aid in summarising key items needed when reporting clinical trials and other well designed evaluations of complex interventions in order that findings can be replicated or built on reliably. Neurofeedback (NF) using functional MRI (fMRI) is a multicomponent intervention that should be considered a complex intervention. The TIDieR checklist (with minor modification to increase applicability in this context) was distributed to NF researchers as a survey of current practice in the design and conduct of clinical studies. The aim was to document practice and convergence between research groups, highlighting areas for discussion and providing a basis for recommendations for harmonisation and standardisation.MethodsThe TIDieR checklist was interpreted and expanded (21 questions) to make it applicable to neurofeedback research studies. Using the web-based Bristol Online Survey (BOS) tool, the revised checklist was disseminated to researchers in the BRAINTRAIN European research collaborative network (supported by the European Commission) and others in the fMRI-neurofeedback community.ResultsThere were 16 responses to the survey. Responses were reported under eight main headings which covered the six domains of the TIDieR checklist: What, Why, When, How, Where and Who.ConclusionsThis piece of work provides encouraging insight into the ability to be able to map neuroimaging interventions to a structured framework for reporting purposes. Regardless of the considerable variability of design components, all studies could be described in standard terms of diagnostic groups, dose/duration, targeted areas/signals, and psychological strategies and learning models. Recommendations are made which include providing detailed rationale of intervention design in study protocols.

BackgroundThe purpose of this study was to evaluate a programme of lesion surgery carried out on patients with treatment-resistant depression (TRD).MethodThis was a retrospective study looking at clinical and psychometric data from 45 patients with TRD who had undergone bilateral stereotactic anterior capsulotomy surgery over a period of 15 years, with the approval of the Mental Health Act Commission (37 with unipolar depression and eight with bipolar disorder). The Beck Depression Inventory (BDI) before and after surgery was used as the primary outcome measure. The Montgomery–Asberg Depression Rating Scale was administered and cognitive aspects of executive and memory functions were also examined. We carried out a paired-samplesttest on the outcome measures to determine any statistically significant change in the group as a consequence of surgery.ResultsPatients improved on the clinical measure of depression after surgery by −21.20 points on the BDI with a 52% change. There were no significant cognitive changes post-surgery. Six patients were followed up in 2013 by phone interview and reported a generally positive experience. No major surgical complications occurred.ConclusionsWith the limitations of an uncontrolled, observational study, our data suggest that capsulotomy can be an effective treatment for otherwise TRD. Performance on neuropsychological tests did not deteriorate.