Schizophrenia is a severe neuropsychiatric disorder with high heritability, though its exact etiopathogenesis is yet unknown. An increasing number of studies point to the importance of white matter anomalies in the pathophysiology of schizophrenia. While several studies have identified the impact of schizophrenia susceptibility gene variants on gray matter anatomy in both schizophrenia patients and healthy risk variant carriers, studies dealing with the impact of these gene variants on white matter integrity are still scarce. We here present a study on the effects of a Dysbindin schizophrenia susceptibility gene variant on fiber tract integrity in healthy young subjects. 101 subjects genotyped for Dysbindin-gene variant rs1018381, though without personal or first degree relative history of psychiatric disorders underwent diffusion tensor imaging (DTI), 83 of them were included in the final analysis. We used Tract-Based Spatial Statistics (TBSS) analysis to delineate the major fiber tracts. Carriers of the minor allele T of the rs1018381 in the Dysbindin gene showed two clusters of reduced fractional anisotropy (FA) values in the perihippocampal region of the right temporal lobe compared to homozygote carriers of the major allele C. Clusters of increased FA values in T-allele carriers were found in the left prefrontal white matter, the right fornix, the right midbrain area, the left callosal body, the left cerebellum and in proximity of the right superior medial gyrus. Dysbindin has been implicated in neurite outgrowth and morphology. Impairments in anatomic connectivity as found associated with the minor Dysbindin allele in our study may result in increased risk for schizophrenia due to altered fiber tracts.

Emotions are often encountered in a multimodal fashion. Consequently, contextual framing by other modalities can alter the way that an emotional facial expression is perceived and lead to emotional conflict. Whole brain fMRI data was collected when 35 healthy subjects judged emotional expressions in faces while concurrently being exposed to emotional (scream, laughter) or neutral (yawning) sounds. The behavioral results showed that subjects rated fearful and neutral faces as being more fearful when accompanied by screams than compared to yawns (and laughs for fearful faces). Moreover, the imaging data revealed that incongruence of emotional valence between faces and sounds led to increased activation in the middle cingulate cortex, right superior frontal cortex, right supplementary motor area as well as the right temporoparietal junction. Against expectations no incongruence effects could be found in the amygdala. Further analyses revealed that, independent of emotional valence congruency, the left amygdala was consistently activated when the information from both modalities was emotional. If a neutral stimulus was present in one modality and emotional in the other, activation in the left amygdala was significantly attenuated. These results indicate that incongruence of emotional valence in audiovisual integration activates a cingulate-fronto-parietal network involved in conflict monitoring and resolution. Furthermore in audiovisual pairing amygdala responses seem to signal also the absence of any neutral feature rather than only the presence of an emotionally charged one.

Echo time dependence of the BOLD sensitivity is an important topic in fMRI whenever brain regions are considered where the EPI data quality suffers from susceptibility gradients. Here, an fMRI study is presented showing that a reduced echo time EPI sequence significantly enhances the statistical inference in subcortical (limbic) brain regions, with special focus on the amygdala. As a consequence, to facilitate whole-brain fMRI with optimal echo times, a sequence with slice-dependent echo time is demonstrated with a focus on structures suffering from susceptibility changes. The applicability of this method is shown in a second fMRI study aimed at both, cortical, and limbic brain regions. The results are in good agreement with theoretical descriptions of the BOLD sensitivity under the influence of susceptibility gradients.

Tourette syndrome is a neuropsychiatric disorder with the cardinal symptoms of motor and vocal tics. Often tics are accompanied by comorbidities such as obsessive-compulsive disorder, attention-deficit-hyperactivity disorder or depression. Research has mainly focused on the cortico-striato-thalamo circuit, but clinical symptoms and recent neuroimaging studies reporting altered resting network connectivity have suggested abnormalities in Tourette syndrome beyond the major motor circuits. We acquired diffusion-weighted data at 1.5T in nineteen adult patients fulfilling the DSM-IV-TR criteria for Tourette syndrome and in a healthy control group. Diffusion tensor imaging (DTI) analysis in our adult TS sample shows a decrease of FA and increase in radial diffusivity in the corticospinal tract. There are widespread changes (reduced FA and increased radial diffusivity) in the anterior and posterior limb of the internal capsule. Furthermore, it confirms prior findings of altered interhemispheric connectivity as indicated by a FA-decrease in the corpus callosum. In addition, our results indicate that TS is not restricted to motor pathways alone but affects association fibres such as the inferior fronto-occipitalis fascicle, the superior longitudinal fascicle and fascicle uncinatus as well. Tics are the hallmark of Tourette syndrome, so the involvement of the corticospinal tract fits in well with clinical symptoms. Cortical regions as well as limbic structures take part in the modulation of tics. Our findings of alterations in long association fibre tracts and the corpus callosum are a potential source for hindered interhemispheric and transhemispheric interaction. The change in radial diffusivity points toward a deficit in myelination as one pathophysiological factor in Tourette syndrome.

