Biomedical subjects

Sifis Micheloyannis

Publications and source records attributed to Sifis Micheloyannis.

9 recordsLinked to original sources

PubMed2006

Small-world networks and disturbed functional connectivity in schizophrenia.

Disturbances in "functional connectivity" have been proposed as a major pathophysiological mechanism for schizophrenia, and in particular, for cognitive disorganization. Detection and estimation of these disturbances would be of clinical interest. Here we characterize the spatial pattern of functional connectivity by computing the "synchronization likelihood" (SL) of EEG at rest and during performance of a 2Back working memory task using letters of the alphabet presented on a PC screen in subjects with schizophrenia and healthy controls. The spatial patterns of functional connectivity were then characterized with graph theoretical measures to test whether a disruption of an optimal spatial pattern ("small-world") of the functional connectivity network underlies schizophrenia. Twenty stabilized patients with schizophrenia, who were able to work, and 20 healthy controls participated in the study. During the working memory (WM) task healthy subjects exhibited small-world properties (a combination of local clustering and high overall integration of the functional networks) in the alpha, beta and gamma bands. These properties were not present in the schizophrenia group. These findings are in accordance with a partially inadequate organization of neuronal networks in subjects with schizophrenia. This method could be helpful for diagnosis and evaluation of the severity of the disease, as well as understanding the pathophysiologic mechanisms underlying cognitive dysfunction in schizophrenia.

Adult↗

PubMed2006

Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis.

Previous studies demonstrated that intelligence is significantly related to an impressive array of psychological, social, biological and genetic factors and that working memory (WM) can be considered as a general cognitive resource strongly related with a wide variety of higher order cognitive competencies and intelligence. Also, evaluating the WM of subjects might allow one to test the neural efficiency hypothesis (NEH). WM typically involves functional interactions between frontal and parietal cortices. We recorded EEG signals to study neuronal interactions during one WM test in individuals who had few years of formal education (LE) as compared to individuals with university degrees (UE). The two groups of individuals differed in the scores they obtained in psychological tests. To quantify the synchronization between EEG channels in several frequency bands, we evaluated the "synchronization likelihood" (SL), which takes into consideration nonlinear processes as well as linear ones. SL was then converted into graphs to estimate the distance from "small-world network" (SWN) organization, i.e., an optimally organized network that would give rise to the data. In comparison to LE subjects, those with university degrees exhibited less prominent SWN properties in most frequency bands during the WM task. This finding supports the NEH and suggests that the connections between brain areas of well-educated subjects engaged in WM tasks are not as well-organized in the sense of SWN.

Adult↗

PubMed2006

Significant EEG features involved in mathematical reasoning: evidence from wavelet analysis.

Using electroencephalographic (EEG) signals and a novel methodology based on wavelet measures in the time-scale domain, we evaluated cortex reactions during mathematical thinking. Our purpose was to extract more precise information from the cortex reactions during this cognitive task. Initially, the brain areas (lobes) of significant activation during the task are extracted using time-averaged wavelet power spectrum estimation. Then, a refinement step makes use of statistical significance-based criteria for comparing wavelet power spectra between the task and the rest condition. EEG signals are recorded from 15 young normal volunteers using 30 scalp electrodes as participants performed one difficult arithmetic task and the results are compared with a rest situation. The results are in accordance with similar previous studies, showing activations of frontal and central regions. Compared with the alternative spectral-based techniques, the method we propose achieves higher task discrimination on the same dataset and provides additional detail-signal information to evaluate cortical reactivity during local cortical activation.

Adult↗

PubMed2004

Neural networks involved in mathematical thinking: evidence from linear and non-linear analysis of electroencephalographic activity.

Using linear and non-linear methods, electroencephalographic (EEG) signals were measured at various brain regions to provide information regarding patterns of local and coordinated activity during performance of three arithmetic tasks (number comparison, single-digit multiplication, and two-digit multiplication) and two control tasks that did not require arithmetic operations. It was hypothesized that these measures would reveal the engagement of local and increasingly complex cortical networks as a function of task specificity and complexity. Results indicated regionally increased neuronal signalling as a function of task complexity at frontal, temporal and parietal brain regions, although more robust task-related changes in EEG-indices of activation were derived over the left hemisphere. Both linear and non-linear indices of synchronization among EEG signals recorded from over different brain regions were consistent with the notion of more "local" processing for the number comparison task. Conversely, multiplication tasks were associated with a widespread pattern of distant signal synchronizations, which could potentially indicate increased demands for neural networks cooperation during performance of tasks that involve a greater number of cognitive operations.

Adult↗

PubMed2003

Changes in linear and nonlinear EEG measures as a function of task complexity: evidence for local and distant signal synchronization.

