This paper investigates the relation between mental engagement level and sustained attention in 9 healthy adults performing a Conners' "not-X" continuous performance test (CPT), while their electroencephalographic (EEG) activity was simultaneously acquired. Spectral powers were estimated extracted classical EEG frequency bands. The index (β/α) calculated employing four different cortical montages suggested by literature. Results show efficacy of measures detecting changes state its...

Two key ingredients of a successful neuro-rehabilitative intervention have been identified as intensive and repetitive training subject's active participation, which can be coupled in an robot-assisted training. To exploit these two elements, we recorded electroencephalography, electromyography kinematics signals from nine healthy subjects performing 2×2 factorial design protocol, with volitional intention robotic glove assistance factors. We quantitatively evaluated primary sensorimotor,...

Abstract The systematic observation and imagination of actions promotes acquisition motor skills. Furthermore, studies demonstrated that early sleep after practice enhances learning through an offline stabilization process. Here, we investigated behavioral effects neurodynamical correlates action imagery training (AO + MI-training) on in terms manual dexterity. Forty-five healthy participants were randomized into three groups receiving a 3 week intervention consisting AO MI-training...

Software programming is an acquired evolutionary skill originating from consolidated cognitive functions (i.e., attentive, logical, coordination, mathematic calculation, and language comprehension), but the underlying neurophysiological processes are still not completely known. In present study, we investigated compared brain activities supporting realistic programming, text code reading tasks, analyzing Electroencephalographic (EEG) signals 11 experienced programmers. Multichannel spectral...

Neuronal spike sorting algorithms are designed to retrieve neuronal network activity on a single-cell level from extracellular multiunit recordings with Microelectrode Arrays (MEAs). In typical analysis of MEA data, one algorithm is applied indiscriminately all electrode signals. However, this approach neglects the dependency algorithms’ performances signals properties at each channel, which require data-centric methods. Moreover, commonly performed off-line, time and memory consuming...

Objective: In the electroencephalogram (EEG) quadratic phase coupling (QPC) phenomenon indicates presence of non-linear interactions among brain rhythms that could affect interpretation their physiological meaning. We propose use bicoherence as a QPC quantification method to understand nature rhythm interplay. Methods: firstly provide simulation study show under which condition signal noise ratio (SNR) is reliable quantifier and how interpret results. Secondly, in light results, we applied...

Electroencephalography (EEG) to study brain functions has become fundamental in many research settings across very different protocols. Indeed, a plethora of processing methods have been developed, for both data preparation (pre-processing) and analysis. While an effect the pre-processing on signal is admitted accepted, there increasing effort better understand which extent such influence may affect analysis results, be best practices correct pre-processing. Pre-processing procedures include...

The increasingly widespread diffusion of wearable devices makes possible the continuous monitoring vital signs, such as heart rate (HR), variability (HRV), and breath signal. However, these usually do not record "gold-standard" signals, namely electrocardiography (ECG) respiratory activity, but a single photoplethysmographic (PPG) signal, which can be exploited to estimate HR activity. In addition, employ low sampling rates limit power consumption. Hence, proper methods should adopted...

A multiscale functional clustering approach is proposed to investigate the organization of epileptic networks during different sleep stages and in relation with occurrence seizures.Stereo-electroencephalographic signals from seven pharmaco-resistant patients (focal cortical dysplasia type II) were analyzed. The discrete wavelet transform provided a framework on which data-driven procedure was applied, based multivariate measures integration mutual information. most interacting clusters (FCs)...

When deciding how to pre-process EEG data, researchers need make a choice at each single step of the procedure among different possibilities, equally valid. Therefore, in this work, we illustrate these decisions may affect quality final cleaned data an Action Observation/Motor Imagery protocol, using quantitative indices. In particular, showed effect segmenting or not epochs around stimulus presentation time on independent component analysis (ICA) used for artifact removal. For ICA analysis,...

