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Abstract: Variation in the CACNA1C gene has consistently been associated with psychosis in genome wide association studies. We have previously shown in a sample of n=110 healthy subjects that carriers of the CACNA1C rs1006737 risk variant exhibit hippocampal and perigenual anterior cingulate dysfunction (pgACC) during episodic memory recall. Here, we aimed to replicate our results, by testing for the effects of the rs1006737 risk variant in a new large cohort of healthy controls. We furthermore sought to refine these results by identifying the impact of a CACNA1C specific, gene-wide risk score in the absence of clinical pathology. An independent sample of 179 healthy subjects genotyped for rs1006737 underwent functional magnetic resonance imaging (fMRI) while performing an associative episodic memory task and underwent psychological testing similar to the discovery sample. The effect of gene-wide risk scores was analyzed in the combined sample of 289 subjects. We replicated our discovery findings of hippocampal and pgACC dysfunction in carriers of the rs1006737 risk variant. Additionally, we observed diminished activation of the dorsolateral prefrontal cortex, in the replication sample. Our replicated results as well as this new effect were also observable in the combined sample. Moreover, the same system-level phenotypes were significantly associated with the individual gene-based genetic risk score. Our findings suggest that altered hippocampal and frontolimbic function is associated with variants in the CACNA1C gene. Since CACNA1C variants have been associated repeatedly with psychosis at a genome-wide level, and preclinical data provide convergent evidence for the relevance of the CACNA1C gene for hippocampal and frontolimbic plasticity and adaptive regulation of stress, our data suggest a potential pathophysiological mechanism conferred by CACNA1C variants that may mediate risk for symptom dimensions shared among bipolar disorder, major depression, and schizophrenia. [Copyright &y& Elsevier]

Abstract: I provide a brief and subjective view of where the field of imaging genetics is heading. After recapitulating early debates between imagers and geneticists revolving around the topic of candidate gene studies, I point out the importance of genome-wide significant, rare and common variants. I propose that the next stages will be dominated by large-scale multi-site studies that will enable the examination of rare-high penetrance variants and methodological developments that will be required to properly assess the effects of pleiotropy, epistasis, and gene-by environment interactions. The incorporation of new sources of biological information such as whole genome sequencing, proteomic, lipidomic and expression profiles and cellular models derived from induced pluripotent stem cells opens new vistas for imaging genetics in a translational enterprise that is ultimately hoped to improve and create therapeutic options for psychiatric disorders. [Copyright &y& Elsevier]

Abstract: Williams syndrome (WS) is a rare genetic disorder caused by the deletion of ∼25 genes on chromosome 7q11.23 and is characterized by both hypersociability and increases in specific phobia and anticipatory anxiety regarding non-social entities or circumstances. Alterations in amygdala reactivity and prefrontal regulation consistent with the observed behavioral pattern of social versus non-social abnormalities have been previously demonstrated in individuals with WS (). However, in that study, the social stimulus (faces) matching task was more difficult than the non-social scene (IAPS stimuli) matching task, making it impossible to disambiguate the relative contributions of task difficulty and stimulus type (social versus non-social). In the present study, we examined the performance of the same group of participants with WS and normal IQs during a more cognitively demanding task using the same scene stimuli as in the prior study. Confirming previous findings, the results indicated (a) a differential response of prefrontal regions as a function of task difficulty and (b) a persistently increased activation of the amygdala to non-social scenes by individuals with WS regardless of cognitive load. These data provide further evidence of disruption in amygdala-prefrontal circuitry in individuals with WS. [Copyright &y& Elsevier]

