Advanced paternal age as a risk factor for neurodevelopmental disorders: a translational study.

Advanced paternal age (APA) is a risk factor for several neurodevelopmental disorders, including autism and schizophrenia. The potential mechanisms conferring this risk are poorly understood. Here, we show that the personality traits schizotypy and neuroticism correlated with paternal age in healthy subjects (N = 677). Paternal age was further positively associated with gray matter volume (VBM, N = 342) in the right prefrontal and the right medial temporal cortex. The integrity of fiber tracts (DTI, N = 222) connecting these two areas correlated positively with paternal age. Genome-wide methylation analysis in humans showed differential methylation in APA individuals, linking APA to epigenetic mechanisms. A corresponding phenotype was obtained in our rat model. APA rats displayed social-communication deficits and emitted fewer pro-social ultrasonic vocalizations compared to controls. They further showed repetitive and stereotyped patterns of behavior, together with higher anxiety during early development. At the neurobiological level, microRNAs miR-132 and miR-134 were both differentially regulated in rats and humans depending on APA. This study demonstrates associations between APA and social behaviors across species. They might be driven by changes in the expression of microRNAs and/or epigenetic changes regulating neuronal plasticity, leading to brain morphological changes and fronto-hippocampal connectivity, a network which has been implicated in social interaction.

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

10Kin1day: A Bottom-Up Neuroimaging Initiative.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Evidence of brain network aberration in healthy subjects with urban upbringing - A multimodal DTI and VBM study.

City living represents not only the allegory of modern life, but also - due to attractive living conditions, employment and infrastructure - a crucial reality for a growing portion of the global society. Regarding the remarkable increase of the schizophrenia incidence in individuals exposed to an urban environment during upbringing the understanding of responsible pathogenetic mechanisms is important. Schizophrenia has been conceptualized as a disorder of brain dysconnectivity. We investigated the association between urban upbringing and gray matter as well as white matter in a large sample of healthy subjects (n = 290). Voxelwise analyses revealed a strong inverse correlation of early life urbanicity and gray matter volume of the bilateral dorsolateral prefrontal cortices (DLPFC) and the right inferior parietal lobe (IPL) as well as the white matter characteristics in the left superior longitudinal fasciculus (SLF). A positive correlation was found for the gray matter volume of the left precuneus. These results may point to an altered brain development associated with urban upbringing, which not only affects single brain regions but a fronto-parietal network. Considering a DLPFC susceptibility to stress, our findings support the hypothesis of the pathogenetic role of social stress in an urban environment.

A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol.

Large-scale consortium efforts such as Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) and other collaborative efforts show that combining statistical data from multiple independent studies can boost statistical power and achieve more accurate estimates of effect sizes, contributing to more reliable and reproducible research. A meta- analysis would pool effects from studies conducted in a similar manner, yet to date, no such harmonized protocol exists for resting state fMRI (rsfMRI) data. Here, we propose an initial pipeline for multi-site rsfMRI analysis to allow research groups around the world to analyze scans in a harmonized way, and to perform coordinated statistical tests. The challenge lies in the fact that resting state fMRI measurements collected by researchers over the last decade vary widely, with variable quality and differing spatial or temporal signal-to-noise ratio (tSNR). An effective harmonization must provide optimal measures for all quality data. Here we used rsfMRI data from twenty-two independent studies with approximately fifty corresponding T1-weighted and rsfMRI datasets each, to (A) review and aggregate the state of existing rsfMRI data, (B) demonstrate utility of principal component analysis (PCA)-based denoising and (C) develop a deformable ENIGMA EPI template based on the representative anatomy that incorporates spatial distortion patterns from various protocols and populations.

Longitudinal brain volume changes in major depressive disorder.