Magnetoencephalography (MEG) is a powerful tool for estimating brain connectivity with both good spatial and temporal resolution. It particularly helpful in epilepsy to characterize non-invasively the epileptic networks. However, using MEG map networks requires solving difficult inverse problem that introduces uncertainty activity localization measures. Our goal here was compare independent component analysis (ICA) followed by dipole source linearly constrained minimum-variance beamformer...

Flickering visual stimulation is known to evoke rhythmic oscillations in the electroencephalographic (EEG) activity, called steady-state visually evoked potentials (SSVEP). The presence of harmonic components EEG signals during SSVEP suggests non-linearity visual-system response stimulation, but nature this behavior has not been deeply understood. aim study quantitative evaluation and characterization non-linear phenomenon its interference with physiological alpha rhythm by means spectral...

Objective. The subthalamic nucleus (STN) is the most selected target for placement of Deep Brain Stimulation (DBS) electrode to treat Parkinson's disease. Its identification a delicate and challenging task which based on interpretation STN functional activity acquired through microelectrode recordings (MERs). Aim this work explore potentiality set 25 features build classification model discrimination MER signals belonging STN.Approach.We explored use different sets spike-dependent...

The color-word Stroop paradigm is a neuropsychological test often employed for the evaluation of cognitive processing when conflict between different attributes same visual stimulus present. In clinical environments, standard practice administration still based on paper supports and stopwatches. Thus, aim present pilot study was to investigate usability in completely computerized system administration. developed this made up following modules: i) PC stimuli data acquisition connected two...

This paper focuses on the analysis of experienced programmers' central nervous system response during a software development protocol. The main aim was to explore neurological mechanisms (i.e., involved brain areas and rhythms) triggered by such complex task. To do this, 29-channel EEG signal acquired ten programmers development-like exercise. Then, power spectral density at each channel in standard Delta, Theta, Alpha Beta bands has been computed evaluated. subjects show average significant...

Attention-deficit hyperactivity disorder (ADHD) is a neurobiological condition mostly affecting children. The diagnosis and treatment of ADHD has been controversial subject among researchers. In this study, we analyzed the accountability using theta/beta ratio beta activations as EEG-based biomarkers for assessing brain activity acquired during an attention task in children (n = 7) normal control subjects 7). showed reduced higher at rest, line with previous research findings. Furthermore,...

Electroencephalography (EEG) has been widely used for the search of robust biomarkers to characterize neurodevelopmental disorders, such as Attention-Deficit/Hyperactivity Disorder (ADHD). Besides classical spectral measures, brain functional connectivity is emerging in last years and ADHD associated with network abnormalities respect normally developing children. Such a finding obtained reproduced mainly during resting-state periods, thus changing patterns cognitive task are still...

The objective of this work was to design and experiment a robotic hand rehabilitation device integrated with wireless EEG system, going towards patient active participation maximization during the exercise. This has been done through i) movement actively triggered by patients muscular activity as revealed electromyographic signals (i.e., target for session is defined, required start only when overcomes predefined threshold, patient-initiated supported); ii) an EEG-based biofeedback...

Action Observation Therapy (AOT) is a rehabilitation method which aims at stimulating motor memory by means of the repetitive observation tasks presented through video-clips. Since sleep seems to have positive effect on learning processes, it reasonable hypothesize that delivery AOT immediately before hours could enhance effects training. The objective present work was test delivered in terms improvements manual dexterity and changes cortical activity Electroencephalography (EEG) healthy...

In this study, a functional clustering approach is proposed and tested for the identification of brain networks emerging during sleep-related seizures. Stereo-EEG signals recorded in patients with Type II Focal Cortical Dysplasia (FCD type II), were analyzed. This novel able to identify network configuration changes pre-ictal early ictal periods, by grouping on basis Cluster Index, after wavelet multiscale decomposition. Results showed that method detect clusters interacting leads, mainly...