scholarly journals A Study Over Brain Connectivity Network of Parkinson's Patients, Using Nonparametric Bayesian Model

2021 ◽  
pp. 1-18
Author(s):  
Fatemeh Pourmotahari ◽  
◽  
Seyyed Mohammad Tabatabaei ◽  
Nasrin Borumandnia ◽  
Naghmeh Khadembashi ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Functional Connectivity ◽  
Correlation Coefficient ◽  
Resting State ◽  
Bayesian Model ◽  
Functional Relationship ◽  
Brain Connectivity ◽  
Healthy Individuals ◽  
Nonparametric Bayesian ◽  
The Brain

Introduction: Parkinson’s disease is a neurodegenerative disease that disrupts functional brain networks. Many neurodegenerative disorders are associated with changes in brain communication patterns. Resting-state functional connectivity studies can distinguish the topological structure of Parkinson's patients from healthy individuals by analyzing patterns between different regions of the brain. Accordingly, the present study aimed to determine the brain topological features and functional connectivity in patients with Parkinson's disease, using a Bayesian approach. Method: The data of this study were downloaded from the open neuro site. These data include "Resting-State Functional MRI" (rs-fMRI) of 11 healthy individuals and 11 Parkinson’s patients with mean ages of 64.36 and 63.73, respectively. An advanced nonparametric Bayesian model was used to evaluate topological characteristics, including clustering of brain regions and correlation coefficient of the clusters. The significance of functional relationships based on each edge between the two groups was examined through false discovery rate (FDR) and network-based statistics (NBS) methods. Results: Brain connectivity results showed a major difference in terms of the number of regions in each cluster and the correlation coefficient between the patient and healthy groups. The largest clusters in the patient and control groups were 26 and 53 regions, respectively, with clustering correlation values of 0.36 and 0.26. Although there are 15 common areas across the two clusters, the intensity of the functional relationship between these areas was different in the two groups. Moreover, using NBS and FDR methods, no significant difference was observed for each edge between the patient and healthy groups (p-value>0.05). Conclusion: The results of this study show a different topological configuration of the brain network between the patient and healthy groups, indicating changes in the functional relationship between a set of areas of the brain.

scholarly journals Learning differentially reorganizes brain activity and connectivity

2020 ◽  
Author(s):  
Maxwell A. Bertolero ◽  
Azeez Adebimpe ◽  
Ankit N. Khambhati ◽  
Marcelo G. Mattar ◽  
Daniel Romer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Learning Performance ◽  
Functional Architecture ◽  
Time Space ◽  
Novel Objects ◽  
Value Learning ◽  
The Brain

Human learning is a complex process in which future behavior is altered via the reorganization of brain activity and connectivity. It remains unknown whether activity and connectivity differentially reorganize during learning, and, if so, how that differential reorganization tracks stages of learning across distinct brain areas. Here, we address this gap in knowledge by measuring brain activity and functional connectivity in a longitudinal fMRI experiment in which healthy adult human participants learn the values of novel objects over the course of four days. An increasing similarity in activity or functional connectivity across subjects during learning reflects reorganization toward a common functional architecture. We assessed the presence of reorganization in activity and connectivity both during value learning and during the resting-state, allowing us to differentiate common elicited processes from intrinsic processes. We found a complex and dynamic reorganization of brain connectivity and activity—as a function of time, space, and performance—that occurs while subjects learn. Spatially localized brain activity reorganizes across the brain to a common functional architecture early in learning, and this reorganization tracks early learning performance. In contrast, spatially distributed connectivity reorganizes across the brain to a common functional architecture as training progresses, and this reorganization tracks later learning performance. Particularly good performance is associated with a sticky connectivity, that persists into the resting state. Broadly, our work uncovers distinct principles of reorganization in activity and connectivity at different phases of value learning, which inform the ongoing study of learning processes more generally.

scholarly journals Computerized physical exercise improves the functional architecture of the brain in patients with Parkinson’s Disease: a network science resting-state EEG study

2020 ◽  
Author(s):  
Vasileios Rafail Xefteris ◽  
Charis Styliadis ◽  
Alexandra Anagnostopoulou ◽  
Panagiotis Kartsidis ◽  
Evangelos Paraskevopoulos ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Connectivity ◽  
Physical Exercise ◽  
Resting State ◽  
Network Science ◽  
Brain Network ◽  
Motor Execution ◽  
The Brain

