Organization Of Functional Brain Networks Research Articles

Functional brain network organization supports cognitive function in patients with Alzheimer's Disease‐related pathological burden and brain atrophy

Functional brain network organization supports cognitive function in patients with Alzheimer's Disease‐related pathological burden and brain atrophy

Functional brain network organization and multidomain resilience to neighborhood disadvantage in youth.

Though youth living in disadvantaged neighborhoods experience greater risk for poor behavioral and mental health outcomes, many go on to show resilience in the face of adversity. A few recent studies have identified neural markers of resilience in cognitive and affective brain networks, yet the broader network organization supporting resilience in youth remains unknown, particularly in relation to neighborhood disadvantage. Moreover, most studies have defined resilience as the absence of psychopathology, which does not consider growing evidence that resilience also includes positive outcomes across multiple domains (e.g., social, academic). We examined associations between brain network organization and multiple resilience domains in a sample of 708 twins (7-19 years old) recruited from neighborhoods with above-average poverty levels. Graph analysis on functional connectivity data from resting-state and task-based functional magnetic resonance imaging was used to characterize features of intrinsic whole-brain and network-level organization, from which we explored associations with resilience in three domains: psychological, social, and academic. Fewer connections between a brain network involved in self-referential processing (i.e., default mode network) and the subcortical system were associated with greater social resilience. Further, greater whole-brain functional integration (i.e., efficiency) was associated with better psychological resilience among youth with relatively lower levels of cumulative adversity exposure. Alternatively, lower whole-brain efficiency and higher whole-brain robustness to disruption (i.e., assortativity) were associated with greater psychological and social resilience among youth with relatively higher levels of cumulative adversity. These findings advance support for multidimensional resilience models and reveal distinct neural mechanisms supporting resilience to neighborhood disadvantage across specific domains in youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reconfiguration of functional brain network organization and dynamics with changing cognitive demands in children with attention-deficit/hyperactivity disorder

BackgroundThe pathophysiology of attention-deficit/hyperactivity disorder (ADHD) is characterized by atypical brain network organization and dynamics. Although functional brain networks adaptively reconfigure across cognitive contexts, previous studies have largely focused on network dysfunction during the resting-state. This preliminary study examined how functional brain network organization and dynamics flexibly reconfigure across rest and two cognitive control tasks with different cognitive demands in 30 children with ADHD and 36 typically developing (TD) children (8-12 years). MethodsWe leveraged graph theoretical analyses to interrogate the segregation (modularity, within-module degree) and integration (global efficiency, node dissociation index) of fronto-parietal, cingulo-opercular/salience, default mode, somatomotor, and visual networks. We also conducted edge timeseries analyses to quantify connectivity dynamics within and between these networks. ResultsAcross resting and task-based states, children with ADHD demonstrated significantly lower whole-graph modularity and greater node dissociation index between default mode and visual networks. Further, a significant task-by-diagnosis interaction was observed for fronto-parietal network within-module degree, which decreased from rest to task in children with ADHD but increased in TD children. Finally, children with ADHD displayed significantly more dynamic connectivity within and across cingulo-opercular/salience, default mode, and somatomotor networks, especially during task performance. Exploratory analyses revealed associations between network dynamics, cognitive performance, and ADHD symptoms. ConclusionsBy integrating static and dynamic network analyses across changing cognitive demands, this study provides novel insight into how context-specific, context-general, and timescale-dependent network connectivity is altered in children with ADHD. Our findings highlight the involvement and clinical relevance of both association and sensory/motor systems in ADHD.

Reverse engineering of feedforward cortical-Hippocampal microcircuits for modelling neural network function and dysfunction

Engineered biological neural networks are indispensable models for investigation of neural function and dysfunction from the subcellular to the network level. Notably, advanced neuroengineering approaches are of significant interest for their potential to replicate the topological and functional organization of brain networks. In this study, we reverse engineered feedforward neural networks of primary cortical and hippocampal neurons, using a custom-designed multinodal microfluidic device with Tesla valve inspired microtunnels. By interfacing this device with nanoporous microelectrodes, we show that the reverse engineered multinodal neural networks exhibit capacity for both segregated and integrated functional activity, mimicking brain network dynamics. To advocate the broader applicability of our model system, we induced localized perturbations with amyloid beta to study the impact of pathology on network functionality. Additionally, we demonstrate long-term culturing of subregion- and layer specific neurons extracted from the entorhinal cortex and hippocampus of adult Alzheimer’s-model mice and rats. Our results thus highlight the potential of our approach for reverse engineering of anatomically relevant multinodal neural networks to study dynamic structure-function relationships in both healthy and pathological conditions.