Abstract: Imaging genetics provides an enormous amount of functional–structural data on gene effects in living brain, but the sheer quantity of potential phenotypes raises concerns about false discovery. Here, we provide the first empirical results on false positive rates in imaging genetics. We analyzed 720 frequent coding SNPs without significant association with schizophrenia and a subset of 492 of these without association with cognitive function. Effects on brain structure (using voxel-based morphometry, VBM) and brain function, using two archival imaging tasks, the n-back working memory task and an emotional face matching task, were studied in whole brain and regions of interest and corrected for multiple comparisons using standard neuroimaging procedures. Since these variants are unlikely to impact relevant brain function, positives obtained provide an upper empirical estimate of the false positive association rate. In a separate analysis, we randomly permuted genotype labels across subjects, removing any true genotype–phenotype association in the data, to derive a lower empirical estimate. At a set correction level of 0.05, in each region of interest and data set used, the rate of positive findings was well below 5% (0.2–4.1%). There was no relationship between the region of interest and the false positive rate. Permutation results were in the same range as empirically derived rates. The observed low rates of positives provide empirical evidence that the type I error rate is well controlled by current commonly used correction procedures in imaging genetics, at least in the context of the imaging paradigms we have used. In fact, our observations indicate that these statistical thresholds are conservative. [Copyright &y& Elsevier]

Abstract: In the past decade, imaging genetics has evolved into a highly successful neuroimaging discipline with a variety of sophisticated research tools. To date, several neural systems mechanisms have been identified that mediate genetic risk for mental disorders linked to common candidate and genome-wide-supported variants. In particular, the examination of intermediate connectivity phenotypes has recently gained increasing popularity. This paper gives an overview of the scientific methods and evidence that link indices of neural network organization to the genetic susceptibility for mental illness with a focus on the effects of candidate genes and genome-wide supported risk variants on brain structure and function. [Copyright &y& Elsevier]

Social interactions are essential to our daily life. We tested the hypothesis that social interactions during joint attention (JA) require bidirectional communication, each with a different mechanism. We used a novel multivariate functional connectivity analysis, which enables obtaining directed pathways between four regions at each time-frequency point, with hyper-scanning MRI data of real-time JA interaction. Constructing multiple "4-regional directed pathways" and counting the number of times, regions engaged in feedforward or feedback processes in the 'sender' or the 'receiver brains, we obtained the following. (1) There were more regions in feedforward than in feedback processes (125 versus 99). (2) The right hemisphere was more involved in feedforward (74 versus 33), while the left hemisphere in feedback (66 versus 51). (3) The dmPFC was more engaged in feedforward (73 versus 44) while the TPJ in both (49 versus 45). (4) The dmPFC was more involved in the sending processes (i.e. initiation of feedforward and feedback) while the TPJ in the receiving processes. (5) JA interaction was involved with high MRI frequencies (0.04–0.1 Hz), while continues interactions by low MRI frequencies (0.01–0.04 Hz). (6) Initiation and responding to JA (i.e. IJA and RJA) evolved with composite neural systems: similar systems for pathways that included the dmPFC, vmPFC and the STS, and different systems for pathways that included the TPJ, vmPFC, PCC and the STS. These findings have important consequences in the basic understanding of social interaction and could help in diagnose and follow-up of social impairments. • Joint attention (JA) interaction is bidirectional. • Feedforward was mainly through the right hemisphere. • dmPFC was more engaged in feedforward while TPJ in both. • JA interaction was encoded by higher MRI frequencies. [ABSTRACT FROM AUTHOR]

Background Accumulating evidence suggests that altered dopamine transmission may increase the risk of mental disorders such as ADHD, schizophrenia or depression, possibly mediated by reward system dysfunction. This study aimed to clarify the impact of the COMT Val 158 Met polymorphism in interaction with environmental variation (G × E) on neuronal activity during reward processing. Methods 168 healthy young adults from a prospective study conducted over 25 years participated in a monetary incentive delay task measured with simultaneous EEG-fMRI. DNA was genotyped for COMT , and childhood family adversity (CFA) up to age 11 was assessed by a standardized parent interview. Results At reward delivery, a G × E revealed that fMRI activation for win vs. no-win trials in reward-related regions increased with the level of CFA in Met homozygotes as compared to Val/Met heterozygotes and Val homozygotes, who showed no significant effect. During the anticipation of monetary vs. verbal rewards, activation decreased with the level of CFA, which was also observed for EEG, in which the CNV declined with the level of CFA. Conclusions These results identify convergent genetic and environmental effects on reward processing in a prospective study. Moreover, G × E effects during reward delivery suggest that stress during childhood is associated with higher reward sensitivity and reduced efficiency in processing rewarding stimuli in genetically at-risk individuals. Together with previous evidence, these results begin to define a specific system mediating interacting effects of early environmental and genetic risk factors, which may be targeted by early intervention and prevention. [ABSTRACT FROM AUTHOR]

