Elucidation of the neural correlates of time perception constitutes an important research topic in cognitive neuroscience. The focus to date has been on durations in the millisecond to seconds range, but here we used electroencephalography (EEG) to examine brain functional connectivity during much longer durations (i.e., 15 min). For this purpose, we conducted an initial exploratory experiment followed by a confirmatory experiment. Our results showed that those participants who overestimated time exhibited lower activity of beta (18–30 Hz) at several electrode sites. Furthermore, graph theoretical analysis indicated significant differences in the beta range (15–30 Hz) between those that overestimated and underestimated time. Participants who underestimated time showed higher clustering coefficient compared to those that overestimated time. We discuss our results in terms of two aspects. FFT results, as a linear approach, are discussed within localized/dedicated models (i.e., scalar timing model). Second, non-localized properties of psychological interval timing (as emphasized by intrinsic models) are addressed and discussed based on results derived from graph theory. Results suggested that although beta amplitude in central regions (related to activity of BG-thalamocortical pathway as a dedicated module) is important in relation to timing mechanisms, the properties of functional activity of brain networks; such as the segregation of beta network, are also crucial for time perception. These results may suggest subjective time may be created by vector units instead of scalar ticks.

Objective. Transcranial photobiomodulation (tPBM) is a recently proposed non-invasive brain stimulation approach with various effects on the nervous system from the cells to the whole brain networks. Specially in the neural network level, tPBM can alter the topology and synchronizability of functional brain networks. However, the functional properties of the neural networks after tPBM are still poorly clarified. Approach. Here, we employed electroencephalography and different methods (conventional and spectral) in the graph theory analysis to track the significant effects of tPBM on the resting state brain networks. The non-parametric statistical analysis showed that just one short-term tPBM session over right medial frontal pole can significantly change both topological (i.e. clustering coefficient, global efficiency, local efficiency, eigenvector centrality) and dynamical (i.e. energy, largest eigenvalue, and entropy) features of resting state brain networks. Main results. The topological results revealed that tPBM can reduce local processing, centrality, and laterality. Furthermore, the increased centrality of central electrode was observed. Significance. These results suggested that tPBM can alter topology of resting state brain network to facilitate the neural information processing. On the other hand, the dynamical results showed that tPBM reduced stability of synchronizability and increased complexity in the resting state brain networks. These effects can be considered in association with the increased complexity of connectivity patterns among brain regions and the enhanced information propagation in the resting state brain networks. Overall, both topological and dynamical features of brain networks suggest that although tPBM decreases local processing (especially in the right hemisphere) and disrupts synchronizability of network, but it can increase the level of information transferring and processing in the brain network.

No abstract

Congenital heart defects are structural cardiovascular malformations that arise from abnormal formation of the heart or major blood vessels during the fetal period. To investigate the association of 4 single nucleotide polymorphisms (SNPs) in the MTHFD1, eNOS, CBS and ACE genes, we evaluated their relationship with CHD in Iranian patients. In this case-control study, a total of 102 children with CHD and 98 control children were enrolled. Four SNPs including MTHFD1 G1958A, eNOS G894T, CBS C-4673G and ACE A2350G were genotyped by PCR-SSCP, Multiplex ARMS PCR and PCR-RFLP methods and confirmed by direct sequencing. We genotyped 102 patients and 98 controls for four polymorphisms by statistically analysis. There were three SNPs including MTHFD1 G1958A, eNOS G894T and ACE A2350G which might increase the risk of CHD, but CBS C-4673G was not significantly different between patients and controls. (P = 0.017, P = 0.048, P = 0.025 and P = 0.081 respectively). The allele frequencies of three SNPs for MTHFD1 G1958A, eNOS G894T and ACE A2350G in CHD are higher than that in control. Our results show that there is a significant relationship between MTHFD1 G1958A, eNOS G894T and ACE A2350G polymorphisms with CHD. Therefore, The AA and GA genotypes of MTHFD1 G1958A, TT and GT genotypes of eNOS G894T and the AA and GA genotypes of ACE A2350G are susceptible factors for CHD and may increase the risk of CHD.

Foodborne diseases are manifested through a wide array of symptoms, such as gastrointestinal disorders, diarrhea, and vomiting, which are most common. Failure in the treatment of such diseases could cause damage to the joints, nervous system, kidneys, and heart [5]. On the other hand, if appropriate measures are not taken to control foodborne diseases, these disorders spread quickly, affecting a larger number of individuals [6].According to the estimates of the Centers for Disease Background: Proper food management during food preparation and maintenance is essential to reducing foodborne diseases. The theory of planned behavior (TPB) is commonly used for the examination of health behaviors. No research has assessed the effectiveness of TPB in predicting food safety behaviors in Iran. The present study aimed to examine food safety behaviors based on the TPB. Methods: This cross-sectional study was conducted on 220 women in Yazd, Iran in 2018. Data were collected using a researcher-made questionnaire consisting of items on food safety behaviors and TPB constructs with confirmed reliability and validity. Data analysis was performed in SPSS version 21.0. Results: A significant, positive correlation was observed between food safety behaviors and all the TPB constructs (r = 0.15-0.38; P < 0.05). In addition, intention was significantly correlated with food safety behaviors (r = 0.35; P < 0.001), and 27% of the behavior variance was explained by the TPB constructs. Perceived behavioral control was the strongest predictor (β = 0.3; P < 0.001), and 31% of the intention variance was explained by the TPB constructs. Subjective norm was considered the strongest predictor (β = 0.41; P < 0.001). Conclusion:The TPB could be used as a framework for the educational interventions aimed at health observance in food preparation.