Neurophysiologie Clinique/Clinical Neurophysiology最新文献

Objective

MScanFit motor unit number estimation (MUNE) is a sensitive method for detecting motor unit loss and has demonstrated high reproducibility in various settings. In this study, our aim was to assess the outputs of this method when the nerve conduction distance is increased.

Methods

MScanFit recordings were obtained from the abductor digiti minimi muscle of 20 healthy volunteers. To evaluate the effect of nerve conduction distance, the ulnar nerve was stimulated from the wrist and elbow respectively. Reproducibility of MUNE, compound muscle action potential (CMAP), and other motor unit parameters were assessed using intraclass correlation coefficients (ICCs).

Results

Motor unit numbers obtained from stimulation at the wrist and elbow did not significantly differ and exhibited strong consistency in the ICC test (120.3 ± 23.7 vs. 118.5 ± 27.9, p > 0.05, ICC: 0.88). Similar repeatability values were noted for other parameters. However, the Largest Unit (%) displayed notable variability between the two regions and exhibited a negative correlation with nerve conduction distance.

Conclusion

Our findings indicate that MScanFit can consistently calculate motor unit numbers and most of its outputs without substantial influence from nerve conduction distance. Exploring MScanFit's capabilities in various settings could enhance our understanding of its strengths and limitations for extensive use in clinical practice.

Objective

This study aimed to explore the relationships between potential neurophysiological biomarkers and upper limb motor function recovery in stroke patients, specifically focusing on combining two neurophysiological markers: electroencephalography (EEG) and transcranial magnetic stimulation (TMS).

Methods

This cross-sectional study analyzed neurophysiological, clinical, and demographical data from 102 stroke patients from the DEFINE cohort. We searched for correlations of EEG and TMS measurements combined to build a prediction model for upper limb motor functionality, assessed by five outcomes, across five assessments: Fugl-Meyer Assessment (FMA), Handgrip Strength Test (HST), Finger Tapping Test (FTT), Nine-Hole Peg Test (9HPT), and Pinch Strength Test (PST).

Results

Our multivariate models agreed on a specific neural signature: higher EEG Theta/Alpha ratio in the frontal region of the lesioned hemisphere is associated with poorer motor outcomes, while increased MEP amplitude in the non-lesioned hemisphere correlates with improved motor function. These relationships are held across all five motor assessments, suggesting the potential of these neurophysiological measures as recovery biomarkers.

Conclusion

Our findings indicate a potential neural signature of brain compensation in which lower frequencies of EEG power are increased in the lesioned hemisphere, and lower corticospinal excitability is also increased in the non-lesioned hemisphere. We discuss the meaning of these findings in the context of motor recovery in stroke.

This study aimed to compare the diagnostic performance of visual assessment of electroencephalography (EEG) using the Grand Total EEG (GTE) score and quantitative EEG (QEEG) using spectral analysis in the context of cognitive impairment.

This was a retrospective study of patients with mild cognitive impairment, with (MCI+V) or without (MCI) vascular dysfunction, and patients with dementia including Alzheimer's disease, Lewy Body Dementia and vascular dementia.

The results showed that the GTE is a simple scoring system with some potential applications, but limited ability to distinguish between dementia subtypes, while spectral analysis appeared to be a powerful tool, but its clinical development requires the use of artificial intelligence tools.

Objective

The objective of this study was to develop artificial intelligence-based deep learning models and assess their potential utility and accuracy in diagnosing and predicting the future occurrence of diabetic distal sensorimotor polyneuropathy (DSPN) among individuals with type 2 diabetes mellitus (T2DM) and prediabetes.

Methods

In 394 patients (T2DM=300, Prediabetes=94), we developed a DSPN diagnostic and predictive model using Random Forest (RF)-based variable selection techniques, specifically incorporating the combined capabilities of the Clinical Toronto Neuropathy Score (TCNS) and nerve conduction study (NCS) to identify relevant variables. These important variables were then integrated into a deep learning framework comprising Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. To evaluate temporal predictive efficacy, patients were assessed at enrollment and one-year follow-up.