Advances in social neuroscience have made neural signatures of social exchange measurable simultaneously across people. This has identified brain regions differentially active during social interaction between human dyads, but the underlying systems-level mechanisms are incompletely understood. This paper introduces dynamic causal modeling and Bayesian model comparison to assess the causal and directed connectivity between two brains in the context of hyperscanning (h-DCM). In this setting, correlated neuronal responses become the data features that have to be explained by models with and without between-brain (effective) connections. Connections between brains can be understood in the context of generalized synchrony, which explains how dynamical systems become synchronized when they are coupled to each another. Under generalized synchrony, each brain state can be predicted by the other brain or a mixture of both. Our results show that effective connectivity between brains is not a feature within dyads per se but emerges selectively during social exchange. We demonstrate a causal impact of the sender's brain activity on the receiver of information, which explains previous reports of two-brain synchrony. We discuss the implications of this work; in particular, how characterizing generalized synchrony enables the discovery of between-brain connections in any social contact, and the advantage of h-DCM in studying brain function on the subject level, dyadic level, and group level within a directed model of (between) brain function. [ABSTRACT FROM AUTHOR]

Amygdala function is of high interest for cognitive, social and psychiatric neuroscience, emphasizing the need for reliable assessments in humans. Previous work has indicated unsatisfactorily low within-subject reliability of amygdala activation fMRI measures. Based on basic science evidence for strong habituation of amygdala response to repeated stimuli, we investigated whether a quantification of habituation provides additional information beyond the usual estimate of the overall mean activity. We assessed the within-subject reliability of amygdala habituation measures during a facial emotion matching paradigm in 25 healthy subjects. We extracted the amygdala signal decrement across the course of the fMRI run for the two test–retest measurement sessions and compared reliability estimates with previous findings based on mean response amplitude. Retest-reliability of the session-wise amygdala habituation was significantly higher than the evoked amygdala mean amplitude (intraclass correlation coefficients (ICC) = 0.53 vs. 0.16). To test the task-specificity of this finding, we compared the retest-reliability of amygdala habituation across two different tasks. Significant amygdala response decrement was also seen in a cognitive task (n-back working memory) that did not per se activate the amygdala, but was totally unreliable in that context (ICC ~ 0.0), arguing for task-specificity. Together the results show that emotion-dependent amygdala habituation is a robust and considerably more reliable index than the mean amplitude, and provides a robust potential endpoint for within-subject designs including pharmaco-fMRI studies. [ABSTRACT FROM AUTHOR]

Abstract: Inhibitory response control has been extensively investigated in both electrophysiological (ERP) and hemodynamic (fMRI) studies. However, very few multimodal results address the coupling of these inhibition markers. In fMRI, response inhibition has been most consistently linked to activation of the anterior insula and inferior frontal cortex (IFC), often also the anterior cingulate cortex (ACC). ERP work has established increased N2 and P3 amplitudes during NoGo compared to Go conditions in most studies. Previous simultaneous EEG–fMRI imaging reported association of the N2/P3 complex with activation of areas like the anterior midcingulate cortex (aMCC) and anterior insula. In this study we investigated inhibitory control in 23 healthy young adults (mean age=24.7, n=17 for EEG during fMRI) using a combined Flanker/NoGo task during simultaneous EEG and fMRI recording. Separate fMRI and ERP analysis yielded higher activation in the anterior insula, IFG and ACC as well as increased N2 and P3 amplitudes during NoGo trials in accordance with the literature. Combined analysis modelling sequential N2 and P3 effects through joint parametric modulation revealed correlation of higher N2 amplitude with deactivation in parts of the default mode network (DMN) and the cingulate motor area (CMA) as well as correlation of higher central P3 amplitude with activation of the left anterior insula, IFG and posterior cingulate. The EEG–fMRI results resolve the localizations of these sequential activations. They suggest a general role for allocation of attentional resources and motor inhibition for N2 and link memory recollection and internal reflection to P3 amplitude, in addition to previously described response inhibition as reflected by the anterior insula. [Copyright &y& Elsevier]

