scholarly journals Disentangling functional connectivity effects of age and expertise in long-term meditators

2019 ◽  
Author(s):  
Roberto Guidotti ◽  
Cosimo Del Gratta ◽  
Mauro Gianni Perrucci ◽  
Gian Luca Romani ◽  
Antonino Raffone
Keyword(s):  
Functional Connectivity ◽  
Brain Networks ◽  
Focused Attention ◽  
Brain Areas ◽  
Age Related ◽  
Connectivity Patterns ◽  
Open Monitoring ◽  
Multivariate Pattern ◽  
Neurocognitive Decline

AbstractThe effects of intensive meditation practices on the functional and structural organization of the human brain have been addressed by a growing number of neuroscientific studies. However, the different modulations of meditation expertise and of ageing, in the underlying brain areas and networks, have not yet been fully elucidated. These effects should be distinguished in order to clarify how long-term meditation can modulate the connectivity between brain areas. To address this issue, we tested whether meditation expertise and age can be predicted from the multivariate pattern of functional Magnetic Resonance Imaging connectivity, in Theravada Buddhist monks with long-term practice in two different meditation forms: Focused Attention (FA) and Open Monitoring (OM).We found that functional connectivity patterns in both meditation forms can be used to predict expertise and age of long-term meditators. Our findings suggest that meditation expertise is associated with meditation-specific brain networks modulations, while age-related modifications are general and independent from the meditation type. Specifically, expertise modulated patterns during FA meditation include nodes and connections implicated in focusing, sustaining and monitoring attention, while the predictive patterns during OM meditation include nodes associated with cognitive and affective monitoring. Thus, the two forms of meditation may differentially contribute to counteract the effects of neurocognitive decline with ageing by neuroplasticity of brain networks.

scholarly journals Neuroplasticity Within and between Functional Brain Networks in Mental Training Based on Long-Term Meditation

2021 ◽  
Vol 11 (8) ◽  
pp. 1086
Author(s):  
Roberto Guidotti ◽  
Cosimo Del Gratta ◽  
Mauro Gianni Perrucci ◽  
Gian Luca Romani ◽  
Antonino Raffone
Keyword(s):  
Large Scale ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Connectivity Pattern ◽  
Mental Training ◽  
Functional Brain ◽  
Connectivity Patterns ◽  
Open Monitoring ◽  
The Impact

(1) The effects of intensive mental training based on meditation on the functional and structural organization of the human brain have been addressed by several neuroscientific studies. However, how large-scale connectivity patterns are affected by long-term practice of the main forms of meditation, Focused Attention (FA) and Open Monitoring (OM), as well as by aging, has not yet been elucidated. (2) Using functional Magnetic Resonance Imaging (fMRI) and multivariate pattern analysis, we investigated the impact of meditation expertise and age on functional connectivity patterns in large-scale brain networks during different meditation styles in long-term meditators. (3) The results show that fMRI connectivity patterns in multiple key brain networks can differentially predict the meditation expertise and age of long-term meditators. Expertise-predictive patterns are differently affected by FA and OM, while age-predictive patterns are not influenced by the meditation form. The FA meditation connectivity pattern modulated by expertise included nodes and connections implicated in focusing, sustaining and monitoring attention, while OM patterns included nodes associated with cognitive control and emotion regulation. (4) The study highlights a long-term effect of meditation practice on multivariate patterns of functional brain connectivity and suggests that meditation expertise is associated with specific neuroplastic changes in connectivity patterns within and between multiple brain networks.

scholarly journals Age-Related Reorganizational Changes in Modularity and Functional Connectivity of Human Brain Networks

2014 ◽  
Vol 4 (9) ◽  
pp. 662-676 ◽  
Author(s):  
Jie Song ◽  
Rasmus M. Birn ◽  
Mélanie Boly ◽  
Timothy B. Meier ◽  
Veena A. Nair ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Brain Networks ◽  
Age Related

The relation between structural and functional connectivity patterns in complex brain networks

2016 ◽  
Vol 103 ◽  
pp. 149-160 ◽  
Author(s):  
C.J. Stam ◽  
E.C.W. van Straaten ◽  
E. Van Dellen ◽  
P. Tewarie ◽  
G. Gong ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Networks ◽  
Connectivity Patterns

scholarly journals A Signal-Processing-Based Approach to Time-Varying Graph Analysis for Dynamic Brain Network Identification

