Brain perfusion changes in beta-thalassemia.

BACKGROUND: Brain injury in hereditary hemoglobinopathies is commonly attributed to anemia-related relative hypoperfusion in terms of impaired oxygen blood supply. Supratentorial and infratentorial vascular watershed regions seem to be especially vulnerable, but data are very scarce. AIMS: We investigated a large beta-thalassemia sample with arterial spin labeling in order to characterize regional perfusion changes and their correlation with phenotype and anemia severity. METHODS: We performed a multicenter single-scanner cross-sectional 3T-MRI study analyzing non-invasively the brain perfusion in 54 transfusion-dependent thalassemia (TDT), 23 non-transfusion-dependent thalassemia (NTDT) patients and 56 Healthy Controls (HC). Age, hemoglobin levels, and cognitive functioning were recorded. RESULTS: Both TDT and NTDT patients showed globally increased brain perfusion values compared to healthy controls, while no difference was found between patient subgroups. Using age and sex as covariates and scaling the perfusion maps for the global cerebral blood flow, beta-thalassemia patients showed relative hyperperfusion in supratentorial/infratentorial watershed regions. Perfusion changes correlated with hemoglobin levels (p = 0.013) and were not observed in the less severely anemic patients (hemoglobin level > 9.5 g/dL). In the hyperperfused regions, white matter density was significantly decreased (p = 0.0003) in both patient subgroups vs. HC. In NTDT, white matter density changes correlated inversely with full-scale Intelligence Quotient (p = 0.007) while in TDT no correlation was found. CONCLUSION: Relative hyperperfusion of watershed territories represents a hemodynamic hallmark of beta-thalassemia anemia challenging previous hypotheses of brain injury in hereditary anemias. A careful management of anemia severity might be crucial for preventing structural white matter changes and subsequent long-term cognitive impairment.

Altered domain-specific striatal functional connectivity in patients with Parkinson's disease and urinary symptoms.

BACKGROUND: In this study, we aimed at investigating the possible association of urinary symptoms with whole-brain MRI resting-state functional connectivity (FC) alterations from distinct striatal subregions in a large cohort of early PD patients. METHODS: Seventy-nine drug-naive PD patients (45 PD-urinary+/34 PD-urinary-) and 38 healthy controls (HCs) were consecutively enrolled. Presence/absence of urinary symptoms were assessed by means of the Nonmotor Symptom Scale - domain 7. Using an a priori connectivity-based domain-specific parcellation, we defined three ROIs (per each hemisphere) for different striatal functional subregions (sensorimotor, limbic and cognitive) from which seed-based FC voxel-wise analyses were conducted over the whole brain. RESULTS: Compared to PD-urinary-, PD-urinary+ patients showed increased FC between striatal regions and motor and premotor/supplementary motor areas as well as insula/anterior dorsolateral PFC. Compared to HC, PD-urinary+ patients presented decreased FC between striatal regions and parietal, insular and cingulate cortices. CONCLUSIONS: Our findings revealed a specific pattern of striatal FC alteration in PD patients with urinary symptoms, potentially associated to altered stimuli perception and sensorimotor integration even in the early stages. These results may potentially help clinicians to design more effective and tailored rehabilitation and neuromodulation protocols for PD patients.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis.

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated ( ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.

Capability of Machine Learning Algorithms to Classify Safe and Unsafe Postures during Weight Lifting Tasks Using Inertial Sensors.

