IU Indianapolis ScholarWorks :: Browsing by Subject "Functional connectivity"

Browsing by Subject "Functional connectivity"

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Altered amygdala-cortical connectivity in individuals with Cannabis use disorder
(Sage, 2021) Aloi, Joseph; McCusker, Marie C.; Lew, Brandon J.; Schantell, Mikki; Eastman, Jacob A.; Frenzel, Michaela R.; Wilson, Tony W.; Psychiatry, School of Medicine
Background: Cannabis is one of the most commonly used substances in the United States. Prior literature using task-based functional magnetic resonance imaging (fMRI) has identified that individuals with Cannabis use disorder (CUD) show impairments in emotion processing circuitry. However, whether the functional networks involving these regions are also altered in CUD remains poorly understood. Aims: Investigate changes in resting-state functional connectivity (rsFC) in regions related to emotional processing in CUD. Methods: Sixty-two participants completed resting-state fMRI, including 21 with CUD, 20 with histories of illicit substance use but no current CUD diagnosis, and 21 with no history of illicit substance use. Whole-brain seed-based connectivity analyses were performed and one-way analyses of covariance (ANCOVAs) were conducted to detect group differences in the bilateral amygdalae, hippocampi, and the anterior and posterior cingulate cortices. Results: The CUD group exhibited significant reductions in rsFC between the amygdala and the cuneus, paracentral lobule, and supplementary motor area, and between the cingulate cortices and the occipital and temporal lobes. There were no significant group differences in hippocampal functional connectivity. In addition, CUD symptom counts based on the Structured Clinical Interview for DSM-5 (SCID) and the Cannabis Use Disorders Identification Test (CUDIT) significantly correlated with multiple connectivity metrics. Conclusion: These data expand on emerging literature indicating that CUD is associated with dysfunction in the neural circuits underlying emotion processing. Dysfunction in emotion processing circuits may play a role in the behavioral impairments seen in emotion processing tasks in individuals with CUD, and the severity of CUD symptoms appears to be directly related to the degree of dysfunction in these circuits.
The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement
(Elsevier, 2017-05) Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R., Jr.; Jagust, William; Morris, John C.; Petersen, Ronald C.; Salazar, Jennifer; Saykin, Andrew J.; Shaw, Leslie M.; Toga, Arthur W.; Trojanowski, John Q.; Radiology and Imaging Sciences, School of Medicine
INTRODUCTION: The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study. METHODS: ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. RESULTS: Multimodal analyses will provide insight into AD pathophysiology and disease progression. DISCUSSION: ADNI-3 will aim to inform AD treatment trials and facilitate development of AD disease-modifying treatments.
Association of Frequent Sexual Choking/Strangulation With Neurophysiological Responses: A Pilot Resting-State fMRI Study
(Mary Ann Liebert, 2023) Hou, Jiancheng; Huibregtse, Megan E.; Alexander, Isabella L.; Klemsz, Lillian M.; Fu, Tsung-Chieh; Fortenberry, J. Dennis; Herbenick, Debby; Kawata, Keisuke; Pediatrics, School of Medicine
Being choked or strangled during partnered sex is an emerging sexual behavior, prevalent among young adult women. The goal of this study was to test whether, and to what extent, frequently being choked or strangled during sex is associated with cortical surface functioning and functional connectivity. This case-control study consisted of two groups (choking vs. choking-naïve). Women who were choked 4 or more times during sex in the past 30 days were enrolled into the choking group, whereas those without were assigned to the choking-naïve group. We collected structural and resting-state functional magnetic resonance imaging (fMRI) data and analyzed the data for amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) using cortical surface-based resting-state fMRI analysis, followed by static and dynamic resting-state fMRI connectivity analysis. Forty-one participants (choking n = 20; choking-n-aïve n = 21) contributed to the analysis. An inter-hemispheric imbalance in neuronal activation pattern was observed in the choking group. Specifically, we observed significantly lower ALFF and ReHo in the left cortical regions (e.g., angular gyrus, orbitofrontal gyrus) and higher ALFF and ReHo in the right cortical regions (e.g., pre-central/post-central gyri) in the choking group compared with the choking-naïve group. A significant group difference was found in static functional connectivity between the bilateral angular gyrus and the whole brain, in which the choking group's angular gyrus showed hyperconnectivity with, for example, the post-central gyrus, pre-central gyrus, and Rolandic operculum, relative to the choking-naïve group. The dynamic analysis revealed hyperconnectivity between the left angular gyrus and the bilateral postcentral gyrus in the choking group compared with the choking-naïve group. Taken together, our data show that multiple experiences of sexual choking/strangulation are associated with an inter-hemispheric imbalance in neural activation pattern and hyperconnectivity between the angular gyrus and brain regions related to motor control, consciousness, and emotion. A longitudinal study using multi-modal neurological assessments is needed to clarify the acute and chronic consequences of sexual choking/strangulation.