Differential reconfiguration of brain networks in children in response to standard versus rewarded go/no-go task demands.

Response inhibition and sustained attention are critical for higher-order cognition and rely upon specific patterns of functional brain network organization. This study investigated how functional brain networks reconfigure to execute these cognitive processes during a go/no-go task with and without the presence of rewards in 26 children between the ages of 8 and 12 years. First, we compared task performance between standard and rewarded versions of a go/no-go task. We found that the presence of rewards reduced commission error rate, a measure considered to indicate improved response inhibition. Tau, thought to index sustained attention, did not change across task conditions. Next, changes in functional brain network organization were assessed between the resting state, the standard go/no-go task, and the rewarded go/no-go task. Relative to the resting state, integration decreased and segregation increased during the standard go/no-go task. A further decrease in integration and increase in segregation was observed when rewards were introduced. These patterns of reconfiguration were present globally and across several key brain networks of interest, as well as in individual regions implicated in the processes of response inhibition, attention, and reward processing. These findings align with patterns of brain network organization found to support the cognitive strategy of sustained attention, rather than response inhibition, during go/no-go task performance and suggest that rewards enhance this organization. Overall, this study used large-scale brain network organization and a within-subjects multi-task design to examine different cognitive strategies and the influence of rewards on response inhibition and sustained attention in late childhood.

Sex Differences in Hierarchical and Modular Organization of Functional Brain Networks: Insights from Hierarchical Entropy and Modularity Analysis.

Existing studies have demonstrated significant sex differences in the neural mechanisms of daily life and neuropsychiatric disorders. The hierarchical organization of the functional brain network is a critical feature for assessing these neural mechanisms. But the sex differences in hierarchical organization have not been fully investigated. Here, we explore whether the hierarchical structure of the brain network differs between females and males using resting-state fMRI data. We measure the hierarchical entropy and the maximum modularity of each individual, and identify a significant negative correlation between the complexity of hierarchy and modularity in brain networks. At the mean level, females show higher modularity, whereas males exhibit a more complex hierarchy. At the consensus level, we use a co-classification matrix to perform a detailed investigation of the differences in the hierarchical organization between sexes and observe that the female group and the male group exhibit different interaction patterns of brain regions in the dorsal attention network (DAN) and visual network (VIN). Our findings suggest that the brains of females and males employ different network topologies to carry out brain functions. In addition, the negative correlation between hierarchy and modularity implies a need to balance the complexity in the hierarchical organization of the brain network, which sheds light on future studies of brain functions.

Impaired brain ability of older adults to transit and persist to latent states with well-organized structures at wakeful rest.

The intrinsic brain functional network organization continuously changes with aging. By integrating spatial and temporal information, the process of how brain networks temporally reconfigure and remain well-organized spatial structure largely reflects the brain function, thereby holds the potential to capture its age-related declines. In this study, we examined the spatiotemporal brain dynamics from resting-state functional Magnetic Resonance Imaging (fMRI) data of healthy young and older adults using a Hidden Markov Model (HMM). Six brain states were generated by HMM, with the young group showing higher fractional occupancy and mean dwell time in states 1, 3, and 4 (SY1, SY2 and SY3), and the older group in states 2, 5, and 6 (SO1, SO2 and SO3). Importantly, comparisons of transition probabilities revealed that the older group showed a reduced brain ability to transition into states dominated by the younger group, as well as a diminished capacity to persist in them. Moreover, graph analysis revealed that these young-specific states exhibited higher modularity and k-coreness. Collectively, these findings suggested that the older group showed impaired brain ability of both transition into and sustain well spatially organized states. This emphasized that the temporal changes in brain state organization, rather than its static mode, could be a key biomarker for detecting age-related functional decline. These insights may pave the way for targeted interventions aimed at mitigating cognitive decline in the aging population.

Reproducible Sex Differences in Personalized Functional Network Topography in Youth.