According to the Reinforcement Sensitivity Theory (RST), Gray's dimension of impulsivity, reflecting human trait reward sensitivity, determines the extent to which stimuli activate the Behavioural Approach System (BAS). The potential neural underpinnings of the BAS, however, remain poorly understood. In the present study, we examined the association between Gray's impulsivity as defined by the RST and event-related fMRI BOLD-response to anticipation of reward in twenty healthy human subjects in brain regions previously associated with reward processing. Anticipation of reward during a Monetary Incentive Delay Task elicited activation in key components of the human reward circuitry such as the ventral striatum, the amygdala and the orbitofrontal cortex. Interindividual differences in Gray's impulsivity accounted for a significant amount of variance of the reward-related BOLD-response in the ventral striatum and the orbitofrontal cortex. Specifically, higher trait reward sensitivity was associated with increased activation in response to cues indicating potential reward. Extending previous evidence, here we show that variance in functional brain activation during anticipation of reward is attributed to interindividual differences regarding Gray's dimension of impulsivity. Thus, trait reward sensitivity contributes to the modulation of responsiveness in major components of the human reward system which thereby display a core property of the BAS. Generally, fostering our understanding of the neural underpinnings of the association of reward-related interindividual differences in affective traits might aid researchers in quest for custom-tailored treatments of psychiatric disorders, further disentangling the complex relationship between personality traits, emotion, and health.

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces.

Pattern recognition approaches, such as the Support Vector Machine (SVM), have been successfully used to classify groups of individuals based on their patterns of brain activity or structure. However these approaches focus on finding group differences and are not applicable to situations where one is interested in accessing deviations from a specific class or population. In the present work we propose an application of the one-class SVM (OC-SVM) to investigate if patterns of fMRI response to sad facial expressions in depressed patients would be classified as outliers in relation to patterns of healthy control subjects. We defined features based on whole brain voxels and anatomical regions. In both cases we found a significant correlation between the OC-SVM predictions and the patients' Hamilton Rating Scale for Depression (HRSD), i.e. the more depressed the patients were the more of an outlier they were. In addition the OC-SVM split the patient groups into two subgroups whose membership was associated with future response to treatment. When applied to region-based features the OC-SVM classified 52% of patients as outliers. However among the patients classified as outliers 70% did not respond to treatment and among those classified as non-outliers 89% responded to treatment. In addition 89% of the healthy controls were classified as non-outliers.

Neuregulin 1 (NRG1) has been found to be associated with schizophrenia. Impaired performance in episodic memory tasks is an often replicated finding in this disorder. In functional neuroimaging studies, this dysfunction has been linked to signal changes in prefrontal and medial temporal areas. Therefore, it is of interest whether genes associated with the disorder, such as NRG1, modulate episodic memory performance and its neural correlates. Ninety-four healthy individuals performed an episodic memory encoding and a retrieval task while brain activation was measured with functional MRI. All subjects were genotyped for the single nucleotide polymorphism (SNP) rs35753505 in the NRG1 gene. The effect of genotype on brain activation was assessed with fMRI during the two tasks. While there were no differences in performance, brain activation in the cingulate gyrus (BA 24), the left middle frontal gyrus (BA 9), the bilateral fusiform gyrus and the left middle occipital gyrus (BA 19) was positively correlated with the number of risk alleles in NRG1 during encoding. During retrieval brain activation was positively correlated with the number of risk alleles in the left middle occipital gyrus (BA 19). NRG1 genotype does modulate brain activation during episodic memory processing in key areas for memory encoding and retrieval. The results suggest that subjects with risk alleles show hyperactivations in areas associated with elaborate encoding strategies.