Beyond Massive Univariate Tests: Covariance Regression Reveals Complex Patterns of Functional Connectivity Related to Attention-Deficit/Hyperactivity Disorder, Age, Sex, and Response Control
(Elsevier, 2022) Zhao, Yi; Nebel, Mary Beth; Caffo, Brian S.; Mostofsky, Stewart H.; Rosch, Keri S.; Biostatistics and Health Data Science, School of Medicine
Background: Studies of brain functional connectivity (FC) typically involve massive univariate tests, performing statistical analysis on each individual connection. In this study we apply a novel whole-matrix regression approach referred to as Covariate Assisted Principal (CAP) regression to identify resting-state FC brain networks associated with attention-deficit/hyperactivity disorder (ADHD) and response control. Methods: Participants included 8-12 year-old children with ADHD (n=115, 29 girls) and typically developing controls (n=102, 35 girls) who completed a resting-state fMRI scan and a go/no-go task (GNG). We modeled three sets of covariates to identify resting-state networks associated with an ADHD diagnosis, sex, and response inhibition (commission errors) and variability (ex-Gaussian parameter tau). Results: The first network includes FC between striatal-cognitive control (CC) network subregions and thalamic-default mode network (DMN) subregions and is positively related to age. The second consists of FC between CC-visual-somatomotor regions and between CC-DMN subregions and is positively associated with response variability in boys with ADHD. The third consists of FC within the DMN and between DMN-CC-visual regions and differs between boys with and without ADHD. The fourth consists of FC between visual-somatomotor regions and between visual-DMN regions and differs between girls and boys with ADHD and is associated with response inhibition and variability in boys with ADHD. Unique networks were also identified in each of the three models suggesting some specificity to the covariates of interest. Conclusions: These findings demonstrate the utility of our novel covariance regression approach to studying functional brain networks relevant for development, behavior, and psychopathology.
Cognitive and Affective Empathy as Indirect Paths Between Heterogeneous Depression Symptoms on Default Mode and Salience Network Connectivity in Adolescents
(Springer, 2023) Winters, Drew E.; Pruitt, Patrick J.; Gambin, Malgorzata; Fukui, Sadaaki; Cyders, Melissa A.; Pierce, Barbara J.; Lay, Kathy; Damoiseaux, Jessica S.; School of Social Work
Depression amongst adolescents is a prevalent disorder consisting of heterogeneous emotional and functional symptoms-often involving impairments in social domains such as empathy. Cognitive and affective components of empathy as well as their associated neural networks (default mode network for cognitive empathy and salience network for affective empathy) are affected by depression. Depression commonly onsets during adolescence, a critical period for brain development underlying empathy. However, the available research in this area conceptualizes depression as a homogenous construct, and thereby miss to represent the full spectrum of symptoms. The present study aims to extend previous literature by testing whether cognitive and affective empathy indirectly account for associations between brain network connectivity and heterogeneous depression symptoms in adolescents. Heterogeneous functional and emotional symptoms of depression were measured using the child depression inventory. Our results indicate that cognitive empathy mediates the association between default mode network functional connectivity and emotional symptoms of depression. More specifically, that adolescents with a stronger positive association between the default mode network and cognitive empathy show lower emotional depression symptoms. This finding highlights the importance of cognitive empathy in the relationship between brain function and depression symptoms, which may be an important consideration for existing models of depression in adolescents.
