Deep brain stimulation (DBS) has been used to modulate aberrant circuits associated with Parkinson's disease (PD) for decades and has shown robust therapeutic benefits. However, the mechanism of action of DBS remains incompletely understood. With technological advances, there is an emerging use of functional magnetic resonance imaging (fMRI) after DBS implantation to explore the effects of stimulation on brain networks in PD. This systematic review was designed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to summarize peer-reviewed articles published within the past 10 years in which fMRI was employed on patients with PD-DBS. Search in PubMed database provided 353 references, and screenings resulted in a total of 19 studies for qualitative synthesis regarding study designs (fMRI scan timepoints and paradigm), methodology, and PD subtypes. This review concluded that fMRI may be used in patients with PD-DBS after proper safety test; resting-state and block-based fMRI designs have been employed to explore the effects of DBS on brain networks and the mechanism of action of the DBS, respectively. With further validation of safety use of fMRI and advances in imaging techniques, fMRI may play an increasingly important role in better understanding of the mechanism of stimulation as well as in improving clinical care to provide subject-specific neuromodulation treatments.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8984293 | PMC |
| http://dx.doi.org/10.3389/fneur.2022.849918 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Deep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach.
Sci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFPhysical unclonable in-memory computing for simultaneous protecting private data and deep learning models.
Nat Commun
January 2025
Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, China.
Compute-in-memory based on resistive random-access memory has emerged as a promising technology for accelerating neural networks on edge devices. It can reduce frequent data transfers and improve energy efficiency. However, the nonvolatile nature of resistive memory raises concerns that stored weights can be easily extracted during computation.
View Article and Find Full Text PDFA Joint three-plane Physics-constrained Deep learning based Polynomial Fitting Approach for MR Electrical Properties Tomography.
Neuroimage
January 2025
Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea. Electronic address:
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact.
View Article and Find Full Text PDFDynamic cycles between brain states during creative storytelling.
Neuroimage
January 2025
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern, Institute for Brain Research, Beijing Normal University, Beijing 100875, PR China. Electronic address:
Many theories suggest that creative thinking involves a dynamic transition between different mental states, yet empirical evidence supporting this notion remains scarce. The dual process model proposes that spontaneous thinking and deliberate thinking drive the dwell in and the transitions between different mental states during creative thinking, but there is a debate over whether the two types of thinking operate in parallel or in sequence. To address these gaps, we conducted a functional magnetic resonance imaging (fMRI) study in 41 college students during a creative storytelling task.
View Article and Find Full Text PDFImmersive exposure to simulated visual hallucinations modulates high-level human cognition.
Conscious Cogn
January 2025
Humane Technology Lab, Catholic University of Sacred Heart, Milan, Italy; Applied Technology for Neuro-Psychology Lab., Istituto Auxologico Italiano IRCCS, Milan, Italy. Electronic address:
Psychedelic drugs offer valuable insights into consciousness, but disentangling their causal effects on perceptual and high-level cognition is nontrivial. Technological advances in virtual reality (VR) and machine learning have enabled the immersive simulation of visual hallucinations. However, comprehensive experimental data on how these simulated hallucinations affects high-level human cognition is lacking.
View Article and Find Full Text PDFWant 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!