Occupational ergonomics aims to optimize the work environment and to enhance both productivity and worker well-being. Work-related exposure assessment, such as lifting loads, is a crucial aspect of this discipline, as it involves the evaluation of physical stressors and their impact on workers' health and safety, in order to prevent the development of musculoskeletal pathologies. In this study, we explore the feasibility of machine learning (ML) algorithms, fed with time- and frequency-domain features extracted from inertial signals (linear acceleration and angular velocity), to automatically and accurately discriminate safe and unsafe postures during weight lifting tasks. The signals were acquired by means of one inertial measurement unit (IMU) placed on the sternums of 15 subjects, and subsequently segmented to extract several time- and frequency-domain features. A supervised dataset, including the extracted features, was used to feed several ML models and to assess their prediction power. Interesting results in terms of evaluation metrics for a binary safe/unsafe posture classification were obtained with the logistic regression algorithm, which outperformed the others, with accuracy and area under the receiver operating characteristic curve values of up to 96% and 99%, respectively. This result indicates the feasibility of the proposed methodology-based on a single inertial sensor and artificial intelligence-to discriminate safe/unsafe postures associated with load lifting activities. Future investigation in a wider study population and using additional lifting scenarios could confirm the potentiality of the proposed methodology, supporting its applicability in the occupational ergonomics field.

Intrinsic brain functional connectivity predicts treatment-related motor complications in early Parkinson's disease patients.

BACKGROUND: Treatment-related motor complications may develop progressively over the course of Parkinson's disease (PD). OBJECTIVE: We investigated intrinsic brain networks functional connectivity (FC) at baseline in a cohort of early PD patients which successively developed treatment-related motor complications over 4 years. METHODS: Baseline MRI images of 88 drug-naïve PD patients and 20 healthy controls were analyzed. After the baseline assessments, all PD patients were prescribed with dopaminergic treatment and yearly clinically re-assessed. At the 4-year follow-up, 36 patients have developed treatment-related motor complications (PD-Compl) whereas 52 had not (PD-no-Compl). Single-subject and group-level independent component analyses were used to investigate FC changes within the major large-scale resting-state networks at baseline. A multivariate Cox regression model was used to explore baseline predictors of treatment-related motor complications at 4-year follow-up. RESULTS: At baseline, an increased FC in the right middle frontal gyrus within the frontoparietal network as well as a decreased connectivity in the left cuneus within the default-mode network were detected in PD-Compl compared with PD-no-Compl. PD-Compl patients showed a preserved sensorimotor FC compared to controls. FC differences were found to be independent predictors of treatment-related motor complications over time. CONCLUSION: Our findings demonstrated that specific FC differences may characterize drug-naïve PD patients more prone to develop treatment-related complications. These findings may reflect the presence of an intrinsic vulnerability across frontal and prefrontal circuits, which may be potentially targeted as a future biomarker in clinical trials.

The impact of emotional valence and stimulus habituation on fMRI signal reliability during emotion generation.

BACKGROUND: The emotional domain is often impaired across many neurological diseases, for this reason it represents a relevant target of rehabilitation interventions. Functional changes in neural activity related to treatment can be assessed with functional MRI (fMRI) using emotion-generation tasks in longitudinal settings. Previous studies demonstrated that within-subject fMRI signal reliability can be affected by several factors such as repetition suppression, type of task and brain anatomy. However, the differential role of repetition suppression and emotional valence of the stimuli on the fMRI signal reliability and reproducibility during an emotion-generation task involving the vision of emotional pictures is yet to be determined. METHODS: Sixty-two healthy subjects were enrolled and split into two groups: group A (21 subjects, test-retest reliability on same-day and with same-task-form), group B (30 subjects, test-retest reproducibility with 4-month-interval using two equivalent-parallel forms of the task). Test-retest reliability and reproducibility of fMRI responses and patterns were evaluated separately for positive and negative emotional valence conditions in both groups. The analyses were performed voxel-wise, using the general linear model (GLM), and via a region-of-interest (ROI)-based approach, by computing the intra-class correlation coefficient (ICC) on the obtained contrasts. RESULTS: The voxel-wise GLM test yielded no significant differences for both conditions in reliability and reproducibility analyses. As to the ROI-based approach, across all areas with significant main effects of the stimuli, the reliability, as measured with ICC, was poor (<0.4) for the positive condition and ranged from poor to excellent (0.4-0.75) for the negative condition. The ICC-based reproducibility analysis, related to the comparison of two different parallel forms, yielded similar results. DISCUSSION: The voxel-wise GLM analysis failed to capture the poor reliability of fMRI signal which was instead highlighted using the ROI-based ICC analysis. The latter showed higher signal reliability for negative valence stimuli with respect to positive ones. The implementation of two parallel forms allowed to exclude neural suppression as the predominant effect causing low signal reliability, which could be instead ascribed to the employment of different neural strategies to cope with emotional stimuli over time. This is an invaluable information for a better assessment of treatment and rehabilitation effects in longitudinal studies of emotional neural processing.