The purpose of the present study was threefold: First, to replicate previous findings of changes in local gamma band power as a function of the complexity of a visuo-semantic processing task, second, to extend these findings in tasks delivered in the auditory modality, and third to explore the use of non-linear algorithms as indices of complexity and distant synchronization in the EEG signal. EEG was recorded from 28 scalp locations as participants performed three visual discrimination tasks designed to tap into increasingly more complex operations regularly involved in the recognition of living animate objects. Two auditory processing tasks involving the same stimuli, but requiring no semantic processing, served as controls. The degree of complexity of the semantic decision was associated with the predicted changes in local gamma power, as well as with broadband changes in the non-linear predictability of the signal (an index derived using an artificial neural network algorithm). These changes were observed at all scalp regions, a finding consistent with the wide cortical distribution of component processes involved in the tasks. In addition, the synchronization between temporal and parieto-occipital electrodes and the remaining recording sites was highest in the gamma bands and lowest in the alpha bands for the task that required the most complex visuo-semantic decision. This trend reversed with reduced task complexity, consistent with the view that multidimensional semantic decisions require the involvement of distributed cortical networks in auditory and visual association areas and in the frontal lobes.

Acoustic Stimulation↗

PubMed2002

Ongoing electroencephalographic signal study of simple arithmetic using linear and non-linear measures.

This study examined patterns of variation in the ongoing electroencephalogram during performance of three visual tasks. One task required exact arithmetic calculations on Arabic numerals. A second task involved pseudoword processing as a control for the verbal (phonological) component that is, by definition, part of arithmetic tasks. A third task primarily required visual/graphemic processing, which is also involved in the other two tasks. Spectral power in the alpha range was lowest during the pseudoword task, followed by power during the arithmetic task, and finally by power in the visual task, indicating more prominent desynchronization during engagement in the analysis of word-like printed material. Finally, linear (power in the gamma range) and non-linear measures (correlation dimension) provided evidence of predominant right hemisphere engagement during the arithmetic task.

Adult↗

PubMed2002

Variability of EEG synchronization during a working memory task in healthy subjects.

Working memory is associated with an increase in EEG theta synchronization and a decrease in lower alpha band synchronization. We investigated whether such changes in mean synchronization level are accompanied by changes in small scale fluctuations of synchronization. EEGs (19 channels; average reference; sample frequency 250 Hz) were recorded in 21 healthy subjects (12 males; mean age 62.5 years; S.D. 2.1) at rest and during a visual working memory condition. EEG synchronization was computed in six frequency bands (2-6; 6-10; 10-14; 14-18; 18-22; 22-50 Hz) using the synchronization likelihood. Variability of the synchronization was quantified with synchronization entropy. During the working memory condition synchronization increased in the 2-6 Hz band, and decreased in the 6-10, 14-18 and 18-22 Hz bands. Working memory was associated with increased variability in the 2-6 Hz band, and decreased variability in the 6-10 Hz band and, to a lesser extent, in the 14-18 and 18-22 Hz bands. Working memory is accompanied not only by characteristic changes in the mean level of interactions between neural networks, but also by changes in small scale fluctuations in such interactions. Strong, but rapidly fluctuating coupling between neural systems might provide a mechanism to optimize the balance between local differentiation and global integration of brain activity.

Adult↗

PubMed2002

Modulation of gamma-band spectral power by cognitive task complexity.

This study evaluated the utility of electroencephalographic (EEG) measures as indices of regional cerebral activation during performance of visuo-semantic analysis tasks in neurologically intact adult volunteers. EEG was recorded from 28 scalp locations as participants performed three visual discrimination tasks designed to tap into increasingly more complex operations regularly involved in the recognition of living animate objects. In addition, data from a control task involving the same stimuli, but requiring no cognitive decision or response, was included. EEG records were quantified using power spectrum measures in five frequency bands (delta, theta, alpha, beta, and gamma). Results showed a significant linear increase in absolute power in the gamma band with increasing task complexity over left hemisphere frontal and occipital regions, and over right temporoparietal regions.

Adult↗

PubMed2002

Decision support system for classification of epilepsies in childhood.

Diagnosis of epilepsy in childhood is often difficult as the symptoms are often atypical and the epilepsy syndromes are multiform. Methods from the domain of artificial intelligence give the opportunity to formalize medical knowledge and standardize various diagnostic procedures in specific domains of medicine. We developed a decision support system using artificial intelligence techniques for the classification and ultimately the diagnosis of epilepsies and epilepsy syndromes in children. The system incorporates knowledge from the International Classification of Epilepsies and Epileptic Syndromes. It was assessed using clinical data and the system's conclusions were compared with the diagnoses proposed by an experienced doctor. The system and the physician reached identical diagnoses in 85.2% of the cases. In an additional 8.2% of the cases, the system's diagnosis was similar to that of the physician, thus raising its overall success rate to 93.4%. The system can be helpful, especially for trainees, since it only needs to import the clinical and laboratory data. Decision making and differential diagnosis are then performed automatically.

Child↗