by Keyword: EEG

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Pacheco Estefan, D., Zucca, Riccardo, Arsiwalla, X. D., Principe, A., Zhang, Hui, Rocamora, R., Axmacher, N., Verschure, P., (2021). Volitional learning promotes theta phase coding in the human hippocampus Proceedings of the National Academy of Sciences of the United States of America 118, (10), e2021238118

Electrophysiological studies in rodents show that active navigation enhances hippocampal theta oscillations (4–12 Hz), providing a temporal framework for stimulus-related neural codes. Here we show that active learning promotes a similar phase coding regime in humans, although in a lower frequency range (3–8 Hz). We analyzed intracranial electroencephalography (iEEG) from epilepsy patients who studied images under either volitional or passive learning conditions. Active learning increased memory performance and hippocampal theta oscillations and promoted a more accurate reactivation of stimulus-specific information during memory retrieval. Representational signals were clustered to opposite phases of the theta cycle during encoding and retrieval. Critically, during active but not passive learning, the temporal structure of intracycle reactivations in theta reflected the semantic similarity of stimuli, segregating conceptually similar items into more distant theta phases. Taken together, these results demonstrate a multilayered mechanism by which active learning improves memory via a phylogenetically old phase coding scheme.

Keywords: Active learning, Intracranial EEG, Theta oscillations, Neural phase coding, Hippocampus

Casals, Alicia, Fedele, Pasquale, Marek, Tadeusz, Molfino, Rezia, Muscolo, GiovanniGerardo, Recchiuto, CarmineTommaso, (2014). A robotic suit controlled by the human brain for people suffering from quadriplegia Lecture Notes in Computer Science Towards Autonomous Robotic Systems (ed. Natraj, Ashutosh, Cameron, Stephen, Melhuish, Chris, Witkowski, Mark), Springer Berlin Heidelberg , 294-295

The authors present an introductory work for the implementation of an international cooperative project aimed at designing, developing and validating a new generation of ergonomic robotic suits, wearable by the users and controlled by the human brain. The aim of the proposers is to allow the motion of people affected by paralysis or with reduced motor abilities. Therefore, the project will focus on the fusion between neuroergonomics and robotics, also by means of brain-machine interfaces. Breakthrough solutions will compose the advanced robotic suit, endowed with soft structures to increment safety and human comfort, and with an advanced real-time control that takes into account the interaction with the human body.

Keywords: Neuroergonomics, Brain computer interfaces, Robotics, Robotic suits, Compliant actuators, Exoskeleton, EEG, Dynamic balance control

Antelis, J.M., Montesano, L., Giralt, X., Casals, A., Minguez, J., (2012). Detection of movements with attention or distraction to the motor task during robot-assisted passive movements of the upper limb Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6410-6413

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

Mesquita, J., Poree, F., Carrault, G., Fiz, J. A., Abad, J., Jané, R., (2012). Respiratory and spontaneous arousals in patients with Sleep Apnea Hypopnea Syndrome Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6337-6340

Sleep in patients with Sleep Apnea-Hypopnea Syndrome (SAHS) is frequently interrupted with arousals. Increased amounts of arousals result in shortening total sleep time and repeated sleep-arousal change can result in sleep fragmentation. According to the American Sleep Disorders Association (ASDA) an arousal is a marker of sleep disruption representing a detrimental and harmful feature for sleep. The nature of arousals and its role on the regulation of the sleep process raises controversy and has sparked the debate in the last years. In this work, we analyzed and compared the EEG spectral content of respiratory and spontaneous arousals on a database of 45 SAHS subjects. A total of 3980 arousals (1996 respiratory and 1984 spontaneous) were analyzed. The results showed no differences between the spectral content of the two kinds of arousals. Our findings raise doubt as to whether these two kinds of arousals are truly triggered by different organic mechanisms. Furthermore, they may also challenge the current beliefs regarding the underestimation of the importance of spontaneous arousals and their contribution to sleep fragmentation in patients suffering from SAHS.

Keywords: Adaptive filters, Correlation, Databases, Electroencephalography, Hospitals, Sleep apnea, Electroencephalography, Medical signal processing, Pneumodynamics, Sleep, EEG spectral content, Organic mechanism, Respiratory, Sleep apnea hypopnea syndrome, Sleep fragmentation, Spectral content, Spontaneous arousal

Iranzo, A., Isetta, V., Molinuevo, J. L., Serradell, M., Navajas, D., Farre, R., Santamaria, J., (2010). Electroencephalographic slowing heralds mild cognitive impairment in idiopathic REM sleep behavior disorder Sleep Medicine , 11, (6), 534-539

Objective: Patients with idiopathic rapid eye movement (REM) sleep behavior disorder (IRBD) may show electroencephalographic (EEG) slowing reflecting cortical dysfunction and are at risk for developing neurological conditions characterized by cognitive dysfunction including mild cognitive impairment (MCI), dementia with Lewy bodies and Parkinson's disease with associated dementia. We hypothesized that those IRBD patients who later developed MCI had pronounced cortical EEG slowing at presentation. Methods: Power EEG spectral analysis was blindly quantified from the polysomnographic studies of 23 IRBD patients without cognitive complaints and 10 healthy controls without RBD. After a mean clinical follow-up of 2.40 +/- 1.55 years, 10 patients developed MCI (RBD + MCI) and the remaining 13 remained idiopathic. Results: Patients with RBD + MCI had marked EEG slowing (increased delta and theta activity) in central and occipital regions during wakefulness and REM sleep, particularly in the right hemisphere, when compared with controls and, to a lesser extent, with IRBD subjects who remained idiopathic. The EEG spectral pattern of the RBD + MCI group was similar to that seen in patients with dementia with Lewy bodies and Parkinson's disease associated with dementia. Conclusion: Our findings suggest that the presence of marked EEG slowing on spectral analysis might be indicative of the short-term development of MCI in patients initially diagnosed with IRBD.

Keywords: Idiopathic REM sleep behavior disorder, Power EEG spectral analysis, Mild cognitive impairment, REM sleep, Parkinson's disease, Dementia with Lewy bodies