Cognitive complaints in older adults at risk for Alzheimer's disease are associated with altered resting-state networks
(Elsevier, 2016-12-22) Contreras, Joey A.; Goni, Joaquin; Risacher, Shannon L.; Amico, Enrico; Yoder, Karmen; Dzemidzic, Mario; West, John D.; McDonald, Brenna C.; Farlow, Martin R.; Sporns, Olaf; Saykin, Andrew J.; Department of Radiology and Imaging Sciences, IU School of Medicine
INTRODUCTION: Pathophysiological changes that accompany early clinical symptoms in prodromal Alzheimer's disease (AD) may have a disruptive influence on brain networks. We investigated resting-state functional magnetic resonance imaging (rsfMRI), combined with brain connectomics, to assess changes in whole-brain functional connectivity (FC) in relation to neurocognitive variables. METHODS: Participants included 58 older adults who underwent rsfMRI. Individual FC matrices were computed based on a 278-region parcellation. FastICA decomposition was performed on a matrix combining all subjects' FC. Each FC pattern was then used as a response in a multilinear regression model including neurocognitive variables associated with AD (cognitive complaint index [CCI] scores from self and informant, an episodic memory score, and an executive function score). RESULTS: Three connectivity independent component analysis (connICA) components (RSN, VIS, and FP-DMN FC patterns) associated with neurocognitive variables were identified based on prespecified criteria. RSN-pattern, characterized by increased FC within all resting-state networks, was negatively associated with self CCI. VIS-pattern, characterized by an increase in visual resting-state network, was negatively associated with CCI self or informant scores. FP-DMN-pattern, characterized by an increased interaction of frontoparietal and default mode networks (DMN), was positively associated with verbal episodic memory. DISCUSSION: Specific patterns of FC were differently associated with neurocognitive variables thought to change early in the course of AD. An integrative connectomics approach relating cognition to changes in FC may help identify preclinical and early prodromal stages of AD and help elucidate the complex relationship between subjective and objective indices of cognitive decline and differences in brain functional organization.
Differences in functional connectivity distribution after transcranial direct-current stimulation: A connectivity density point of view
(Wiley, 2023) Tang, Bohao; Zhao, Yi; Venkataraman, Archana; Tsapkini, Kyrana; Lindquist, Martin A.; Pekar, James; Caffo, Brian; Biostatistics, School of Public Health
In this manuscript, we consider the problem of relating functional connectivity measurements viewed as statistical distributions to outcomes. We demonstrate the utility of using the distribution of connectivity on a study of resting-state functional magnetic resonance imaging association with an intervention. The method uses the estimated density of connectivity between nodes of interest as a functional covariate. Moreover, we demonstrate the utility of the procedure in an instance where connectivity is naturally considered an outcome by reversing the predictor/response relationship using case/control methodology. The method utilizes the density quantile, the density evaluated at empirical quantiles, instead of the empirical density directly. This improved the performance of the method by highlighting tail behavior, though we emphasize that by being flexible and non-parametric, the technique can detect effects related to the central portion of the density. To demonstrate the method in an application, we consider 47 primary progressive aphasia patients with various levels of language abilities. These patients were randomly assigned to two treatment arms, transcranial direct-current stimulation and language therapy versus sham (language therapy only), in a clinical trial. We use the method to analyze the effect of direct stimulation on functional connectivity. As such, we estimate the density of correlations among the regions of interest and study the difference in the density post-intervention between treatment arms. We discover that it is the tail of the density, rather than the mean or lower order moments of the distribution, that demonstrates a significant impact in the classification. The new approach has several benefits. Among them, it drastically reduces the number of multiple comparisons compared with edge-wise analysis. In addition, it allows for the investigation of the impact of functional connectivity on the outcomes where the connectivity is not geometrically localized.
Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
(Elsevier, 2021) Gass, Natalia; Peterson, Zeru; Reinwald, Jonathan; Sartorius, Alexander; Weber-Fahr, Wolfgang; Sack, Markus; Chen, Junfang; Cao, Han; Didriksen, Michael; Stensbøl, Tine Bryan; Klemme, Gabriele; Schwarz, Adam J.; Schwarz, Emanuel; Meyer-Lindenberg, Andreas; Nickl-Jockschat, Thomas; Radiology and Imaging Sciences, School of Medicine
Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.
Edge time series components of functional connectivity and cognitive function in Alzheimer's disease
(Springer, 2024) Chumin, Evgeny J.; Cutts, Sarah A.; Risacher, Shannon L.; Apostolova, Liana G.; Farlow, Martin R.; McDonald, Brenna C.; Wu, Yu‑Chien; Betzel, Richard; Saykin, Andrew J.; Sporns, Olaf; Radiology and Imaging Sciences, School of Medicine
Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer’s disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer’s Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer’s disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.
Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer’s Disease
(medRxiv, 2023-11-18) Chumin, Evgeny J.; Cutts, Sarah A.; Risacher, Shannon L.; Apostolova, Liana G.; Farlow, Martin R.; McDonald, Brenna C.; Wu, Yu-Chien; Betzel, Richard; Saykin, Andrew J.; Sporns, Olaf; Radiology and Imaging Sciences, School of Medicine
Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer’s disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer’s Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer’s disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.

Browsing by Subject "Functional connectivity"

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