Working memory dysfunctions are a prominent feature in schizophrenia. These impairments have been linked to alterations in prefrontal brain activation with studies reporting hypo- and hyperactivations. Since schizophrenia has a high heritability, it is of interest whether susceptibility genes modulate working memory and its neural correlates. The aim of the present study was to test the influence of the NRG1 schizophrenia susceptibility gene on working memory and its neural correlates in healthy subjects. 429 healthy individuals performed a verbal and a spatial working memory task. A subsample of 85 subjects performed a 2-back version of the Continuous Performance Test (CPT) in a functional MRI study. The NRG1 SNP8NRG221533 (rs35753505) carrier status was determined and correlated with working memory performance and brain activation. There were no effects of genetic status on behavioural performance in the working memory tasks in the 429 subjects and in the fMRI task (n=85). A linear effect of NRG1 SNP8NRG221533 carrier status on neuronal activation emerged in the fMRI experiment. Hyperactivation of the superior frontal gyrus (BA 10) was correlated with the number of risk alleles. The fMRI data suggest that performance measures between groups did not differ due to a compensational activation of BA 10 in risk-allele carriers. Our results are in line with functional imaging studies in patients with schizophrenia, which also showed a differential activation in lateral prefrontal areas.

Emotional experience in healthy men has been shown to rely on a brain network including subcortical as well as cortical areas in a complex interaction, which may be substantially influenced by many internal personal and external factors such as individuality, gender, stimulus material and task instructions. The divergent results may be interpreted by taking these considerations into account. Hence, many aspects remain to be clarified in characterizing the neural correlates underlying the subjective experience of emotion. One unresolved question refers to the influence of emotion quality on the cerebral substrates. Hence, 26 male healthy subjects were investigated with functional magnetic resonance imaging during standardized sad and happy mood induction as well as a cognitive control task to explore brain responses differentially involved in positive and negative emotional experience. Sad and happy mood in contrast to the control task produced similarly significant activations in the amygdala-hippocampal area extending into the parahippocampal gyrus as well as in the prefrontal and temporal cortex, the anterior cingulate, and the precuneus. Significant valence differences emerged when comparing both tasks directly. More activation has been demonstrated in the ventrolateral prefrontal cortex (VLPFC), the anterior cingulate cortex (ACC), the transverse temporal gyrus, and the superior temporal gyrus during sadness. Happiness, on the other hand, produced stronger activations in the dorsolateral prefrontal cortex (DLPFC), the cingulate gyrus, the inferior temporal gyrus, and the cerebellum. Hence, negative and positive moods reveal distinct cortical activation foci within a common neural network, probably making the difference between qualitatively different emotional feelings.

Neural processing inferred from hemodynamic responses measured with functional near infrared spectroscopy (fNIRS) may be confounded with individual anatomical or systemic physiological sources of variance. This may hamper the validity of fNIRS signal interpretations and associations between individual traits and brain activation, such as the link between impulsivity-related personality traits and decreased prefrontal cognitive control during reward-based decision making. Hemodynamic responses elicited by an intertemporal choice reward task in 20 healthy subjects were investigated for multimodal correlations of simultaneous fNIRS-fMRI and for an impact of anatomy and scalp fMRI signal fluctuations on fNIRS signals. Moreover, correlations of prefrontal activation with trait "sensitivity to reward" (SR) were investigated for differences between methods. While showing substantial individual variability, temporal fNIRS-fMRI correlations increased with the activation, which both methods consistently detected within right inferior/middle frontal gyrus. Here, up to 41% of fNIRS channel activation variance was explained by individual gray matter volume simulated to be reached by near-infrared light, and up to 20% by scalp-cortex distance. Extracranial fMRI and fNIRS time series showed significant temporal correlations in the temple region. SR was negatively correlated with fMRI but not fNIRS activation elicited by immediate rewards of choice within right inferior/middle frontal gyrus. Higher SR increased the correlation between extracranial fMRI and fNIRS signals and decreased fNIRS-fMRI correlations. Task-related fNIRS signals might be impacted by regionally and individually weighted sources of anatomical and systemic physiological error variance. Trait-activation correlations might be affected or biased by systemic physiological responses, which should be accounted for in future fNIRS studies of interindividual differences.

