Papers by Christos Papadelis
PloS one, 2012
Acute alcohol intake is known to enhance inhibition through facilitation of GABA A receptors, whi... more Acute alcohol intake is known to enhance inhibition through facilitation of GABA A receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN). To test our hypothesis, electroencephalographic (EEG) measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC) on standardized Low Resolution Electromagnetic Tomography (sLORETA) solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p,0.05, corrected with False Discovery Rate, FDR corrected) in alpha, beta (eyesopen) and theta bands (eyes-closed) following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p,0.05). Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo). Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially-be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as expected, to increased GABA transmission and functional connectivity, while long-term alcohol consumption may be linked to exactly the opposite effect. Citation: Lithari C, Klados MA, Pappas C, Albani M, Kapoukranidou D, et al. (2012) Alcohol Affects the Brain's Resting-State Network in Social Drinkers. PLoS ONE 7(10): e48641.
Coordination between vision and action relies on a fronto-parietal network that receives visual a... more Coordination between vision and action relies on a fronto-parietal network that receives visual and proprioceptive sensory input in order to compute motor control signals. Here, we investigated with magnetoencephalography (MEG) which cortical areas are functionally coupled on the basis of synchronization during visuomotor integration. MEG signals were recorded from twelve healthy adults while performing a unimanual visuomotor (VM) task and control conditions. The VM task required the integration of pinch motor commands with visual sensory feedback. By using a beamformer, we localized the neural activity in the frequency range of 1–30 Hz during the VM compared to rest. Virtual sensors were estimated at the active locations. A multivariate autoregressive model was used to estimate the power and coherence of estimated activity at the virtual sensors. Event-related desynchronisation (ERD) during VM was observed in early visual areas, the rostral part of the left inferior frontal gyrus (IFG), the right IFG, the superior parietal lobules, and the left hand motor cortex (M1). Functional coupling in the alpha frequency band bridged the regional activities observed in motor and visual cortices (the start and the end points in the visuomotor loop) through the left or right IFG. Coherence between the left IFG and left M1 correlated inversely with the task performance. Our results indicate that an occipital-prefrontal-motor functional network facilitates the modulation of instructed motor responses to visual cues. This network may supplement the mechanism for guiding actions that is fully incorporated into the dorsal visual stream.
Introduction The primary goal of neuroimaging is to help determine the etiology of neonatal seizu... more Introduction The primary goal of neuroimaging is to help determine the etiology of neonatal seizures, which in turn helps to guide clinical management and prognosis. Neuroimaging serves as a complement to the clinical examination, electroencepahalography (EEG) evaluation and laboratory investigations and must be interpreted in this context. The most common neuroimaging modalities used in the evaluation of neonatal seizures are ultrasound and magnetic resonance imaging (MRI). Ultrasound is a non-invasive, inexpensive , bedside screening tool typically used to search for hemorrhage or hydrocephalus when a neonate, especially a preterm or unstable neonate, presents with seizures. Computed tomography (CT) may be performed to provide an urgent assessment when there is concern for fractures or hemorrhage. Otherwise, CT is rarely performed unless MRI is unavailable because of the exposure to ionizing radiation as well as the lower sensitivity and specificity for diagnosing brain disorders associated with seizures compared to MRI. MRI is the modality of choice when seizures are identified because of the multiple contrast mechanisms and rich physiological information it provides. In most institutions, neonatal MRI can be performed without sedation or anesthesia, making it an insignificant risk study. In this chapter we will provide an overview of ultrasound and MRI technologies as well as imaging findings in the most common disorders associated with neonatal seizures. We conclude with a brief discussion on the emerging role of near infrared spectroscopy (NIRS) and magnetoencephalography (MEG).