Patients with major depressive disorder (MDD) exhibit gray matter volume (GMV) reductions in limbic regions. Clinical variables-such as the number of depressive episodes-seem to affect volume alterations. It is unclear whether the observed cross-sectional GMV abnormalities in MDD change over time, and whether there is a longitudinal relationship between GMV changes and the course of disorder. We investigated T1 structural MRI images of 54 healthy control (HC) and 37 MDD patients in a 3-Tesla-MRI with a follow-up interval of 3 years. The Cat12 toolbox was used to analyze longitudinal data (p < 0.05, FWE-corrected, whole-brain analysis; flexible factorial design). Interaction effects indicated increasing GMV in MDD in the bilateral amygdala, and decreasing GMV in the right thalamus between T1 and T2. Further analyses comparing patients with a mild course of disorder (MCD; 0-1 depressive episode during the follow-up) to patients with a severe course of disorder (SCD; > 1 depressive episode during the follow-up) revealed increasing amygdalar volume in MCD. Our study confirms structural alterations in limbic regions in MDD patients and an association between these impairments and the course of disorder. Thus, we assume that the reported volumetric alterations in the left amygdala (i.e. volumetric normalization) are reversible and apparently driven by the clinical phenotype. Hence, these results support the assumption that the severity and progression of disease influences amygdalar GMV changes in MDD or vice versa.

Neural correlates of working memory in first episode and recurrent depression: An fMRI study.

BACKGROUND: Patients suffering from major depressive disorder (MDD) show deficits in working memory (WM) performance accompanied by bilateral fronto-parietal BOLD signal changes. It is unclear whether patients with a first depressive episode (FDE) exhibit the same signal changes as patients with recurrent depressive episodes (RDE). METHODS: We investigated seventy-four MDD inpatients (48 RDE, 26 FDE) and 74 healthy control (HC) subjects performing an n-back WM task (0-back, 2-back, 3-back condition) in a 3T-fMRI. RESULTS: FMRI analyses revealed deviating BOLD signal in MDD in the thalamus (0-back vs. 2-back), the angular gyrus (0-back vs. 3-back), and the superior frontal gyrus (2-back vs. 3-back). Further effects were observed between RDE vs. FDE. Thus, RDE displayed differing neural activation in the middle frontal gyrus (2-back vs. 3-back), the inferior frontal gyrus, and the precentral gyrus (0-back vs. 2-back). In addition, both HC and FDE indicated a linear activation trend depending on task complexity. CONCLUSIONS: Although we failed to find behavioral differences between the groups, results suggest differing BOLD signal in fronto-parietal brain regions in MDD vs. HC, and in RDE vs. FDE. Moreover, both HC and FDE show similar trends in activation shapes. This indicates a link between levels of complexity-dependent activation in fronto-parietal brain regions and the stage of MDD. We therefore assume that load-dependent BOLD signal during WM is impaired in MDD, and that it is particularly affected in RDE. We also suspect neurobiological compensatory mechanisms of the reported brain regions in (working) memory functioning.

Effects of cumulative illness severity on hippocampal gray matter volume in major depression: a voxel-based morphometry study.

BACKGROUND: Patients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients' cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression. METHODS: We estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients' cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients' individual component scores on hippocampal volume. RESULTS: Principal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients' Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores. CONCLUSIONS: Variables associated with patients' history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients' cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.

Polygenic risk for schizophrenia affects working memory and its neural correlates in healthy subjects.

Schizophrenia is a disorder with a high heritability. Patients as well as their first degree relatives display lower levels of performance in a number of cognitive domains compared to subjects without genetic risk. Several studies could link these aberrations to single genetic variants, however, only recently, polygenic risk scores as proxies for genetic risk have been associated with cognitive domains and their neural correlates. In the present study, a sample of healthy subjects (n=137) performed a letter version of the n-back task while scanned with 3-T fMRI. All subjects were genotyped with the PsychChip and polygenic risk scores were calculated based on the PGC2 schizophrenia GWAS results. Polygenic risk for schizophrenia was associated with a lower degree of brain activation in prefrontal areas during the 3-back compared to the 0-back baseline condition. Furthermore, polygenic risk was associated with lower levels of brain activation in the right inferior frontal gyrus during the 3-back compared to a 2-back condition. Polygenic risk leads to a shift in the underlying activation pattern to the left side, thus resembling results reported in patients with schizophrenia. The data may point to polygenic risk for schizophrenia being associated with brain function in a cognitive task known to be impaired in patients and their relatives.

