scholarly journals Modular-Level Alterations of Single-Subject Gray Matter Networks in Schizophrenia

2021 ◽  
Author(s):  
Jie Xiang ◽  
Yunxiao Ma ◽  
Gongshu Wang ◽  
Dandan Li ◽  
Tong Wang ◽  
...  
Keyword(s):  
Gray Matter ◽  
Inferior Frontal Gyrus ◽  
Brain Network ◽  
Control Group ◽  
Single Subject ◽  
Connection Strength ◽  
Schizophrenic Patients ◽  
Topological Characteristics ◽  
Structural Brain Network ◽  
The Brain

Abstract Schizophrenia is often regarded as a psychiatric disorder caused by disrupted connections in the brain. Evidence suggests that the gray matter of schizophrenia patients is damaged in a modular pattern. Recently, abnormal topological organization was observed in the gray matter networks of patients with schizophrenia. However, the modular-level alteration of gray matter networks in schizophrenia remains unclear. In this study, single-subject gray matter networks were constructed for a total of 217 subjects (116 patients with schizophrenia and 101 controls). We analyzed the topological characteristics of the brain network and the strengths of connections between and within modules. Compared with the outcomes in the control group, the global efficiency and participation coefficient values of the single-subject gray matter networks in schizophrenic patients were significantly reduced. The nodal participation coefficient of the regions involving the FPN, DMN and SCN were significantly decreased in subjects with schizophrenia. The intermodule connections between the FPN and VIS and between the DMN and SCN, in the FPN were significantly reduced in the patient group. In the FPN, the intramodule nodal connection strength of the left orbital inferior frontal gyrus and right inferior parietal gyrus was significantly decreased in schizophrenia patients. Reduced intermodule nodal connection strength between the FPN and VIS was associated with the severity of schizophrenia symptoms. These findings suggest that abnormal intramodule and intermodule connections in the structural brain network may a biomarker of schizophrenia symptoms.

scholarly journals BrainNetVis: An Open-Access Tool to Effectively Quantify and Visualize Brain Networks

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Eleni G. Christodoulou ◽  
Vangelis Sakkalis ◽  
Vassilis Tsiaras ◽  
Ioannis G. Tollis
Keyword(s):  
Open Access ◽  
Brain Network ◽  
Global Network ◽  
Control Group ◽  
Network Modelling ◽  
Network Information ◽  
Network Measures ◽  
Graph Metrics ◽  
Network Metrics ◽  
The Brain

This paper presents BrainNetVis, a tool which serves brain network modelling and visualization, by providing both quantitative and qualitative network measures of brain interconnectivity. It emphasizes the needs that led to the creation of this tool by presenting similar works in the field and by describing how our tool contributes to the existing scenery. It also describes the methods used for the calculation of the graph metrics (global network metrics and vertex metrics), which carry the brain network information. To make the methods clear and understandable, we use an exemplar dataset throughout the paper, on which the calculations and the visualizations are performed. This dataset consists of an alcoholic and a control group of subjects.

Assessment of Brain Damage in a Geriatric Population through Use of a Visual-Searching Task

1980 ◽  
Vol 50 (2) ◽  
pp. 371-375
Author(s):  
Milton Turbiner ◽  
Robert M. Derman
Keyword(s):  
Brain Damage ◽  
Normal Subjects ◽  
Control Group ◽  
Geriatric Population ◽  
Schizophrenic Patients ◽  
Derived Data ◽  
The Brain

This study was designed to assess the discriminative capacity of a visual-searching task for brain damage, as described by Goldstein and Kyc (1978) , for 10 hospitalized male, brain-damaged patients, 10 hospitalized male schizophrenic patients, and 10 normal subjects in a control group, all of whom were approximately 65 yr. old. The derived data indicated, at a statistically significant level, that the visual-searching task was effective in successfully classifying 80% of the brain-damaged sample when compared to the schizophrenic patients and discriminating 90% of the brain-damaged patients from normal subjects.

scholarly journals Association Between Trait Empathy and Resting Brain Activity in Women With Primary Dysmenorrhea During the Pain and Pain-Free Phases

2020 ◽  
Vol 11 ◽  
Author(s):  
Wanghuan Dun ◽  
Tongtong Fan ◽  
Qiming Wang ◽  
Ke Wang ◽  
Jing Yang ◽  
...  
Keyword(s):  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Network ◽  
Primary Dysmenorrhea ◽  
Pain Experience ◽  
Current State ◽  
The Neural Network ◽  
The Right ◽  
The Brain