AbstractPhysical exercise is an effective non-pharmaceutical treatment for Parkinson’s disease (PD) symptoms, both motor and non-motor. Despite the numerous reports on the neuroplastic role of physical exercise in patients with PD (PwPD), its effects have not been thoroughly explored via brain network science, which can provide a coherent framework for understanding brain functioning. We used resting-state EEG data to investigate the functional connectivity changes of the brain’s intrinsic cortical networks due to physical exercise. The brain activity of 14 PwPD before and after a ten-week protocol of computerized physical training was statistically compared to quantify changes in directed functional connectivity in conjunction with psychometric and somatometric assessments. PwPD showed a significant reorganization of the post-training brain network along with increases in their physical capacity. Specifically, our results revealed significant adjustments in clustering, increased characteristic path length, and decreased global efficiency, in correlation to the improved physical capacity. Our results go beyond previous findings by indicating a transition to a reparative network architecture of enhanced connectivity. We present a meaningful relationship between network characteristics and motor execution capacity which support the use of motor treatment in tandem with medication. This trial is registered with ClinicalTrials.gov Identifier NCT04426903.Impact StatementThe effects of physical training (PT) on the neuroplasticity attributes of patients with Parkinson’s Disease (PwPD) have been well documented via neurophysiological evaluations. However, there is a knowledge gap on the role of training-induced neuroplasticity in whole-brain network organization. We investigated the PT effects on the brain network organization of 14 PwPD, using EEG and network indices coupled with psychosomatometric tests. We report evidence of reparative functional reorganization of the brain with more balanced integration and segregation abilities, in correlation to improved motor performance. The PD brain can repair and reestablish a better level of motor execution and control due to computer-empowered physical stimulation.

scholarly journals The Effect of Grain and Grass Fed Beef and Chicken Breast Consumption on the Functional Connectivity in the Brain Using Resting State Functional Magnetic Resonance Imaging

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
E. S. Beyer ◽  
M. F. Miller ◽  
T. H. Davis ◽  
J. F. Legako
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Connectivity ◽  
Chemical Components ◽  
Volatile Components ◽  
Functional Brain ◽  
Dimethyl Sulfone ◽  
True Value ◽  
Significant Difference ◽  
The Brain

ObjectivesUnderstanding functional connectivity after consuming meat can be essential to fully understanding consumer’s preferences and the connection to certain flavor compounds. The objective of this study was to determine differences in the functional brain connectivity of consumers after consuming grass-fed beef, grain-fed beef and chicken while determining the different chemical and volatile components that differentiate the treatments.Materials and MethodsGrass-fed strip steaks, Grain-fed strip steaks and chicken breasts were collected, aged 21 d and cut into 1×1-inch consumer steaks. Each steak was vacuum sealed with a random identification number and frozen at –20°C. 23 volunteered consumers evaluated each treatment randomly followed by a Blood Oxygen Level-Dependent (BOLD) fMRI scan. Each consumer received a resting state scan and three scans following each sample. The beef was cooked to a medium degree of doneness (71°C) and the chicken was cooked to a well-done degree of doneness (75°C), followed by a 1-min resting period. The consumers were asked to complete a sensory ballot for each sample to quantify tenderness, juiciness, flavor, overall liking and quality. Each attribute was evaluated on a 100mm line scale. The sensory ballot, volatile and fatty acid data were analyzed by ANOVA and multiple means comparison using SAS while the fMRI data were analyzed using FSL’s FEAT software.ResultsThe results indicated all treatments were equal for tenderness and flavor, but the chicken was the least juicy (P < 0.05) and the grain-fed steak was ranked higher for overall liking (P < 0.05) in comparison to chicken. Furthermore, based on an independent component analysis, there was a significant difference in the functional connectivity (P < 0.05) from the resting state scan to all three treatments within the insular, medial prefrontal cortex, and amygdala regions. Additionally, there were significant differences in connectivity (P < 0.05) between the insula and orbitofrontal cortex in grass-fed compared to grain-fed beef. These areas are involved in processing sensory characteristics related to smell and taste and tend to track differences in preferences and stimulus value. Also, the samples were evaluated for volatile compounds with GC–MS and fatty acids using the FAMES method. Chicken and grass-fed beef was found to have a higher concentration (P < 0.05) of dimethyl sulfone in comparison to grain-fed beef, while the grass-fed steaks possessed a higher concentration (P < 0.05) of toluene in comparison to grain-fed steaks, but not differing from chicken. Dimethyl sulfone and toluene have been tied to grass-fed beef and chicken flavor profiles (Tansawat et al., 2013).ConclusionThe results from the functional brain connectivity in the reward pathways and the chemical components of the different treatments indicated a trend for grain-fed beef to be the most different from grass-fed beef and chicken. Moreover, tying brain activity to the flavor and chemical components in meat can be vital in understanding consumer’s preferences not observed in behavior alone. Therefore, these results can provide a basis to determine the ability to track reactions within the functional connectivity in the brain and the chemical aspects of different steaks to determine and understand consumer’s preferences and the true value of beef and chicken.