Social rewards are processed by the same dopaminergic-mediated brain networks as non-social rewards, suggesting a common representation of subjective value. Individual differences in personality and motivation influence the reinforcing value of social incentives, but it remains open whether the pursuit of social incentives is analogously supported by the neural reward system when positive social stimuli are connected to approach behavior. To test for a modulation of neural activation by approach motivation, individuals with high and low approach motivation (BAS) completed implicit and explicit social approach-avoidance paradigms during fMRI. High approach motivation was associated with faster implicit approach reactions as well as a trend for higher approach ratings, indicating increased approach tendencies. Implicit and explicit positive social approach was accompanied by stronger recruitment of the nucleus accumbens, middle cingulate cortex, and (pre-)cuneus for individuals with high compared to low approach motivation. These results support and extend prior research on social reward processing, self-other distinctions and affective judgments by linking approach motivation to the engagement of reward-related circuits during motivational reactions to social incentives. This interplay between motivational preferences and motivational contexts might underlie the rewarding experience during social interactions.

Combining neuroimaging and clinical information for diagnosis, as for example behavioral tasks and genetics characteristics, is potentially beneficial but presents challenges in terms of finding the best data representation for the different sources of information. Their simple combination usually does not provide an improvement if compared with using the best source alone. In this paper, we proposed a framework based on a recent multiple kernel learning algorithm called EasyMKL and we investigated the benefits of this approach for diagnosing two different mental health diseases. The well known Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset tackling the Alzheimer Disease (AD) patients versus healthy controls classification task, and a second dataset tackling the task of classifying an heterogeneous group of depressed patients versus healthy controls. We used EasyMKL to combine a huge amount of basic kernels alongside a feature selection methodology, pursuing an optimal and sparse solution to facilitate interpretability. Our results show that the proposed approach, called EasyMKLFS, outperforms baselines (e.g. SVM and SimpleMKL), state-of-the-art random forests (RF) and feature selection (FS) methods.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Facilitation of emotional face recognition is an established phenomenon for audiovisual crossmodal stimulation, but not for other sensory modalities. The present study used a crossmodal priming task to identify brain systems controlling olfactory-visual interactions during emotion processing. BOLD fMRI was acquired for 44 healthy subjects during an emotional face discrimination task preceded by an emotionally valenced odorant. Behavioral performance showed that recognition of disgusted faces was improved by the presentation of an olfactory stimulus irrespective of its emotional valence. No such facilitation was seen for other facial expressions. The neuroimaging data showed a selective default network responsivity to emotional faces which was modulated by odor condition. Among disgust faces, hypoactivations during trials preceded by odorants indicated the presence of priming effects. Consistent with studies investigating the brain systems associated with audiovisual emotional integration, activity modulations in clusters in fusiform gyrus, middle frontal and middle cingulate gyrus corresponded to the observed behavioral facilitation. Our study further shows modulation of signal in the anterior insula during trials combining negatively valenced odor and disgusted faces, suggesting a modality-specific mechanism for integration of the disgust response and olfaction. These results indicate the presence of a central network with modality-specific and -unspecific components modulating emotional face recognition.