Multichannel real time system that automatically identifies burst-suppression. Estimates burst-su... more Multichannel real time system that automatically identifies burst-suppression. Estimates burst-suppression index using neural network technology. Excellent agreement between automated and manual classification of burst-suppression. a b s t r a c t Objective: To develop a real-time monitoring system that has the potential to guide the titration of anesthetic agents in the treatment of pediatric status epilepticus (SE). Methods: We analyzed stored multichannel electroencephalographic (EEG) data collected from 12 pedi-atric patients with generalized SE. EEG recordings were initially segmented in 500 ms time-windows. Features characterizing the power, frequency, and entropy of the signal were extracted from each segment. The segments were annotated as bursts (B), suppressions (S), or artifacts (A) by two electroen-cephalographers. The EEG features together with the annotations were inputted in a three-layer feed forward neural network (NN). The sensitivity and specificity of NNs with different architectures and training algorithms to classify segments into B, S, or A were estimated. Results: The maximum sensitivity (95.96% for B, 89.25% for S, and 75% for A) and specificity (89.36 for B, 96.26% for S, and 99.8% for A) was observed for the NN with 10 nodes in the hidden layer. By using this NN, we designed a real-time system that estimates the burst-suppression index (BSI). Conclusions: Our system provides a reliable real-time estimate of multichannel BSI requiring minimal memory and computation time. Significance: The system has the potential to assist intensive care unit attendants in the continuous EEG monitoring.
Over the past three decades, insights into the role of the cerebellum in emotional processing hav... more Over the past three decades, insights into the role of the cerebellum in emotional processing have substantially increased. Indeed, methodological refinements in cerebellar le-sion studies and major technological advancements in the field of neuroscience are in particular responsible to an exponential growth of knowledge on the topic. It is timely to review the available data and to critically evaluate the current status of the role of the cerebellum in emotion and related domains. The main aim of this article is to present an overview of current facts and ongoing debates relating to clinical, neuroimaging, and neurophysiological findings on the role of the cerebellum in key aspects of emotion. Experts in the field of cerebellar research discuss the range of cerebellar contributions to emotion in nine topics. Topics include the role of the cerebellum in perception and recognition, forwarding and encoding of emotional information, and the experience and regulation of emotional states in relation to motor, cognitive, and social behaviors. In addition, perspectives including cerebellar involvement in emotional learning, pain, emotional aspects of speech, and neuropsychiatric aspects of the cerebellum in mood
Objective: The objective of this study is the development and evaluation of efficient neurophysio... more Objective: The objective of this study is the development and evaluation of efficient neurophysiological signal statistics, which may assess the driver's alertness level and serve as potential indicators of sleepiness in the design of an on-board countermeasure system. Methods: Multichannel EEG, EOG, EMG, and ECG were recorded from sleep-deprived subjects exposed to real field driving conditions. A number of severe driving errors occurred during the experiments. The analysis was performed in two main dimensions: the mac-roscopic analysis that estimates the ongoing temporal evolution of physiological measurements during the driving task, and the microscopic event analysis that focuses on the physiological measurements' alterations just before, during, and after the driving errors. Two independent neurophysiologists visually interpreted the measurements. The EEG data were analyzed by using both linear and non-linear analysis tools. Results: We observed the occurrence of brief paroxysmal bursts of alpha activity and an increased synchrony among EEG channels before the driving errors. The alpha relative band ratio (RBR) significantly increased, and the Cross Approximate Entropy that quantifies the synchrony among channels also significantly decreased before the driving errors. Quantitative EEG analysis revealed significant variations of RBR by driving time in the frequency bands of delta, alpha, beta, and gamma. Most of the estimated EEG statistics, such as the Shannon Entropy, Kullback–Leibler Entropy, Coherence, and Cross-Approximate Entropy, were significantly affected by driving time. We also observed an alteration of eyes blinking duration by increased driving time and a significant increase of eye blinks' number and duration before driving errors. Conclusions: EEG and EOG are promising neurophysiological indicators of driver sleepiness and have the potential of monitoring sleepi-ness in occupational settings incorporated in a sleepiness countermeasure device. Significance: The occurrence of brief paroxysmal bursts of alpha activity before severe driving errors is described in detail for the first time. Clear evidence is presented that eye-blinking statistics are sensitive to the driver's sleepiness and should be considered in the design of an efficient and driver-friendly sleepiness detection countermeasure device.
Magnetoencephalography for Clinical Pediatrics: Recent Advances in Hardware, Methods, and Clinical Applications
Journal of Pediatric Epilepsy, 2015
Medical informatics in a united and healthy
The role of delta oscillations to emotional processing of visual stimuli
Cognitive functions are the result of the interaction between assemblies of neurons located in th... more Cognitive functions are the result of the interaction between assemblies of neurons located in the brain and organized in networks. The activation of such networks due to a stimulus (e.g. acoustic or visual) can be observed as changes of on-going signals recorded either by EEG or MEG. The most common way to observe these changes is by ERP analysis. However, during the past decade neuroscientists have recognized the importance of oscillatory analysis. The main portion of oscillatory analysis of cognitive processing is focused till now on specific frequency bands (e.g. theta, alpha, but till now analysis of delta oscillations is not very extensive. Consequently, the place of generation of delta activity is not certain. Previous studies indicate a significant increase of delta activity during sexual arousal and orgasm. More precisely, under the above condition there is suppression of alpha activity and increase of delta oscillations even with the view of erotic films. The above changes...
Autonomic changes in psychogenic nonepileptic seizures: toward a potential diagnostic biomarker?
Clinical EEG and neuroscience, 2015
Disturbances of the autonomic nervous system (ANS) are common in neuropsychiatric disorders. Dise... more Disturbances of the autonomic nervous system (ANS) are common in neuropsychiatric disorders. Disease specific alterations of both sympathetic and parasympathetic activity can be assessed by heart rate variability (HRV), whereas electrodermal activity (EDA) can assess sympathetic activity. In posttraumatic stress disorder (PTSD), parasympathetic HRV parameters are typically decreased and EDA is increased, whereas in major depressive disorder (MDD) and dissociation, both parasympathetic and sympathetic markers are decreased. ANS abnormalities have also been identified in psychogenic nonepileptic seizures (PNES) by using HRV, indicating lower parasympathetic activity at baseline. In addition to reviewing the current literature on ANS abnormalities in PTSD, MDD, and disorders with prominent dissociation, including borderline personality disorder (BPD), this article also presents data from a pilot study on EDA in patients with PNES. Eleven patients with PNES, during an admission to our e...
The dissociability of nouns and verbs and of their morphosyntactic operations has been firmly est... more The dissociability of nouns and verbs and of their morphosyntactic operations has been firmly established by lesion data. However, the hypothesis that they are processed by distinct neural substrates is inconsistently supported by neuroimaging studies. We tackled this issue in a silent reading experiment during MEG. Participants silently read noun/verb homonyms in minimal syntactic context: article-noun (NPs), pronoun-verb (VPs) (e.g., il ballo/i balli, the dance/the dances; io ballo/tu balli, I dance/you dance). Homonyms allow to rule out prelexical or postlexical nuisance factors-they are orthographically and phonologically identical, but serve different grammatical functions depending on context. Under these experimental conditions, different activity to nouns and verbs can be confidently attributed to representational/processing distinctions. At the sensor level, three components of event-related magnetic fields were observed for the function word and four for the content word, but Global Field Power (GFP) analysis only showed differences between VPs and NPs at several but very short time windows. By contrast, source level analysis based on Minimum Norm Estimates (MNE) yielded significantly greater activity for VPs in left frontal areas and in a left frontoparietal network at late time windows (380-397 and 393-409 ms). These results are fully consistent with lesion data, and show that verbs and nouns are processed differently in the brain. Frontal and parietal activation to verbs might correspond to morphosyntactic processes and to working memory recruitment (or thematic role assignment), respectively. Findings are consistent with the view that nouns and verbs and their morphosyntactic operations involve at least partially distinct neural substrates. However, they do not entirely rule out that nouns and verbs are processed in a shared neural substrate, and that differences result from greater complexity of verbal morphosyntax.
2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007
For the purposes of insomnia treatment, pharmacotherapy is widely used, despite the possibility f... more For the purposes of insomnia treatment, pharmacotherapy is widely used, despite the possibility for the use of behavioural treatment of insomnia. Thus, the assessment and treatment of patients with insomnia needs further investigation. This work addresses insomnia treatment evaluation and medication side-effect assessment based on continuous physiological signals such as EEG and ECG monitoring and analysis. EEG and ECG measurements regarding drug medication (verum/placebo cases) have been used in a series of experiments, where spectral and non-linear features have been calculated, for assessing a possible distinct behaviour between the verum/placebo condition and furthermore the relation of features to a physiological conditions. Results show that a combination of EEG and ECG based characteristics, both spectral and non-linear, can be used to reveal the differences introduced with insomnia medication treatment, either being improvement in the hyperarousal state, or undesired side effects.
On the classification of emotional biosignals evoked while viewing affective pictures: an integrated data mining based approach for healthcare applications.
Recent neuroscience findings demonstrate the fundamental role of emotion in the maintenance of ph... more Recent neuroscience findings demonstrate the fundamental role of emotion in the maintenance of physical and mental health. In the present study, a novel architecture is proposed for the robust discrimination of emotional physiological signals evoked upon viewing pictures selected from the International Affective Picture System (IAPS). Biosignals are multi-channel recordings from both the central and the autonomic nervous systems. Following the bi-directional emotion theory model, IAPS pictures are rated along two dimensions, namely, their valence and arousal. Following this model, biosignals in this paper are initially differentiated according to their valence dimension by means of a data mining approach, that is the C4.5 decision tree algorithm. Then, the valence and the gender information serve as an input to a Mahalanobis distance classifier, which dissects the data into high and low arousing. Results are described in XML format, thereby accounting for platform independency, easy inter-connectivity and information exchange. The average recognition (success) rate was 77.68% for the discrimination of four emotional states differing both in theirarousal and valence dimension. It is therefore, envisaged that the proposed approach holds promise for the efficient discrimination of negative and positive emotions and it is hereby discussed how future developments may be steered to serve for affective healthcare applications such as the monitoring of the elderly or chronically ill people.
Studies in health …, Jan 1, 2007
Source: PubMed CITATIONS 9 READS 25 7 authors, including:
Clinical Neurophysiology, 2007
Objective: The objective of this study is the development and evaluation of efficient neurophysio... more Objective: The objective of this study is the development and evaluation of efficient neurophysiological signal statistics, which may assess the driver's alertness level and serve as potential indicators of sleepiness in the design of an on-board countermeasure system. Methods: Multichannel EEG, EOG, EMG, and ECG were recorded from sleep-deprived subjects exposed to real field driving conditions. A number of severe driving errors occurred during the experiments. The analysis was performed in two main dimensions: the macroscopic analysis that estimates the on-going temporal evolution of physiological measurements during the driving task, and the microscopic event analysis that focuses on the physiological measurements' alterations just before, during, and after the driving errors. Two independent neurophysiologists visually interpreted the measurements. The EEG data were analyzed by using both linear and nonlinear analysis tools. Results: We observed the occurrence of brief paroxysmal bursts of alpha activity and an increased synchrony among EEG channels before the driving errors. The alpha relative band ratio (RBR) significantly increased, and the Cross Approximate Entropy that quantifies the synchrony among channels also significantly decreased before the driving errors. Quantitative EEG analysis revealed significant variations of RBR by driving time in the frequency bands of delta, alpha, beta, and gamma. Most of the estimated EEG statistics, such as the Shannon Entropy, Kullback-Leibler Entropy, Coherence, and Cross-Approximate Entropy, were significantly affected by driving time. We also observed an alteration of eyes blinking duration by increased driving time and a significant increase of eye blinks' number and duration before driving errors. Conclusions: EEG and EOG are promising neurophysiological indicators of driver sleepiness and have the potential of monitoring sleepiness in occupational settings incorporated in a sleepiness countermeasure device. Significance: The occurrence of brief paroxysmal bursts of alpha activity before severe driving errors is described in detail for the first time. Clear evidence is presented that eye-blinking statistics are sensitive to the driver's sleepiness and should be considered in the design of an efficient and driver-friendly sleepiness detection countermeasure device.