Empathy refers to the ability to understand someone else's emotions and fluctuates with the current state in healthy individuals. However, little is known about the neural network of empathy in clinical populations at different pain states. The current study aimed to examine the effects of long-term pain on empathy-related networks and whether empathy varied at different pain states by studying primary dysmenorrhea (PDM) patients. Multivariate partial least squares was employed in 46 PDM women and 46 healthy controls (HC) during periovulatory, luteal, and menstruation phases. We identified neural networks associated with different aspects of empathy in both groups. Part of the obtained empathy-related network in PDM exhibited a similar activity compared with HC, including the right anterior insula and other regions, whereas others have an opposite activity in PDM, including the inferior frontal gyrus and right inferior parietal lobule. These results indicated an abnormal regulation to empathy in PDM. Furthermore, there was no difference in empathy association patterns in PDM between the pain and pain-free states. This study suggested that long-term pain experience may lead to an abnormal function of the brain network for empathy processing that did not vary with the pain or pain-free state across the menstrual cycle.

scholarly journals Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Shuang Liu ◽  
Jie Guo ◽  
Jiayuan Meng ◽  
Zhijun Wang ◽  
Yang Yao ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Functional Connectivity ◽  
Healthy Subjects ◽  
Brain Network ◽  
Control Group ◽  
Stroke Patients ◽  
Cerebral Disease ◽  
Essential Information ◽  
Stroke Group ◽  
The Brain

Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional connectivity in patients with acute thalamic ischemic stroke and healthy subjects. Electroencephalography (EEG) in resting condition with eyes closed was recorded for 12 stroke patients and 11 healthy subjects as control group. Lempel-Ziv complexity (LZC), Sample Entropy (SampEn), and brain network using partial directed coherence (PDC) were calculated for feature extraction. Results showed that patients had increased mean LZC and SampEn than the controls, which implied the stroke group has higher EEG complexity. For the brain network, the stroke group displayed a trend of weaker cortical connectivity, which suggests a functional impairment of information transmission in cortical connections in stroke patients. These findings suggest that nonlinear analysis and brain network could provide essential information for better understanding the brain dysfunction in the stroke and assisting monitoring or prognostication of stroke evolution.

scholarly journals Differences in working memory coding of biological motion attributed to oneself and others

2021 ◽  
Author(s):  
Mateusz Woźniak ◽  
Timo Torsten Schmidt ◽  
Yuan-hao Wu ◽  
Felix Blankenburg ◽  
Jakob Hohwy
Keyword(s):  
Working Memory ◽  
Inferior Frontal Gyrus ◽  
Body Movement ◽  
Univariate Analysis ◽  
Memory Task ◽  
Brain Network ◽  
Temporoparietal Junction ◽  
Ventral Medial Prefrontal Cortex ◽  
The Brain ◽  
Full Body

AbstractThe question how the brain distinguishes between information about oneself and the rest of the world is of fundamental interest to both philosophy and neuroscience. This question can be approached empirically by investigating how associating stimuli with oneself leads to differences in neurocognitive processing. However, little is known about the brain network involved in forming such self-associations for, specifically, bodily stimuli. In this fMRI study, we sought to distinguish the neural substrates of representing a full-body movement as one’s movement and as someone else’s movement. Participants performed a delayed match-to-sample working memory task where a retained full-body movement (displayed using point-light walkers) was arbitrarily labelled as one’s own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self-association was coded. Movement specific activation patterns was found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain-general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self-associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.

PARTICULARITIES ASSOCIATED WITH THE EXPRESSION OF GLIAL ACIDIC FIBRILLARY PROTEIN ON THE STRUCTURAL COMPONENTS OF CEREBELLUM OF THE RATS INFLUENCED BY THE FOOD ADDITIVES COMPLEX

2021 ◽  
Vol 74 (6) ◽  
pp. 1409-1413
Author(s):  
Serhii M. Bilash ◽  
Bohdan S. Kononov ◽  
Olena M. Pronina ◽  
Maryna M. Kononova ◽  
Valentina P. Bilash ◽  
...  
Keyword(s):  
Gray Matter ◽  
Food Additives ◽  
Subsequent Development ◽  
Control Group ◽  
Compensatory Mechanism ◽  
Structural Components ◽  
Complex Materials ◽  
Study Results ◽  
Astrocytic Glia ◽  
The Brain

