Loneliness is broadly described as a negative emotional response resulting from the differences between the actual and desired social relations of an individual, which is related to the neural responses in connection with social and emotional stimuli. Prior research has discovered that some neural regions play a role in loneliness. However, little is known about the differences among individuals in loneliness and the relationship of those differences to differences in neural networks. The current study aimed to investigate individual differences in perceived loneliness related to the causal interactions between resting-state networks (RSNs), including the dorsal attentional network (DAN), the ventral attentional network (VAN), the affective network (AfN) and the visual network (VN). Using conditional granger causal analysis of resting-state fMRI data, we revealed that the weaker causal flow from DAN to VAN is related to higher loneliness scores, and the decreased causal flow from AfN to VN is also related to higher loneliness scores. Our results clearly support the hypothesis that there is a connection between loneliness and neural networks. It is envisaged that neural network features could play a key role in characterizing the loneliness of an individual.

Resting-state functional magnetic resonance imaging was utilized to measure the amplitude low frequency fluctuations (ALFF) in human subjects with Alzheimer’s disease (AD) and normal control (NC). Two specific frequency bands (Slow5: 0.01-0.027Hz and Slow4: 0.027-0.073Hz) were analysed in the main cognitive control related four subregions of the right ventral lateral prefrontal cortex (VLPFC), i.e. IFJ, posterior-VLPFC, mid-VLPFC, and anterior-VLPFC. Differences in ALFF values between the AD and the NC group were found throughout the subregions of the right VLPFC. Compared to normal control group, decreased ALFF values were observed in AD patients in the IFJ (in two given frequency bands), and the mid-VLPFC (in Slow5). In contrast, increased ALFF valued were observed in AD patients in the posterior- and anterior-VLPFC (in both Slow5 and Slow4), and also in the mid-VLPFC in Slow4. Moreover, significant ALFF differences between the IFJ and three other subregions of the right VLPFC were found. Furthermore, ALFF values in the right VLPFC showed significant correlations with the time course of disease. Taken together, our findings suggest that AD patients have largely abnormalities in intrinsic neural oscillations which are in line with the AD pathophysiology, and further reveal that the abnormalities are dependent on specific frequency bands. Thus, frequency-domain analyses of the ALFF may provide a useful tool to investigate the AD pathophysiology.

About 35 million people worldwide were suffered from Alzheimer’s disease (AD) in 2014 and the number of patients was expected to increase by 4-fold in 2050. As a neurodegenerative disease impacting our society, the pathogenesis and prognosis of AD have not yet fully understood. Senile plaque is generally regarded as one of the hallmarks of the disease, which may be due to the imbalance of Aβ peptides in the brain. Over the last decades, studies of early onset familial AD have led us to a deeper understanding of the genetics and molecular biology of AD. There is increasing evidence to suggest that the pathogenesis of AD is more likely to be caused by multiple genetic mutations. However, the precise genetic component leading to AD pathogenesis remains unclear. In this review, we will briefly introduce the classification of AD in the context of genetics. Then we will discuss the gene mutations in chromosome 21, 19 and presenilin as well as their links to Aβ peptides. Imaging data will be discussed alongside to complement the associated structural and physiological changes in the brain. It is our hope that future research in genetics will continue to enhance our understanding of the pathogenesis of AD and the mechanisms leading to the formation of senile plaques.