Metabolic Dynamics in the Prefrontal Cortex during a Working Memory Task in Young Adult Smokers.

INTRODUCTION: Cigarette smoking is known to modulate brain metabolism and brain function. How the dynamics of these metabolic alterations influence the active performance of higher order cognitive tasks in smokers, compared to non-smokers, is still unclear. The present exploratory study sought to examine the impact of smoking on the "complete" metabolic profile while the participants performed a working memory (N-back) task. METHODS: The study sample consisted of 40 young male healthy participants (smokers [n = 20] and non-smokers [n = 20]). Functional magnetic resonance spectroscopy data were acquired using a 3 T whole-body MR system. Data analysis was performed using Java-based Magnetic Resonance User Interface software, and metabolite ratios with respect to creatine (Cr) were calculated. RESULTS: On a behavioural level, smokers showed worse performance (measured by d') than non-smokers. However, we observed significant differences in the metabolite concentrations in smokers compared to non-smokers, which also changed over the course of the N-back task. A significant effect of the group was observed with smokers showing lower glutamate/Cr (Glx/Cr) and choline/Cr (Cho/Cr) ratios than non-smokers. Further, N-acetyl aspartate (NAA/Cr) and Cho/Cr ratios were significantly different during the rest and the task conditions. In addition, our results demonstrated the metabolite interactions (NAA and Cho, Glx and myo-inositol [mI], and Cho and mI). CONCLUSION: Further studies are necessary to shed more light on the association between smoking behaviours and metabolic alterations. However, our preliminary findings would assist in this future research to have a complete understanding of the metabolite interactions not only in smoking but also in addiction research.

Variability of clinical functional MR imaging results: a multicenter study.

PURPOSE: To investigate intersite variability of clinical functional magnetic resonance (MR) imaging, including influence of task standardization on variability and use of various parameters to inform the clinician whether the reliability of a given functional localization is high or low. MATERIALS AND METHODS: Local ethics committees approved the study; all participants gave written informed consent. Eight women and seven men (mean age, 40 years) were prospectively investigated at three experienced functional MR sites with 1.5- (two sites) or 3-T (one site) MR. Nonstandardized motor and highly standardized somatosensory versions of a frequently requested clinical task (localization of the primary sensorimotor cortex) were used. Perirolandic functional MR variability was assessed (peak activation variability, center of mass [COM] variability, intraclass correlation values, overlap ratio [OR], activation size ratio). Data quality measures for functional MR images included percentage signal change (PSC), contrast-to-noise ratio (CNR), and head motion parameters. Data were analyzed with analysis of variance and a correlation analysis. RESULTS: Localization of perirolandic functional MR activity differed by 8 mm (peak activity) and 6 mm (COM activity) among sites. Peak activation varied up to 16.5 mm (COM range, 0.4-16.5 mm) and 45.5 mm (peak activity range, 1.8-45.5 mm). Signal strength (PSC, CNR) was significantly lower for the somatosensory task (mean PSC, 1.0% ± 0.5 [standard deviation]; mean CNR, 1.2 ± 0.4) than for the motor task (mean PSC, 2.4% ± 0.8; mean CNR, 2.9 ± 0.9) (P < .001, both). Intersite variability was larger with low signal strength (negative correlations between signal strength and peak activation variability) even if the task was highly standardized (mean OR, 22.0% ± 18.9 [somatosensory task] and 50.1% ± 18.8 [motor task]). CONCLUSION: Clinical practice and clinical functional MR biomarker studies should consider that the center of task-specific brain activation may vary up to 16.5 mm, with the investigating site, and should maximize functional MR signal strength and evaluate reliability of local results with PSC and CNR.

Self-similarity and recursion as default modes in human cognition.

Humans generate recursive hierarchies in a variety of domains, including linguistic, social and visuo-spatial modalities. The ability to represent recursive structures has been hypothesized to increase the efficiency of hierarchical processing. Theoretical work together with recent empirical findings suggests that the ability to represent the self-similar structure of hierarchical recursive stimuli may be supported by internal neural representations that compress raw external information and increase efficiency. In order to explicitly test whether the representation of recursive hierarchies depends on internalized rules we compared the processing of visual hierarchies represented either as recursive or non-recursive, using task-free resting-state fMRI data. We aimed to evaluate the relationship between task-evoked functional networks induced by cognitive representations with the corresponding resting-state architecture. We observed increased connectivity within Default Mode Network (DMN) related brain areas during the representation of recursion, while non-recursive representations yielded increased connectivity within the Fronto-Parietal Control-Network. Our results suggest that human hierarchical information processing using recursion is supported by the DMN. In particular, the representation of recursion seems to constitute an internally-biased mode of information-processing that is mediated by both the core and dorsal-medial subsystems of the DMN. Compressed internal rule representations mediated by the DMN may help humans to represent and process hierarchical structures in complex environments by considerably reducing information processing load.