The aim: To define the degree for glial acidic fibrillary protein expression on the structural components of cerebellum of the rats in health and when rats influenced by the food additives complex. Materials and methods: In order to determine the degree of expression of the immunohistochemical marker GFAP on the structural components of the cerebellum of rats we applied immunohistochemical, morphometric and statistical methods in our study. Results: In histological specimens at the end of 1st week of observation in the gray matter of the cerebellum there occurred a gradual increase in 1.16 times of the average number of GFAP-positive cells. At the end of 4th week of the experimental study, the average number of GFAP-positive cells increased accurately (at p<0.05 compared to the control group) in 1.27 times, at the end of 8th week it has increased in 1.99 times, at the end of 12th week in 2.25, and at the end of 16th week in 2.39 times. Conclusions: The outcomes of our study are as follows the increase in the average number of GFAP-positive cells is directly related to the decrease in the average number of major neurons of the gray matter of the brain, while the fluctuations in the average number of astrocytic glia cells represent a compensatory mechanism in the recovery of gray matter neurons of the brain from neural stem cells with the subsequent development of reactive astrogliosis and, thereafter the possible development of neuropathology.

scholarly journals PECULIARITIES OF STRUCTURAL CHANGES IN BRAIN OF PATIENTS WITH HYPERTENSION, HYPOTHYROIDISM AND DURING THE COMORBID COURSE OF THESE TWO DISEASES

2020 ◽  
Vol 20 (4) ◽  
pp. 67-71
Author(s):  
M.I. Lesiv ◽  
V.A. Hryb
Keyword(s):  
Frontal Lobe ◽  
Gray Matter ◽  
Structural Changes ◽  
Structural Parameters ◽  
Control Group ◽  
Group Iii ◽  
Average Value ◽  
Group I ◽  
Significant Difference ◽  
The Brain

This article presents the investigation of structural parameters of the brain in 67 patients aged 47.23 ± 2.64 years, whose duration of the disease was 13.27 ± 0.75 (from 2 to 19) years. The control group included 18 healthy individuals of the same age (47.84 ± 0.36 years), whose selection was carried out based on the anamnesis and the absence of hypothyroidism and hypertension. According to the data we discussed in our previous publications, during neuropsychological testing we registered memory deterioration in patients with hypertension assessed by the test for learning 10 words according to the method proposed by A.R. Luria (p <0.05), as well as serial counting by the Matisse scale (p <0.05). The patients with hypothyroidism were found as demonstrating attention deficiency (p <0.05) by applying the method of "Selectivity of attention" (G. Munsterberg test). For more detailed assessment, we used Schulte tables, the result of which demonstrates the state of the domain of the patient's executive functions and proves the instability of attention. The analysis of the results showed that taking into account the interaction between hypertension and hypothyroidism, the most affected cognitive domains were memory and attention, respectively (p <0.05). To diagnose cognitive and mnestic disorders of all groups, we used MR imaging, measured the transverse dimensions of the medial, lateral (temporal horn) and vertical perihippocampal spaces, and evaluated the volume of gray matter (cortex) of the frontal lobe of the brain in 3 zones. The measurements were performed in the right and left hemispheres. There was a significant increase in the indices of the medial and upper perihippocampal right and left in the patients in group III compared with the groups I and II. The lateral perihypocampal index did not differ significantly in the three groups (p> 0.05). Thus, taking into account the interaction of factors (hypertension and hypothyroidism), the patients were found to have an increase in perihippocampal indices (p> 0.05). Based on the data in table 2, in the patients of group I the average value of the frontal lobe was 634.06 ± 10.92. In the patients of group II, the average value of the frontal lobe was 638.6 ± 7.82, and in the patients of group III, the average value of the frontal lobe was 601.3 ± 3,325. There was no statistically significant difference between groups I and II (p = 0.05). But groups I and III demonstrated statistically significant difference between the indicators (p <0.05). We also found a statistically significant difference between groups II and III (p <0.05). Thus, in patients with hypertension, hypothyroidism and hypertension with concomitant hypothyroidism, an increase in perihippocampal indices, a decrease in the volume of gray matter (cortex) of the frontal lobe of the brain (right and left), significantly exceeded possible (involutional or otherwise). Thus, the results of the study indicate that in cases of isolated hypertension, hypothyroidism, and in the comorbidity of hypertension and hypothyroidism, there has been detected a significant acceleration of atrophic processes.

scholarly journals On the brain networks organization of individuals with high versus average fluid intelligence: a combined DTI and MEG study

2021 ◽  
Author(s):  
Silvia EP Bruzzone ◽  
Massimo Lumaca ◽  
Elvira Brattico ◽  
Peter Vuust ◽  
Morten L Kringelbach ◽  
...  
Keyword(s):  
Degree Distribution ◽  
Fluid Intelligence ◽  
Diffusion Tensor ◽  
Functional Integration ◽  
Structural Connectivity ◽  
Brain Network ◽  
Opposite Pattern ◽  
Structural Brain Network ◽  
Fast Oscillations ◽  
The Brain