Polygenic risk for depression and the neural correlates of working memory in healthy subjects.

INTRODUCTION: Major depressive disorder (MDD) patients show impairments of cognitive functioning such as working memory (WM), and furthermore alterations during WM-fMRI tasks especially in frontal and parietal brain regions. The calculation of a polygenic risk score (PRS) can be used to describe the genetic influence on MDD, hence imaging genetic studies aspire to combine both genetics and neuroimaging data to identify the influence of genetic factors on brain functioning. We aimed to detect the effect of MDD-PRS on brain activation during a WM task measured with fMRI and expect healthy individuals with a higher PRS to be more resembling to MDD patients. METHOD: In total, n=137 (80 men, 57 women, aged 34.5, SD=10.4years) healthy subjects performed a WM n-back task [0-back (baseline), 2-back and 3-back condition] in a 3T-MRI-tomograph. The sample was genotyped using the Infinium PsychArray BeadChip and a polygenic risk score was calculated for MDD using PGC MDD GWAS results. RESULTS: A lower MDD risk score was associated with increased activation in the bilateral middle occipital gyri (MOG), the bilateral middle frontal gyri (MFG) and the right precentral gyrus (PCG) during the 2-back vs. baseline condition. Moreover, a lower PRS was associated with increased brain activation during the 3-back vs. baseline condition in the bilateral cerebellum, the right MFG and the left inferior parietal lobule. A higher polygenic risk score was associated with hyperactivation in brain regions comprising the right MFG and the right supplementary motor area during the 3-back vs. 2-back condition. DISCUSSION: The results suggest that part of the WM-related brain activation patterns might be explained by genetic variants captured by the MDD-PRS. Furthermore we were able to detect MDD-associated activation patterns in healthy individuals depending on the MDD-PRS and the task complexity. Additional gene loci could contribute to these task-dependent brain activation patterns.

Structural brain changes in schizophrenia at different stages of the illness: A selective review of longitudinal magnetic resonance imaging studies.

OBJECTIVE: Schizophrenia is a devastating mental disorder accompanied by aberrant structural brain connectivity. The question whether schizophrenia is a progressive brain disorder is yet to be resolved. Thus, it is not clear when these structural alterations occur and how they develop over time. METHODS: In our selective review, we summarized recent findings from longitudinal magnetic resonance imaging studies investigating structural brain alterations and its impact on clinical outcome at different stages of the illness: (1) subjects at ultra-high risk of developing psychosis, (2) patients with a first episode psychosis, and (3) chronically ill patients. Moreover, we reviewed studies examining the longitudinal effects of medication on brain structure in patients with schizophrenia. RESULTS: (1) Studies from pre-clinical stages to conversion showed a more pronounced cortical gray matter loss (i.e. superior temporal and inferior frontal regions) in those individuals who later made transition to psychosis. (2) Studies investigating patients with a first episode psychosis revealed a decline in multiple gray matter regions (i.e. frontal regions and thalamus) over time as well as progressive cortical thinning in the superior and inferior frontal cortex. (3) Studies focusing on patients with chronic schizophrenia showed that gray matter decreased to a greater extent (i.e. frontal and temporal areas, thalamus, and cingulate cortices)-especially in poor-outcome patients. Very few studies reported effects on white matter microstructure in the longitudinal course of the illness. CONCLUSION: There is adequate evidence to suggest that schizophrenia is associated with progressive gray matter abnormalities particularly during the initial stages of illness. However, causal relationships between structural changes and illness course-especially in chronically ill patients-should be interpreted with caution. Findings might be confounded by longer periods of treatment and higher doses of antipsychotics or epiphenomena related to the illness.

White matter integrity and symptom dimensions of schizophrenia: A diffusion tensor imaging study.

