Imaging emotional brain functions: conceptual and methodological issues

This article reviews the psychophysiological and brain imaging literature on emotional brain function from a methodological point of view. The difficulties in defining, operationalising and measuring emotional activation and, in particular, aversive learning will be considered. Emotion is a response of the organism during an episode of major significance and involves physiological activation, motivational, perceptual, evaluative and learning processes, motor expression, action tendencies and monitoring/subjective feelings. Despite the advances in assessing the physiological correlates of emotional perception and learning processes, a critical appraisal shows that functional neuroimaging approaches encounter methodological difficulties regarding measurement precision (e.g., response scaling and reproducibility) and validity (e.g., response specificity, generalisation to other paradigms, subjects or settings). Since emotional processes are not only the result of localised but also of widely distributed activation, a more representative model of assessment is needed that systematically relates the hierarchy of high- and low-level emotion constructs with the corresponding patterns of activity and functional connectivity of the brain.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

The alpha and beta subunits of the metalloprotease meprin are expressed in separate layers of human epidermis, revealing different functions in keratinocyte proliferation and differentiation

The zinc endopeptidase meprin (EC 3.4.24.18) is expressed in brush border membranes of intestine and kidney tubules, intestinal leukocytes, and certain cancer cells, suggesting a role in epithelial differentiation and cell migration. Here we show by RT-PCR and immunoblotting that meprin is also expressed in human skin. As visualized by immunohistochemistry, the two meprin subunits are localized in separate cell layers of the human epidermis. Meprin alpha is expressed in the stratum basale, whereas meprin beta is found in cells of the stratum granulosum just beneath the stratum corneum. In hyperproliferative epidermis such as in psoriasis vulgaris, meprin alpha showed a marked shift of expression from the basal to the uppermost layers of the epidermis. The expression patterns suggest distinct functions for the two subunits in skin. This assumption is supported by diverse effects of recombinant meprin alpha and beta on human adult low-calcium high-temperature keratinocytes. Here, beta induced a dramatic change in cell morphology and reduced the cell number, indicating a function in terminal differentiation, whereas meprin alpha did not affect cell viability, and may play a role in basal keratinocyte proliferation.

The experimental combination of rTMS and fMRI reveals the functional relevance of parietal cortex for visuospatial functions

We combined repetitive transcranial magnetic stimulation (rTMS) and functional magnetic resonance imaging (fMRI) to investigate the functional relevance of parietal cortex activation during the performance of visuospatial tasks. fMRI provides information about local transient changes in neuronal activation during behavioural or cognitive tasks. Information on the functional relevance of this activation was obtained by using rTMS to induce temporary regional deactivations. We thereby turned the physiological parameter of brain activity into an independent variable controlled and manipulated by the experimenter and investigated its effect on the performance of the cognitive tasks within a controlled experimental design. We investigated cognitive tasks that were performed on the same visual material but differed in the demand on visuospatial functions. For the visuospatial tasks we found a selective enhancement of fMRI signal in the superior parietal lobule (SPL) and a selective impairment of performance after rTMS to this region in comparison to a control group. We could thus show that the parietal cortex is functionally important for the execution of spatial judgements on visually presented material and that TMS as an experimental tool has the potential to interfere with higher cognitive functions such as visuospatial information processing.