Ricerc@Sapienza

Meditation has been integrated into different therapeutic interventions. To inform the evidence-based selection of specific meditation types it is crucial to understand the neural processes associated with different meditation practices. Here we explore commonalities and differences in electroencephalographic oscillatory spatial synchronisation patterns across three important meditation types. Highly experienced meditators engaged in focused attention, open monitoring, and loving kindness meditation.

Rhythmic non-invasive brain stimulations are promising tools to modulate brain activity by entraining neural oscillations in specific cortical networks. The aim of the study was to assess the possibility to influence the neural circuits of the wake-sleep transition in awake subjects via a bilateral transcranial alternating current stimulation at 5 Hz (theta-tACS) on fronto-temporal areas. 25 healthy volunteers participated in two within-subject sessions (theta-tACS and sham), one week apart and in counterbalanced order.

Many applications Internet-of-things (loT) based exploit Distributed Measurement System (DMS) to acquire data from sensors equipping objects or measurement instruments constituting the DMS nodes. The heterogeneity of the smart objects used to develop IoT applications has become a challenge in the design of the DMS, and very strong is the need to move towards new paradigm for programming and managing such systems. In fact, a current major limitation in the DMS development is the requirement of a deep knowledge about the different programming language and communication protocols.

Muscular fatigue occurs when motor units are no longer able to maintain an established force level. From an electromyographic point of view, fatigue is associated with a decrement of median frequency of contracting fibers. When the muscle is exposed to mechanical vibration, it undergoes a superimposition of voluntary contraction and stretch reflex, latter being synchronized to the mechanical frequency. The present paper is aimed to study the changes of muscular synchronization in long-lasting muscular tasks using a specific index change (?SL).

Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, affecting about 65 millions individuals worldwide. Objective: This work proposes a patient-specific approach for short-term prediction (i.e., within few minutes) of epileptic seizures. Methods: We use noninvasive EEG data, since the aim is exploring the possibility of developing a noninvasive monitoring/control device for the prediction of seizures. Our approach is based on finding synchronization patterns in the EEG that allow to distinguish in real time preictal from interictal states.