Impaired fiber bundle connectivity between brain regions is a key neuropathological finding in schizophrenia. Symptom dimensions in schizophrenia can be clustered into factor models. Single syndromes have been related to grey and white matter brain structure alterations. We associated all core syndromes of schizophrenia in a single patient group with changes in white matter integrity. Diffusion weighted images (3T MRI) and SAPS/SANS scores were measured in 26 male patients and 26 healthy controls. First, group differences in fractional anisotropy (FA) were calculated with TBSS. Second, core symptom dimensions of schizophrenia were correlated with FA within these altered tracts. We found differences between groups in nine white matter tracts. Hallucinations were positively correlated with FA in the left uncinate fasciculus and left corticospinal tract. Ego-disturbances (passivity phenomena) showed a positive correlation with FA in the right anterior thalamic radiation. Positive formal thought disorders (FTD) corresponded negatively with FA in the right cingulum bundle. Negative symptoms were positively associated with the right anterior thalamic radiation and negatively with the right ventral cingulum bundle. For the first time, we analyzed the whole range of psychopathological factors in one schizophrenia patient group. We could validate our novel results for positive FTD and passivity phenomena by replicating findings for hallucinations and negative symptoms. Only those brain circuits which are most vulnerable at a given time during neurodevelopment are affected by a particular pathological impact (genetic, environmental). This scenario could explain the predominance of particular psychopathological syndromes related to specific white matter anomalies.

A genome-wide supported psychiatric risk variant in NCAN influences brain function and cognitive performance in healthy subjects.

The A allele of the single nucleotide polymorphism (SNP) rs1064395 in the NCAN gene has recently been identified as a susceptibility factor for bipolar disorder and schizophrenia. NCAN encodes neurocan, a brain-specific chondroitin sulfate proteoglycan that is thought to influence neuronal adhesion and migration. Several lines of research suggest an impact of NCAN on neurocognitive functioning. In the present study, we investigated the effects of rs1064395 genotype on neural processing and cognitive performance in healthy subjects. Brain activity was measured with functional magnetic resonance imaging (fMRI) during an overt semantic verbal fluency task in 110 healthy subjects who were genotyped for the NCAN SNP rs1064395. Participants additionally underwent comprehensive neuropsychological testing. Whole brain analyses revealed that NCAN risk status, defined as AA or AG genotype, was associated with a lack of task-related deactivation in a large left lateral temporal cluster extending from the middle temporal gyrus to the temporal pole. Regarding neuropsychological measures, risk allele carriers demonstrated poorer immediate and delayed verbal memory performance when compared to subjects with GG genotype. Better verbal memory performance was significantly associated with greater deactivation of the left temporal cluster during the fMRI task in subjects with GG genotype. The current data demonstrate that common genetic variation in NCAN influences both neural processing and cognitive performance in healthy subjects. Our study provides new evidence for a specific genetic influence on human brain function.

Effects of Long-Term Mindfulness Meditation on Brain's White Matter Microstructure and its Aging.

Although research on the effects of mindfulness meditation (MM) is increasing, still very little has been done to address its influence on the white matter (WM) of the brain. We hypothesized that the practice of MM might affect the WM microstructure adjacent to five brain regions of interest associated with mindfulness. Diffusion tensor imaging was employed on samples of meditators and non-meditators (n = 64) in order to investigate the effects of MM on group difference and aging. Tract-Based Spatial Statistics was used to estimate the fractional anisotrophy of the WM connected to the thalamus, insula, amygdala, hippocampus, and anterior cingulate cortex. The subsequent generalized linear model analysis revealed group differences and a group-by-age interaction in all five selected regions. These data provide preliminary indications that the practice of MM might result in WM connectivity change and might provide evidence on its ability to help diminish age-related WM degeneration in key regions which participate in processes of mindfulness.

Altered neural function during episodic memory encoding and retrieval in major depression.

