Assessment of Electrical Brain Activity of Healthy Volunteers Exposed to 3.5 GHz of 5G Signals within Environmental Levels: A Controlled-Randomised Study.

Following the recent deployment of fifth-generation (5G) radio frequencies, several questions about their health impacts have been raised. Due to the lack of experimental research on this subject, the current study aimed to investigate the bio-physiological effects of a generated 3.5 GHz frequency. For this purpose, the wake electroencephalograms (EEG) of 34 healthy volunteers were explored during two "real" and "sham" exposure sessions. The electromagnetic fields were antenna-emitted in an electrically shielded room and had an electrical field root-mean-square intensity of 2 V/m, corresponding to the current outdoor exposure levels. The sessions were a maximum of one week apart, and both contained an exposure period of approximately 26 min and were followed by a post-exposure period of 17 min. The power spectral densities (PSDs) of the beta, alpha, theta, and delta bands were then computed and corrected based on an EEG baseline period. This was acquired for 17 min before the subsequent phases were recorded under two separate conditions: eyes open (EO) and eyes closed (EC). A statistical analysis showed an overall non-significant change in the studied brain waves, except for a few electrodes in the alpha, theta, and delta spectra. This change was translated into an increase or decrease in the PSDs, in response to the EO and EC conditions. In conclusion, this studhy showed that 3.5 GHz exposure, within the regulatory levels and exposure parameters used in this protocol, did not affect brain activity in healthy young adults. Moreover, to our knowledge, this was the first laboratory-controlled human EEG study on 5G effects. It attempted to address society's current concern about the impact of 5G exposure on human health at environmental levels.

Brain dysfunction in gait disorders of Caribbean atypical Parkinsonism and progressive supranuclear palsy patients: A comparative study.

INTRODUCTION: Gait disorders and falls occur early in progressive supranuclear palsy (PSP-RS) and Caribbean atypical parkinsonism (Caribbean AP). However, the link between these signs and brain lesions has never been explored in these patient populations. Here, we investigate and compare the imaging factors that relate to gait and balance disorders in Caribbean AP and PSP-RS patients. METHODS: We assessed gait and balance using clinical scales and gait recordings in 16 Caribbean AP and 15 PSP-RS patients and 17 age-matched controls. We measured the grey and white matter brain volumes on 3 T brain MRI images. We performed a principal component analysis (PCA) including all the data to determine differences and similarities between groups, and explore the relationship between gait disorders and brain volumes. RESULTS: Both Caribbean AP patients and PSP-RS have marked gait and balance disorders with similar severity. In both groups, gait and balance disorders were found to be most strongly related to structural changes in the lateral cerebellum, caudate nucleus, and fronto-parietal areas. In Caribbean AP patients, gait disorders were also related to additional changes in the cortex, including frontal, insular, temporal and cuneus lobes, whereas in PSP-RS patients, additional white matter changes involved the mesencephalon and parahippocampal gyrus. CONCLUSION: Gait and balance disorders in Caribbean AP patients are mainly related to dysfunction of cortical brain areas involved in visuo-sensorimotor processing and self-awareness, whereas these signs mainly result from premotor-brainstem-cerebellar network dysfunction in PSP-RS patients, brain areas involved in initiation and maintenance of locomotor pattern and postural adaptation.

Theta band brainwaves in human resting EEG modulated by mobile phone radiofrequency.

PURPOSE: Wireless communication has become an integral part of our lives. The growing number of antennas in our environment and the expanding use of mobile phones (MPs) are increasing the population's exposure to electromagnetic fields. The present study aimed to examine the potential impact of MPs radiofrequency electromagnetic fields (RF-EMF) exposure on the brainwaves of the resting electroencephalogram (EEG) in humans. MATERIALS AND METHODS: Twenty-one healthy volunteers were exposed to Global System for Mobile communications (GSM) signal at 900 MHz MP RF-EMF. The maximum specific absorption rate (SAR) of the MP averaged on 10 g tissue and 1 g tissue were measured at 0.49 W/kg, 0.70 W/kg, respectively. RESULTS: Results showed that while delta and beta rhythms of resting EEG were not affected, theta brainwaves were significantly modulated during exposure to RF-EMF related to MPs. For the first time, it was shown that this modulation is dependent on the eye condition, i.e. closed or open. CONCLUSIONS: This study strongly suggests that acute exposure to RF-EMF alters the EEG theta rhythm at rest. Long-term exposure studies are required to explore the effect of this disruption in high-risk or sensitive populations.