Abstract: The investigation of the brain connectome with functional magnetic resonance imaging (fMRI) and graph theory analyses has recently gained much popularity, but little is known about the robustness of these properties, in particular those derived from active fMRI tasks. Here, we studied the test–retest reliability of brain graphs calculated from 26 healthy participants with three established fMRI experiments (n-back working memory, emotional face-matching, resting state) and two parcellation schemes for node definition (AAL atlas, functional atlas proposed by Power et al.). We compared the intra-class correlation coefficients (ICCs) of five different data processing strategies and demonstrated a superior reliability of task-regression methods with condition-specific regressors. The between-task comparison revealed significantly higher ICCs for resting state relative to the active tasks, and a superiority of the n-back task relative to the face-matching task for global and local network properties. While the mean ICCs were typically lower for the active tasks, overall fair to good reliabilities were detected for global and local connectivity properties, and for the n-back task with both atlases, smallworldness. For all three tasks and atlases, low mean ICCs were seen for the local network properties. However, node-specific good reliabilities were detected for node degree in regions known to be critical for the challenged functions (resting-state: default-mode network nodes, n-back: fronto-parietal nodes, face-matching: limbic nodes). Between-atlas comparison demonstrated significantly higher reliabilities for the functional parcellations for global and local network properties. Our findings can inform the choice of processing strategies, brain atlases and outcome properties for fMRI studies using active tasks, graph theory methods, and within-subject designs, in particular future pharmaco-fMRI studies. [Copyright &y& Elsevier]

Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a , were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level. [ABSTRACT FROM AUTHOR]

Abstract: Even more than in cognitive research applications, moving fMRI to the clinic and the drug development process requires the generation of stable and reliable signal changes. The performance characteristics of the fMRI paradigm constrain experimental power and may require different study designs (e.g., crossover vs. parallel groups), yet fMRI reliability characteristics can be strongly dependent on the nature of the fMRI task. The present study investigated both within-subject and group-level reliability of a combined three-task fMRI battery targeting three systems of wide applicability in clinical and cognitive neuroscience: an emotional (face matching), a motivational (monetary reward anticipation) and a cognitive (n-back working memory) task. A group of 25 young, healthy volunteers were scanned twice on a 3T MRI scanner with a mean test–retest interval of 14.6days. FMRI reliability was quantified using the intraclass correlation coefficient (ICC) applied at three different levels ranging from a global to a localized and fine spatial scale: (1) reliability of group-level activation maps over the whole brain and within targeted regions of interest (ROIs); (2) within-subject reliability of ROI-mean amplitudes and (3) within-subject reliability of individual voxels in the target ROIs. Results showed robust evoked activation of all three tasks in their respective target regions (emotional task=amygdala; motivational task=ventral striatum; cognitive task=right dorsolateral prefrontal cortex and parietal cortices) with high effect sizes (ES) of ROI-mean summary values (ES=1.11–1.44 for the faces task, 0.96–1.43 for the reward task, 0.83–2.58 for the n-back task). Reliability of group level activation was excellent for all three tasks with ICCs of 0.89–0.98 at the whole brain level and 0.66–0.97 within target ROIs. Within-subject reliability of ROI-mean amplitudes across sessions was fair to good for the reward task (ICCs=0.56–0.62) and, dependent on the particular ROI, also fair-to-good for the n-back task (ICCs=0.44–0.57) but lower for the faces task (ICC=−0.02–0.16). In conclusion, all three tasks are well suited to between-subject designs, including imaging genetics. When specific recommendations are followed, the n-back and reward task are also suited for within-subject designs, including pharmaco-fMRI. The present study provides task-specific fMRI reliability performance measures that will inform the optimal use, powering and design of fMRI studies using comparable tasks. [Copyright &y& Elsevier]