Ambroxol as a disease-modifying treatment to reduce the risk of cognitive impairment in GBA-associated Parkinson's disease: a multicentre, randomised, double-blind, placebo-controlled, phase II trial. The AMBITIOUS study protocol.

Background: Heterozygous mutations in the GBA gene, encoding the lysosomal enzyme ß-glucocerebrosidase (GCase), are the most frequent genetic risk factor for Parkinson's disease (PD). GBA-related PD (GBA-PD) patients have higher risk of dementia and reduced survival than non-carriers. Preclinical studies and one open-label trial in humans demonstrated that the chaperone ambroxol (ABX) increases GCase levels and modulates α-synuclein levels in the blood and cerebrospinal fluid (CSF). Methods and analysis: In this multicentre, double-blind, placebo-controlled, phase II clinical trial, we randomise patients with GBA-PD in a 1:1 ratio to either oral ABX 1.2 g/day or placebo. The duration of treatment is 52 weeks. Each participant is assessed at baseline and weeks 12, 26, 38, 52 and 78. Changes in the Montreal Cognitive Assessment score and the frequency of mild cognitive impairment and dementia between baseline and weeks 52 are the primary outcome measures. Secondary outcome measures include changes in validated scales/questionnaires assessing motor and non-motor symptoms. Neuroimaging features and CSF neurodegeneration markers are used as surrogate markers of disease progression. GCase activity, ABX and α-synuclein levels are also analysed in blood and CSF. A repeated-measures analysis of variance will be used for elaborating results. The primary analysis will be by intention to treat. Ethics and dissemination: The study and protocols have been approved by the ethics committee of centres. The study is conducted according to good clinical practice and the Declaration of Helsinki. The trial findings will be published in peer-reviewed journals and presented at conferences. Trial registration numbers: NCT05287503, EudraCT 2021-004565-13.

Functional MRI activation of the nucleus tractus solitarius after taste stimuli at ultra-high field: a proof-of-concept single-subject study.

Using ultra-high field (7 Tesla) functional MRI (fMRI), we conducted the first in-vivo functional neuroimaging study of the normal human brainstem specifically designed to examine neural signals in the Nucleus Tractus Solitarius (NTS) in response to all basic taste stimuli. NTS represents the first relay station along the mammalian taste processing pathway which originates at the taste buds in the oral cavity and passes through the thalamus before reaching the primary taste cortex in the brain. In our proof-of-concept study, we acquired data from one adult volunteer using fMRI at 1.2 mm isotropic resolution and performed a univariate general linear model analysis. During fMRI acquisition, three shuffled injections of sweet, bitter, salty, sour, and umami solutions were administered following an event-related design. We observed a statistically significant blood oxygen level-dependent (BOLD) response in the anatomically predicted location of the NTS for all five basic tastes. The results of this study appear statistically robust, even though they were obtained from a single volunteer. The information derived from a similar experimental strategy may inspire novel research aimed at clarifying important details of central nervous system involvement in eating disorders, at designing and monitoring tailored therapeutic strategies.

Repetitive Transcranial Magnetic Stimulation (rTMS) in Mild Cognitive Impairment: Effects on Cognitive Functions-A Systematic Review.

