Publications by authors named "E Sarrias-Arrabal"

The aim of this study was to describe the spectral features of pre-stimulus event-related potential (ERP) components elicited in visual tasks such as the Bereitschaftspotential (BP), prefrontal negativity (pN) and visual negativity (vN). ERPs are considered time-locked and phase-locked (evoked) activity, but we have also analyzed the non-phase but time-locked (induced) activity in the same interval by applying the temporal spectral evolution (TSE) method. Participants (N = 26) were tested in a passive task, a simple response task (SRT) and a discriminative response task (DRT), where EEG activity was recorded with 64 scalp electrodes.

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Background And Objectives: Intermittent theta-burst stimulation (iTBS) is a patterned form of excitatory transcranial magnetic stimulation that has yielded encouraging results as an adjunctive therapeutic option to alleviate the emergence of clinical deficits in Parkinson's disease (PD) patients. Although it has been demonstrated that iTBS influences dopamine-dependent corticostriatal plasticity, little research has examined the neurobiological mechanisms underlying iTBS-induced clinical enhancement. Here, our primary goal is to verify whether iTBS bilaterally delivered over the primary motor cortex (M1) is effective as an add-on treatment at reducing scores for both motor functional impairment and nonmotor symptoms in PD.

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Recent studies have suggested that nonphase-locked activity can reveal cognitive mechanisms that cannot be observed in phase-locked activity. In fact, we describe a concomitant decrease in nonphase-locked alpha activity (desynchronization) when stimuli were processed (alpha phase-locked modulation). This desynchronization may represent a reduction in "background activity" in the visual cortex that facilitates stimulus processing.

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Introduction: The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

Objective: We present a systematic review of the application of ML algorithms in MS.

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