Call Characteristic Network Reveal Geographical Patterns of Call Similarity:Applying Network Analysis to Frog’s Call Research

Individual’s phenotypic traits are the results of adaptation to ecological conditions.Therefore,different selection pressures caused by heterogeneous environments may result in phenotypic difference,especially for individuals in different geographical populations.Here,we illustrated for the first time to use social network analysis(SNA)for examining whether geographical proximity predicts the similarity patterns in call characteristics among populations of an anuran species.We recorded calls from 150 male dorsal-striped opposite-fingered treefrogs(Chiromantis doriae)at 11 populations in Hainan Province and one population in Guangdong Province in China's Mainland,and we measured eight acoustic variables for each male.Mantel test didn’t show a correlation between geographical proximity and the similarity in call characteristics among populations.In addition,we failed to find correlations between a population’s eigenvector centrality and the distance to its nearest neighbor,nor between the coefficient of variation of similarity in call characteristics of a population and the average distance to all other populations.Nevertheless,three acoustic clusters were identified by the Girvan-Newman algorithm,and clustering was partially associated with geography.Furthermore,the most central populations were included in the same cluster,but the top betweenness populations were located within different clusters,suggesting that centrality populations are not necessary bridging between clusters.These results demonstrate the potential usefulness of the SNA toolbox and indicate that SNA helps to uncover the patterns that often overlooked in other analytical methods.By using SNA in frog’s call studies,researchers could further uncover the potential relationship in call characteristics between geographical populations,further reveal the effects of ecological factors on call characteristics,and probably enhance our understanding of the adaptive evolution of acoustic signals.

Aberrant functional connectivity network in subjective memory complaint individuals relates to pathological biomarkers

Background:Individuals with subjective memory complaints(SMC)feature a higher risk of cognitive decline and clinical progression of Alzheimer’s disease(AD).However,the pathological mechanism underlying SMC remains unclear.We aimed to assess the intrinsic connectivity network and its relationship with AD-related pathologies in SMC individuals.Methods:We included 44 SMC individuals and 40 normal controls who underwent both resting-state functional MRI and positron emission tomography(PET).Based on graph theory approaches,we detected local and global functional connectivity across the whole brain by using degree centrality(DC)and eigenvector centrality(EC)respectively.Additionally,we analyzed amyloid deposition and tauopathy via florbetapir-PET imaging and cerebrospinal fluid(CSF)data.The voxel-wise two-sample T-test analysis was used to examine between-group differences in the intrinsic functional network and cerebral amyloid deposition.Then,we correlated these network metrics with pathological results.Results:The SMC individuals showed higher DC in the bilateral hippocampus(HP)and left fusiform gyrus and lower DC in the inferior parietal region than controls.Across all subjects,the DC of the bilateral HP and left fusiform gyrus was positively associated with total tau and phosphorylated tau181.However,no significant between-group difference existed in EC and cerebral amyloid deposition.Conclusion:We found impaired local,but not global,intrinsic connectivity networks in SMC individuals.Given the relationships between DC value and tau level,we hypothesized that functional changes in SMC individuals might relate to pathological biomarkers.