scholarly journals Reconfiguration of directed functional connectivity among triple networks with aging: Considering the role of thalamo-cortical interactions

2019 ◽  
Author(s):  
Moumita Das ◽  
Vanshika Singh ◽  
Lucina Uddin ◽  
Arpan Banerjee ◽  
Dipanjan Roy
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Young Group ◽  
Resting State Functional Connectivity ◽  
Functional Changes ◽  
Age Related ◽  
Directional Connectivity

AbstractThe human brain undergoes significant structural and functional changes across the lifespan. Our current understanding of the underlying causal relationships of dynamical changes in functional connectivity with age is limited. On average, functional connectivity within resting-state networks (RSNs) weakens in magnitude, while connections between RSNs tend to increase with age. Recent studies show that effective connectivity within and between large scale resting-state functional networks changes over the healthy lifespan. The vast majority of previous studies have focused primarily on characterizing cortical networks, with little work exploring the influence of subcortical nodes such as the thalamus on large-scale network interactions across the lifespan. Using directed connectivity and weighted net causal outflow measures applied to resting-state fMRI data, we examine the age-related changes in both cortical and thalamocortical causal interactions within and between RSNs. The three core neurocognitive networks from the triple network theory (default mode: DMN, salience: SN, and central executive: CEN) were identified independently using ICA and spatial matching of hub regions with these important RSNs previously reported in the literature. Multivariate granger causal analysis (GCA) was performed to test for directional connectivity and weighted causal outflow between selected nodes of RSNs accounting for thalamo-cortical interactions. Firstly, we observe that within-network causal connections become progressively weaker with age, and network dynamics are substantially reconfigured via strong thalamic drive particularly in the young group. Our findings manifest stronger between-network directional connectivity, which is further strongly mediated by the SN in flexible co-ordination with the CEN, and DMN in the old group compared with the young group. Hence, causal within- and between- triple network connectivity largely reflects age-associated effects of resting-state functional connectivity. Thalamo-cortical causality effects on the triple networks with age were next explored. We discovered that left and right thalamus exhibit substantial interactions with the triple networks and play a crucial role in the reconfiguration of directed connections and within network causal outflow. The SN displayed directed functional connectivity in strongly driving both the CEN and DMN to a greater extent in the older group. Notably, these results were largely replicated on an independent dataset of matched young and old individuals. Our findings based on directed functional connectivity and weighted causal outflow measures strengthen the hypothesis that balancing within and between network connectivity is perhaps critical for the preservation and flexibility of cognitive functioning with aging.

scholarly journals Resting-State Functional Connectivity of the Ageing Female Brain—Differences Between Young and Elderly Female Adults on Multislice Short TR rs-fMRI

2021 ◽  
Vol 12 ◽  
Author(s):  
Przemysław Podgórski ◽  
Marta Waliszewska-Prosół ◽  
Anna Zimny ◽  
Marek Sąsiadek ◽  
Joanna Bladowska
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
World Health ◽  
Resting State Functional Connectivity ◽  
Default Mode ◽  
Young Females ◽  
Eyes Closed ◽  
Age Related ◽  
Healthy Female

Introduction: Age-related brain changes are one of the most important world health problems due to the rising lifespan and size of the elderly populations. The aim of the study was to assess the effect of ageing in women on coordinated brain activity between eight resting-state networks.Material and Methods: The study group comprised 60 healthy female volunteers who were divided into two age groups: younger women (aged 20–30 n = 30) and older women (aged 55–80 n = 30). Resting-state data were collected during a 15 min scan in the eyes-closed condition using a 3T MR scanner. Data were preprocessed and analysed using the CONN toolbox version 19.c. The large-scale network analysis included a priori selected regions of interest of the default mode, the sensorimotor, the visual, the salience, the dorsal attention, the fronto-parietal, the language, and the cerebellar network.Results: Within the visual, the default mode, the salience, and the sensorimotor network, the intra-network resting-state functional connectivity (RSFC) was significantly higher with increasing age. There was also a significant increase in the inter-network RSFC in older females compared to young females found in the following networks: sensorimotor lateral and salience, salience and language, salience and fronto-parietal, cerebellar anterior and default mode, cerebellar posterior and default mode, visual and sensorimotor lateral, visual and sensorimotor, visual lateral and default mode, language and cerebellar anterior, language and cerebellar posterior, fronto-parietal and cerebellar anterior, dorsal attention and sensorimotor, dorsal attention and default mode, sensorimotor superior, and salience. Compared to young females, elderly women presented bilaterally significantly lower inter-network RSFC of the salience supramarginal gyrus and cerebellar posterior, sensorimotor lateral, and cerebellar anterior network, and sensorimotor lateral and cerebellar posterior as well as sensorimotor superior and cerebellar posterior network.Conclusion: Increased RSFC between some brain networks including the visual, the default mode, the salience, the sensorimotor, the language, the fronto-parietal, the dorsal attention, and the cerebellar networks in elderly females may function as a compensation mechanism during the ageing process of the brain. To the best of our knowledge, this study is the first to report the importance of increase of cerebellar networks RSFC during healthy female ageing.