… in Medicine and …, Jan 1, 2007
In the context of generating new home based insomnia treatment procedures which incorporate novel... more In the context of generating new home based insomnia treatment procedures which incorporate novel sensors systems and biosignal processing methodologies, this work addresses insomnia treatment evaluation and medication side-effect assessment based on continuous physiological signals monitoring and analysis. For this purpose, EEG and ECG have been recorded in a series of experiments regarding drug medication (verum/placebo cases), where various features have been calculated and processed. Results show that a combination of EEG and ECG based characteristics, both spectral and non-linear, can be used to reveal the differences introduced with insomnia medication treatment, either being improvement in the hyperarousal state, or undesired side effects.
Human Brain Mapping, 2014
Animal, as well as behavioural and neuroimaging studies in humans have documented integration of ... more Animal, as well as behavioural and neuroimaging studies in humans have documented integration of bilateral tactile information at the level of primary somatosensory cortex (SI). However, it is still debated whether integration in SI occurs early or late during tactile processing, and whether it is somatotopically organized. To address both the spatial and temporal aspects of bilateral tactile processing we used magnetoencephalography in a tactile repetition-suppression paradigm. We examined somatosensory evoked-responses produced by probe stimuli preceded by an adaptor, as a function of the relative position of adaptor and probe (probe always at the left index finger; adaptor at the index or middle finger of the left or right hand) and as a function of the delay between adaptor and probe (0, 25, or 125 ms). Percentage of response-amplitude suppression was computed by comparing paired (adaptor 1 probe) with single stimulations of adaptor and probe. Results show that response suppression varies differentially in SI and SII as a function of both spatial and temporal features of the stimuli. Remarkably, repetition suppression of SI activity emerged early in time, regardless of whether the adaptor stimulus was presented on the same and the opposite body side with respect to the probe. at the fingers; MEG r r r Early Integration of Bilateral Touch in SI r r 3 r r Early Integration of Bilateral Touch in SI r r 15 r
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
Driver sleepiness due to sleep deprivation is a causative factor in 1% to 3% of all motor vehicle... more Driver sleepiness due to sleep deprivation is a causative factor in 1% to 3% of all motor vehicle crashes. In recent studies, the importance of developing driver fatigue countermeasure devices has been stressed, in order to help prevent driving accidents and errors. Although numerous physiological indicators are available to describe an individual's level of alertness, the EEG signal has been shown to be one of the most predictive and reliable, since it is a direct measure of brain activity. In the present study, multichannel EEG data that were collected from 20 sleep-deprived subjects during real environmental conditions of driving are presented for the first time. EEG data's annotation made by two independent Medical Doctors revealed an increase of slowing activity and an acute increase of the alpha waves 5-10 seconds before driving events. From the EEG data that were collected, the Relative Band Ratio (RBR) of the EEG frequency bands, the Shannon Entropy, and the Kullback-Leibler (KL) Entropy were estimated for each one second segment. The mean values of these measurements were estimated for 5 minutes periods. Analysis revealed a significant increase of alpha waves relevant band ratios (RBR), a decrease of gamma waves RBR, and a significant decrease of KL entropy when the first and the last 5-min periods were compared. A rapid decrease of both Shannon and K-L entropies was observed just before the driving events. Conclusively, EEG can assess effectively the brain activity alterations that occur a few seconds before sleeping/drowsiness events in driving, and its quantitative measurements can be used as potential sleepiness Manuscript
Procedia - Social and Behavioral Sciences, 2010
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Papers by Christos Papadelis