A key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex. We aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks. We leveraged person-specific atlases of functional brain networks defined using nonnegative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout ("topography") of personalized functional networks (PFNs). Next, we trained support vector machines to classify participants' sex from multivariate patterns of PFN topography. Finally, we leveraged transcriptomic data from the Allen Human Brain Atlas to evaluate spatial correlations between sex differences in PFN topography and gene expression. Sex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants' PFNs were able to classify participant sex with high accuracy. Brain regions with the greatest sex differences in PFN topography were enriched in expression of X-linked genes as well as genes expressed in astrocytes and excitatory neurons. Sex differences in PFN topography are robust, replicate across large-scale samples of youth, and are associated with expression patterns of X-linked genes. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence.

Individual patterns of functional connectivity in neonates as revealed by surface-based Bayesian modeling.

Resting-state functional connectivity is a widely used approach to study the functional brain network organization during early brain development. However, the estimation of functional connectivity networks in individual infants has been rather elusive due to the unique challenges involved with functional magnetic resonance imaging (fMRI) data from young populations. Here, we use fMRI data from the developing Human Connectome Project (dHCP) database to characterize individual variability in a large cohort of term-born infants (N = 289) using a novel data-driven Bayesian framework. To enhance alignment across individuals, the analysis was conducted exclusively on the cortical surface, employing surface-based registration guided by age-matched neonatal atlases. Using 10 minutes of resting-state fMRI data, we successfully estimated subject-level maps for fourteen brain networks/subnetworks along with individual functional parcellation maps that revealed differences between subjects. We also found a significant relationship between age and mean connectivity strength in all brain regions, including previously unreported findings in higher-order networks. These results illustrate the advantages of surface-based methods and Bayesian statistical approaches in uncovering individual variability within very young populations.

Eigenvector Centrality Mapping Reveals Volatility of Functional Brain Dynamics in Anti-NMDA Receptor Encephalitis

BackgroundAnti-NMDA receptor encephalitis (NMDARE) causes long-lasting cognitive deficits associated with altered functional connectivity. Eigenvector centrality (EC) mapping represents a powerful new method for data-driven voxelwise and time-resolved estimation of network importance—beyond changes in classical static functional connectivity. MethodsTo assess changes in functional brain network organization, we applied EC mapping in 73 patients with NMDARE and 73 matched healthy control participants. Areas with significant group differences were further investigated using 1) spatial clustering analyses, 2) time series correlation to assess synchronicity between the hippocampus and cortical brain regions, and 3) correlation with cognitive and clinical parameters. ResultsDynamic, time-resolved EC showed significantly higher variability in 13 cortical areas (familywise error p < .05) in patients with NMDARE compared with healthy control participants. Areas with dynamic EC group differences were spatially organized in centrality clusters resembling resting-state networks. Importantly, variability of dynamic EC in the frontotemporal cluster was associated with impaired verbal episodic memory in patients (r = −0.25, p = .037). EC synchronicity between the hippocampus and the medial prefrontal cortex was reduced in patients compared with healthy control participants (familywise error p < .05, tmax = 3.76) and associated with verbal episodic memory in patients (r = 0.28, p = .019). Static EC analyses showed group differences in only one brain region (left intracalcarine cortex). ConclusionsWidespread changes in network dynamics and reduced hippocampal-medial prefrontal synchronicity were associated with verbal episodic memory deficits and may thus represent a functional neural correlate of cognitive dysfunction in NMDARE. Importantly, dynamic EC detected substantially more network alterations than traditional static approaches, highlighting the potential of this method to explain long-term deficits in NMDARE.

Association of physical function with connectivity in the sensorimotor and dorsal attention networks: why examining specific components of physical function matters

Declining physical function with aging is associated with structural and functional brain network organization. Gaining a greater understanding of network associations may be useful for targeting interventions that are designed to slow or prevent such decline. Our previous work demonstrated that the Short Physical Performance Battery (eSPPB) score and body mass index (BMI) exhibited a statistical interaction in their associations with connectivity in the sensorimotor cortex (SMN) and the dorsal attention network (DAN). The current study examined if components of the eSPPB have unique associations with these brain networks. Functional magnetic resonance imaging was performed on 192 participants in the BNET study, a longitudinal and observational trial of community-dwelling adults aged 70 or older. Functional brain networks were generated for resting state and during a motor imagery task. Regression analyses were performed between eSPPB component scores (gait speed, complex gait speed, static balance, and lower extremity strength) and BMI with SMN and DAN connectivity. Gait speed, complex gait speed, and lower extremity strength significantly interacted with BMI in their association with SMN at rest. Gait speed and complex gait speed were interacted with BMI in the DAN at rest while complex gait speed, static balance, and lower extremity strength interacted with BMI in the DAN during motor imagery. Results demonstrate that different components of physical function, such as balance or gait speed and BMI, are associated with unique aspects of brain network organization. Gaining a greater mechanistic understanding of the associations between low physical function, body mass, and brain physiology may lead to the development of treatments that not only target specific physical function limitations but also specific brain networks.

EEG connectivity in functional brain networks supporting visuomotor integration processes in dominant and non-dominant hand movements

Objective. This study explores the changes in the organization of functional brain networks induced by performing a visuomotor integration task, as revealed by noninvasive spontaneous electroencephalographic traces (EEG). Approach. EEG data were acquired during the execution of the Nine Hole Peg Test (NHPT) with the dominant and non-dominant hands in a group of 44 right-handed volunteers. Both spectral analysis and phase-based connectivity analysis were performed in the theta (ϑ), mu ( μ ) and beta (ß) bands. Graph Theoretical Analysis (GTA) was also performed to investigate the topological reorganization induced by motor task execution. Main results. Spectral analysis revealed an increase of frontoparietal ϑ power and a spatially diffused reduction of µ and ß contribution, regardless of the hand used. GTA showed a significant increase in network integration induced by movement performed with the dominant limb compared to baseline in the ϑ band. The µ and ß bands were associated with a reduction in network integration during the NHPT. In the µ rhythm, this result was more evident for the right-hand movement, while in the ß band, results did not show dependence on the laterality. Finally, correlation analysis highlighted an association between frequency-specific topology measures and task performance for both hands. Significance. Our results show that functional brain networks reorganize during visually guided movements in a frequency-dependent manner, differently depending on the hand used (dominant/non dominant).

26. Understanding Cognitive Development by Capturing Complex, Multidimensional, Childhood Environments and Individual-Specific Patterns of Functional Brain Network Organization

26. Understanding Cognitive Development by Capturing Complex, Multidimensional, Childhood Environments and Individual-Specific Patterns of Functional Brain Network Organization

Accelerated epigenetic age is associated with whole-brain functional connectivity and impaired cognitive performance in older adults

While chronological age is a strong predictor for health-related risk factors, it is an incomplete metric that fails to fully characterize the unique aging process of individuals with different genetic makeup, neurodevelopment, and environmental experiences. Recent advances in epigenomic array technologies have made it possible to generate DNA methylation-based biomarkers of biological aging, which may be useful in predicting a myriad of cognitive abilities and functional brain network organization across older individuals. It is currently unclear which cognitive domains are negatively correlated with epigenetic age above and beyond chronological age, and it is unknown if functional brain organization is an important mechanism for explaining these associations. In this study, individuals with accelerated epigenetic age (i.e. AgeAccelGrim) performed worse on tasks that spanned a wide variety of cognitive faculties including both fluid and crystallized intelligence (N = 103, average age = 68.98 years, 73 females, 30 males). Additionally, fMRI connectome-based predictive models suggested a mediating mechanism of functional connectivity on epigenetic age acceleration-cognition associations primarily in medial temporal lobe and limbic structures. This research highlights the important role of epigenetic aging processes on the development and maintenance of healthy cognitive capacities and function of the aging brain.

