Ageing in a collective: the impact of ageing individuals on social network structure

Ageing affects many phenotypic traits, but its consequences for social behaviour have only recently become apparent. Social networks emerge from associations between individuals. The changes in sociality that occur as individuals get older are thus likely to impact network structure, yet this remains unstudied. Here we use empirical data from free-ranging rhesus macaques and an agent-based model to test how age-based changes in social behaviour feed up to influence: (i) an individual's level of indirect connectedness in their network and (ii) overall patterns of network structure. Our empirical analyses revealed that female macaques became less indirectly connected as they aged for some, but not for all network measures examined. This suggests that indirect connectivity is affected by ageing, and that ageing animals can remain well integrated in some social contexts. Surprisingly, we did not find evidence for a relationship between age distribution and the structure of female macaque networks. We used an agent-based model to gain further understanding of the link between age-based differences in sociality and global network structure, and under which circumstances global effects may be detectable. Overall, our results suggest a potentially important and underappreciated role of age in the structure and function of animal collectives, which warrants further investigation. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Diffusion tensor imaging based network analysis detects alterations of neuroconnectivity in patients with clinically early relapsing-remitting multiple sclerosis

Although it is inarguable that conventional MRI (cMRI) has greatly contributed to the diagnosis and assessment of multiple sclerosis (MS), cMRI does not show close correlation with clinical findings or pathologic features, and is unable to predict prognosis or stratify disease severity. To this end, diffusion tensor imaging (DTI) with tractography and neuroconnectivity analysis may assist disease assessment in MS. We, therefore, attempted this pilot study for initial assessment of early relapsing-remitting MS (RRMS). Neuroconnectivity analysis was used for evaluation of 24 early RRMS patients within 2 years of presentation, and compared to the network measures of a group of 30 age-and-gender-matched normal control subjects. To account for the situation that the connections between two adjacent regions may be disrupted by an MS lesion, a new metric, network communicability, was adopted to measure both direct and indirect connections. For each anatomical area, the brain network communicability and average path length were computed and compared to characterize the network changes in efficiencies. Statistically significant (P < 0.05) loss of communicability was revealed in our RRMS cohort, particularly in the frontal and hippocampal/parahippocampal regions as well as the motor strip and occipital lobes. Correlation with the 25-foot Walk test with communicability measures in the left superior frontal (r = -0.71) as well as the left superior temporal gyrus (r = -0.43) and left postcentral gyrus (r = -0.41) were identified. Additionally identified were increased communicability between the deep gray matter structures (left thalamus and putamen) with the major interhemispheric and intrahemispheric white matter tracts, the corpus callosum, and cingulum, respectively. These foci of increased communicability are thought to represent compensatory changes. The proposed DTI-based neuroconnectivity analysis demonstrated quantifiable, structurally relevant alterations of fiber tract connections in early RRMS and paves the way for longitudinal studies in larger patient groups.