Andreas Koupparis

Dr. Andreas Koupparis

Cyprus Institute of Neurology and Genetics, Nicosia, Lefkosía, Cyprus
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Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2013 in Frontiers in Human Neuroscience
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Kokkinos VasileiosKokkinos Vasileios
Kokkinos Vasileios
AKAndreas Koupparis
Andreas Koupparis
GKGeorge K. Kostopoulos
George K. Kostopoulos
NREM sleep is characterized by K-complexes (KCs), over the negative phase of which we identified brief activity in the theta range. We recorded high resolution EEG of whole-night sleep from 7 healthy volunteers and visually identified 2nd and 3rd stage NREM spontaneous KCs. We identified 3 major categories: a) KCs without intra-KC-activity (iKCa), b) KCs with non-oscillatory iKCa, and c) KCs with oscillatory iKCa. The latter group of KCs with intra-KC-oscillation (iKCo), was clustered according to the duration of the iKCo. iKCa was observed in most KCs (1150/1522, 75%). iKCos with 2, 3 and 4 waves were observed in 52% (786/1522) of KCs in respective rates of 49% (386/786), 44% and 7%. Successive waves of iKCos showed on average a shift of their maximal amplitude in the anterio-posterior axis, while the average amplitude of the slow KC showed no spatial shift in time. The iKCo spatial shift was accompanied by transient increases in instantaneous frequency from the theta band towards the alpha band, followed by decreases to upper theta. The study shows that the KC is most often concurrently accompanied by an independent brief iKCo exhibiting topographical relocation of amplitude maxima with every consecutive peak and transient increases in frequency. The iKCo features are potentially reflecting arousing processes taking place during the KC.

12 October 2021 in Neurology
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AKAndreas Koupparis
Andreas Koupparis
NENicolás von Ellenrieder
Nicolás von Ellenrieder
HKHui Ming Khoo
Hui Ming Khoo
NZNatalja Zazubovits
Natalja Zazubovits
DNDang Khoa Nguyen
Dang Khoa Nguyen
JGJean Gotman
Jean Gotman
Objective: To assess the utility of EEG-fMRI for epilepsy surgery, we evaluated surgical outcome in relation to the resection of the most significant EEG-fMRI response. Methods: Patients with post-operative neuroimaging and follow-up of at least one year were included. In EEG-fMRI responses, we defined as “primary” the cluster with the highest absolute t-value located in the cortex, and evaluated three levels of confidence for the results. The threshold for low confidence was t ≥ 3.1 (p < 0.005); the one for medium confidence corresponded to correction for multiple comparisons with a false discovery rate of 0.05; and a result reached high confidence when the primary cluster was much more significant than the next highest cluster. Concordance with the resection was determined by comparison to post-operative neuroimaging. Results: We evaluated 106 epilepsy surgeries in 84 patients. An increasing association between concordance and surgical outcome with higher levels of confidence was demonstrated. If the peak response was not resected, the surgical outcome was likely to be poor: for the high confidence level, no patient had a good outcome; for the medium and low levels, only 18% and 28% had a good outcome. The positive predictive value remained low for all confidence levels, indicating that removing the maximum cluster did not ensure seizure freedom. Conclusion: Resection of the primary EEG-fMRI cluster, especially in high confidence cases, is necessary to obtain a good outcome, but not sufficient. Classification of Evidence: This study provided Class II evidence that failure to resect the primary EEG-fMRI cluster is associated with poorer epilepsy surgery outcomes.