Longitudinal Monitoring of Microstructural Alterations in Cerebral Ischemia with in Vivo Diffusion-weighted MR Spectroscopy.

Background The time course of cellular damage after acute ischemic stroke (IS) is currently not well known, and specific noninvasive markers of microstructural alterations linked to inflammation are lacking, which hinders the monitoring of anti-inflammatory treatment. Purpose To evaluate the temporal pattern of neuronal and glial microstructural changes after stroke using in vivo single-voxel diffusion-weighted MR spectroscopy. Materials and Methods In this prospective longitudinal study, participants with IS and healthy volunteers (HVs) underwent MRI at 3.0 T. In participants with IS, apparent diffusion coefficients (ADCs) and concentrations of total N-acetyl-aspartate (tNAA), total creatine (tCr), and total choline (tCho) were measured in volumes of interest (VOIs), including the lesion VOI (VOIles) and the contralateral VOI (VOIcl) at 2 weeks, 1 month, and 3 months after IS. HVs were examined once, with VOIs located in the same brain regions as participants with IS. Within- and between-group differences and longitudinal changes were examined using linear mixed-effects models. Results Twenty participants with IS (mean age, 61 years ± 13 [SD]; 12 women) and 20 HVs (mean age, 59 years ± 13; 12 women) were evaluated. No differences in ADCs or concentrations were observed in VOIcl between HVs and participants with IS. In participants with IS, the ADC of tCr was higher in VOIles than in VOIcl at 1 month (+14.4%, P = .004) and 3 months after IS (+19.0%, P < .001), while the ADC of tCho was higher only at 1 month (+16.7%, P = .001). No difference in the ADC of tNAA was observed between the two VOIs at any time point. tNAA and tCr concentrations were lower in VOIles than in VOIcl and were stable over time (approximately -50% and -30%, respectively; P < .001). Conclusion High diffusivity of choline-containing compounds and total creatine (tCr) in the ischemic lesion 1 month after ischemic stroke (IS) indicates glial morphologic changes, suggesting that active inflammation is still ongoing at this time point. High tCr diffusivity up to 3 months after IS likely reflects the presence of astrogliosis at the chronic stage of cerebral ischemia. Clinical trial registration no. NCT02833961 © RSNA, 2022 Online supplemental material is available for this article.

The cost of attentional reorienting on conscious visual perception: an MEG study.

How do attentional networks influence conscious perception? To answer this question, we used magnetoencephalography in human participants and assessed the effects of spatially nonpredictive or predictive supra-threshold peripheral cues on the conscious perception of near-threshold Gabors. Three main results emerged. (i) As compared with invalid cues, both nonpredictive and predictive valid cues increased conscious detection. Yet, only predictive cues shifted the response criterion toward a more liberal decision (i.e. willingness to report the presence of a target under conditions of greater perceptual uncertainty) and affected target contrast leading to 50% detections. (ii) Conscious perception following valid predictive cues was associated to enhanced activity in frontoparietal networks. These responses were lateralized to the left hemisphere during attentional orienting and to the right hemisphere during target processing. The involvement of frontoparietal networks occurred earlier in valid than in invalid trials, a possible neural marker of the cost of re-orienting attention. (iii) When detected targets were preceded by invalid predictive cues, and thus reorienting to the target was required, neural responses occurred in left hemisphere temporo-occipital regions during attentional orienting, and in right hemisphere anterior insular and temporo-occipital regions during target processing. These results confirm and specify the role of frontoparietal networks in modulating conscious processing and detail how invalid orienting of spatial attention disrupts conscious processing.

NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network.

BACKGROUND: Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI. OBJECTIVE: Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI. METHODS: We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (Cvol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach's alpha and Bland-Altman plots were estimated to assess inter-method consistency. RESULTS: Using both methods, Vol, Cvol, NSI and CNR measurements differed between PD and HV with an effect of sex for Cvol and CNR. ICC values between the methods demonstrated optimal agreement for Cvol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were -27.4 % and -17.7 % for Vol, -30.0 % and -22.2 % for Cvol, -15.8 % and -14.4 % for NSI, -17.1 % and -16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for Cvol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for Cvol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements. CONCLUSIONS: We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.

Deep Learning-Based Neuromelanin MRI Changes of Isolated REM Sleep Behavior Disorder.

BACKGROUND: Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of parkinsonism. Neurodegenerative changes in the substantia nigra pars compacta (SNc) in parkinsonism can be detected using neuromelanin-sensitive MRI. OBJECTIVE: To investigate SNc neuromelanin changes in iRBD patients using fully automatic segmentation. METHODS: We included 47 iRBD patients, 134 early Parkinson's disease (PD) patients and 55 healthy volunteers (HVs) scanned at 3 Tesla. SNc regions-of-interest were delineated automatically using convolutional neural network. SNc volumes, volumes corrected by total intracranial volume, signal-to-noise ratio (SNR) and contrast-to-noise ratio were computed. One-way general linear models (GLM) analysis of covariance (ANCOVA) was conducted while adjusting for age and sex. RESULTS: All SNc measurements differed significantly between the three groups (except SNR in iRBD). Changes in iRBD were intermediate between those in PD and HVs. CONCLUSIONS: Using fully automated SNc segmentation method and neuromelanin-sensitive imaging, iRBD patients showed neurodegenerative changes in the SNc at a lower level than in PD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Human resting-state EEG and radiofrequency GSM mobile phone exposure: the impact of the individual alpha frequency.

PURPOSE: With the extensive use of mobile phone (MP), several studies have been realized to investigate the effects of radiofrequency electromagnetic fields (RF-EMF) exposure on brain activity at rest via electroencephalography (EEG), and the most consistent effect has been seen on the alpha band power spectral density (PSD). However, some studies reported an increase or a decrease of the PSD, while others showed no effect. It has been suggested that these differences might partly be due to a variability of the physiological state of the brain between subjects. So, the aim of this study was to investigate the alpha band modulation, exploring the impact of the alpha band frequency ranges applied in the PSD analysis. MATERIALS AND METHODS: Twenty-one healthy volunteers took part to the study with a double-blind, randomized and counterbalanced crossover design, during which eyes-open (EO) and eyes-closed (EC) resting-state EEG was recorded. The exposure system was a sham or a real GSM (global system for mobile) 900 MHz MP (pulse modulated at 217 Hz, mean power of 250 mW and 2 W peak, with a maximum specific absorption rate of 0.70 W/kg on 1 g tissue). The experimental protocol presented a baseline recording phase without MP exposure, an exposure phase during which the exposure system was placed against the left ear, and the post-exposure phase without MP. EEG data from baseline and exposure phases were analyzed and PSD was computed for the alpha band in the fixed range of 8-12 Hz and for the individual alpha band frequency range (IAF). RESULTS: Results showed a trend in decrease or increase of EEG power of both alpha oscillations during exposure in relation to EC and EO recording conditions, respectively, but not reaching statistical significance. Findings did not provide evidence for a different sensitivity to RF-EMF MP related to individual variability in the frequency of the alpha band. CONCLUSION: In conclusion, these results did not show alpha band activity modulation during resting-state under RF-EMF. It might be argued the need of a delay after the exposure in order to appreciate an EEG spectral power modulation related to RF-EMF exposure.

Modulation of magnetoencephalography alpha band activity by radiofrequency electromagnetic field depicted in sensor and source space.

Several studies reported changes in spontaneous electroencephalogram alpha band activity related to radiofrequency electromagnetic fields, but findings showed both an increase and a decrease of its spectral power or no effect. Here, we studied the alpha band modulation after 900 MHz mobile phone radiofrequency exposure and localized cortical regions involved in these changes, via a magnetoencephalography (MEG) protocol with healthy volunteers in a double-blind, randomized, counterbalanced crossover design. MEG was recorded during eyes open and eyes closed resting-state before and after radiofrequency exposure. Potential confounding factors, known to affect alpha band activity, were assessed as control parameters to limit bias. Entire alpha band, lower and upper alpha sub-bands MEG power spectral densities were estimated in sensor and source space. Biochemistry assays for salivary biomarkers of stress (cortisol, chromogranin-A, alpha amylase), heart rate variability analysis and high-performance liquid chromatography for salivary caffeine concentration were realized. Results in sensor and source space showed a significant modulation of MEG alpha band activity after the radiofrequency exposure, with different involved cortical regions in relation to the eyes condition, probably because of different attention level with open or closed eyes. None of the control parameters reported a statistically significant difference between experimental sessions.

Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: a double-blind randomized study.

The neuromodulation induced by neurofeedback training (NFT) remains a matter of debate. Investigating the modulation of brain activity specifically associated with NF requires controlling for multiple factors, such as reward, performance, congruency between task and targeted brain activity. This can be achieved using sham feedback (FB) control condition, equating all aspects of the experiment but the link between brain activity and FB. We aimed at investigating the modulation of individual alpha EEG activity induced by NFT in a double-blind, randomized, sham-controlled study. Forty-eight healthy participants were assigned to either NF (n = 25) or control (n = 23) group and performed alpha upregulation training (over 12 weeks) with a wearable EEG device. Participants of the NF group received FB based on their individual alpha activity. The control group received the auditory FB of participants of the NF group. An increase of alpha activity across training sessions was observed in the NF group only (p < 0.001). This neuromodulation was selective in that there was no evidence for similar effects in the theta (4-8 Hz) and low beta (13-18 Hz) bands. While alpha upregulation was found in the NF group only, psychological outcome variables showed overall increased feeling of control, decreased anxiety level and increased relaxation feeling, without any significant difference between the NF and the control groups. This is interpreted in terms of learning context and placebo effects. Our results pave the way to self-learnt, NF-based neuromodulation with light-weighted, wearable EEG systems.

The spatiotemporal changes in dopamine, neuromelanin and iron characterizing Parkinson's disease.

In Parkinson's disease, there is a progressive reduction in striatal dopaminergic function, and loss of neuromelanin-containing dopaminergic neurons and increased iron deposition in the substantia nigra. We tested the hypothesis of a relationship between impairment of the dopaminergic system and changes in the iron metabolism. Based on imaging data of patients with prodromal and early clinical Parkinson's disease, we assessed the spatiotemporal ordering of such changes and relationships in the sensorimotor, associative and limbic territories of the nigrostriatal system. Patients with Parkinson's disease (disease duration < 4 years) or idiopathic REM sleep behaviour disorder (a prodromal form of Parkinson's disease) and healthy controls underwent longitudinal examination (baseline and 2-year follow-up). Neuromelanin and iron sensitive MRI and dopamine transporter single-photon emission tomography were performed to assess nigrostriatal levels of neuromelanin, iron, and dopamine. For all three functional territories of the nigrostriatal system, in the clinically most and least affected hemispheres separately, the following was performed: cross-sectional and longitudinal intergroup difference analysis of striatal dopamine and iron, and nigral neuromelanin and iron; in Parkinson's disease patients, exponential fitting analysis to assess the duration of the prodromal phase and the temporal ordering of changes in dopamine, neuromelanin or iron relative to controls; and voxel-wise correlation analysis to investigate concomitant spatial changes in dopamine-iron, dopamine-neuromelanin and neuromelanin-iron in the substantia nigra pars compacta. The temporal ordering of dopaminergic changes followed the known spatial pattern of progression involving first the sensorimotor, then the associative and limbic striatal and nigral regions. Striatal dopaminergic denervation occurred first followed by abnormal iron metabolism and finally neuromelanin changes in the substantia nigra pars compacta, which followed the same spatial and temporal gradient observed in the striatum but shifted in time. In conclusion, dopaminergic striatal dysfunction and cell loss in the substantia nigra pars compacta are interrelated with increased nigral iron content.

Longitudinal Changes in Neuromelanin MRI Signal in Parkinson's Disease: A Progression Marker.

BACKGROUND: Development of reliable and accurate imaging biomarkers of dopaminergic cell neurodegeneration is necessary to facilitate therapeutic drug trials in Parkinson's disease (PD). Neuromelanin-sensitive MRI techniques have been effective in detecting neurodegeneration in the substantia nigra pars compacta (SNpc). The objective of the current study was to investigate longitudinal neuromelanin signal changes in the SNpc in PD patients. METHODS: In this prospective, longitudinal, observational case-control study, we included 140 PD patients and 64 healthy volunteers divided into 2 cohorts. Cohort I included 99 early PD patients (disease duration, 1.5 ± 1.0 years) and 41 healthy volunteers analyzed at baseline (V1), where 79 PD patients and 32 healthy volunteers were rescanned after 2.0 ± 0.2 years of follow-up (V2). Cohort II included 41 progressing PD patients (disease duration, 9.3 ± 3.7 years) and 23 healthy volunteers at V1, where 30 PD patients were rescanned after 2.4 ± 0.5 years of follow-up. Subjects were scanned at 3 T MRI using 3-dimensional T1-weighted and neuromelanin-sensitive imaging. Regions of interest were delineated manually to calculate SN volumes, volumes corrected by total intracranial volume, signal-to-noise ratio, and contrast-to-noise ratio. RESULTS: Results showed (1) significant reduction in volume and volume corrected by total intracranial volume between visits, greater in progressing PD than nonsignificant changes in healthy volunteers; (2) no significant effects of visit for signal intensity (signal-to-noise ratio); (3) significant interaction in volume between group and visit; (4) greater volume corrected by total intracranial volume at baseline in female patients and greater decrease in volume and increase in the contrast-to-noise ratio in progressing female PD patients compared with male patients; and (5) correlations between neuromelanin SN changes and disease severity and duration. CONCLUSIONS: We observed a progressive and measurable decrease in neuromelanin-based SN signal and volume in PD, which might allow a direct noninvasive assessment of progression of SN loss and could represent a target biomarker for disease-modifying treatments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Automated Categorization of Parkinsonian Syndromes Using Magnetic Resonance Imaging in a Clinical Setting.

BACKGROUND: Machine learning algorithms using magnetic resonance imaging (MRI) data can accurately discriminate parkinsonian syndromes. Validation in patients recruited in routine clinical practice is missing. OBJECTIVE: The aim of this study was to assess the accuracy of a machine learning algorithm trained on a research cohort and tested on an independent clinical replication cohort for the categorization of parkinsonian syndromes. METHODS: Three hundred twenty-two subjects, including 94 healthy control subjects, 119 patients with Parkinson's disease (PD), 51 patients with progressive supranuclear palsy (PSP) with Richardson's syndrome, 35 with multiple system atrophy (MSA) of the parkinsonian variant (MSA-P), and 23 with MSA of the cerebellar variant (MSA-C), were recruited. They were divided into a training cohort (n = 179) scanned in a research environment and a replication cohort (n = 143) examined in clinical practice on different MRI systems. Volumes and diffusion tensor imaging (DTI) metrics in 13 brain regions were used as input for a supervised machine learning algorithm. To harmonize data across scanners and reduce scanner-dependent effects, we tested two types of normalizations using patient data or healthy control data. RESULTS: In the replication cohort, high accuracies were achieved using volumetry in the classification of PD-PSP, PD-MSA-C, PSP-MSA-C, and PD-atypical parkinsonism (balanced accuracies: 0.840-0.983, area under the receiver operating characteristic curves: 0.907-0.995). Performances were lower for the classification of PD-MSA-P, MSA-C-MSA-P (balanced accuracies: 0.765-0.784, area under the receiver operating characteristic curve: 0.839-0.871) and PD-PSP-MSA (balanced accuracies: 0.773). Performance using DTI was improved when normalizing by controls, but remained lower than that using volumetry alone or combined with DTI. CONCLUSIONS: A machine learning approach based on volumetry enabled accurate classification of subjects with early-stage parkinsonism, examined on different MRI systems, as part of their clinical assessment. © 2020 International Parkinson and Movement Disorder Society.

Parkinson Disease Propagation Using MRI Biomarkers and Partial Least Squares Path Modeling.

OBJECTIVES: The classic Braak neuropathologic staging model in Parkinson disease (PD) suggests that brain lesions progress from the medulla oblongata to the cortex. An alternative model in which neurodegeneration first occurs in the cortex has also been proposed. These 2 models may correspond to different patient phenotypes. To test these 2 models and to investigate whether they were influenced by the presence of REM sleep behavior disorder (RBD), we used multimodal MRI and partial least squares path modeling (PLS-PM) assuming that patients with RBD followed distinct neurodegeneration pattern. METHODS: Fifty-four patients with PD (34 with RBD) and 25 healthy volunteers were scanned with T1-weighted, diffusion tensor, and neuromelanin-sensitive imaging. Volume, signal, and mean, axial, and radial diffusivities were calculated in brainstem, basal forebrain, and cortical regions. PLS-PM, estimating a network of causal relationships between blocks of variables, was used to build and test an analytical model based on Braak staging. The overall quality of the model was assessed with goodness of fit coefficient (Gof). RESULTS: PLS-PM was run on patients with PD with RBD and without RBD separately. In PD with RBD, a brainstem-to-cortex model had significant Gof (0.71, p = 0.01), whereas a cortex-to-brainstem model did not. In contrast, in patients with PD without RBD, the brainstem-to-cortex model was not significant (Gof = 0.64, p = 0.27), and the cortex-to-brainstem model was highly significant (Gof = 0.72, p = 0.008). CONCLUSIONS: With the PLS-PM imaging-based model, the neurodegeneration pattern of patients with PD with RBD was consistent with the Braak brainstem-to-cortex model, whereas that of patients without RBD followed the cortex-to-brainstem model.

Antisaccade, a predictive marker for freezing of gait in Parkinson's disease and gait/gaze network connectivity.

Freezing of gait is a challenging sign of Parkinson's disease associated with disease severity and progression and involving the mesencephalic locomotor region. No predictive factor of freezing has been reported so far. The primary objective of this study was to identify predictors of freezing occurrence at 5 years. In addition, we tested whether functional connectivity of the mesencephalic locomotor region could explain the oculomotor factors at baseline that were predictive of freezing onset. We performed a prospective study investigating markers (parkinsonian signs, cognitive status and oculomotor recordings, with a particular focus on the antisaccade latencies) of disease progression at baseline and at 5 years. We identified two groups of patients defined by the onset of freezing at 5 years of follow-up; the 'Freezer' group was defined by the onset of freezing in the ON medication condition during follow-up (n = 17), while the 'non-Freezer' group did not (n = 8). Whole brain resting-state functional MRI was recorded at baseline to determine how antisaccade latencies were associated with connectivity of the mesencephalic locomotor region networks in patients compared to 25 age-matched healthy volunteers. Results showed that, at baseline and compared to the non-Freezer group, the Freezer group had equivalent motor or cognitive signs, but increased antisaccade latencies (P = 0.008). The 5-year course of freezing of gait was correlated with worsening antisaccade latencies (P = 0.0007). Baseline antisaccade latencies was also predictive of the freezing onset (χ2 = 0.008). Resting state connectivity of mesencephalic locomotor region networks correlated with (i) antisaccade latency differently in patients and healthy volunteers at baseline; and (ii) the further increase of antisaccade latency at 5 years. We concluded that antisaccade latency is a predictive marker of the 5-year onset of freezing of gait. Our study suggests that functional networks associated with gait and gaze control are concurrently altered during the course of the disease.

Spatiotemporal changes in substantia nigra neuromelanin content in Parkinson's disease.

This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with early or progressing Parkinson's disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson's disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson's disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson's disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra's morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson's disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.

Iron Imaging as a Diagnostic Tool for Parkinson's Disease: A Systematic Review and Meta-Analysis.

Background: Parkinson's disease (PD) is a progressive neurodegenerative disease whose main neuropathological feature is the loss of dopaminergic neurons of the substantia nigra (SN). There is also an increase in iron content in the SN in postmortem and imaging studies using iron-sensitive MRI techniques. However, MRI results are variable across studies. Objectives: We performed a systematic meta-analysis of SN iron imaging studies in PD to better understand the role of iron-sensitive MRI quantification to distinguish patients from healthy controls. We also studied the factors that may influence iron quantification and analyzed the correlations between demographic and clinical data and iron load. Methods: We searched PubMed and ScienceDirect databases (from January 1994 to December 2019) for studies that analyzed iron load in the SN of PD patients using T2*, R2*, susceptibility weighting imaging (SWI), or quantitative susceptibility mapping (QSM) and compared the values with healthy controls. Details for each study regarding participants, imaging methods, and results were extracted. The effect size and confidence interval (CI) of 95% were calculated for each study as well as the pooled weighted effect size for each marker over studies. Hence, the correlations between technical and clinical metrics with iron load were analyzed. Results: Forty-six articles fulfilled the inclusion criteria including 27 for T2*/R2* measures, 10 for SWI, and 17 for QSM (3,135 patients and 1,675 controls). Eight of the articles analyzed both R2* and QSM. A notable effect size was found in the SN in PD for R2* increase (effect size: 0.84, 95% CI: 0.60 to 1.08), for SWI measurements (1.14, 95% CI: 0.54 to 1.73), and for QSM increase (1.13, 95% CI: 0.86 to 1.39). Correlations between imaging measures and Unified Parkinson's Disease Rating Scale (UPDRS) scores were mostly observed for QSM. Conclusions: The consistent increase in MRI measures of iron content in PD across the literature using R2*, SWI, or QSM techniques confirmed that these measurements provided reliable markers of iron content in PD. Several of these measurements correlated with the severity of motor symptoms. Lastly, QSM appeared more robust and reproducible than R2* and more suited to multicenter studies.

Multimodal Magnetic Resonance Imaging Quantification of Brain Changes in Progressive Supranuclear Palsy.

BACKGROUND: Progressive supranuclear palsy (PSP) is a neurodegenerative clinically heterogeneous disorder, formal diagnosis being based on postmortem histological brain examination. OBJECTIVE: We aimed to perform a precise in vivo staging of neurodegeneration in PSP using quantitative multimodal MRI. The ability of MRI biomarkers to differentiate PSP from PD was also evaluated. METHODS: Eleven PSP patients were compared to 26 age-matched healthy controls and 51 PD patients. Images were acquired at 3 Tesla (three-dimensional T1 -weighted, diffusion tensor, and neuromelanin-sensitive images) and 7 Tesla (three-dimensional-T2 * images). Regions of interest included the cortical areas, hippocampus, amygdala, basal ganglia, basal forebrain, brainstem nuclei, dentate nucleus, and cerebellum. Volumes, mean diffusivity, and fractional anisotropy were measured. In each region, a threshold value for group categorization was calculated, and four grades of change (0-3) were determined. RESULTS: PSP patients showed extensive volume decreases and diffusion changes in the midbrain, SN, STN, globus pallidus, basal forebrain, locus coeruleus, pedunculopontine nucleus, and dentate nucleus, in close agreement with the degrees of impairment in histological analyses. The predictive factors for the separation of PSP and healthy controls were, in descending order, the neuromelanin-based SN volume; midbrain fractional anisotropy; volumes of the midbrain, globus pallidus, and putamen; and fractional anisotropy in the locus coeruleus. The best predictors for separating PSP from PD were the neuromelanin-based volume in the SN, fractional anisotropy in the pons, volumes of the midbrain and globus pallidus, and fractional anisotropy in the basal forebrain. CONCLUSIONS: These results suggest that it is possible to evaluate brain neurodegeneration in PSP noninvasively, even in small brainstem nuclei, in close agreement with previously published histological data. © 2019 International Parkinson and Movement Disorder Society.

Effect of short exposure to radiofrequency electromagnetic fields on saliva biomarkers: a study on the electrohypersensitive individuals.

Context: Some individuals are reporting being sensitive to electromagnetic fields. They report some unspecific symptoms like headeache, sleep disruption, heart palpitations, itching, etc. The lack of scientific objective links between EHS symptoms and EMF exposure renders the diagnosis of EHS more complex. Purpose: Our present work aimed to look for the effect of RF EMF exposure on saliva alpha amylase (AA) and other biological markers such as cortisol and IgA in EHS individuals. Participants and methods: Ten EHS individuals participated in this double-blind provocation study. They were aged between 35 and 63 yr. Experiment consisted of two sessions (sham and real exposure). No external EMF sources were allowed, and the exposure consisted of a series of EMF signals emitted from a generator (Rhode & Schwarz) and a horn antenna (Schwarzbeck BBHA9120b). Consecutive RF signals were applied: GSM 900, GSM 1800, DECT, and Wi-Fi signals for 5 min each. Results: Exposure to 4 consecutive radiofrequency signals did not show any significant modification (p > .05) on the saliva AA, cortisol or immunoglobulin A concentrations in the electrohypersensitive individuals. Conclusions: Our study, under current conditions, do not presently allow us to propose an identification of marker for EHS.

Multimodal magnetic resonance imaging investigation of basal forebrain damage and cognitive deficits in Parkinson's disease.

BACKGROUND: Cognitive deficits in Parkinson's disease (PD) may result from damage in the cortex as well as in the dopaminergic, noradrenergic, and cholinergic inputs to the cortex. Cholinergic inputs to the cortex mainly originate from the basal forebrain and are clustered in several regions, called Ch1 to Ch4, that project to the hippocampus (Ch1-2), the olfactory bulb (Ch3), and the cortex and amygdala (Ch4). OBJECTIVE: We investigated changes in basal forebrain and their role in cognitive deficits in PD. METHODS: We studied 52 nondemented patients with PD (Hoehn & Yahr 1-2) and 25 age-matched healthy controls using diffusion and resting state functional MRI. RESULTS: PD patients had a loss of structural integrity within the Ch1-2 and Ch3-4 nuclei of the basal forebrain as well as in the fornix. Tractography showed that the probability of anatomical connection was decreased in PD between Ch3-4 and the associative prefrontal cortex, occipital cortex, and peri-insular regions. There was a reduction in functional connectivity between Ch1-2 and the bilateral hippocampi and parahippocampal gyri, the left middle and superior temporal gyri, and the left fusiform gyrus and between Ch3-4 and the right inferior frontal gyrus and the right and left thalamus. In Ch1-2, loss of structural integrity and connectivity correlated with scores at the memory tests, whereas changes in Ch3-4 correlated with scores of global cognition and executive functions. CONCLUSION: This study highlights the association between deficits of different cholinergic nuclei of the basal forebrain and the extent of cognitive impairments in nondemented PD patients. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.