scholarly journals Age-related differences in resting state functional connectivity in pediatric migraine

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tiffany Bell ◽  
Akashroop Khaira ◽  
Mehak Stokoe ◽  
Megan Webb ◽  
Melanie Noel ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Power Spectra ◽  
Interaction Effects ◽  
Resting State Functional Connectivity ◽  
Default Mode ◽  
Pediatric Migraine ◽  
Age Related ◽  
Status Interaction ◽  
Underlying Mechanisms

Abstract Background Migraine affects roughly 10% of youth aged 5–15 years, however the underlying mechanisms of migraine in youth are poorly understood. Multiple structural and functional alterations have been shown in the brains of adult migraine sufferers. This study aims to investigate the effects of migraine on resting-state functional connectivity during the period of transition from childhood to adolescence, a critical period of brain development and the time when rates of pediatric chronic pain spikes. Methods Using independent component analysis, we compared resting state network spatial maps and power spectra between youth with migraine aged 7–15 and age-matched controls. Statistical comparisons were conducted using a MANCOVA analysis. Results We show (1) group by age interaction effects on connectivity in the visual and salience networks, group by sex interaction effects on connectivity in the default mode network and group by pubertal status interaction effects on connectivity in visual and frontal parietal networks, and (2) relationships between connectivity in the visual networks and the migraine cycle, and age by cycle interaction effects on connectivity in the visual, default mode and sensorimotor networks. Conclusions We demonstrate that brain alterations begin early in youth with migraine and are modulated by development. This highlights the need for further study into the neural mechanisms of migraine in youth specifically, to aid in the development of more effective treatments.

scholarly journals Reduced resting state functional connectivity with increasing age-related hearing loss and McGurk susceptibility

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Alina Schulte ◽  
Christiane M. Thiel ◽  
Anja Gieseler ◽  
Maike Tahden ◽  
Hans Colonius ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Functional Connectivity ◽  
Resting State ◽  
Mcgurk Effect ◽  
Functional Coupling ◽  
Resting State Functional Connectivity ◽  
Visual Integration ◽  
Age Related ◽  
Hearing Thresholds ◽  
Age Related Hearing Loss

Abstract Age-related hearing loss has been related to a compensatory increase in audio-visual integration and neural reorganization including alterations in functional resting state connectivity. How these two changes are linked in elderly listeners is unclear. The current study explored modulatory effects of hearing thresholds and audio-visual integration on resting state functional connectivity. We analysed a large set of resting state data of 65 elderly participants with a widely varying degree of untreated hearing loss. Audio-visual integration, as gauged with the McGurk effect, increased with progressing hearing thresholds. On the neural level, McGurk illusions were negatively related to functional coupling between motor and auditory regions. Similarly, connectivity of the dorsal attention network to sensorimotor and primary motor cortices was reduced with increasing hearing loss. The same effect was obtained for connectivity between the salience network and visual cortex. Our findings suggest that with progressing untreated age-related hearing loss, functional coupling at rest declines, affecting connectivity of brain networks and areas associated with attentional, visual, sensorimotor and motor processes. Especially connectivity reductions between auditory and motor areas were related to stronger audio-visual integration found with increasing hearing loss.