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique also used as a non-pharmacological intervention against cognitive impairment. The purpose of the present review was to summarize what is currently known about the effectiveness of rTMS intervention on different cognitive domains in patients with mild cognitive impairment (MCI) and to address potential neuromodulation approaches in combination with electroencephalography (EEG) and neuroimaging, especially functional magnetic resonance imaging (fMRI). In this systematic review, we consulted three main databases (PubMed, Science Direct, and Scopus), and Google Scholar was selected for the gray literature search. The PRISMA flowchart drove the studies' inclusion. The selection process ensured that only high-quality studies were included; after removing duplicate papers, explicit ratings were given based on the quality classification as high (A), moderate (B), or low (C), considering factors such as risks of bias, inaccuracies, inconsistencies, lack of direction, and publication bias. Seven full-text articles fulfilled the stated inclusion, reporting five double-blind, randomized, sham-controlled studies, a case study, and a randomized crossover trial. The results of the reviewed studies suggested that rTMS in MCI patients is safe and effective for enhancing cognitive functions, thus making it a potential therapeutic approach for MCI patients. Changes in functional connectivity within the default mode network (DMN) after targeted rTMS could represent a valuable indicator of treatment response. Finally, high-frequency rTMS over the dorsolateral prefrontal cortex (DLPFC) has been shown to significantly enhance cognitive functions, such as executive performance, together with the increase of functional connectivity within frontoparietal networks. The main limitations were the number of included studies and the exclusion of studies using intermittent theta-burst stimulation, used in studies on Alzheimer's disease. Therefore, neuroimaging techniques in combination with rTMS have been shown to be useful for future network-based, fMRI-guided therapeutic approaches.

sEMG Spectral Analysis and Machine Learning Algorithms Are Able to Discriminate Biomechanical Risk Classes Associated with Manual Material Liftings.

Manual material handling and load lifting are activities that can cause work-related musculoskeletal disorders. For this reason, the National Institute for Occupational Safety and Health proposed an equation depending on the following parameters: intensity, duration, frequency, and geometric characteristics associated with the load lifting. In this paper, we explore the feasibility of several Machine Learning (ML) algorithms, fed with frequency-domain features extracted from electromyographic (EMG) signals of back muscles, to discriminate biomechanical risk classes defined by the Revised NIOSH Lifting Equation. The EMG signals of the multifidus and erector spinae muscles were acquired by means of a wearable device for surface EMG and then segmented to extract several frequency-domain features relating to the Total Power Spectrum of the EMG signal. These features were fed to several ML algorithms to assess their prediction power. The ML algorithms produced interesting results in the classification task, with the Support Vector Machine algorithm outperforming the others with accuracy and Area under the Receiver Operating Characteristic Curve values of up to 0.985. Moreover, a correlation between muscular fatigue and risky lifting activities was found. These results showed the feasibility of the proposed methodology-based on wearable sensors and artificial intelligence-to predict the biomechanical risk associated with load lifting. A future investigation on an enriched study population and additional lifting scenarios could confirm the potential of the proposed methodology and its applicability in the field of occupational ergonomics.

Frequency and imaging correlates of neuropsychiatric symptoms in Progressive Supranuclear Palsy.

Neuropsychiatric symptoms are intrinsic to Progressive Supranuclear Palsy (PSP) and a spoonful of studies investigated their imaging correlates. Describe (I) the frequency and severity of neuropsychiatric symptoms in PSP and (II) their structural imaging correlates. Twenty-six PSP patients underwent Neuropsychiatric Inventory (NPI) and brain 3D T1-weighted MRI. Spearman's rho with Bonferroni correction was used to investigate correlations between NPI scores and volumes of gray matter regions. More than 80% of patients presented at least one behavioral symptom of any severity. The most frequent and severe were depression/dysphoria, apathy, and irritability/lability. Significant relationships were found between the severity of irritability and right pars opercularis volume (p < 0.001) as well as between the frequency of agitation/aggression and left lateral occipital volume (p < 0.001). Depression, apathy, and irritability are the most common neuropsychiatric symptoms in PSP. Moreover, we found a relationship between specific positive symptoms as irritability and agitation/aggression and greater volume of the right pars opercularis cortex and lower volume of the left occipital cortex, respectively, which deserve further investigations.

Accumbal-thalamic connectivity and associated glutamate alterations in human cocaine craving: A state-dependent rs-fMRI and 1H-MRS study.

