Objective: A network of cortical, subcortical and brainstem structures might be involved in freezing of gait (FOG). Subthalamic nucleus (STN) deep brain stimulation (DBS) could modulate this network. The audio-spinal reflex (ASR), reduced in PD, but increased by treatment, can be used to further investigate that locomotor network. The aim of this study is to find whether a correlation exists between ASR and FOG in PD patients under DBS.
Methods: In 14 PD patients with STN DBS and previous FOG, ASR was recorded, with DBS switched on and off. We also assessed FOG Questionnaire (FOGQ) and Unified Parkinson's Disease Rating Scale (UPDRS) Part III.
Results: Switching "on" DBS increased ASR amplitude (+ 33.2% with DBS ON, p = 0.048). We also found a significant inverse correlation between FOGQ and modulation of ASR by DBS (r = -0.59, r = 0.35, p < 0.05).
Conclusions: This study shows that the incremental effect of DBS on ASR is greater in PD patients with less severe FOG.
Significance: This study shows a link between electrophysiological and clinical data about gait control. It might contribute to better understand why some DBS patients report heavy FOG and others do not. ASR might be used to evaluate or maybe predict the effect of stimulation parameters changes on FOG.
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http://dx.doi.org/10.1016/j.clinph.2018.07.006 | DOI Listing |
Neurosurg Rev
January 2025
Department of Neurosurgery, Hospital Universitario Fundación Jiménez Díaz, Av. De los Reyes Católicos, 2, Madrid, 28040, Spain.
Matched-controlled long-term disease evaluation and neuropsychological outcomes derived from deep brain stimulation of the subthalamic nucleus (STN-DBS) in Parkinson´s disease (PD) are lacking, with inconsistent results regarding the cognitive impact of this procedure. Here we study the long-term effects associated to DBS comparing outcomes with a matched control group. A prospective observational study of 40 patients with PD with bilateral STN-DBS, with a mean follow-up of 9 (6-12) years was conducted.
View Article and Find Full Text PDFAnimal Model Exp Med
January 2025
School of Psychological and Cognitive Sciences, IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
Background: Quantifying the rich home-cage activities of tree shrews provides a reliable basis for understanding their daily routines and building disease models. However, due to the lack of effective behavioral methods, most efforts on tree shrew behavior are limited to simple measures, resulting in the loss of much behavioral information.
Methods: To address this issue, we present a deep learning (DL) approach to achieve markerless pose estimation and recognize multiple spontaneous behaviors of tree shrews, including drinking, eating, resting, and staying in the dark house, etc.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
Background And Aims: The lack of therapeutic response characterizes treatment-resistant depression despite undergoing at least two adequate monotherapy trials with medications from distinct pharmacologic classes. The inability to attain remission in patients diagnosed with major depressive disorder (MDD) is a significant issue of concern within public health. Therefore, the management of treatment-resistant depression (TRD) poses significant obstacles for both patients and healthcare professionals.
View Article and Find Full Text PDFFront Aging Neurosci
January 2025
Department of Radiology, Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Background: White matter hyperintensity (WMH) and brain atrophy, as imaging marker of cerebral small-vessel diseases (CSVD), have a high prevalence and strong prognostic value in stroke. We aimed to explore the association between lymphocyte count, a maker of inflammation, and WMH and brain atrophy in patients with acute ischemic stroke (AIS).
Methods: A total of 727 AIS patients with lymphocyte count and brain magnetic resonance imaging data were enrolled.
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