Clinical correlates of hypothalamic functional changes in migraine patients

Cephalalgia ◽  
2021 ◽  
pp. 033310242110466
Author(s):  
Roberta Messina ◽  
Maria A Rocca ◽  
Paola Valsasina ◽  
Paolo Misci ◽  
Massimo Filippi
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Visual Processing ◽  
Episodic Migraine ◽  
Resting State Functional Connectivity ◽  
Functional Interaction ◽  
Functional Changes ◽  
Lingual Gyrus ◽  
Headache Impact

Objective To elucidate the hypothalamic involvement in episodic migraine and investigate the association between hypothalamic resting state functional connectivity changes and migraine patients’ clinical characteristics and disease progression over the years. Methods Ninety-one patients with episodic migraine and 73 controls underwent interictal resting state functional magnetic resonance imaging. Twenty-three patients and controls were re-examined after a median of 4.5 years. Hypothalamic resting state functional connectivity changes were investigated using a seed-based correlation approach. Results At baseline, a decreased functional interaction between the hypothalamus and the parahippocampus, cerebellum, temporal, lingual and orbitofrontal gyrus was found in migraine patients versus controls. Increased resting state functional connectivity between the hypothalamus and bilateral orbitofrontal gyrus was demonstrated in migraine patients at follow-up versus baseline. Migraine patients also experienced decreased right hypothalamic resting state functional connectivity with ipsilateral lingual gyrus. A higher migraine attack frequency was associated with decreased hypothalamic-lingual gyrus resting state functional connectivity at baseline, while greater headache impact at follow-up correlated with decreased hypothalamic-orbitofrontal gyrus resting state functional connectivity at baseline. At follow-up, a lower frequency of migraine attacks was associated with higher hypothalamic-orbitofrontal gyrus resting state functional connectivity. Conclusions During the interictal phase, the hypothalamus modulates the activity of pain and visual processing areas in episodic migraine patients. The hypothalamic-cortical interplay changes dynamically over time according to patients’ clinical features.

scholarly journals Altered hypothalamus functional connectivity with limbic system in fibromyalgia and the modulation effect of intervention

2020 ◽  
Author(s):  
Jian Kong ◽  
Yiting Huang ◽  
Jiao Liu ◽  
Siyi Yu ◽  
Ming Cheng ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Limbic System ◽  
Resting State ◽  
Tai Chi ◽  
Effective Connectivity ◽  
Resting State Fmri ◽  
Trial Registration ◽  
Modulation Effect ◽  
Resting State Functional Connectivity ◽  
Before And After

Abstract Background: This study aims to investigate the resting state functional connectivity (rsFC) changes of the hypothalamus in Fibromyalgia patients and the modulation effect of effective treatments. Methods: Fibromyalgia patients and matched healthy controls (HC’s) were recruited. Resting state fMRI data were collected from fibromyalgia patients before and after a 12-week Tai Chi intervention and once from HC’s. Results: Data analysis showed that fibromyalgia patients displayed significantly decreased medial hypothalamus (MH) rsFC with the thalamus and amygdala when compared to HC’s at baseline. After the intervention, fibromyalgia patients showed increased (normalized) MH rsFC in the thalamus and amygdala. Effective connectivity analysis showed disrupted MH and thalamus interaction in fibromyalgia, which nonetheless could be partially restored by Tai Chi. Conclusions: Elucidating the role of the diencephalon and limbic system in the pathophysiology and development of fibromyalgia may facilitate the development of new treatment methods for this prevalent disorder. Trial registration: Trial registration ClinicalTrials.gov Identifier: NCT02407665. Registered 3 April 2015 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02407665

scholarly journals The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI

2019 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Adeel Razi ◽  
Karl Friston ◽  
Daniele Marinazzo
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Measurement Noise ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Global Signal ◽  
Leibler Divergence