Abstract: The drug metabolizing cytochrome P450 2D6 enzyme (CYP2D6) is highly expressed in brain and potentially involved in neurotransmitter biotransformation. Here, we report the effect of the CYP2D6 genotype on brain activation during a working memory and an emotional face matching task measured with fMRI. Subjects were taken from an ongoing large scale multicenter imaging genetic study. CYP2D6 genotyping of the alleles *2, *3, *4, *5, *6, *9, *10, *17, *35, *41 and the duplication was performed in N =114 healthy drug free individuals. All individuals had completed two tasks in functional brain imaging: an n-back working memory task and an implicit emotional face matching task. Contrast images were analyzed in second-level random effects models with CYP2D6 enzyme activity levels as regressor of interest and age, sex and scanning site as covariates. In the working memory task, a significant effect of CYP2D6 genotype was found in the fusiform gyrus and the precuneus. In the emotional face matching task, an effect was detected in the cuneus. No significant activation results were found in the thalamus. A conjunction analysis confirmed a significant joint effect of the CYP2D6 association in both regions. In both tasks activation increased with increasing CYP2D6 activity. In conclusion, we confirmed a central nervous system effect of CYP2D6 activity in a large independent sample using a different imaging modality, and provide evidence that basic cognitive processes related to such as alertness may be impacted. [Copyright &y& Elsevier]

Abstract: Characterizing the brain connectome using neuroimaging data and measures derived from graph theory emerged as a new approach that has been applied to brain maturation, cognitive function and neuropsychiatric disorders. For a broad application of this method especially for clinical populations and longitudinal studies, the reliability of this approach and its robustness to confounding factors need to be explored. Here we investigated test–retest reliability of graph metrics of functional networks derived from functional magnetic resonance imaging (fMRI) recorded in 33 healthy subjects during rest. We constructed undirected networks based on the Anatomic-Automatic-Labeling (AAL) atlas template and calculated several commonly used measures from the field of graph theory, focusing on the influence of different strategies for confound correction. For each subject, method and session we computed the following graph metrics: clustering coefficient, characteristic path length, local and global efficiency, assortativity, modularity, hierarchy and the small-worldness scalar. Reliability of each graph metric was assessed using the intraclass correlation coefficient (ICC). Overall ICCs ranged from low to high (0 to 0.763) depending on the method and metric. Methodologically, the use of a broader frequency band (0.008–0.15Hz) yielded highest reliability indices (mean ICC=0.484), followed by the use of global regression (mean ICC=0.399). In general, the second order metrics (small-worldness, hierarchy, assortativity) studied here, tended to be more robust than first order metrics. In conclusion, our study provides methodological recommendations which allow the computation of sufficiently robust markers of network organization using graph metrics derived from fMRI data at rest. [Copyright &y& Elsevier]

Abstract: In the social neuroscience of face processing, multiple roles are attributed to amygdala: signalling of fear/threat-stimuli, of emotional expression, and general salience. The current study aimed at a direct comparison of amygdala activation attributable to these conditions by contrasting amygdala responses to matched emotional (threatening and non-threatening) and of non-emotional salient faces in a visual search paradigm using cartoon faces. Participants (21 healthy volunteers) had to detect a target face (angry, happy, blue, red, differing in the exact same features) in an array of closely matched non-target faces. Behavioural results revealed a pop-out effect for all targets compared to non-targets, indicating that they were all salient, independently of being emotional or non-emotional. While significant amygdala activation was obtained for all trials with salient faces (compared to those containing only non-target faces), no significant differences in activation emerged between emotional threatening, emotional non-threatening, and non-emotional targets. Moreover, right and left amygdala activation for target trials was found correlated to the behavioural measure of target detection. These findings provide evidence for a general role of the amygdala in signalling salience in a visual search independent of modality. Given the critical involvement of the amygdala in several neuropsychiatric disorders, the current findings may contribute to further our understanding on dysfunctional neural circuits in these disorders. [ABSTRACT FROM AUTHOR]

Abstract: Alterations of connectivity are central to the systems-level pathophysiology of schizophrenia. One of the best-established genome-wide significant risk variants for this highly heritable disorder, the rs1344706 single nucleotide polymorphism in ZNF804A, was recently shown to modulate connectivity in healthy carriers during working memory (WM) in a pattern mirroring that which was found in overt disease. However, it was unclear whether this finding is specific to WM or if it is present regardless of cognitive state. Therefore, we examined genotype effects on connectivity in healthy carriers during rest and an emotion processing task without WM component. 111 healthy German subjects performed a battery of functional imaging tasks. Functional connectivity with the right dorsolateral prefrontal cortex during rest and an implicit emotion recognition task was determined using the seed voxel method and compared to results during WM. During rest and during the emotional task, a pattern of reduced interhemispheric prefrontal connectivity with increasing number of rs1344706 risk alleles could be seen that was close to identical to that during WM, suggesting a state-independent influence of the genetic variant on interhemispheric processing, possibly through structural effects. By contrast, the abnormal prefronto-hippocampal connectivity was only seen during the WM task, indicating a degree of task specificity in agreement with prior results in patients with schizophrenia. Our findings confirm a key role for disturbed functional connectivity in the genetic risk architecture of schizophrenia and identify cognitive state-dependent and independent components with regard to WM function. [Copyright &y& Elsevier]