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Ali Yener Mutlu ◽  
Edward Bernat ◽  
Selin Aviyente
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Dynamic Network ◽  
Principal Component ◽  
Brain Network ◽  
Event Related Potential ◽  
Time Varying ◽  
Error Related Negativity ◽  
Connectivity Patterns

In recent years, there has been a growing need to analyze the functional connectivity of the human brain. Previous studies have focused on extracting static or time-independent functional networks to describe the long-term behavior of brain activity. However, a static network is generally not sufficient to represent the long term communication patterns of the brain and is considered as an unreliable snapshot of functional connectivity. In this paper, we propose a dynamic network summarization approach to describe the time-varying evolution of connectivity patterns in functional brain activity. The proposed approach is based on first identifying key event intervals by quantifying the change in the connectivity patterns across time and then summarizing the activity in each event interval by extracting the most informative network using principal component decomposition. The proposed method is evaluated for characterizing time-varying network dynamics from event-related potential (ERP) data indexing the error-related negativity (ERN) component related to cognitive control. The statistically significant connectivity patterns for each interval are presented to illustrate the dynamic nature of functional connectivity.

Convergent and divergent functional connectivity patterns in patients with long-term left-sided and right-sided deafness

2018 ◽  
Vol 665 ◽  
pp. 74-79 ◽  
Author(s):  
Yanyang Zhang ◽  
Zhiqi Mao ◽  
Shiyu Feng ◽  
Wenxin Wang ◽  
Jun Zhang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Connectivity Patterns

scholarly journals Source Space Analysis of Event-Related Dynamic Reorganization of Brain Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Andreas A. Ioannides ◽  
Stavros I. Dimitriadis ◽  
George A. Saridis ◽  
Marotesa Voultsidou ◽  
Vahe Poghosyan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Activity ◽  
Clinical Applications ◽  
Brain Areas ◽  
Connectivity Patterns ◽  
The Brain ◽  
Typical Subject ◽  
Different Parts ◽  
Neuroimaging Techniques

How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

scholarly journals Transmission delays and frequency detuning can regulate information flow between brain regions

2020 ◽  
Author(s):  
Aref Pariz ◽  
Ingo Fischer ◽  
Alireza Valizadeh ◽  
Claudio Mirasso
Keyword(s):  
Functional Connectivity ◽  
Information Transfer ◽  
Effective Connectivity ◽  
Signal Transmission ◽  
Brain Networks ◽  
Frequency Detuning ◽  
Brain Oscillations ◽  
Brain Areas ◽  
Neural Populations

AbstractBrain networks exhibit very variable and dynamical functional connectivity and flexible configurations of information exchange despite their overall fixed structure (connectome). Brain oscillations are hypothesized to underlie time-dependent functional connectivity by periodically changing the excitability of neural populations. In this paper, we investigate the role that the connection delay and the frequency detuning between different neural populations play in the transmission of signals. Based on numerical simulations and analytical arguments, we show that the amount of information transfer between two oscillating neural populations can be determined solely by their connection delay and the mismatch in their oscillation frequencies. Our results highlight the role of the collective phase response curve of the oscillating neural populations for the efficacy of signal transmission and the quality of the information transfer in brain networks.Author summaryCollective dynamics in brain networks is characterized by a coordinated activity of their constituent neurons that lead to brain oscillations. Many evidences highlight the role that brain oscillations play in signal transmission, the control of the effective communication between brain areas and the integration of information processed by different specialized regions. Oscillations periodically modulate the excitability of neurons and determine the response those areas receiving the signals. Based on the communication trough coherence (CTC) theory, the adjustment of the phase difference between local oscillations of connected areas can specify the timing of exchanged signals and therefore, the efficacy of the communication channels. An important factor is the delay in the transmission of signals from one region to another that affects the phase difference and timing, and consequently the impact of the signals. Despite this delay plays an essential role in CTC theory, its role has been mostly overlooked in previous studies. In this manuscript, we concentrate on the role that the connection delay and the oscillation frequency of the populations play in the signal transmission, and consequently in the effective connectivity, between two brain areas. Through extensive numerical simulations, as well as analytical results with reduced models, we show that these parameters have two essential impacts on the effective connectivity of the neural networks: First, that the populations advancing in phase to others do not necessarily play the role of the information source; and second, that the amount and direction of information transfer dependents on the oscillation frequency of the populations.

Caudal inferior parietal cortex supports the hypothesis about a modulating cortical area

2022 ◽  
Author(s):  
Fatemeh Tabassi Mofrad ◽  
Niels O. Schiller
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Parietal Cortex ◽  
Resting State ◽  
Cortical Area ◽  
Control Area ◽  
Brain Areas ◽  
Inferior Parietal Cortex ◽  
Connectivity Patterns ◽  
The Brain

The cytoarchitectonically tripartite organization of the inferior parietal cortex (IPC) into the rostral, the middle and the caudal clusters has been generally ignored when associating different functions to this part of the cortex, resulting in inconsistencies about how IPC is understood. In this study, we investigated the patterns of functional connectivity of the caudal IPC in a task requiring cognitive control of language, using multiband EPI. This part of the cortex demonstrated functional connectivity patterns dissimilar to a cognitive control area and at the same time the caudal IPC showed negative functional associations with both task-related brain areas and the precuneus cortex, which is active during resting state. We found evidence suggesting that the traditional categorization of different brain areas into either task-related or resting state-related networks cannot accommodate the functions of the caudal IPC. This underlies the hypothesis about a modulating cortical area proposing that its involvement in task performance, in a modulating manner, is marked by deactivation in the patterns of functional associations with parts of the brain that are recognized to be involved in doing a task, proportionate to task difficulty; however, their patterns of functional connectivity in some other respects do not correspond to the resting state-related parts of the cortex.

scholarly journals Diverse functional connectivity patterns of resting-state brain networks associated with good and poor hand outcomes following stroke

2019 ◽  
Vol 24 ◽  
pp. 102065 ◽  
Author(s):  
Wenjun Hong ◽  
Qixiang Lin ◽  
Zaixu Cui ◽  
Feiwen Liu ◽  
Rong Xu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Networks ◽  
Connectivity Patterns

scholarly journals The Effects of the BAILAMOS Dance Program on Brain Functional Connectivity of Older Latinos: An Exploratory Study

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 504-505
Author(s):  
Guilherme Moraes Balbim ◽  
Olusola Ajilore ◽  
Melissa Lamar ◽  
Kirk Erickson ◽  
Susan Aguiñaga ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Decline ◽  
Resting State ◽  
Leisure Time Physical Activity ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Post Intervention ◽  
Age Related ◽  
Brain Functional Connectivity ◽  
Age Related Cognitive Decline

Abstract Compared to non-Latinos whites, older Latinos are at higher risk of cognitive impairment and engage in less leisure-time physical activity (PA). Resting-state brain functional connectivity (FC) is a putative biomarker for age-related cognitive decline. PA plays a role in FC of brain networks associated with cognitive decline. Objective: Investigate the effects of the BAILAMOS™ dance program on FC in three brain networks associated with age-related cognitive decline (Default Mode [DMN], Frontoparietal [FPN], and Salience [SAL] networks). Methods: Single-group pre-post design. Ten cognitively intact older Latinos participated in the four-month (2x/week for 60min) BAILAMOS™ dance program with four Latin dance styles. MRI was obtained pre- and post-intervention. FC was analyzed using the resting-state fMRI toolbox (CONN) via pairwise BOLD signal correlations and then converted into z-scores. We performed dependent t-tests, computed Cohen’s d and 95%CI for p < 0.05. Results: Within-FPN FC significantly increased (t(9) = 2.35, p = 0.043, d = 0.70) from pre (M=0.49±0.15) to post-intervention (M=0.59±0.13). In the DMN, we observed moderate effect size changes in the ratio of the FC between-networks by the FC within-networks (Mdiff = 0.10; 95%CI = -0.01; 0.21, p = 0.08, d = 0.64). Conclusions: The BAILAMOS™ program increased within-FPN FC, which is a cognitive-control network related to adaptive control and flexibility. Moderate changes between- vs. within-DMN FC suggest BAILAMOS™ also increased whole-brain DMN integration. Taken together, results might signal that Latin dance can combat the disruption of FC between the DMN and other networks, and within-FPN, which are associated with cognitive decline.

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