Memory impairments are common in major depression. Neural processing during non-emotional episodic memory in depressed patients has only sparsely been investigated, since the majority of studies have focused on emotional stimuli. The aim of this study was to explore neural correlates of episodic memory in depressive patients and to assess brain regions related to subsequent memory performance. Forty-six participants (23 depressed patients) performed a non-emotional episodic memory encoding and retrieval task while brain activation was measured with functional magnetic resonance imaging. Patients with depression showed decreased activation in the right prefrontal cortex and right cingulate cortex during memory encoding, but increased activation in the right inferior frontal gyrus (IFG) during recognition memory. While a strong association between hippocampal and parahippocampal activation during memory encoding with subsequent memory performance became evident in healthy controls, this relationship was absent in patients with depression. Taken together, these findings demonstrate that memory related brain regions are affected in their appropriate functioning during memory encoding in depressed patients. Therefore, patients with depression may rely to a greater degree on other brain regions such as the IFG during episodic memory retrieval.

Genetic variation in CACNA1C affects neural processing in major depression.

Genetic studies found the A allele of the single nucleotide polymorphism rs1006737 in the CACNA1C gene, which encodes for the alpha 1C subunit of the voltage-dependent, L-type calcium ion channel Cav1.2, to be overrepresented in patients with major depressive disorder (MDD). Altered prefrontal brain functioning and impaired semantic verbal fluency (SVF) are robust findings in these patients. A recent functional magnetic resonance imaging (fMRI) study found the A allele to be associated with poorer performance and increased left inferior frontal gyrus (IFG) activation during SVF tasks in healthy subjects. In the present study, we investigated the effects of rs1006737 on neural processing during SVF in MDD. In response to semantic category cues, 40 patients with MDD and 40 matched controls overtly generated words while brain activity was measured with fMRI. As revealed by whole brain analyses, genotype significantly affected brain activity in patients. Compared to patients with GG genotype, patients with A allele demonstrated increased task-related activation in the left middle/inferior frontal gyrus and the bilateral cerebellum. Patients with A allele also showed enhanced functional coupling between left middle/inferior and right superior/middle frontal gyri. No differential effects of genotype on SVF performance or brain activation were found between diagnostic groups. The current data provide further evidence for an impact of rs1006737 on the left IFG and demonstrate that genetic variation in CACNA1C modulates neural responses in patients with MDD. The observed functional alterations in prefrontal and cerebellar areas might represent a mechanism by which rs1006737 influences susceptibility to MDD.

Increased neural activity during overt and continuous semantic verbal fluency in major depression: mainly a failure to deactivate.

Major depression is associated with impairments in semantic verbal fluency (VF). However, the neural correlates underlying dysfunctional cognitive processing in depressed subjects during the production of semantic category members still remain unclear. In the current study, an overt and continuous semantic VF paradigm was used to examine these mechanisms in a representative sample of 33 patients diagnosed with a current episode of unipolar depression and 33 statistically matched healthy controls. Subjects articulated words in response to semantic category cues while brain activity was measured with functional magnetic resonance imaging (fMRI). Compared to controls, patients showed poorer task performance. On the neural level, a group by condition interaction analysis, corrected for task performance, revealed a reduced task-related deactivation in patients in the right parahippocampal gyrus, the right fusiform gyrus, and the right supplementary motor area. An additional and an increased task-related activation in patients were observed in the right precentral gyrus and the left cerebellum, respectively. These results indicate that a failure to suppress potentially interfering activity from inferior temporal regions involved in default-mode network functions and visual imagery, accompanied by an enhanced recruitment of areas implicated in speech initiation and higher-order language processes, may underlie dysfunctional cognitive processing during semantic VF in depression. The finding that patients with depression demonstrated both decreased performance and aberrant brain activation during the current semantic VF task demonstrates that this paradigm is a sensitive tool for assessing brain dysfunctions in clinical populations.

The impact of a CACNA1C gene polymorphism on learning and hippocampal formation in healthy individuals: a diffusion tensor imaging study.

