Predicting Decisions in Human Social Interactions Using Real-Time fMRI and Pattern Classification

Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives

Malignant Tumors of the Central Nervous System

Malignant tumors of the central nervous system in adults comprise a heterogeneous group of malignancies, the largest subgroups comprising astrocytomas, ependymomas, and oligodendrogliomas. Glioblastomas are the most common tumor type, and they have dismal prognosis. Due to differences in cell type of origin, as well as pathogenesis, it is plausible that their etiology also differs between tumor types. The etiology of malignant CNS tumors is largely unknown and no occupational risk factors have been definitively identified. High doses of ionizing radiation increase the risk, but in occupational settings the dose levels appear too small to result in discernible excesses. Several studies have assessed possible effect of extremely low frequency and radiofrequency electromagnetic fields, but the results are inconsistent. Increased brain tumor risk has been reported in agricultural workers, but no specific exposure has been linked to them. Pesticides have been analyzed in several studies without showing a clear increase in risk.acceptedVersionPeer reviewe

Impact of Systemic Inflammation and Autoimmune Diseases on apoA-I and HDL Plasma Levels and Functions

The cholesterol of high-density lipoproteins (HDLs) and its major proteic component, apoA-I, have been widely investigated as potential predictors of acute cardiovascular (CV) events. In particular, HDL cholesterol levels were shown to be inversely and independently associated with the risk of acute CV diseases in different patient populations, including autoimmune and chronic inflammatory disorders. Some relevant and direct anti-inflammatory activities of HDL have been also recently identified targeting both immune and vascular cell subsets. These studies recently highlighted the improvement of HDL function (instead of circulating levels) as a promising treatment strategy to reduce inflammation and associated CV risk in several diseases, such as systemic lupus erythematosus and rheumatoid arthritis. In these diseases, anti-inflammatory treatments targeting HDL function might improve both disease activity and CV risk. In this narrative review, we will focus on the pathophysiological relevance of HDL and apoA-I levels/functions in different acute and chronic inflammatory pathophysiological conditions

Time-restricted feeding alters lipid and amino acid metabolite rhythmicity without perturbing clock gene expression

Time-restricted feeding (TRF) improves metabolism independent of dietary macronutrient composition or energy restriction. To elucidate mechanisms underpinning the effects of short-term TRF, we investigated skeletal muscle and serum metabolic and transcriptomic profiles from 11 men with overweight/obesity after TRF (8 h day−1) and extended feeding (EXF, 15 h day−1) in a randomised cross-over design (trial registration: ACTRN12617000165381). Here we show that muscle core clock gene expression was similar after both interventions. TRF increases the amplitude of oscillating muscle transcripts, but not muscle or serum metabolites. In muscle, TRF induces rhythmicity of several amino acid transporter genes and metabolites. In serum, lipids are the largest class of periodic metabolites, while the majority of phase-shifted metabolites are amino acid related. In conclusion, short-term TRF in overweight men affects the rhythmicity of serum and muscle metabolites and regulates the rhythmicity of genes controlling amino acid transport, without perturbing core clock gene expression