Published: Jan. 1, 2024
I am truly thankful for the invaluable opportunity to be a part of your hospitals few
Language: Английский
Revue Neurologique, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 1, 2024
Language: Английский
Citations
6
Journal of Neurology Neurosurgery & Psychiatry, Journal Year: 2023, Volume and Issue: unknown, P. jnnp - 332069
Published: Oct. 5, 2023
Background Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis rarely causes visible lesions in conventional MRI, yet advanced imaging detects extensive white matter damage. To improve prognostic capabilities, we evaluate the T1-weighted/T2-weighted (T1w/T2w) ratio, a measure of integrity computable from clinical MRI sequences, NMDAR and examine its associations with cognitive impairment. Methods T1-weighted T2-weighted were acquired cross-sectionally at 3 Tesla 53 patients (81% women, mean age 29 years) matched healthy controls. Quantitative voxel-wise group differences T1w/T2w ratios neuropsychological outcomes assessed. P-values false discovery rate (FDR) adjusted where multiple tests conducted. Results Patients had significantly lower across normal appearing (p=0.009, Hedges’ g=−0.51), which was associated worse verbal episodic memory performance (r=0.39, p=0.005, p(FDR)=0.026). White loss observed corticospinal tract, superior longitudinal fascicle, optic radiation callosal body medium to large effects (Cohen’s d=[0.42–1.17]). In addition, showed decreased hippocampus (p=0.002, p(FDR)=0.005, g=−0.62), amygdala g=−0.63) thalamus (p=0.010, p(FDR)=0.019, g=−0.51). Conclusions The ratio microstructural changes grey that correlate performance. Computable this shows promise bridging clinico-radiological dissociation could serve as an outcome trials.
Language: Английский
Citations
4
Journal of Neurology, Journal Year: 2024, Volume and Issue: 271(9), P. 5886 - 5898
Published: July 8, 2024
Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization global local changes their relationship clinical deficits in NMDAR encephalitis.
Language: Английский
Citations
1
Brain Imaging and Behavior, Journal Year: 2024, Volume and Issue: 18(3), P. 686 - 697
Published: Feb. 16, 2024
Language: Английский
Citations
1
Biological Psychiatry Cognitive Neuroscience and Neuroimaging, Journal Year: 2024, Volume and Issue: 9(11), P. 1222 - 1229
Published: July 27, 2024
Anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) causes long-lasting cognitive deficits associated with altered functional connectivity. Eigenvector centrality (EC) mapping represents a powerful new method for data-driven voxel-wise and time-resolved estimation of network importance – beyond changes in classical 'static' To assess brain organization, we applied EC 73 patients NMDARE matched healthy controls. Areas significant group differences were further investigated using (i) spatial clustering analyses, (ii) time series correlation to synchronicity between the hippocampus cortical regions, (iii) clinical parameters. Dynamic, showed significantly higher variability 13 areas (p(FWE)<0.05) compared HC. dynamic spatially organized clusters resembling resting-state networks. Importantly, frontotemporal cluster was impaired verbal episodic memory (r=-0.25, p=0.037). medial prefrontal cortex reduced HC (p(FWE)<0.05, t(max)=3.76), (r=0.28, p=0.019). Static analyses only one region (left intracalcarine cortex). Widespread dynamics hippocampal-medial may thus represent neural correlate dysfunction NMDARE. detected substantially more alterations than traditional static approaches, highlighting potential this explain long-term
Language: Английский
Citations
1
NeuroImage, Journal Year: 2023, Volume and Issue: 280, P. 120332 - 120332
Published: Aug. 23, 2023
The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter analyse neural signals in specific frequency ranges, known as "canonical" bands. However, this segmentation, is not exempt from limitations, mainly due to the lack adaptation idiosyncrasies each individual. In study, we introduce a new data-driven method automatically identify ranges based on topological similarity frequency-dependent functional network. resting-state activity 195 cognitively healthy subjects three different databases (MEG: 123 subjects; EEG1: 27 EEG2: 45 subjects) was analysed. first step, MEG EEG were filtered with narrow-band bank (1 Hz bandwidth) 1 70 0.5 step. Next, connectivity these estimated using orthogonalized version amplitude envelope correlation obtain Finally, community detection algorithm used communities domain showing similar network topology. We have called approach "Connectivity-based Meta-Bands" (CMB) algorithm. Additionally, two types synthetic configure hyper-parameters CMB observed that classical approaches band segmentation are partially aligned underlying topologies at group level for signals, but they missing individual may be biasing previous studies, revealed by our methodology. On other hand, sensitivity reflect structure limited, revealing simpler parcellation, defined To best knowledge, study proposes an unsupervised across frequencies. This methodology fully accounts subject-specific patterns, providing more robust personalized analyses, paving way focused exploring brain connectivity.
Language: Английский
Citations
3
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown
Published: Aug. 21, 2023
Abstract Introduction Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization global local changes their relationship clinical deficits in NMDAR encephalitis. Objective To investigate connectivity efficiency use probabilistic whole-brain tractography graph theoretical networks. Methods networks from sixty-one patients post-acute stage (median time acute hospital discharge: 18 months) age- sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based anatomically-constrained spherical deconvolution-informed filtering tractograms. We calculated global, modular, nodal measures indicative reorganization special focus on default-mode network, lobe, Pathologically altered metrics included multiple regression analyses to potential association course, disease severity, cognitive outcome. Results Patients showed regular metrics, but bilateral reductions hippocampal node strength (left: p =0.049; right: =0.013) increased right precuneus ( compared HC. Betweenness centrality was decreased left-sided entorhinal cortex =0.042) left caudal middle frontal gyrus (p = 0.037). Correlation a significant between reduced verbal long-term memory impairment =0.021) Conclusion Focal property indicate hub failure that associated at stage, while remain unaltered. Graph theory provides new pathophysiological insight into persistent
Language: Английский
Citations
2
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown
Published: April 2, 2023
Abstract The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter analyse neural signals in specific frequency ranges, known as “canonical” bands. However, this segmentation, is not exempt from limitations, mainly due to the lack adaptation idiosyncrasies each individual. In study, we introduce a new data-driven method automatically identify ranges based on topological similarity frequency-dependent functional network. resting-state activity 195 cognitively healthy subjects three different databases (MEG: 123 subjects; EEG 1 : 27 2 45 subjects) was analysed. first step, MEG were filtered with narrow-band bank (1 Hz bandwidth) 70 0.5 step. Next, connectivity these estimated using orthogonalized version amplitude envelope correlation obtain Finally, community detection algorithm used communities domain showing similar network topology. We have called approach “Connectivity-based Meta-Bands” (CMB) algorithm. Additionally, two types synthetic configure hyper-parameters CMB observed that classical approaches band segmentation reflect underlying topologies at group level for signals, but they fail adapt individual differentiating patterns revealed by our methodology. On other hand, sensitivity structure limited. To best knowledge, study proposes an unsupervised across frequencies. This methodology fully accounts subject-specific patterns, providing more robust personalized analyses, paving way focused exploring brain connectivity.
Language: Английский
Citations
1
Published: Jan. 1, 2024
I am truly thankful for the invaluable opportunity to be a part of your hospitals few
Language: Английский
Citations
0