Voluntary suppression of thoughts is influenced by anxious and ruminative tendencies in healthy volunteers.

Replicating thought suppression effects with the Think/No-Think paradigm (TNT) has failed in some studies investigating the phenomenon of below-baseline recall of suppressed stimuli. Attempts have been made to isolate factors that might explain inter-individual differences in suppression performance. Certain personality traits, whether associated with a pathological state or investigated in a community sample, have been shown to interfere with successful thought suppression and might be responsible for some of the negative results obtained in TNT studies. In the present study we investigate the influence of psychometric measures of depression and anxiety in a fairly large sample of healthy volunteers. We show that high brooding and anxious tendencies predict worse suppression performance. While no suppression was shown when investigating the TNT not taking the psychometric measures into account, including these two traits in the analysis resulted in a pattern of below-baseline recall only for low brooders and low anxious participants. We argue that inclusion of variables measuring personality traits is warranted using the TNT and that these variables already exert their influence at minimal levels of variance, significantly improving the interpretability of the results. Future research should therefore cautiously investigate potential confounding personality characteristics before analysing their data.

Functional near-infrared spectroscopy for the assessment of speech related tasks.

Over the past years functional near-infrared spectroscopy (fNIRS) has substantially contributed to the understanding of language and its neural correlates. In contrast to other imaging techniques, fNIRS is well suited to study language function in healthy and psychiatric populations due to its cheap and easy application in a quiet and natural measurement setting. Its relative insensitivity for motion artifacts allows the use of overt speech tasks and the investigation of verbal conversation. The present review focuses on the numerous contributions of fNIRS to the field of language, its development, and related psychiatric disorders but also on its limitations and chances for the future.

Independent component analysis applied to pharmacological magnetic resonance imaging (phMRI): new insights into the functional networks underlying panic attacks as induced by CCK-4.

Pharmacological magnetic resonance imaging (phMRI) is a method to study effects of psychopharmacological agents on neural activation. Changes of the blood oxygen level dependent (BOLD), the basis of functional MRI (fMRI), are typically obtained at relatively high sampling frequencies. This has more recently been exploited in the field of fMRI by applying independent component analysis (ICA), an explorative data analysis method decomposing activation into distinct neural networks. While already successfully used to investigate resting network and task-induced activity, its use in phMRI is new. Further extension of this method to tensorial probabilistic ICA (tensor PICA) allows to group similar brain activation across the anatomical, temporal, subject or session domain. This approach is useful for pharmacological experiments when no pharmacokinetic model exists. We exemplify this method using data from a placebo-controlled cholecystokinine-4 (CCK-4) injection experiment performed on 16 neuropsychiatrically and medically healthy males (age 25.6 +/- 4.2 years). Tensor PICA identified strong increases in activity in 12 networks. Comparison with results gained from the standard approach (voxelwise regression analysis) revealed good reproduction of areas previously associated with CCK-4 action, such as the anterior cingulate, orbitofrontal cortex, cerebellum, temporolateral, left parietal and insular areas, striatum, and precuneus. Several other components such as the dorsal anterior cingulate and medial prefrontal cortex were identified, suggesting higher sensitivity of the method. Exploration of the time courses of each activated network revealed differences, that might be lost when a fixed time course is modeled, e. g. neuronal responses to an acoustic warning signal prior to injection. Comparison of placebo and CCK-4 runs further showed that a proportion of networks are newly elicited by CCK-4 whereas other components are significantly active in the placebo conditions but further enhanced by CCK-4. In conclusion, group ICA is a promising tool for phMRI studies that allows quantifying and visualizing the modulation of neural networks by pharmacological interventions.