scholarly journals Functional Brain Connectivity Patterns Associated with Visual Hallucinations in Dementia with Lewy Bodies

2021 ◽  
pp. 1-10
Author(s):  
Stefania Pezzoli ◽  
Matteo De Marco ◽  
Giovanni Zorzi ◽  
Annachiara Cagnin ◽  
Annalena Venneri
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Dementia With Lewy Bodies ◽  
Brain Connectivity ◽  
Lewy Bodies ◽  
Resting State Fmri ◽  
Group Differences ◽  
Visual Hallucinations ◽  
Functional Brain ◽  
Functional Brain Networks

Background: The presence of recurrent, complex visual hallucinations (VH) is among the core clinical features of dementia with Lewy bodies (DLB). It has been proposed that VH arise from a disrupted organization of functional brain networks. However, studies are still limited, especially investigating the resting-state functional brain features underpinning VH in patients with dementia. Objective: The aim of the present pilot study was to investigate whether there were any alterations in functional connectivity associated with VH in DLB. Methods: Seed-based analyses and independent component analysis (ICA) of resting-state fMRI scans were carried out to explore differences in functional connectivity between DLB patients with and without VH. Results: Seed-based analyses reported decreased connectivity of the lateral geniculate nucleus, the superior parietal lobule and the putamen with the medial frontal gyrus in DLB patients with VH. Visual areas showed a pattern of both decreased and increased functional connectivity. ICA revealed between-group differences in the default mode network (DMN). Conclusion: Functional connectivity analyses suggest dysfunctional top-down and bottom-up processes and DMN-related alterations in DLB patients with VH. These impairments might foster the generation of false visual images that are misinterpreted, ultimately resulting in VH.

scholarly journals Characterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity Induced by Ayahuasca

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 128 ◽  
Author(s):  
Aline Viol ◽  
Fernanda Palhano-Fontes ◽  
Heloisa Onias ◽  
Draulio de Araujo ◽  
Philipp Hövel ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Resting State ◽  
Structural Information ◽  
Brain Connectivity ◽  
Functional Brain ◽  
States Of Consciousness ◽  
Functional Brain Networks ◽  
Empirical Networks ◽  
Emergent Behaviors

With the aim of further advancing the understanding of the human brain’s functional connectivity, we propose a network metric which we term the geodesic entropy. This metric quantifies the Shannon entropy of the distance distribution to a specific node from all other nodes. It allows to characterize the influence exerted on a specific node considering statistics of the overall network structure. The measurement and characterization of this structural information has the potential to greatly improve our understanding of sustained activity and other emergent behaviors in networks. We apply this method to study how the psychedelic infusion Ayahuasca affects the functional connectivity of the human brain in resting state. We show that the geodesic entropy is able to differentiate functional networks of the human brain associated with two different states of consciousness in the awaking resting state: (i) the ordinary state and (ii) a state altered by ingestion of the Ayahuasca. The functional brain networks from subjects in the altered state have, on average, a larger geodesic entropy compared to the ordinary state. Finally, we discuss why the geodesic entropy may bring even further valuable insights into the study of the human brain and other empirical networks.

scholarly journals Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer’s disease

2018 ◽  
Author(s):  
Julia Schumacher ◽  
Luis R. Peraza ◽  
Michael Firbank ◽  
Alan J. Thomas ◽  
Marcus Kaiser ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Functional Connectivity ◽  
Resting State ◽  
Dementia With Lewy Bodies ◽  
Lewy Bodies ◽  
Brain Network ◽  
Visual Hallucinations ◽  
Dynamic Functional Connectivity ◽  
Dynamic Connectivity ◽  
Cognitive Fluctuations

AbstractWe studied the dynamic functional connectivity profile of dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) and the relationship between dynamic connectivity and the temporally transient symptoms of cognitive fluctuations and visual hallucinations in DLB.Resting state fMRI data from 31 DLB, 29 AD, and 31 healthy control participants were analysed using dual regression to determine between-network functional connectivity. We used a sliding window approach followed by k-means clustering and dynamic network analyses to study dynamic functional connectivity changes associated with AD and DLB. Network measures that showed significant group differences were tested for correlations with clinical symptom severity.AD and DLB patients spent more time than controls in sparse connectivity configurations with absence of strong positive and negative connections and a relative isolation of motor networks from other networks. Additionally, DLB patients spent less time in a more strongly connected state and the variability of global brain network efficiency was reduced in DLB compared to controls. However, there were no significant correlations between dynamic connectivity measures and clinical scores.The loss of global efficiency variability in DLB might indicate the presence of an abnormally rigid brain network and the lack of economical dynamics, factors which could contribute to an inability to respond appropriately to situational demands. However, the absence of significant clinical correlations indicates that the severity of transient cognitive symptoms such as cognitive fluctuations and visual hallucinations might not be directly related to these dynamic connectivity changes observed during a short resting state scan.