Performance of cognitive tasks and functional brain activity in anxiety disorders

Objective. To improve understanding of psychophysiological underpinnings of anxiety disorders a comprehensive study, that included the analysis of cognitive tasks performance, event-related potentials and psychometric scales, has been conducted.Materials and Methods. Participants were patients with generalized anxiety disorder (GAD group — 12 s.), mixed anxiety and depressive disorder (ADD group — 16 s.) and healthy volunteers (control group — 16 s.). The psychometric techniques included the questionnaires of Spielberger, HADS (Hospital Anxiety and Depression Scale) and Carver-White (BIS/BAS Scale). Psychophysiological methods included antisaccade task (AS) and event-related evoked potentials P300 that were recorded during auditory oddball task.Results. The significantly increased anxiety and depression scales, as well as the decreased BAS Reward Responsiveness scale, was found in patients of both clinical groups compared to control one; the increased BIS scale was revealed only in ADD group. In GAD and ADD groups AS performance was worse in response to stimuli in left hemi-field that are initially processed in right hemisphere; on the contrary, decreased number of target stimuli omissions was found in oddball task in clinical groups. P300 amplitude was larger, and P300 latency was shorter for patients with ADD compared to controls. Analysis of asymmetry demonstrated that P300 amplitudes were greater over the frontal-central right than over the left hemisphere in ADD group.Conclusion. The study demonstrated that anxiety disorders are accompanied by reallocation of attentional resources and changes in functional organization of brain networks involved in attention and executive functions. With the same direction, the shifts were greater in ADD group.

Modular organization of functional brain networks in patients with degenerative cervical myelopathy

Previous studies have indicated that brain functional plasticity and reorganization in patients with degenerative cervical myelopathy (DCM). However, the effects of cervical cord compression on the functional integration and separation between and/or within modules remain unclear. This study aimed to address these questions using graph theory. Functional MRI was conducted on 46 DCM patients and 35 healthy controls (HCs). The intra- and inter-modular connectivity properties of the whole-brain functional network and nodal topological properties were then calculated using theoretical graph analysis. The difference in categorical variables between groups was compared using a chi-squared test, while that between continuous variables was evaluated using a two-sample t-test. Correlation analysis was conducted between modular connectivity properties and clinical parameters. Modules interaction analyses showed that the DCM group had significantly greater inter-module connections than the HCs group (DMN-FPN: t = 2.38, p = 0.02); inversely, the DCM group had significantly lower intra-module connections than the HCs group (SMN: t = − 2.13, p = 0.036). Compared to HCs, DCM patients exhibited higher nodal topological properties in the default-mode network and frontal–parietal network. In contrast, DCM patients exhibited lower nodal topological properties in the sensorimotor network. The Japanese Orthopedic Association (JOA) score was positively correlated with inter-module connections (r = 0.330, FDR p = 0.029) but not correlated with intra-module connections. This study reported alterations in modular connections and nodal centralities in DCM patients. Decreased nodal topological properties and intra-modular connection in the sensory-motor regions may indicate sensory-motor dysfunction. Additionally, increased nodal topological properties and inter-modular connection in the default mode network and frontal-parietal network may serve as a compensatory mechanism for sensory-motor dysfunction in DCM patients. This could provide an implicative neural basis to better understand alterations in brain networks and the patterns of changes in brain plasticity in DCM patients.

A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child’s environment (“exposome”) and investigate associations with each child’s unique, multidimensional pattern of functional brain network organization (“functional topography”) and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9–10) and future (ages 11–12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child’s exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children’s complex, multidimensional environments in cognitive neurodevelopment.

Topological features of functional brain networks and subclinical impulsivity: an investigation in younger and older adults.

Impulsive traits (i.e., the tendency to act without forethought regardless of negative outcomes) are frequently found in healthy populations. When exposed to risk factors, individuals may develop debilitating disorders of impulse control (addiction, substance abuse, gambling) characterized by behavioral and cognitive deficits, eventually leading to huge socioeconomic costs. With the far-reaching aim of preventing the onset of impulsive disorders, it is relevant to investigate the topological organization of functional brain networks associated with impulsivity in sub-clinical populations. Taking advantage of the open-source LEMON dataset, we investigated the topological features of resting-state functional brain networks associated with impulsivity in younger (n=146, age: 20-35) and older (n=61, age: 59-77) individuals, using a graph-theoretical approach. Specifically, we computed indices of segregation and integration at the level of specific circuits and nodes known to be involved in impulsivity (frontal, limbic, and striatal networks). In younger individuals, results revealed that impulsivity was associated with a more widespread, less clustered and less efficient functional organization, at all levels of analyses and in all selected networks. Conversely, impulsivity in older individuals was associated with reduced integration and increased segregation of striatal regions. Speculatively, such alterations of functional brain networks might underlie behavioral and cognitive abnormalities associated with impulsivity, a working hypothesis worth being tested in future research. Lastly, differences between younger and older individuals might reflect the implementation of age-specific adaptive strategies, possibly accounting for observed differences in behavioral manifestations. Potential interpretations, limitations and implications are discussed.