Craving is a core symptom of cocaine use disorder and a major factor for relapse risk. To date, there is no pharmacological therapy to treat this disease or at least to alleviate cocaine craving as a core symptom. In animal models, impaired prefrontal-striatal signalling leading to altered glutamate release in the nucleus accumbens appear to be the prerequisite for cocaine-seeking. Thus, those network and metabolic changes may constitute the underlying mechanisms for cocaine craving and provide a potential treatment target. In humans, there is recent evidence for corresponding glutamatergic alterations in the nucleus accumbens, however, the underlying network disturbances that lead to this glutamate imbalance remain unknown. In this state-dependent randomized, placebo-controlled, double-blinded, cross-over multimodal study, resting state functional magnetic resonance imaging in combination with small-voxel proton magnetic resonance spectroscopy (voxel size: 9.4 × 18.8 × 8.4 mm3) was applied to assess network-level and associated neurometabolic changes during a non-craving and a craving state, induced by a custom-made cocaine-cue film, in 18 individuals with cocaine use disorder and 23 healthy individuals. Additionally, we assessed the potential impact of a short-term challenge of N-acetylcysteine, known to normalize disturbed glutamate homeostasis and to thereby reduce cocaine-seeking in animal models of addiction, compared to a placebo. We found increased functional connectivity between the nucleus accumbens and the dorsolateral prefrontal cortex during the cue-induced craving state. However, those changes were not linked to alterations in accumbal glutamate levels. Whereas we additionally found increased functional connectivity between the nucleus accumbens and a midline part of the thalamus during the cue-induced craving state. Furthermore, obsessive thinking about cocaine and the actual intensity of cocaine use were predictive of cue-induced functional connectivity changes between the nucleus accumbens and the thalamus. Finally, the increase in accumbal-thalamic connectivity was also coupled with craving-related glutamate rise in the nucleus accumbens. Yet, N-acetylcysteine had no impact on craving-related changes in functional connectivity. Together, these results suggest that connectivity changes within the fronto-accumbal-thalamic loop, in conjunction with impaired glutamatergic transmission, underlie cocaine craving and related clinical symptoms, pinpointing the thalamus as a crucial hub for cocaine craving in humans.

Iron and Ferroptosis More than a Suspect: Beyond the Most Common Mechanisms of Neurodegeneration for New Therapeutic Approaches to Cognitive Decline and Dementia.

Neurodegeneration is a multifactorial process that involves multiple mechanisms. Examples of neurodegenerative diseases are Parkinson's disease, multiple sclerosis, Alzheimer's disease, prion diseases such as Creutzfeldt-Jakob's disease, and amyotrophic lateral sclerosis. These are progressive and irreversible pathologies, characterized by neuron vulnerability, loss of structure or function of neurons, and even neuron demise in the brain, leading to clinical, functional, and cognitive dysfunction and movement disorders. However, iron overload can cause neurodegeneration. Dysregulation of iron metabolism associated with cellular damage and oxidative stress is reported as a common event in several neurodegenerative diseases. Uncontrolled oxidation of membrane fatty acids triggers a programmed cell death involving iron, ROS, and ferroptosis, promoting cell death. In Alzheimer's disease, the iron content in the brain is significantly increased in vulnerable regions, resulting in a lack of antioxidant defenses and mitochondrial alterations. Iron interacts with glucose metabolism reciprocally. Overall, iron metabolism and accumulation and ferroptosis play a significant role, particularly in the context of diabetes-induced cognitive decline. Iron chelators improve cognitive performance, meaning that brain iron metabolism control reduces neuronal ferroptosis, promising a novel therapeutic approach to cognitive impairment.

Memory Phenotypes In Early, De Novo Parkinson's Disease Patients with Mild Cognitive Impairment.

