keyvan olazadeh

Traumatic brain injury (TBI) is one of the most common types of brain injuries associated with cognitive impairments. Functional magnetic resonance imaging (fMRI) studies can provide a unique opportunity to examine brain connectivity patterns and understand the neural substrates of cognitive outcomes following traumatic injury. Therefore, this study aims to determine changes in functional connectivity patterns in patients with TBI compared to healthy individuals using two graph models, adaptive dense subgraph discovery (ADSD) and variance component.

This study used fMRI data downloaded from https://openneuro.org. These data included 14 patients with TBI aged between 18 and 36 and 12 healthy individuals (female: N=6, male: N=6) aged between 19 and 52. Out of the 74 regions examined, a cluster of 18 regions related to TBI was identified using the ADSD model. Subsequently, these identified regions were used as input for the variance component model to investigate changes in connectivity patterns.

Functional connectivity between an 18-brain region cluster, such as the Rectus (Left, Right), Supp_Motor_Area (Left, Right), and Middle Cingulum (Left, Right), differed between the patient and healthy groups. Based on the analysis of functional connectivity between pairs of brain regions, 153 connections between pairs of brain regions were compared in the two groups, out of which 63 connections showed significant differences between the two groups. Compared to other regions, Supp_Motor_Area_Right and Rectus_Left had more connections.

The study’s results indicate that the functional connectivity between the Cingulum, Hippocampus, Fusiform, Supp_Motor_Area, and Precentral regions differs between the two groups. Since these regions are involved in processes such as memory, learning, spatial orientation, face recognition, coordination, and motor control, changes in their functional connectivity may lead to impairments in these areas

Traumatic brain injury (TBI) is one of the leading causes of death globally and one of the most important diseases indicated by the World Health Organization (WHO). Several studies have concluded that brain damage can dramatically increase functional connectivity (FC) in the brain. The effects of this hyper-connectivity are not yet fully understood and are being studied by neuroscientists. Accordingly, this study identifies areas of the brain where, after brain injury, an acute increase in FC in such areas is observed.

The data used in this study were downloaded from the accessible open functional magnetic resonance imaging (fMRI) site. The data included fMRI of 14 patients with severe TBI and 12 healthy individuals. The longitudinal model of variance components investigated the difference between FC in the baseline effect and the longitudinal trend between the TBI and control groups.

After fitting the longitudinal model of variance components, no difference was observed between the FC of the two groups due to the baseline effect. However, in the longitudinal trend of FC, there was a statistically significant difference between the three pairs of cerebellum left, cerebellum right, superior frontal gyrus left, superior frontal gyrus right, thalamus left, and thalamus right in the TBI group compared to the control group.

The results showed that FC was sharply increased in 3 pairs of areas in people with TBI. This hyper-connectivity can affect individuals' cognitive functions, including motor and sensory functions. The exact extent of this effect is unclear and requires further investigation by neuroscientists.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, with atherosclerosis servingas a primary factor in their development. Platelets, leukocytes, and their interactions play a crucial role ininitiating and amplifying atherosclerosis. This study aims to evaluate the levels of platelet-monocyte aggregates (PMA)and specific integrins involved in leukocyte recruitment, including macrophage-1 antigen (Mac-1) and lymphocytefunction-associated antigen-1 (Lfa-1), in patients with acute coronary syndrome (ACS). In this case-control study, thirty-two subjects with ACS and 30 healthy individuals participated.It aimed to evaluate PMA expression and the median fluorescence intensity (MFI) of Mac-1 and Lfa-1 using flowcytometry. Dot plots and Pearson correlation coefficient were employed to examine the relationship between PMA,Mac-1, and Lfa-1. Multilevel model analysis was used to explore the effects and relationships of various parameters,including Mac-1 and Lfa-1, on PMA. Finally, receiver operating characteristic (ROC) curves were utilized to assessthe diagnostic accuracy of PMA, Mac-1, and Lfa-1 markers. It was observed that patients had higher PMA levels compared to the control group (58.99 ± 16.27 vs.29.99 ± 4.19 in controls, P<0.001), which correlated with PLT (ρ=0.512, P=0.035). Additionally, CD18 and CD11bexpression on monocytes were significantly elevated in patients (P<0.001) and were positively associated with PMA(β=19.09, P<0.001; β=6.90, P=0.022), but no significant relationship between CD11a and PMA was observed (β=5.06,P=0.315). PMA and Mac-1 were identified as better markers for differentiating patients from healthy individuals.(respectively, AUC=0.94, Sensitivity= 0.84, specificity=0.98; AUC=0.84, Sensitivity= 0.93, specificity=0.70). The study results indicated an increase in both Mac-1 and PMA levels in patients with ACS. Additionally,the significant association observed between Mac-1 and PMA in the patient group suggests a potential relationshipbetween these markers and ACS.

Parkinson 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 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 disease, using a Bayesian approach. 

The data of this study were downloaded from the open neuro site. These data include resting-state functional magnetic resonance imaging (rs-fMRI) of 11 healthy individuals and 11 Parkinson 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. 

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>0.05). 

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.

In recent years, investigating the differences in Functional Connectivity (FC) network in different brain regions in Functional Magnetic Resonance Imagining (fMRI) has appealed to neurological researchers. Examining the functional connectivity differences between two groups can assist in improving neurological disorders cure. The present study explores the differences in functional connectivity between two groups, one using Modafinil and the other placebo, as to consider the impact of this medicine, concerning functional connectivity of regions of interests among young, healthy people.

Data was downloadedfrom website "Open fMRI." Downloaded data included 26 young, healthy men with no history of mental disease. They are divided into two groups of 13. The first group received 100mgr Modafinil, and the second group 100mgr placebo. Three scans were taken from each group during the time. The data were analyzed through a longitudinal model, using a variance component.

Exploring the functional connectivity difference between the two groups, using intervention and placebo in the baseline effect did not showa significant statistical difference, but investigating the functional connectivity difference between the two groups in longitudinal trends showed a significant statistical difference in Inter-Hemispheric and Right-Brainstem.

After statistical analysis over applying a longitudinal model using a variance component, it was observed that functional connectivity in most paired investigated regions in the group, using Modafinil comparing to the group using a placebo has decreased. According to the present study's findings, Modafinil did not increase functional connectivity in most investigated regions.