Healthy aging is marked by changes in both cognitive performance and the organization of brain networks. Declines in cognition have been linked to reductions in system segregation (SS), as older adults typically exhibit less segregated functional networks than younger adults. While lower segregation has been associated with diminished cognitive abilities, it remains unclear how individual variability in SS contributes to cognitive outcomes across the lifespan. Here, we examine relationships between SS and three cognitive domains (semantic, executive, episodic memory) using resting-state fMRI data from 179 younger (18-29 years) and 117 older adults (60-89 years). SS was measured globally and for specific networks using Schaefer's 7-network parcellation. Our findings confirmed a global age-related reduction in SS, particularly impacting the somatomotor, ventral attention, and frontoparietal networks. This reduction in global SS mediated negative effects of age group on semantic and executive performance. When examining younger and older groups separately, we found that higher SS was associated with better semantic performance in both groups, while observing a similar positive association with executive performance only in older adults, suggesting that executive function becomes increasingly dependent on preserved network architecture with age. Maintaining SS may therefore be critical for supporting healthy cognitive aging.
Network models are a key tool in human neuroscience, and translation into animal models is essential for interrogating mechanistic drivers of network organization. Using magnetic resonance imaging (MRI), we present the first in vivo network representation of the individual rat brain, a key animal model in neuroscience. We measured magnetization transfer ratio (MTR) at each of 53 distinct cortical areas and estimated a cortical similarity network for each scan across two independent cohorts. We characterized normative network development in rats scanned repeatedly between postnatal days 20 (weanling) and 290 (mid-adulthood; N = 47) and then contrasted these findings with a cohort exposed to early life stress (repeated maternal separation [RMS]; N = 40). The normative rat cortical similarity network exhibited biologically meaningful organization, consistent with cytoarchitectonic and tract-tracing data, and displayed complex topological features. Developmental analyses revealed increasing interregional similarity during early postnatal and adolescent periods, followed by divergence in mid-adulthood, particularly within fronto-hippocampal systems. RMS disrupted these trajectories, especially between frontal and parahippocampal regions that were also most dynamic during development and aging. These findings introduce a new network-based methodology for studying cortical organization in a model organism, providing a translational framework to understand how environmental risk factors alter brain network development.
The thalamus is a heterogeneous structure crucial for corticocortical communication, affective-perceptual integration, motor preparation, and memory-related functions. Posttraumatic stress disorder (PTSD) is characterized by various symptoms that likely relate to thalamic functions. Group-level and individual differential structural covariance (SC) analyses were conducted on intrathalamic, thalamocortical, and thalamosubcortical volumetric networks by segmenting structural MRI data from 2,784 subjects (PTSD n = 1,306; controls n = 1,478) into 25 thalamic nuclei per hemisphere. We found that PTSD was associated with stronger intrathalamic and thalamocortical network strength and stronger SC between the limbic thalamus and the somatomotor and auditory thalamus. PTSD severity was related to specific regional alterations in the intrathalamic network involving the lateral pulvinar. Comorbid depression severity positively correlated with global intrathalamic alterations, while avoidance symptoms positively correlated with global thalamosubcortical alterations. Hyperarousal symptoms related to altered SC in the thalamocortical network between the reuniens, central medial, paratenial, centromedian, and limitans-suprageniculate nuclei and lateral cortical regions spanning the occipital, temporal, and orbitofrontal cortices. Differential associations between avoidance, hyperarousal, and comorbid depression symptoms and thalamic SC in PTSD suggest that specific thalamic covariance patterns may be involved in unique facets of PTSD symptomatology.
Alzheimer’s disease (AD) is characterized by progressive neural network degradation. In brain functional networks, overlapping module structures provide more accurate representations of brain function than nonoverlapping structures. Since the involvement of overlapping nodes in multiple modules can vary over time, investigating dynamic functional changes in the brain may provide deeper insights into the structural characteristics of these overlapping modules. However, the spatiotemporal dynamics of overlapping modular brain organization remain unclear. We employed resting-state fMRI to explore the overlapping modular organization and dynamic multilayer modules in 64 AD (Agemean = 74.04) and 61 healthy controls (HC, Agemean = 74.86) from the Alzheimer’s Disease Neuroimaging Initiative. Compared with HC, AD exhibited increased overlapping modules and decreased modularity, with altered nodal overlapping probability, particularly in the superior frontal cortex and hippocampus. Higher nodal overlapping probability correlated with greater flexibility and was associated with larger amyloid deposits. Lasso regression analysis further revealed strong correlations between overlapping nodal characteristics and cognitive performance. Our findings suggest that overlapping nodes are critical components in AD, demonstrating high amyloid deposition, significant functional flexibility, and strong associations to cognitive behavior. These alterations may enhance the understanding of AD pathology and contribute to the development of biomarkers for improved diagnosis and therapeutic strategies.
When using a cortical parcellation, it is generally assumed that the regions correspond across subjects, meaning regions with the same label are expected to have the same structural or functional roles from one subject to any other. However, at a fine-grained scale, environmental and genetic factors shape both cortex and white matter differently, making it challenging to consistently label all parcels for every subject. Brain networks can be constructed with regions as nodes and their connectivity as edges. One critical step while constructing those networks is the definition of the nodes due to the spatial inter-individual variability, which can limit the reliability of group studies’ results. In this work, we propose alignment criteria to register the brain nodes across subjects by allowing the permutation of tiny cortical regions. Those criteria account for multiple brain network perspectives built from different imaging modalities. Our across-subject multimodal alignment of brain networks includes constraints that restrict possible permutations to anatomically plausible ones. The identified permutations are finally applied to the brain networks not used for optimization, and also improve the alignment of these networks. This work has been validated on real magnetic resonance imaging data from the Human Connectome Project.