BACKGROUND: Memory deficits in mild cognitive impairment related to Parkinson's disease (PD-MCI) are quite heterogeneous, and there is no general agreement on their genesis. OBJECTIVES: To define memory phenotypes in de novo PD-MCI and their associations with motor and non-motor features and patients' quality of life. METHODS: From a sample of 183 early de novo patients with PD, cluster analysis was applied to neuropsychological measures of memory function of 82 patients with PD-MCI (44.8%). The remaining patients free of cognitive impairment were considered as a comparison group (n = 101). Cognitive measures and structural magnetic resonance imaging-based neural correlates of memory function were used to substantiate the results. RESULTS: A three-cluster model produced the best solution. Cluster A (65.85%) included memory unimpaired patients; Cluster B (23.17%) included patients with mild episodic memory disorder related to a "prefrontal executive-dependent phenotype"; Cluster C (10.97%) included patients with severe episodic memory disorder related to a "hybrid phenotype," where hippocampal-dependent deficits co-occurred with prefrontal executive-dependent memory dysfunctions. Cognitive and brain structural imaging correlates substantiated the findings. The three phenotypes did not differ in terms of motor and non-motor features, but the attention/executive deficits progressively increased from Cluster A, through Cluster B, to Cluster C. This last cluster had worse quality of life compared to others. CONCLUSIONS: Our results demonstrated the memory heterogeneity of de novo PD-MCI, suggesting existence of three distinct memory-related phenotypes. Identification of such phenotypes can be fruitful in understanding the pathophysiological mechanisms underlying PD-MCI and its subtypes and in guiding appropriate treatments. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Arterial spin labeling MRI applied to migraine: current insights and future perspectives.

INTRODUCTION: Advanced neuroimaging techniques have extensively contributed to elucidate the complex mechanisms underpinning the pathophysiology of migraine, a neurovascular disorder characterized by episodes of headache associated with a constellation of non-pain symptoms. The present manuscript, summarizing the most recent progresses of the arterial spin labelling (ASL) MRI techniques and the most significant findings from ASL studies conducted in migraine, is aimed to clarify how ASL investigations are contributing to the evolving insight on migraine pathophysiology and their putative role in migraine clinical setting. ASL techniques, allowing to quantitatively demonstrate changes in cerebral blood flow (CBF) both during the attacks and in the course of interictal period, could represent the melting point between advanced neuroimaging investigations, conducted with pure scientific purposes, and conventional neuroimaging approaches, employed in the diagnostic decision-making processes. MAIN BODY: Converging ASL evidences have demonstrated that abnormal CBF, exceeding the boundaries of a single vascular territory, with biphasic trend dominated by an initial hypoperfusion (during the aura phenomenon but also in the first part of the headache phase) followed by hyperperfusion, characterizes migraine with aura attack and can represent a valuable clinical tool in the differential diagnosis from acute ischemic strokes and epileptic seizures. Studies conducted during migraine without aura attacks are converging to highlight the involvement of dorsolateral pons and hypothalamus in migraine pathophysiology, albeit not able to disentangle their role as "migraine generators" from mere attack epiphenomenon. Furthermore, ASL findings tend to support the presence of perfusion abnormalities in brain regions known to be involved in aura ignition and propagation as well as in areas involved in multisensory processing, in both patients with migraine with aura and migraine without aura. CONCLUSION: Although ASL studies have dramatically clarified quality and timing of perfusion abnormalities during migraine with aura attacks, the same cannot be said for perfusion changes during migraine attacks without aura and interictal periods. Future studies with more rigorous methodological approaches in terms of study protocol, ASL technique and sample selection and size are mandatory to exploit the possibility of better understanding migraine pathophysiology and identifying neuroimaging biomarkers of each migraine phase in different migraine phenotypes.

Cognitive, behavioral, and brain functional connectivity correlates of fatigue in amyotrophic lateral sclerosis.

INTRODUCTION: Fatigue is defined as a symptom of exhaustion unexplained by drug effects or psychiatric disorders and comprises two main components (i.e., central or "mental" and peripheral or "physical" components), both influencing global disability in amyotrophic lateral sclerosis (ALS). We aim at investigating the clinical correlations between "physical" and "mental" components of fatigue, measured by the Multidimensional Fatigue Inventory scale, and motor and cognitive/behavioral disability in a large sample of patients with ALS. We also investigated the correlations between these measures of fatigue and resting-state functional connectivity of brain functional magnetic resonance imaging (RS-fMRI) large-scale networks in a subset of patients. METHODS: One hundred and thirty ALS patients were assessed for motor disability, cognitive and behavioral dysfunctions, fatigue, anxiety, apathy, and daytime sleepiness. Moreover, the collected clinical parameters were correlated with RS-fMRI functional connectivity changes in the large-scale brain networks of 30 ALS patients who underwent MRI. RESULTS: Multivariate correlation analysis revealed that "physical" fatigue was related to anxiety and respiratory dysfunction, while "mental" fatigue was related to memory impairment and apathy. Moreover, the mental fatigue score was directly related to functional connectivity in the right and left insula (within the salience network), and inversely related to functional connectivity in the left middle temporal gyrus (within the default mode network). CONCLUSIONS: Although the "physical" component of fatigue may be influenced by the disease itself, in ALS the "mental" component of fatigue correlates with cognitive and behavioral impairment, as well as with alterations of functional connectivity in extra-motor networks.

Olfactory Loss and Brain Connectivity after COVID-19: Structural Follow-Up at One Year.

The structural connectivity from the primary olfactory cortex to the main secondary olfactory areas was previously reported as relatively increased in the medial orbitofrontal cortex in a cohort of 27 recently SARS-CoV-2-infected (COV+) subjects, of which 23/27 had clinically confirmed olfactory loss, compared to 18 control (COV-) normosmic subjects, who were not previously infected. To complement this finding, here we report the outcome of an identical high angular resolution diffusion MRI analysis on follow-up data sets collected in 18/27 COV+ subjects (10 males, mean age ± SD: 38.7 ± 8.1 years) and 10/18 COV- subjects (5 males, mean age ± SD: 33.1 ± 3.6 years) from the previous samples who repeated both the olfactory functional assessment and the MRI examination after ~1 year. By comparing the newly derived subgroups, we observed that the increase in the structural connectivity index of the medial orbitofrontal cortex was not significant at follow-up, despite 10/18 COV+ subjects were still found hyposmic after ~1 year from SARS-CoV-2 infection. We concluded that the relative hyperconnectivity of the olfactory cortex to the medial orbitofrontal cortex could be, at least in some cases, an acute or reversible phenomenon linked to the recent SARS-CoV-2 infection with associated olfactory loss.

Subacute changes in brain functional network connectivity after nocturnal sodium oxybate intake are associated with anterior cingulate GABA.

Sodium oxybate (γ-hydroxybutyrate, GHB) is an endogenous GHB/GABAB receptor agonist, clinically used to promote slow-wave sleep and reduce next-day sleepiness in disorders such as narcolepsy and fibromyalgia. The neurobiological signature of these unique therapeutic effects remains elusive. Promising current neuropsychopharmacological approaches to understand the neural underpinnings of specific drug effects address cerebral resting-state functional connectivity (rsFC) patterns and neurometabolic alterations. Hence, we performed a placebo-controlled, double-blind, randomized, cross-over pharmacological magnetic resonance imaging study with a nocturnal administration of GHB, combined with magnetic resonance spectroscopy of GABA and glutamate in the anterior cingulate cortex (ACC). In sum, 16 healthy male volunteers received 50 mg/kg GHB p.o. or placebo at 02:30 a.m. to maximize deep sleep enhancement and multi-modal brain imaging was performed at 09:00 a.m. of the following morning. Independent component analysis of whole-brain rsFC revealed a significant increase of rsFC between the salience network (SN) and the right central executive network (rCEN) after GHB intake compared with placebo. This SN-rCEN coupling was significantly associated with changes in GABA levels in the ACC (pall < 0.05). The observed neural pattern is compatible with a functional switch to a more extrinsic brain state, which may serve as a neurobiological signature of the wake-promoting effects of GHB.

Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative.

The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.