Disrupted properties of functional brain networks in major depressive disorder during emotional face recognition: an EEG study via graph theory analysis.

Previous neuroimaging studies have revealed abnormal brain networks in patients with major depressive disorder (MDD) in emotional processing. While any cognitive task consists of a series of stages, little is yet known about the topology of functional brain networks in MDD for these stages during emotional face recognition. To address this problem, electroencephalography (EEG)-based functional brain networks of MDD patients at different stages of facial information processing were investigated in this study. First, EEG signals were collected from 16 patients with MDD and 18 age-, gender-, and education-matched normal subjects when performing an emotional face recognition task. Second, the global field power (GFP) method was employed to divide group-averaged event-related potentials into different stages. Third, using the phase transfer entropy (PTE) approach, the brain networks of MDD patients and normal individuals were constructed for each stage in negative and positive face processing, respectively. Finally, we compared the topological properties of brain networks of each stage between the two groups using graph theory approaches. The results showed that the analyzed three stages of emotional face processing corresponded to specific neurophysiological phases, namely, visual perception, face recognition, and emotional decision-making. It was also demonstrated that depressed patients showed abnormally decreased characteristic path length at the visual perception stage of negative face recognition and normalized characteristic path length in the stage of emotional decision-making during positive face processing compared to healthy subjects. Furthermore, while both the MDD and normal groups' brain networks were found to exhibit small-world network characteristics, the brain network of patients with depression tended to be randomized. Moreover, for patients with MDD, the centro-parietal region may lose its status as a hub in the process of facial expression identification. Together, our findings suggested that altered emotional function in MDD patients might be associated with disruptions in the topological organization of functional brain networks during emotional face recognition, which further deepened our understanding of the emotion processing dysfunction underlying MDD.

Modifying modularity: aerobic exercise improves functional connectivity in breast cancer survivors

IntroductionAerobic exercise has been shown to improve cancer-associated cognitive decline (CACD) in breast cancer survivors (BCS), and recent findings suggest that one mechanism by which exercise may reduce cognitive decline is through alteration of the brain's functional organization. Many cognitive abilities and measures of functional brain organization change with age and disease, typically reflected in cognitive decline and reduced differentiation of brain networks, or “modularity.” Although previous research has identified associations between lifestyle interventions, such as exercise, and increased modularity, no studies have examined these relationships in cancer populations. The primary aim of this study was to investigate the preliminary effects of a 12-week aerobic exercise program on changes in brain network modularity in BCS. As a secondary aim, we explored correlations between changes in modularity with moderate-to-vigorous physical activity (MVPA) and cognitive function. Data were exploratory and used for hypothesis generation for a future, larger study.MethodsParticipants included a subsample of 10 BCS (M age = 65.9 ± 9.3 years) from a larger pilot study (N = 30 BCS) who were randomized to a 12-week aerobic exercise program (AE) or usual care (UC). The present study collected brain magnetic resonance imaging, Actigraph accelerometry, and cognitive task performance at baseline and 3-month follow-up (i.e., post-intervention; n = 4 AE, n = 6 UC). Intervention effects on modularity, MVPA, and cognition were quantified as magnitude of change between groups (Cohen's d). Changes in modularity were further explored via paired t-tests within groups. Associations between changes in modularity, MVPA, and cognitive performance were explored using Spearman's correlations.ResultsThe magnitude of changes in modularity between groups were small-to-moderate and favored the AE group (d = 0.23 to d = 0.67 across thresholds). Paired t-tests revealed a significant increase in modularity in the AE group from baseline to 3-month follow-up (t = 3.08, p = 0.03, d = 1.17), but not in the UC group. The correlation between changes in MVPA and changes in modularity were not statistically significant (r = 0.36, p = 0.39), and correlations between modularity and cognitive performance yielded mixed effects by cognitive domain.DiscussionFindings suggest that aerobic exercise may influence functional brain network organization and cognition in BCS. These data warrant further investigation in larger exercise trials.