Deep brain stimulation (DBS) has revolutionized the treatment of movement disorders, including Parkinson's disease (PD), essential tremors, dystonia, and treatment-refractory obsessive-compulsive disorder (OCD). This systematic review and meta-analysis aimed to assess the impact of DBS on Body Mass Index (BMI). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, data from 49 studies were reviewed, with 46 studies specifically focusing on BMI and DBS. These studies involved 1,478 participants, predominantly PD patients, with an average age of 58.82 years. The primary DBS implantation site was the subthalamic nucleus (STN). Over six months, the mean BMI increased from 25.69 to 27.41, despite a reduction in daily energy intake from 1992 to 1873 kJ. While the findings suggest a correlation between DBS and weight gain, the study has limitations. The sample largely comprised PD patients (91%), preventing analysis of other subtypes. Additionally, most studies focused on the STN, limiting comparisons with other targets like the globus pallidus internus (GPi). Inconsistencies in assessing daily energy intake and food consumption further complicate the results. Integrating artificial intelligence (AI) in future research could address these gaps. For example, machine learning algorithms, such as those used by Oliveira et al., can predict post-DBS weight changes based on pre-surgical BMI and demographic factors. Similarly, AI-driven models like CLOVER-DBS can optimize DBS settings for improved motor control in PD patients. In conclusion, DBS affects BMI, and AI has the potential to enhance the precision of future studies.
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http://dx.doi.org/10.1007/s10143-024-03041-4 | DOI Listing |
Biosens Bioelectron
December 2024
2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China; School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address:
Anti-seizure medications and deep brain stimulation are widely used therapies to treat seizures; however, both face limitations such as resistance and the unpredictable nature of seizures. Recent advancements, including responsive neural stimulation and on-demand drug release, have been developed to address these challenges. However, a gap remains, as electrical stimulation provides only transient effects while medication has a delayed onset.
View Article and Find Full Text PDFMagn Reson Imaging
December 2024
Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China. Electronic address:
Purpose: To explore the feasibility of Deep learning radiomics nomograms (DLRN) in predicting IDH genotype.
Methods: A total of 402 glioma patients from two independent centers were retrospectively included, and the data from center I was randomly divided into a training cohort (n = 239) and an internal validation cohort (n = 103) on a 7:3 basis. Center II served as an independent external validation cohort (n = 60).
STAR Protoc
December 2024
IGF, CNRS, 34090 Montpellier, France. Electronic address:
Calcium (Ca) imaging is a viable approach for imaging neuronal activity patterns in local brain circuits in living animals. Here, we present a protocol for gradient lens implantation in deep brain structures followed by in vivo Ca imaging. We describe in detail the steps for surgery preparation, followed by lens implantation, setup for awake head-fixed imaging, and the recording process.
View Article and Find Full Text PDFPsychol Res
December 2024
Department of Experimental Psychology, University of Oxford, Oxford, UK.
What are emotions? Despite being a century-old question, emotion scientists have yet to agree on what emotions exactly are. Emotions are diversely conceptualised as innate responses (evolutionary view), mental constructs (constructivist view), cognitive evaluations (appraisal view), or self-organising states (dynamical systems view). This enduring fragmentation likely stems from the limitations of traditional research methods, which often adopt narrow methodological approaches.
View Article and Find Full Text PDFCereb Cortex
December 2024
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
Electroencephalogram (EEG) brain networks describe the driving and synchronous relationships among multiple brain regions and can be used to identify different emotional states. However, methods for extracting interpretable structural features from brain networks are still lacking. In the current study, a novel deep learning structure comprising both an attention mechanism and a domain adversarial strategy is proposed to extract discriminant and interpretable features from brain networks.
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