scholarly journals Brain network dynamics correlate with personality traits

2019 ◽  
Author(s):  
Aya Kabbara ◽  
Veronique Paban ◽  
Arnaud Weill ◽  
Julien Modolo ◽  
Mahmoud Hassan
Keyword(s):  
Functional Connectivity ◽  
Personality Traits ◽  
Resting State ◽  
Brain Networks ◽  
Neural Substrates ◽  
Brain Network ◽  
Functional Brain ◽  
Human Connectome Project ◽  
Functional Brain Networks ◽  
The Brain

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.

scholarly journals Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

2016 ◽  
Vol 11 ◽  
pp. 302-315 ◽  
Author(s):  
Tingting Xu ◽  
Kathryn R. Cullen ◽  
Bryon Mueller ◽  
Mindy W. Schreiner ◽  
Kelvin O. Lim ◽  
...  
Keyword(s):  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Network Analysis ◽  
Resting State ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Borderline Personality ◽  
Functional Brain

Influences of Hunger, Satiety and Oral Glucose on Functional Brain Connectivity: A Multimethod Resting-State fMRI Study

Neuroscience ◽  
2018 ◽  
Vol 382 ◽  
pp. 80-92 ◽  
Author(s):  
Arkan Al-Zubaidi ◽  
Marcus Heldmann ◽  
Alfred Mertins ◽  
Kamila Jauch-Chara ◽  
Thomas F. Münte
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Oral Glucose ◽  
Functional Brain ◽  
Fmri Study

Functional brain connectivity in resting-state fMRI using phase and magnitude data

2018 ◽  
Vol 293 ◽  
pp. 299-309 ◽  
Author(s):  
Zikuan Chen ◽  
Arvind Caprihan ◽  
Eswar Damaraju ◽  
Srinivas Rachakonda ◽  
Vince Calhoun
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Functional Brain

scholarly journals High frequency functional brain networks in neonates revealed by rapid acquisition resting state fMRI

2015 ◽  
Vol 36 (7) ◽  
pp. 2483-2494 ◽  
Author(s):  
Adam P.R. Smith‐Collins ◽  
Karen Luyt ◽  
Axel Heep ◽  
Risto A. Kauppinen
Keyword(s):  
Resting State ◽  
High Frequency ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Functional Brain ◽  
Rapid Acquisition ◽  
Functional Brain Networks

scholarly journals Disrupted Functional Brain Connectivity in Partial Epilepsy: A Resting-State fMRI Study

PLoS ONE ◽  
2012 ◽  
Vol 7 (1) ◽  
pp. e28196 ◽  
Author(s):  
Cheng Luo ◽  
Chuan Qiu ◽  
Zhiwei Guo ◽  
Jiajia Fang ◽  
Qifu Li ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Partial Epilepsy ◽  
Functional Brain ◽  
Fmri Study

scholarly journals Commentary: BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks. Science 348, 1241-4

2016 ◽  
Author(s):  
Spiro P. Pantazatos ◽  
Xinyi Li
Keyword(s):  
Gene Expression ◽  
Resting State ◽  
Euclidean Distance ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Spatial Proximity ◽  
Functional Magnetic Resonance ◽  
Future Directions ◽  
Functional Brain ◽  
Functional Brain Networks

SummaryA recent report claims that functional brain networks defined with resting-state functional magnetic resonance imaging (fMRI) can be recapitulated with correlated gene expression (i.e. high within-network tissue-tissue “strength fraction”, SF) (Richiardi et al., 2015). However, the authors do not adequately control for spatial proximity. We replicated their main analysis, performed a more effective adjustment for spatial proximity, and tested whether “null networks” (i.e. clusters with center coordinates randomly placed throughout cortex) also exhibit high SF. Removing proximal tissue-tissue correlations by Euclidean distance, as opposed to removing correlations within arbitrary tissue labels as in (Richiardi et al., 2015), reduces within-network SF to no greater than null. Moreover, randomly placed clusters also have significantly high SF, indicating that high within-network SF is entirely attributable to proximity and is unrelated to functional brain networks defined by resting-state fMRI. We discuss why additional validations in the original article are invalid and/or misleading and suggest future directions.

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