Gray's Reinforcement Sensitivity Theory (RST) has developed into one of the most prominent personality theories of the last decades. The RST postulates a Behavioral Inhibition System (BIS) modulating the reaction to stimuli indicating aversive events. A number of psychiatric disorders including depression, anxiety disorders, and psychosomatic illnesses have been associated with extreme BIS responsiveness. In recent years, neuroimaging studies have implicated the amygdala-septo-hippocampal circuit as an important neural substrate of the BIS. However, the neurogenetic basis of the regulation of this behaviorally and clinically essential system remains unclear. Investigating the effects of two functional genetic polymorphisms (tryptophan hydroxylase-2, G-703T, and serotonin transporter, serotonin transporter gene-linked polymorphic region) in 89 human participants, we find significantly different patterns of associations between BIS scores and amygdala-hippocampus connectivity during loss anticipation for genotype groups regarding both polymorphisms. Specifically, the correlation between amygdala-hippocampus connectivity and Gray's trait anxiety scores is positive in individuals homozygous for the TPH2 G-allele, while carriers of at least one T-allele show a negative association. Likewise, individuals homozygous for the 5-HTTLPR L(A) variant display a positive association while carriers of the S/L(G) allele show a trend towards a negative association. Thus, we show converging evidence of different neural implementation of the BIS depending on genotype-dependent levels of serotonin. We provide evidence suggesting that genotype-dependent serotonin levels and thus putative changes in the efficiency of serotonergic neurotransmission might not only alter brain activation levels directly, but also more fundamentally impact the neural implementation of personality traits. We outline the direct clinical implications arising from this finding and discuss the complex interplay of neural responses, genes and personality traits in this context.

The basis for different neural activations in response to male and female voices as well as the question, whether men and women perceive male and female voices differently, has not been thoroughly investigated. Therefore, the aim of the present study was to examine the behavioral and neural correlates of gender-related voice perception in healthy male and female volunteers. fMRI data were collected while 39 participants (19 female) were asked to indicate the gender of 240 voice stimuli. These stimuli included recordings of 3-syllable nouns as well as the same recordings pitch-shifted in 2, 4 and 6 semitone steps in the direction of the other gender. Data analysis revealed a) equal voice discrimination sensitivity in men and women but better performance in the categorization of opposite-sex stimuli at least in men, b) increased responses to increasing gender ambiguity in the mid cingulate cortex and bilateral inferior frontal gyri, and c) stronger activation in a fronto-temporal neural network in response to voices of the opposite sex. Our results indicate a gender specific processing for male and female voices on a behavioral and neuronal level. We suggest that our results reflect higher sensitivity probably due to the evolutionary relevance of voice perception in mate selection.

Recent evidence suggests that humans can communicate emotion via chemosensory signals. Olfactory cues signaling anxiety can bias the perception of ambiguous stimuli, but the underlying neurobiological mechanisms of this effect are currently unknown. Here, we investigated the brain responses to subtle changes in facial expressions in response to anxiety chemosensory cues. Ten healthy individuals donated their sweat in two situations: while anticipating an important oral examination (anxiety condition) and during physical exercise (control condition). Subsequently, 24 participants completed a parametrically morphed (neutral to fearful) emotion recognition task under exposure to the olfactory cues of anxiety and sports, in the fMRI scanner. Behaviorally, the participants rated more discernible fearful faces as more fearful and neutral faces as more neutral under exposure to the anxiety cues. For brain response, under exposure to the anxiety cues, increased fearfulness of the face corresponded to increased activity in the left insula and the left middle occipital gyrus extending into fusiform gyrus. Moreover, with higher subjective ratings of facial fearfulness, participants additionally showed increased activity in the left hippocampus. These results suggest that chemosensory anxiety cues facilitate processing of socially relevant fearful stimuli and boost memory retrieval due to enhanced emotional context.

Temporolimbic circuits play a crucial role in the regulation of human emotion. A highly sensitive single-shot multiecho functional magnetic resonance imaging (fMRI) technique with gradient compensation of local magnetic field inhomogeneities and real-time data analysis were used to measure increases in amygdala activation during single 60-s trials of self-induced sadness. Six healthy male and female subjects performed a validated mood induction paradigm with randomized presentation of sad or neutral faces in 10 trials per scan. Subjects reported the intensity of experienced sadness after each trial. Immediate feedback of amygdala activation was given to the subjects during the ongoing scan to reinforce mood induction. Correspondence between increased intensity of predominantly left sided amygdala activation and self-rating of sadness was found in 78% of 120 sad trials, in contrast to only 14% of neutral trials. Amygdala activation was reproducible during repeated scanning sessions and displayed the strongest correlation with self-rating among all regions. These results suggest that amygdala activation may be closely associated with self-induced sadness. This novel real-time fMRI technology is applicable to a wide range of neuroscience studies, particularly those of the limbic system, and to neuropsychiatric conditions, such as depression, in which pathology of the amygdala has been implicated.