Background and Purpose-Numerous preclinical findings and a clinical pilot study suggest that recombinant human erythropoietin (EPO) provides neuroprotection that may be beneficial for the treatment of patients with ischemic stroke. Although EPO has been considered to be a safe and well-tolerated drug over 2 decades, recent studies have identified increased thromboembolic complications and/or mortality risks on EPO administration to patients with cancer or chronic kidney disease. Accordingly, the double-blind, placebo-controlled, randomized German Multicenter EPO Stroke Trial (Phase II/III; ClinicalTrials.gov Identifier: NCT00604630) was designed to evaluate efficacy and safety of EPO in stroke. Methods-This clinical trial enrolled 522 patients with acute ischemic stroke in the middle cerebral artery territory (intent-to-treat population) with 460 patients treated as planned (per-protocol population). Within 6 hours of symptom onset, at 24 and 48 hours, EPO was infused intravenously (40 000 IU each). Systemic thrombolysis with recombinant tissue plasminogen activator was allowed and stratified for. Results-Unexpectedly, a very high number of patients received recombinant tissue plasminogen activator (63.4%). On analysis of total intent-to-treat and per-protocol populations, neither primary outcome Barthel Index on Day 90 (Pϭ0.45) nor any of the other outcome parameters showed favorable effects of EPO. There was an overall death rate of 16.4% (nϭ42 of 256) in the EPO and 9.0% (nϭ24 of 266) in the placebo group (OR, 1.98; 95% CI, 1.16 to 3.38; Pϭ0.01) without any particular mechanism of death unexpected after stroke. Conclusions-Based on analysis of total intent-to-treat and per-protocol populations only, this is a negative trial that also raises safety concerns, particularly in patients receiving systemic thrombolysis. (Stroke. 2009;40:e647-e656.)

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation.

BackgroundCognitive deterioration is a core symptom of many neuropsychiatric disorders and target of increasing significance for novel treatment strategies. Hence, its reliable capture in long-term follow-up studies is prerequisite for recording the natural course of diseases and for estimating potential benefits of therapeutic interventions. Since repeated neuropsychological testing is required for respective longitudinal study designs, occurrence, time pattern and magnitude of practice effects on cognition have to be understood first under healthy good-performance conditions to enable design optimization and result interpretation in disease trials.MethodsHealthy adults (N = 36; 47.3 ± 12.0 years; mean IQ 127.0 ± 14.1; 58% males) completed 7 testing sessions, distributed asymmetrically from high to low frequency, over 1 year (baseline, weeks 2-3, 6, 9, months 3, 6, 12). The neuropsychological test battery covered 6 major cognitive domains by several well-established tests each.ResultsMost tests exhibited a similar pattern upon repetition: (1) Clinically relevant practice effects during high-frequency testing until month 3 (Cohen's d 0.36-1.19), most pronounced early on, and (2) a performance plateau thereafter upon low-frequency testing. Few tests were non-susceptible to practice or limited by ceiling effects. Influence of confounding variables (age, IQ, personality) was minor.ConclusionsPractice effects are prominent particularly in the early phase of high-frequency repetitive cognitive testing of healthy well-performing subjects. An optimal combination and timing of tests, as extractable from this study, will aid in controlling their impact. Moreover, normative data for serial testing may now be collected to assess normal learning curves as important comparative readout of pathological cognitive processes.

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample.

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The personal significance of a language statement depends on its communicative context. However, this is rarely taken into account in neuroscience studies. Here, we investigate how the implied source of single word statements alters their cortical processing. Participants' brain event-related potentials were recorded in response to identical word streams consisting of positive, negative, and neutral trait adjectives stated to either represent personal trait feedback from a human or to be randomly generated by a computer. Results showed a strong impact of perceived sender. Regardless of content, the notion of receiving feedback from a human enhanced all components, starting with the P2 and encompassing early posterior negativity (EPN), P3, and the late positive potential (LPP). Moreover, negative feedback by the "human sender" elicited a larger EPN, whereas positive feedback generally induced a larger LPP. Source estimations revealed differences between "senders" in visual areas, particularly the bilateral fusiform gyri. Likewise, emotional content enhanced activity in these areas. These results specify how even implied sender identity changes the processing of single words in seemingly realistic communicative settings, amplifying their processing in the visual brain. This suggests that the concept of motivated attention extends from stimulus significance to simultaneous appraisal of contextual relevance. Finally, consistent with distinct stages of emotional processing, at least in contexts perceived as social, humans are initially alerted to negative content, but later process what is perceived as positive feedback more intensely.

Diffusion tensor imaging (DTI) detects microstructural changes of the cerebral white matter in Alzheimer's disease (AD). The use of DTI for the diagnosis of AD in a multicenter setting has not yet been investigated. We used voxel-based analysis of fractional anisotropy, mean diffusivity, and grey matter volumes from multimodal magnetic resonance imaging data of 137 AD patients and 143 healthy elderly controls collected across 9 different scanners. We compared different univariate analysis approaches to model the effect of scanner, including a linear model across all scans with a scanner covariate, a random effects model with scanner as a random variable as well as a voxel-based meta-analysis. We found significant reduction of fractional anisotropy and significant increase of mean diffusivity in core areas of AD pathology including corpus callosum, medial and lateral temporal lobes, as well as fornix, cingulate gyrus, precuneus, and prefrontal lobe white matter. Grey matter atrophy was most pronounced in medial and lateral temporal lobe as well as parietal and prefrontal association cortex. The effects of group were spatially more restricted with random effects modeling of scanner effects compared to simple pooled analysis. All three analysis approaches yielded similar accuracy of group separation in block-wise cross-validated logistic regression. Our results suggest similar effects of center on group separation based on different analysis approaches and confirm a typical pattern of cortical and subcortical microstructural changes in AD using a large multimodal multicenter data set.

Language has an intrinsically evaluative and communicative function. Words can serve to describe emotional traits and states in others and communicate evaluations. Using electroencephalography (EEG), we investigate how the cerebral processing of emotional trait adjectives is modulated by their perceived communicative sender in anticipation of an evaluation. 16 students were videotaped while they described themselves. They were told that a stranger would evaluate their personality based on this recording by endorsing trait adjectives. In a control condition a computer program supposedly randomly selected the adjectives. Actually, both conditions were random. A larger parietal N1 was found for adjectives in the supposedly human-generated condition. This indicates that more visual attention is allocated to the presented adjectives when putatively interacting with a human. Between 400 and 700 ms a fronto-central main effect of emotion was found. Positive, and in tendency also negative adjectives, led to a larger late positive potential (LPP) compared to neutral adjectives. A centro-parietal interaction in the LPP-window was due to larger LPP amplitudes for negative compared to neutral adjectives within the ‘human sender’ condition. Larger LPP amplitudes are related to stimulus elaboration and memory consolidation. Participants responded more to emotional content particularly when presented in a meaningful ‘human’ context. This was first observed in the early posterior negativity window (210–260 ms). But the significant interaction between sender and emotion reached only trend-level on post hoc tests. Our results specify differential effects of even implied communicative partners on emotional language processing. They show that anticipating evaluation by a communicative partner alone is sufficient to increase the relevance of particularly emotional adjectives, given a seemingly realistic interactive setting.