BackgroundThe processing of verbal fluency tasks relies on the coordinated activity of a number of brain areas, particularly in the frontal and temporal lobes of the left hemisphere. Recent studies using functional magnetic resonance imaging (fMRI) to study the neural networks subserving verbal fluency functions have yielded divergent results especially with respect to a parcellation of the inferior frontal gyrus for phonemic and semantic verbal fluency. We conducted a coordinate-based activation likelihood estimation (ALE) meta-analysis on brain activation during the processing of phonemic and semantic verbal fluency tasks involving 28 individual studies with 490 healthy volunteers.ResultsFor phonemic as well as for semantic verbal fluency, the most prominent clusters of brain activation were found in the left inferior/middle frontal gyrus (LIFG/MIFG) and the anterior cingulate gyrus. BA 44 was only involved in the processing of phonemic verbal fluency tasks, BA 45 and 47 in the processing of phonemic and semantic fluency tasks.ConclusionsOur comparison of brain activation during the execution of either phonemic or semantic verbal fluency tasks revealed evidence for spatially different activation in BA 44, but not other regions of the LIFG/LMFG (BA 9, 45, 47) during phonemic and semantic verbal fluency processing.

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Impulsivity is regarded as a clinical, diagnostic and pathophysiological hallmark of borderline personality disorder (BPD). Self-report measures of impulsivity consistently support the notion of higher impulsive traits in BPD patients as compared to healthy control subjects. Laboratory tests of impulsivity, i.e. neuropsychological tests of impulse control render weak and inconsistent results both across different cognitive components of impulse control and within the same cognitive component of impulse control. One important factor worsening impulsive behaviors and impulse control deficits in BPD is comorbid attention-deficit/hyperactivity disorder (ADHD). In addition, emotional dysregulation interacts with impulse control especially for BPD salient emotions. In sum, although basic mechanisms of impulse control seem not to be disturbed in BPD, clinically well observed impulsive behaviors may be explained by comorbid ADHD or may be the consequence of dysregulation of BPD salient emotions.

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Disorders such as borderline personality disorder (BPD) or attention-deficit/hyperactivity disorder (ADHD) are characterized by impulsive behaviors. Impulsivity as used in clinical terms is very broadly defined and entails different categories including personality traits as well as different cognitive functions such as emotion regulation or interference resolution and impulse control. Impulse control as an executive function, however, is neither cognitively nor neurobehaviorally a unitary function. Recent findings from behavioral and cognitive neuroscience studies suggest related but dissociable components of impulse control along functional domains like selective attention, response selection, motivational control, and behavioral inhibition. In addition, behavioral and neural dissociations are seen for proactive vs. reactive inhibitory motor control. The prefrontal cortex with its sub-regions is the central structure in executing these impulse control functions. Based on these concepts of impulse control, neurobehavioral findings of studies in BPD and ADHD were reviewed and systematically compared. Overall, patients with BPD exhibited prefrontal dysfunctions across impulse control components rather in orbitofrontal, dorsomedial, and dorsolateral prefrontal regions, whereas patients with ADHD displayed disturbed activity mainly in ventrolateral and medial prefrontal regions. Prefrontal dysfunctions, however, varied depending on the impulse control component and from disorder to disorder. This suggests a dissociation of impulse control related frontal dysfunctions in BPD and ADHD, although only few studies are hitherto available to assess frontal dysfunctions along different impulse control components in direct comparison of these disorders. Yet, these findings might serve as a hypothesis for the future systematic assessment of impulse control components to understand differences and commonalities of prefrontal cortex dysfunction in impulsive disorders.

Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.

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