AbstractThe influence of the global BOLD signal on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus. In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting-state networks – as estimated with dynamic causal modelling (DCM) for resting state fMRI (rsfMRI). DCM incorporates a forward (generative) model that quantifies the contribution of different types of noise (including global measurement noise), effective connectivity, and (neuro)vascular processes to functional connectivity measurements. DCM analyses were applied to two different designs; namely, longitudinal and cross-sectional designs. In the modelling of longitudinal designs, we included four extensive longitudinal resting state fMRI datasets with a total number of 20 subjects. In the analysis of cross-sectional designs, we used rsfMRI data from 361 subjects from the Human Connectome Project. We hypothesized that (1) GSR would have no discernible impact on effective connectivity estimated with DCM, and (2) GSR would be reflected in the parameters representing global measurement noise. Additionally, we performed comparative analyses of the informative value of data with and without GSR. Our results showed negligible to small effects of GSR on connectivity within small (separately estimated) RSNs. For between-network connectivity, we found two important effects: the effect of GSR on between-network connectivity (averaged over all connections) was negligible to small, while the effect of GSR on individual connections was non-negligible. Contrary to our expectations, we found either no effect (in the longitudinal designs) or a non-specific (cross-sectional design) effect of GSR on parameters representing (global) measurement noise. Data without GSR were found to be more informative than data with GSR; however, in small resting state networks the precision of posterior estimates was greater using data after GSR. In conclusion, GSR is a minor concern in DCM studies; however, individual between-network connections (as opposed to average between-network connectivity) and noise parameters should be interpreted quantitatively with some caution. The Kullback-Leibler divergence of the posterior from the prior, together with the precision of posterior estimates, might offer a useful measure to assess the appropriateness of GSR, when nuancing data features in resting state fMRI.

scholarly journals Predicting dysfunctional age-related task activations from resting-state network alterations

2019 ◽  
Author(s):  
Ravi D. Mill ◽  
Brian A. Gordon ◽  
David A. Balota ◽  
Jeffrey M. Zacks ◽  
Michael W. Cole
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Functional Connectivity ◽  
Resting State ◽  
Cognitive Task ◽  
Low Risk ◽  
Flow Modeling ◽  
Resting State Functional Connectivity ◽  
Age Related

AbstractAlzheimer’s disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the timecourse of illness. Study of these fMRI correlates of unhealthy aging has been conducted in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC network alterations associated with Alzheimer’s disease disrupt the ability for activations to flow between brain regions, leading to aberrant task activations. We apply this activity flow modeling framework in a large sample of clinically unimpaired older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) risk factors for AD. We identified healthy task activations in individuals at low risk for AD, and then by estimating activity flow using at-risk AD restFC data we were able to predict the altered at-risk AD task activations. Thus, modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy aged activations. These results provide evidence that activity flow over altered intrinsic functional connections may act as a mechanism underlying Alzheimer’s-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights linking restFC with cognitive task activations, this approach has potential clinical utility as it enables prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.Significance StatementDeveloping analytic approaches that can reliably predict features of Alzheimer’s disease is a major goal for cognitive and clinical neuroscience, with particular emphasis on identifying such diagnostic features early in the timeline of disease. We demonstrate the utility of an activity flow modeling approach, which predicts fMRI cognitive task activations in subjects identified as at-risk for Alzheimer’s disease. The approach makes activation predictions by transforming a healthy aged activation template via the at-risk subjects’ individual pattern of fMRI resting-state functional connectivity (restFC). The observed prediction accuracy supports activity flow as a mechanism linking age-related alterations in restFC and task activations, thereby providing a theoretical basis for incorporating restFC into imaging biomarker and personalized medicine interventions.

scholarly journals Attention network modulation via tRNS correlates with attention gain

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Federica Contò ◽  
Grace Edwards ◽  
Sarah Tyler ◽  
Danielle Parrott ◽  
Emily Grossman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Random Noise ◽  
Cognitive Capacity ◽  
Resting State Functional Connectivity ◽  
Attention Network ◽  
Transcranial Random Noise Stimulation ◽  
The Impact ◽  
Behavioral Improvement

Transcranial random noise stimulation (tRNS) can enhance vision in the healthy and diseased brain. Yet, the impact of multi-day tRNS on large-scale cortical networks is still unknown. We investigated the impact of tRNS coupled with behavioral training on resting-state functional connectivity and attention. We trained human subjects for 4 consecutive days on two attention tasks, while receiving tRNS over the intraparietal sulci, the middle temporal areas, or Sham stimulation. We measured resting-state functional connectivity of nodes of the dorsal and ventral attention network (DVAN) before and after training. We found a strong behavioral improvement and increased connectivity within the DVAN after parietal stimulation only. Crucially, behavioral improvement positively correlated with connectivity measures. We conclude changes in connectivity are a marker for the enduring effect of tRNS upon behavior. Our results suggest that tRNS has strong potential to augment cognitive capacity in healthy individuals and promote recovery in the neurological population.

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