BACKGROUND: Genome-wide association studies have identified the CACNA1C single nucleotide polymorphism (SNP) rs1006737 as one of the most consistent genetic findings as susceptibility locus for major psychiatric disorders. Furthermore, animal and genetic imaging studies have reported strong functional evidence for the association of CACNA1C with learning, memory, neural plasticity, and its association with the hippocampal formation. In the present study we investigated the impact of the CACNA1C SNP rs1006737 on the fractional anisotropy (FA) in the hippocampal formation as well as on verbal learning and memory in healthy individuals. METHODS: 118 healthy individuals (72 males, 46 females, age 18-56years) initially underwent diffusion tensor imaging (DTI), 100 of them were included in the final analysis. We used Tract-Based Spatial Statistics (TBSS) to examine the impact of the CACNA1C SNP rs1006737 on the hippocampal formation as predefined region of interest (ROI). Furthermore, all participants completed the Verbal Learning and Memory Test (VLMT). RESULTS: In the VLMT genotype was significantly associated with learning performance. Bonferroni corrected post-hoc tests indicated a diminished performance at the beginning of the learning curve in risk allele carriers compared to non-risk allele carriers. The TBSS ROI analysis revealed one cluster of reduced FA in risk allele carriers compared to non-risk allele carriers located in the right hippocampal formation. Moreover, an association between the initial learning performance and FA values was found. DISCUSSION: These findings demonstrate that genetic variation in the CACNA1C SNP rs1006737 is associated with FA reduction in the hippocampal formation as well as with differences in learning performance in healthy individuals.

A genome-wide supported variant in CACNA1C influences hippocampal activation during episodic memory encoding and retrieval.

The alpha 1C subunit of the L-type voltage-gated calcium channel (CACNA1C) gene is one of the best replicated susceptibility loci for bipolar disorder, schizophrenia and major depression. It is involved in learning, memory and brain plasticity. Genetic studies using functional magnetic resonance imaging (fMRI) reported evidence of association with the CACNA1C single nucleotide polymorphism rs1006737 with functional correlates of episodic memory encoding and retrieval, especially activations in the hippocampus. These results, however, are inconsistent with regard to the magnitude and directionality of effect. In the present study, brain activation was measured with fMRI during an episodic memory encoding and retrieval task using neutral faces in two independent samples of 94 and 111 healthy subjects, respectively. Within whole brain analyses, a main effect of genotype emerged mainly in the right hippocampus during encoding as well as retrieval within the first sample: Carriers of the minor allele (A) exhibited lower activations compared to G/G allele carriers. This effect could be replicated within the second sample, however, only for the retrieval condition. The results strengthen findings that rs1006737 is associated with neural systems related to memory processes in hippocampal regions which are detectable in healthy subjects.

Neural processing of overt word generation in healthy individuals: the effect of age and word knowledge.

Verbal fluency is a classical and widely used neuropsychological instrument to assess cognitive abilities. Results of previous studies indicate an influence on verbal fluency performance of both, age and word knowledge. So far, no imaging study has investigated the neural mechanisms underlying an age and word knowledge related decline on the quantitative verbal output in a highly demanding overt and continuous semantic fluency task. Fifty healthy volunteers (age 22-56 years, verbal IQ 95-143) overtly and continuously articulated words in response to ten visually presented semantic categories while BOLD signal was measured with fMRI. Verbal responses were recorded with an MRI compatible microphone and transcribed after the scanning session. The number of produced words as well as age, word knowledge and level of education was implemented in the design matrix enabling a separate analysis of these factors on both, neural responses and behavioral differences. There was a significant correlation of level of education and number of generated words, but no significant correlations of generated words and age or word knowledge were observed. On the neural level, a widespread network was found for the word production task as contrasted with the resting condition, encompassing the bilateral superior temporal gyri, the cerebellum and the SMA. An age related positive correlation was found in the bilateral inferior and middle frontal gyri, the anterior cingulate gyrus, the left precentral gyrus and the right insula. A lower word knowledge resulted in enhanced BOLD responses in the right superior temporal gyrus and the left superior frontal gyrus. Results are interpreted in terms of compensation mechanisms countervailing potential age and word knowledge related effects.