Structure and dynamics analysis of brain functional hypernetworks based on the null models.

Brain Res Bull

College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, No.79 Yingze West Street, Taiyuan City, Shanxi Province, China. Electronic address:

Published: December 2024

Brain functional hypernetworks that can characterize the complex and multivariate interactions among multiple brain regions have been widely used in the diagnosis and prediction of brain diseases. However, there are few studies on the structure and dynamics of brain functional hypernetworks. Such studies can help to explore how the important functional features of brain functional hypernetworks characterize the working and pathological mechanisms of the human brain. Therefore, this article introduces the hypernetwork null model to analyze the dependencies between the features of interest. Specifically, first, based on the original brain functional hypernetwork, this article proposed the optimized hyper dK-series algorithm with hyperedges to construct null models that preserved the different node attributes and hyperedge attributes of the original brain functional hypernetwork, respectively. Next, based on the original hypernetwork model and the null model, multiple node attributes and hyperedge attributes were respectively introduced. Then, the level of similarity and correlation between the topological attributes of the original brain functional hypernetwork and the topological attributes of the brain functional hypernetwork null model were calculated to analyze the dependencies between the features of interest. The results showed that there were differences in the level of dependence between the features of interest. Node degree is the main dependency attribute for multiple metrics. Hyperedge degree, node degree-dependent redundancy coefficient, and hyperedge degree-dependent redundancy coefficient are partial dependency attributes for some metrics. The dependency attributes and level of dependency are the same for the hypernetwork clustering coefficients-HCC and HCC. This indicates that the node degree is redundant with respect to other attributes, while the hyperedge degree, node degree-dependent redundancy coefficient, and hyperedge degree-dependent redundancy coefficient perhaps contain other topology information. In addition, there is redundancy between HCC and HCC. Therefore, the effects of these redundant attributes need to be considered when performing network analysis.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brainresbull.2024.111177DOI Listing

Publication Analysis

Top Keywords

brain functional
32
functional hypernetworks
16
functional hypernetwork
16
degree-dependent redundancy
16
redundancy coefficient
16
null model
12
features interest
12
original brain
12
attributes hyperedge
12
brain
11

Similar Publications

Meningiomas are some of the most prevalent primary brain tumors in adults, and are typically non-neuroglial in nature. A variety of symptoms may be observed, including headaches, fluctuations in mental status, ataxia, muscle weakness, nausea and vomiting, seizures, visual changes, speech disorders, and sensory abnormalities. The World Health Organization (WHO) has a grading system for meningiomas based on histological criteria, which is as follows: Grade 1 meningiomas are considered benign; Grade 2 meningiomas have a moderately aggressive nature and usually present with histological atypia; and Grade 3 meningiomas exhibit aggressive malignant behavior.

View Article and Find Full Text PDF

Traditional deep fluorescence imaging has primarily focused on red-shifting imaging wavelengths into the near-infrared (NIR) windows or implementation of multi-photon excitation approaches. Here, we combine the advantages of NIR and multiphoton imaging by developing a dual-infrared two-photon microscope to enable high-resolution deep imaging in biological tissues. We first computationally identify that photon absorption, as opposed to scattering, is the primary contributor to signal attenuation.

View Article and Find Full Text PDF

Anxiety disorders are highly comorbid with sleep disturbance and have also been associated with deficits in emotion regulation, the ability to control and express emotions. However, the extent to which specific dimensions of sleep disturbance and emotion regulation are associated with anxiety diagnosis is not well-explored. This study examined dimensions of emotion regulation and sleep disturbance that may predict greater likelihood of anxiety diagnosis using novel machine learning techniques.

View Article and Find Full Text PDF

Background: Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity. With the continuous development of neuromodulation technology, Repetitive Transcranial Magnetic Stimulation (rTMS) has emerged as a potential non-invasive treatment for ADHD. However, there is a lack of research on the mechanism of rTMS for ADHD.

View Article and Find Full Text PDF

Humans feel visceral disgust when faced with potential contaminants like bodily effluvia. The emotion serves to reject potentially contaminated food and is paired with proto-nausea: alterations in gastric rhythm in response to disgust. Here, we offer a narrative synthesis of the existing literature on the effects of disgust on the stomach as measured through electrogastrography, a non-invasive technique that measures stomach activity with electrodes placed on the abdominal skin surface.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!