Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.7
2.2
Journals
Tomography
Special Issues
New Insights into Functional Magnetic Resonance Imaging (fMRI)
share announcement

New Insights into Functional Magnetic Resonance Imaging (fMRI)

A special issue of Tomography (ISSN 2379-139X).

Deadline for manuscript submissions: closed (24 October 2024) | Viewed by 2821

Special Issue Editor

Dr. Xingfeng Li

E-Mail Website
Guest Editor
Department of Surgery and Cancer, Imperial College London, London SW7 2AZ, UK
Interests: fMRI; image analysis; statistical analysis; cancer; brain

Special Issue Information

Dear Colleagues,

Since the breakthrough of functional magnetic resonance imaging (fMRI) in the late 1980s, it has been applied in countless fields for scientific studies, including (but not limited to) brain encoding and decoding. In brain encoding studies, fMRI has been implemented for brain activation detection, connectivity, and adaptation studies. These methods have been applied in clinical, psychological, and cognitive studies and have led to revolutionary findings that help to explain the normal brain and the brain that is affected by various diseases. However, brain decoding or mind-reading techniques make up a relatively new research area, and algorithms have been designed to read people's thoughts from the brain. Based on fMRI and statistical methods, it is possible to read the mind if there are enough training datasets. This Special Issue aims to present the current findings dedicated to fMRI methods and their application to a wide range of scientific research topics in both clinical and psychological studies. It can be a new method for fMRI studies, and it can also be a new application of fMRI in basic scientific research fields. Our goal is for these works to contribute to the exchange of knowledge and ideas resulting in discoveries in multidisciplinary subjects using fMRI.

Dr. Xingfeng Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Tomography is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fMRI
  • statistical analysis
  • image analysis
  • brain
  • radiology
  • MRI
  • cognitive
  • neuroscience

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

13 pages, 4825 KiB  
Article
Identifying Brain Network Structure for an fMRI Effective Connectivity Study Using the Least Absolute Shrinkage and Selection Operator (LASSO) Method
by Xingfeng Li and Yuan Zhang
Tomography 2024, 10(10), 1564-1576; https://doi.org/10.3390/tomography10100115 - 30 Sep 2024
Viewed by 860
Abstract
Background: Studying causality relationships between different brain regions using the fMRI method has attracted great attention. To investigate causality relationships between different brain regions, we need to identify both the brain network structure and the influence magnitude. Most current methods concentrate on magnitude [...] Read more.
Background: Studying causality relationships between different brain regions using the fMRI method has attracted great attention. To investigate causality relationships between different brain regions, we need to identify both the brain network structure and the influence magnitude. Most current methods concentrate on magnitude estimation, but not on identifying the connection or structure of the network. To address this problem, we proposed a nonlinear system identification method, in which a polynomial kernel was adopted to approximate the relation between the system inputs and outputs. However, this method has an overfitting problem for modelling the input–output relation if we apply the method to model the brain network directly. Methods: To overcome this limitation, this study applied the least absolute shrinkage and selection operator (LASSO) model selection method to identify both brain region networks and the connection strength (system coefficients). From these coefficients, the causality influence is derived from the identified structure. The method was verified based on the human visual cortex with phase-encoded designs. The functional data were pre-processed with motion correction. The visual cortex brain regions were defined based on a retinotopic mapping method. An eight-connection visual system network was adopted to validate the method. The proposed method was able to identify both the connected visual networks and associated coefficients from the LASSO model selection. Results: The result showed that this method can be applied to identify both network structures and associated causalities between different brain regions. Conclusions: System identification with LASSO model selection algorithm is a powerful approach for fMRI effective connectivity study. Full article
(This article belongs to the Special Issue New Insights into Functional Magnetic Resonance Imaging (fMRI))
►▼ Show Figures

Figure 1

13 pages, 1349 KiB  
Article
Application of Diffusion Kurtosis Imaging and Blood Oxygen Level-Dependent Magnetic Resonance Imaging in Kidney Injury Associated with ANCA-Associated Vasculitis
by Wenhui Yu, Weijie Yan, Jing Yi, Lu Cheng, Peiyi Luo, Jiayu Sun, Shenju Gou and Ping Fu
Tomography 2024, 10(7), 970-982; https://doi.org/10.3390/tomography10070073 - 25 Jun 2024
Viewed by 1092
Abstract
Objective: Functional magnetic resonance imaging (fMRI) has been applied to assess the microstructure of the kidney. However, it is not clear whether fMRI could be used in the field of kidney injury in patients with Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Methods: This [...] Read more.
Objective: Functional magnetic resonance imaging (fMRI) has been applied to assess the microstructure of the kidney. However, it is not clear whether fMRI could be used in the field of kidney injury in patients with Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Methods: This study included 20 patients with AAV. Diffusion kurtosis imaging (DKI) and blood oxygen level-dependent (BOLD) scanning of the kidneys were performed in AAV patients and healthy controls. The mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) parameters of DKI, the R2* parameter of BOLD, and clinical data were further analyzed. Results: In AAV patients, the cortex exhibited lower MD but higher R2* values compared to the healthy controls. Medullary MK values were elevated in AAV patients. Renal medullary MK values showed a positive correlation with serum creatinine levels and negative correlations with hemoglobin levels and estimated glomerular filtration rate. To assess renal injury in AAV patients, AUC values for MK, MD, FA, and R2* in the cortex were 0.66, 0.67, 0.57, and 0.55, respectively, and those in the medulla were 0.81, 0.77, 0.61, and 0.53, respectively. Conclusions: Significant differences in DKI and BOLD MRI parameters were observed between AAV patients with kidney injuries and the healthy controls. The medullary MK value in DKI may be a noninvasive marker for assessing the severity of kidney injury in AAV patients. Full article
(This article belongs to the Special Issue New Insights into Functional Magnetic Resonance Imaging (fMRI))
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop