9 results match your criteria: "Institute of Applied Sciences and Intelligent Systems of National Research Council[Affiliation]"

Measuring propagation of perturbations across the human brain and their transmission delays is critical for network neuroscience, but it is a challenging problem that still requires advancement. Here, we compare results from a recently introduced, noninvasive technique of functional delays estimation from source-reconstructed electro/magnetoencephalography, to the corresponding findings from a large dataset of cortico-cortical evoked potentials estimated from intracerebral stimulations of patients suffering from pharmaco-resistant epilepsies. The two methods yield significantly similar probabilistic connectivity maps and signal propagation delays, in both cases characterized with Pearson correlations greater than 0.

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Background: Brain connectome fingerprinting represents a recent and valid approach in assessing individual identifiability on the basis of the subject-specific brain functional connectome. Although this methodology has been tested and validated in several neurological diseases, its performance, reliability and reproducibility in healthy individuals has been poorly investigated. In particular, the impact of the changes in brain connectivity, induced by the different phases of the menstrual cycle (MC), on the reliability of this approach remains unexplored.

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The epilepsy diagnosis still represents a complex process, with misdiagnosis reaching 40%. We aimed at building an automatable workflow, helping the clinicians in the diagnosis of temporal lobe epilepsy (TLE). We hypothesized that neuronal avalanches (NA) represent a feature better encapsulating the rich brain dynamics compared to classically used functional connectivity measures (Imaginary Coherence; ImCoh).

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Altered spreading of fast aperiodic brain waves relates to disease duration in Amyotrophic Lateral Sclerosis.

Clin Neurophysiol

July 2024

Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy; Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France; Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy.

Objective: To test the hypothesis that patients affected by Amyotrophic Lateral Sclerosis (ALS) show an altered spatio-temporal spreading of neuronal avalanches in the brain, and that this may related to the clinical picture.

Methods: We obtained the source-reconstructed magnetoencephalography (MEG) signals from thirty-six ALS patients and forty-two healthy controls. Then, we used the construct of the avalanche transition matrix (ATM) and the corresponding network parameter nodal strength to quantify the changes in each region, since this parameter provides key information about which brain regions are mostly involved in the spreading avalanches.

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Three-dimensional motion analysis represents a quantitative approach to assess spatio-temporal and kinematic changes in health and disease. However, these parameters provide only segmental information, discarding minor changes of complex whole body kinematics characterizing physiological and/or pathological conditions. We aimed to assess how levodopa intake affects the whole body, analyzing the kinematic interactions during gait in Parkinson's disease (PD) through network theory which assess the relationships between elements of a system.

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Flexibility of Fast Brain Dynamics and Disease Severity in Amyotrophic Lateral Sclerosis.

Neurology

November 2022

From the Institute of Diagnosis and Treatment Hermitage Capodimonte (A.P., G.S.), Naples, Italy; Department of Motor Sciences and Wellness (E.T.L., R.M., A.R., G.S.), University of Naples "Parthenope", Italy; Department of Developmental and Social Psychology (M.L., F.L.), University of Rome "La Sapi

Background And Objectives: Amyotrophic lateral sclerosis (ALS) is a multisystem disorder, as supported by clinical, molecular, and neuroimaging evidence. As a consequence, predicting clinical features requires a description of large-scale neuronal dynamics. Normally, brain activity dynamically reconfigures over time, recruiting different brain areas.

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Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative pathology of the upper or lower motor neuron. Evaluation of ALS progression is based on clinical outcomes considering the impairment of body sites. ALS has been extensively investigated in the pathogenetic mechanisms and the clinical profile; however, no molecular biomarkers are used as diagnostic criteria to establish the ALS pathological staging.

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The present study aims at investigating the possible correlation between peripheral markers of inflammation and brain networks. Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease dominated by progressive motor impairment. Among the complex mechanisms contributing to the pathogenesis of the disease, neuroinflammation, which is associated with altered circulating cytokine levels, is suggested to play a prominent role.

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In the present article, we present the experimental results concerning the fine-tuning and optimization of superconducting quantum interference device (SQUID) parameters by thermal annealing. This treatment allows for the modification of the parameters in order to meet a specific application or to adjust the device parameters to prevent the increase of magnetic field noise and work instability conditions due to a different critical current with respect to the design value. In particular, we report the sensor critical current, the voltage-flux (V-Φ) characteristics and the spectral density of the magnetic field of SQUID magnetometers for different annealing temperatures.

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