Modularity Of Functional Networks Research Articles

Functional network modularity and efficiency supports episodic memory in older adults with amyloid‐beta pathology

AbstractBackgroundEpisodic memory is one of the first cognitive domains to decline in preclinical Alzheimer’s disease. We investigated whether graph metrics of functional networks, specifically modularity and local efficiency, are related to episodic memory and amyloid‐β (Aβ) positivity in cognitively normal older adults.MethodSixty‐five cognitively normal older adults (mean age 72.3 ± 6.2 years; 62% female) underwent high‐resolution resting state fMRI (1.8mm3, partial acquisition) to measure functional connectivity, 18F‐Florbetapir‐PET to measure Aβ pathology, and cognitive assessment. Resting state fMRI data was processed with CONN. ROIs (n=135) from the Brainnetome Atlas contained within rsfMRI coverage were used to generate ROI‐to‐ROI functional connectivity matrices. Graph measures of modularity (Q) and local efficiency were computed with the Brain Connectivity Toolbox using binary graphs at costs ranging from 5%‐50% of network sparsity (5% step size). Aβ status was determined using a >1.11 SUVR threshold of a composite region spanning the association cortex, resulting in 32% of the sample being classified as Aβ+. Episodic memory was measured using the immediate recall measure of the Rey Auditory Verbal Learning Test (RAVLT A5).ResultAβ+ participants had significantly increased modularity compared to Aβ‐ (Fig1A, p<0.05 for costs 25 and 50), but no differences in local efficiency (Fig1B). There was no significant effect of Aβ positivity on RAVLT A5 performance (t(63)=‐0.67, p = 0.51). However, there were significant interactions between Aβ status and RAVLT A5 with both modularity and local efficiency at most cost functions (Fig2). Better RAVLT A5 performance was associated with higher modularity (Fig2A; ex. cost 25: r = 0.54, p=0.01) and higher local efficiency (Fig2B; ex. cost 25: r = 0.63, p=0.002) within Aβ+ participants, but not Aβ‐ participants (ps>0.36).ConclusionOur findings suggest that increases in functional network modularity and local efficiency within Aβ+ cognitively normal older adults may act as a compensatory mechanism to maintain equivalent levels of episodic memory performance.

Age differences in functional network reconfiguration with working memory training.

Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10 days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task‐related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default‐mode network for younger adults, it enhanced efficiency within a task‐specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default‐mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between‐network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age‐related trajectories in functional network reorganization with WM training.

Breakdown of the brain’s functional network modularity with awareness

Neurobiological theories of awareness propose divergent accounts of the spatial extent of brain changes that support conscious perception. Whereas focal theories posit mostly local regional changes, global theories propose that awareness emerges from the propagation of neural signals across a broad extent of sensory and association cortex. Here we tested the scalar extent of brain changes associated with awareness using graph theoretical analysis applied to functional connectivity data acquired at ultra-high field while subjects performed a simple masked target detection task. We found that awareness of a visual target is associated with a degradation of the modularity of the brain's functional networks brought about by an increase in intermodular functional connectivity. These results provide compelling evidence that awareness is associated with truly global changes in the brain's functional connectivity.

Altered functional and structural brain network organization in autism

Structural and functional underconnectivity have been reported for multiple brain regions, functional systems, and white matter tracts in individuals with autism spectrum disorders (ASD). Although recent developments in complex network analysis have established that the brain is a modular network exhibiting small-world properties, network level organization has not been carefully examined in ASD. Here we used resting-state functional MRI (n = 42 ASD, n = 37 typically developing; TD) to show that children and adolescents with ASD display reduced short and long-range connectivity within functional systems (i.e., reduced functional integration) and stronger connectivity between functional systems (i.e., reduced functional segregation), particularly in default and higher-order visual regions. Using graph theoretical methods, we show that pairwise group differences in functional connectivity are reflected in network level reductions in modularity and clustering (local efficiency), but shorter characteristic path lengths (higher global efficiency). Structural networks, generated from diffusion tensor MRI derived fiber tracts (n = 51 ASD, n = 43 TD), displayed lower levels of white matter integrity yet higher numbers of fibers. TD and ASD individuals exhibited similar levels of correlation between raw measures of structural and functional connectivity (n = 35 ASD, n = 35 TD). However, a principal component analysis combining structural and functional network properties revealed that the balance of local and global efficiency between structural and functional networks was reduced in ASD, positively correlated with age, and inversely correlated with ASD symptom severity. Overall, our findings suggest that modeling the brain as a complex network will be highly informative in unraveling the biological basis of ASD and other neuropsychiatric disorders.