1 June 2010 in Clinical Neurophysiology
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Kokkinos VasileiosKokkinos Vasileios
Kokkinos Vasileios
MKMichalis Koutroumanidis
Michalis Koutroumanidis
KTKaterina Tsatsou
Katerina Tsatsou
AKAndreas Koupparis
Andreas Koupparis
DTDIMITRIOS TSIPTSIOS
DIMITRIOS TSIPTSIOS
CPChrysostomos P. Panayiotopoulos
Chrysostomos P. Panayiotopoulos

17 February 2016 in Frontiers in Neuroinformatics
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Journal Article
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DSDimitris Sakellariou
Dimitris Sakellariou
AKAndreas Koupparis
Andreas Koupparis
Kokkinos VasileiosKokkinos Vasileios
Kokkinos Vasileios
MKMichalis Koutroumanidis
Michalis Koutroumanidis
GKGeorge K. Kostopoulos
George K. Kostopoulos
During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterise them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an “EEG-element connectivity” methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence of EEG microstructural elements. Network characterisation of specified physiological or pathological EEG microstructural elements can potentially be of great importance in the understanding, identification and prediction of health and disease.

19 December 2018 in SLEEP
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Kokkinos VasileiosKokkinos Vasileios
Kokkinos Vasileios
SVSerge Vulliémoz
Serge Vulliémoz
AKAndreas Koupparis
Andreas Koupparis
MKMichalis Koutroumanidis
Michalis Koutroumanidis
GKGeorge K Kostopoulos
George K Kostopoulos
KGKyriakos Garganis
Kyriakos Garganis
The cyclic alternating pattern (CAP) encompasses the pseudo-periodic appearance of synchronized brain waves and rhythms and is considered a regulator of the NREM sleep vigilance level, reflecting sleep instability. To determine the brain regions responsible for this phenomenon, we scored and analyzed sleep fMRI data acquired with simultaneous EEG (EEG-fMRI). Group analysis revealed a set of brain areas showing statistically significant blood oxygen-level dependent (BOLD) signal correlated positively with the synchronization phase of the CAP, most prominent being the insula, the middle cingulate gyrus, and the basal forebrain. These areas may form a network acting as a synchronization pacemaker, controlling the level of NREM sleep vigilance and the sleeper’s arousability.

Verified
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MPMaria Pechlivanidou
Maria Pechlivanidou
IKIoanna Kousiappa
Ioanna Kousiappa
SAStella Angeli
Stella Angeli
ISIrene Sargiannidou
Irene Sargiannidou
AKAndreas Koupparis
Andreas Koupparis
Kleopas KleopaKleopas Kleopa
Kleopas Kleopa
Gap junctions (GJs) are specialized transmembrane channels assembled by two hemi-channels of six connexin (Cx) proteins that facilitate neuroglial crosstalk in the central nervous system (CNS). Previous studies confirmed the crucial role of glial GJs in neurodegenerative disorders with dementia or motor dysfunction including Alzheimer’s disease (AD). The aim of this study was to examine the alterations in astrocyte and related oligodendrocyte GJs in association with Aβ plaques in the spinal cord of the 5xFAD mouse model of AD. Our analysis revealed abundant Aβ plaque deposition, activated microglia, and astrogliosis in 12-month-old (12M) 5xFAD mice, with significant impairment of motor performance starting from 3-months (3M) of age. Additionally, 12M 5xFAD mice displayed increased immunoreactivity of astroglial Cx43 and Cx30 surrounding Aβ plaques and higher protein levels, indicating upregulated astrocyte-to-astrocyte GJ connectivity. In addition, they demonstrated increased numbers of mature CC1-positive and precursor oligodendrocytes (OPCs) with higher immunoreactivity of Cx47-positive GJs in individual cells. Moreover, total Cx47 protein levels were significantly elevated in 12M 5xFAD, reflecting increased oligodendrocyte-to-oligodendrocyte Cx47–Cx47 GJ connectivity. In contrast, we observed a marked reduction in Cx32 protein levels in 12M 5xFAD spinal cords compared with controls, while qRT-PCR analysis revealed a significant upregulation in Cx32 mRNA levels. Finally, myelin deficits were found focally in the areas occupied by Aβ plaques, whereas axons themselves remained preserved. Overall, our data provide novel insights into the altered glial GJ expression in the spinal cord of the 5xFAD model of AD and the implicated role of GJ pathology in neurodegeneration. Further investigation to understand the functional consequences of these extensive alterations in oligodendrocyte–astrocyte (O/A) GJ connectivity is warranted.