scholarly journals The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review

2019 ◽  
Vol 9 (1) ◽  
pp. 11 ◽  
Author(s):  
Ángel Romero-Martínez ◽  
Macarena González ◽  
Marisol Lila ◽  
Enrique Gracia ◽  
Luis Martí-Bonmatí ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Effective Treatment ◽  
Resting State ◽  
Brain Structures ◽  
Prevention Programs ◽  
Angular Gyrus ◽  
Resting State Functional Connectivity ◽  
Treatment And Prevention ◽  
Reliable Marker ◽  
The Brain

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

Changes in Resting-State Functional Connectivity Related to Freezing of Gait in Parkinson's Disease

Neuroscience ◽  
2019 ◽  
Vol 418 ◽  
pp. 311-317 ◽  
Author(s):  
Alexandra Potvin-Desrochers ◽  
Trina Mitchell ◽  
Thomas Gisiger ◽  
Caroline Paquette
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Connectivity ◽  
Resting State ◽  
Freezing Of Gait ◽  
Resting State Functional Connectivity

scholarly journals Computerized physical and cognitive training improves the functional architecture of the brain in adults with Down syndrome: A network science EEG study

2020 ◽  
pp. 1-21
Author(s):  
Alexandra Anagnostopoulou ◽  
Charis Styliadis ◽  
Panagiotis Kartsidis ◽  
Evangelia Romanopoulou ◽  
Vasiliki Zilidou ◽  
...  
Keyword(s):  
Down Syndrome ◽  
Functional Connectivity ◽  
Cognitive Training ◽  
Resting State ◽  
Network Architecture ◽  
Right Hemisphere ◽  
Random Network ◽  
Brain Activity ◽  
Hierarchical Organization ◽  
The Brain

Understanding the neuroplastic capacity of people with Down syndrome (PwDS) can potentially reveal the causal relationship between aberrant brain organization and phenotypic characteristics. We used resting-state EEG recordings to identify how a neuroplasticity-triggering training protocol relates to changes in the functional connectivity of the brain’s intrinsic cortical networks. Brain activity of 12 PwDS before and after a 10-week protocol of combined physical and cognitive training was statistically compared to quantify changes in directed functional connectivity in conjunction with psychosomatometric assessments. PwDS showed increased connectivity within the left hemisphere and from left-to-right hemisphere, as well as increased physical and cognitive performance. Our findings reveal a strong adaptive neuroplastic reorganization as a result of the training that leads to a less-random network with a more pronounced hierarchical organization. Our results go beyond previous findings by indicating a transition to a healthier, more efficient, and flexible network architecture, with improved integration and segregation abilities in the brain of PwDS. Resting-state electrophysiological brain activity is used here for the first time to display meaningful relationships to underlying Down syndrome processes and outcomes of importance in a translational inquiry. This trial is registered with ClinicalTrials.gov Identifier NCT04390321.

scholarly journals Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

2019 ◽  
Author(s):  
Milou Straathof ◽  
Michel R.T. Sinke ◽  
Theresia J.M. Roelofs ◽  
Erwin L.A. Blezer ◽  
R. Angela Sarabdjitsingh ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Rat Brain ◽  
Resting State ◽  
Structural Connectivity ◽  
Distinct Structure ◽  
Macro Scale ◽  
Function Relationship ◽  
The Brain ◽  
Meso Scale

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in many disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional connectivity and macro-scale diffusion-based structural connectivity, but no correspondence between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Locally, strong functional connectivity was found in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Distinct structure-function relationships across the brain can explain the organization of networks and may underlie variations in the impact of structural damage on functional networks and behavior.

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.

Sign in / Sign up

Export Citation Format

Share Document