Abstract: Magnetic resonance spectroscopy enables the in vivo analysis of certain aspects of brain biochemistry. Reduced N-acetylaspartate in key regions of schizophrenia has been reported repeatedly but not without controversy. Our objective is to investigate whether reduced N-acetylaspartate concentrations determined without correction for individual T2 relaxation time (referred to as ‘apparent tNAA concentration’) are due to a reduced absolute N-acetylaspartate concentration or to altered relaxation properties. For this purpose we measured absolute concentrations while evaluating individual T2 relaxation times. We evaluated the metabolite concentrations and metabolite/water relaxation times of a frontal white matter voxel from 23 patients who met DSM-IV criteria for schizophrenia and 29 healthy control subjects with similar age at a 3 T magnetic resonance scanner. A significantly reduced N-acetylaspartate concentration as well as shortened N-acetylaspartate''s T2 relaxation time in the schizophrenic patient group was found. The apparent N-acetylaspartate concentration difference between healthy controls and patients with schizophrenia increased with the echo time due to a decreased N-acetylaspartate''s T2 in the schizophrenic group. No group difference was found for any other metabolite concentration or metabolite/brain water relaxation time. These findings of reduced N-acetylaspartate as well as shortened N-acetylaspartate''s T2 relaxation time give further evidence for microstructural white matter changes in schizophrenia. Furthermore, they elucidate why reports of a reduced N-acetylaspartate concentration in schizophrenia were not always corroborated. [Copyright &y& Elsevier]

Abstract: Regulatory interactions with the amygdala are thought to be critical for emotional processing in the extended limbic system. Structural equation modeling (path analysis) is a widely used method to quantify interactions among brain regions based on connectivity models, but is often limited by lack of precise anatomical and functional constraints. To address this issue, we developed an automated elaborative path analysis procedure guided by known anatomical connectivity in the macaque. We applied this technique to a large human fMRI data set acquired during perceptual processing of angry or fearful facial stimuli. The derived models were inferentially validated using a bootstrapping split-half approach in pairs of 500 independent groups. Significant paths across the groups were used to form a rigorously validated and consistent path model. We confirm and extend previous observations of amygdala regulation by an extended prefrontal network encompassing cingulate, orbitofrontal, insular, and dorsolateral prefrontal cortex, as well as strong interactions between amygdala and parahippocampal gyrus. This validated model can be used to study neurocognitive correlates as well as genotype or disease-related alterations of functional interactions in the limbic system. [Copyright &y& Elsevier]

• Structural brain networks can be modeled as a trade-off between wiring cost and topological features. • Schizophrenia patients show lower spatial constraints and topological facilitation. • Individual model parameters are associated with genetic risk for schizophrenia and cognition. Alterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of altered brain network formation. We evaluated different generative network models in healthy controls (n =152), schizophrenia patients (n =66), and their unaffected first-degree relatives (n =32), and we identified spatial and topological factors contributing to network formation. We further investigated how these factors relate to cognition and to polygenic risk for schizophrenia. Our data show that among the four tested classes of generative network models, structural brain networks were optimally accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation across study groups. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. Further exploratory analyses point to potential associations of the model parameter reflecting spatial constraints with the polygenic risk for schizophrenia and cognitive performance. Our results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to regular brain network formation as well as altered connectomes in schizophrenia and healthy individuals at familial risk for schizophrenia. On an exploratory level, our data further point to the potential relevance of spatial constraints for the genetic risk for schizophrenia and general cognitive functioning, thereby encouraging future studies in following up on these observations to gain further insights into the biological basis and behavioral relevance of model parameters. [ABSTRACT FROM AUTHOR]