Results

RF-based variable selection identified key factors for diagnosing DSPN. Numbness scores, sensory test results (vibration), reflexes (knee, ankle), sural nerve attributes (sensory nerve action potential [SNAP] amplitude, nerve conduction velocity [NCV], latency), and peroneal/tibial motor NCV were candidate variables at baseline and over one year. Tibial compound motor action potential amplitudes were used for initial diagnosis, and ulnar SNAP amplitude for subsequent diagnoses. CNNs and LSTMs achieved impressive AUC values of 0.98 for DSPN diagnosis prediction, and 0.93 and 0.89 respectively for predicting the future occurrence of DSPN. RF techniques combined with two deep learning algorithms exhibited outstanding performance in diagnosing and predicting the future occurrence of DSPN. These algorithms have the potential to serve as surrogate measures, aiding clinicians in accurate diagnosis and future prediction of DSPN.

Botulinum neurotoxin serotype A (BoNT-A) has several therapeutic indications such as spasticity and dystonia. Although its use is generally considered safe, a systemic diffusion can lead to systemic complications, and a botulism-like syndrome can occur after intramuscular injections. Herein, two adult cases who developed general muscle weakness after a BoNT-A intramuscular injection are reported. Both presented with a progressive decrement on low-frequency (LF) repetitive nerve stimulation (RNS). It is suggested that a progressive decrement on LF-RNS in muscles distant from the injection site strongly supports the diagnosis of iatrogenic botulism.

Objectives

To evaluate the evolution of interhemispheric coherences (ICo) in background and spindle frequency bands during childhood and use it to identify individuals with corpus callosum dysgenesis (CCd).

Methods

A monocentric cohort of children aged from 0.25 to 15 years old, consisting of 13 children with CCd and 164 without, was analyzed. The ICo of background activity (ICO_BckgrdA), sleep spindles (ICO_spindles), and their sum (_sICO) were calculated. The impact of age, gender, and CC status on the ICo was evaluated, and the _sICO was used to discriminate children with or without CCd.

Results

ICO_BckgrdA, ICO_spindles and sICO increased significantly with age without any effect of gender (p < 10⁻⁴), in both groups. The regression equations of the different ICo were stronger, with adjusted R2 values of 0.54, 0.35, and 0.57, respectively. The ICo was lower in children with CCd compared to those without CCd (p < 10⁻⁴ for all comparisons). The area under the precision recall curves for predicting CCd using _sICO was 0.992 with 98.9 % sensitivity and 87.5 % specificity.

Discussion

ICo of spindles and background activity evolve in parallel to brain maturation and depends on the integrity of the corpus callosum. sICO could be an effective diagnostic biomarker for screening children with interhemispheric dysfunction.

Objectives

The primary goal of the current proposal is to fill the gaps in the literature by studying the effectiveness of transcranial direct current stimulation (tDCS) on lifestyle parameters, and physical, behavioral, and cognitive functions among stroke survivors, and understanding the factors that mediate the effects of various domains related to Health-related Quality of life (HRQoL) improvements.

Methods

Anticipated 64 volunteer subacute stroke survivors (>7 days to 3 months post stroke) aged 40–75 years with National Institutes of Health stroke scale (NIHSS) score of >10 and Mini-Mental State Examination (MMSE) score between 18 and 23 will be randomly assigned at a ratio of 1:1 to receive either: (1) 20 sessions of anodal tDCS or (2) sham tDCS in addition to conventional rehabilitation. Battery driven tDCS will be applied at 2 mA intensity to the dorsolateral prefrontal cortex and primary motor cortex for 20 minutes. The primary endpoints of study will be 36-Item Short Form Survey (SF-36) post intervention at 4 weeks. The secondary outcomes will include Stroke Specific Quality of Life Scale (SS_QOL), Montreal cognitive assessment (MCA), Beck Anxiety Inventory (BAI), Fugl-Meyer Assessment (FMA), 10 m walk test and Modified Barthel Activities of daily living (ADL) Index. At 0.05 level of significance, data normality, within group and between group actual differences will be analyzed with a moderate scope software.

Discussion

Our knowledge of this technique and its use is expanding daily as tDCS motor recovery studies—mostly single-center studies—in either single session or many sessions have been completed and shown positive results. The field is prepared for a multi-center, carefully planned, sham-controlled, double-blinded tDCS study to comprehensively examine its feasibility and effectiveness in enhancing outcomes in stroke population.

Conclusion

The function of Transcranial Direct Current Stimulation in aiding stroke recuperation will be ascertained.