The neural underpinning of human fluid intelligence (Gf) has gathered a large interest in the scientific community. Nonetheless, previous research did not provide a full understanding of such intriguing topic. Here, we studied the structural (from diffusion tensor imaging, DTI) and functional (from magnetoencephalography (MEG) resting state) connectivity in individuals with high versus average Gf scores. Our findings showed greater values in the brain areas degree distribution and higher proportion of long-range anatomical connections for high versus average Gfs. Further, the two groups presented different community structures, highlighting the structural and functional integration of the cingulate within frontal subnetworks of the brain in high Gfs. These results were consistently observed for structural connectivity and functional connectivity of delta, theta and alpha. Notably, gamma presented an opposite pattern, showing more segregation and lower degree distribution and connectivity in high versus average Gfs. Our study confirmed and expanded previous perspectives and knowledge on the small-worldness of the brain. Further, it complemented the widely investigated structural brain network of highly intelligent individuals with analyses on fast-scale functional networks in five frequency bands, highlighting key differences in the integration and segregation of information flow between slow and fast oscillations in groups with different Gf.

Functional Brain Connectivity Hyper-Network Embedded with Structural Information for Epilepsy Diagnosis

2021 ◽  
pp. 2250029
Author(s):  
Geng Zhang ◽  
Qi Zhu ◽  
Jing Yang ◽  
Ruting Xu ◽  
Zhiqiang Zhang ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Medical Image Analysis ◽  
Brain Regions ◽  
Brain Network ◽  
Brain Diseases ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Structural Brain Network ◽  
The Brain ◽  
Structural Brain

Automatic diagnosis of brain diseases based on brain connectivity network (BCN) classification is one of the hot research fields in medical image analysis. The functional brain network reflects the brain functional activities and structural brain network reflects the neural connections of the main brain regions. It is of great significance to explore and explain the inner mechanism of the brain and to understand and treat brain diseases. In this paper, based on the graph structure characteristics of brain network, the fusion model of functional brain network and structural brain network is designed to classify the diagnosis of brain mental diseases. Specifically, the main work of this paper is to use the Laplacian graph embed the information of diffusion tensor imaging, which contains the characteristics of structural brain networks, into the functional brain network with hyper-order functional connectivity information built based on functional magnetic resonance data using the sparse representation method, to obtain brain network with both functional and structural characteristics. Projection of the brain network and the two original modes data to the kernel space respectively and then classified by the multi-task learning method. Experiments on the epilepsy dataset show that our method has better performance than several state-of-the-art methods. In addition, brain regions and connections that are highly correlated with disease revealed by our method are discussed.

Plasticity in auditory categorization is supported by differential engagement of the auditory-linguistic network

2019 ◽  
Author(s):  
Gavin M. Bidelman ◽  
Breya Walker
Keyword(s):  
Inferior Frontal Gyrus ◽  
Primary Auditory Cortex ◽  
Brain Regions ◽  
Brain Network ◽  
Eeg Data ◽  
Level Information ◽  
Auditory Experience ◽  
Musical Sounds ◽  
The Brain ◽  
Information Functional

ABSTRACTTo construct our perceptual world, the brain categorizes variable sensory cues into behaviorally-relevant groupings. Categorical representations are apparent within a distributed fronto-temporo-parietal brain network but how this neural circuitry is shaped by experience remains undefined. Here, we asked whether speech (and music) categories might be formed within different auditory-linguistic brain regions depending on listeners’ auditory expertise. We recorded EEG in highly skilled (musicians) vs. novice (nonmusicians) perceivers as they rapidly categorized speech and musical sounds. Musicians showed perceptual enhancements across domains, yet source EEG data revealed a double dissociation in the neurobiological mechanisms supporting categorization between groups. Whereas musicians coded categories in primary auditory cortex (PAC), nonmusicians recruited non-auditory regions (e.g., inferior frontal gyrus, IFG) to generate category-level information. Functional connectivity confirmed nonmusicians’ increased left IFG involvement reflects stronger routing of signal from PAC directed to IFG, presumably because sensory coding is insufficient to construct categories in less experienced listeners. Our findings establish auditory experience modulates specific engagement and inter-regional communication in the auditory-linguistic network supporting CP. Whereas early canonical PAC representations are sufficient to generate categories in highly trained ears, less experienced perceivers broadcast information downstream to higher-order linguistic brain areas (IFG) to construct abstract sound labels.

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