נסיעה

אני שמח לראות שהפורום מחפש גם פסיכיאטר נוסף לעזרתי אני מתקשה להגיע לענות (מרוב עבודה) בימים האחרונים נדרשתי לכתוב פרק בספר שיצא מכינוס יוקרתי בארופה http://www.psychiatricneuroimaging.org אני נוסע לכינוס ולכן לא אהיה בארץ לענות גם עד שבוע הבא

בהצלחה בקונגרס היוקרתי באירופה! המאמר שלך שם: http://www.psychiatricneuroimaging.org/abstracts/peled.htm

Functional connectivity and EEG Monday 30/09/2002, h11.30 Avi Peled MD Institute for Psychiatric Studies, Sha'ar Menashe Mental Health Center, Mobile Post Hefer 38814, Hadera, Israel Bruce Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa, Israel email: [email protected] Functional connectivity is the term commonly used to describe neuronal associations; it is the influence that the activity in one neuronal system has on the activity of the other neuronal system. The term "functional" stresses that influences among neuronal systems are not necessarily made by direct physical synapses, but can be indirect via other far distributed neurons. Functional connectivity is the basis for organization of neuronal cell ensembles in the brain, an organization thought to be the basis of cognitive computations and mental functions in general. Neural network models simulate neural systems and can achieve computations that model cognitive functions. Units of these models are neurons and weighted values represent connections. The connectivity patterns in such models are essential for their effective computation. Similarly it is assumed that functional connectivity in the brain is essential for normal mental functions. Thus it is obvious why the study of brain connectivity is essential. fMRI has good spatial resolution and thus seems most suitable for the study of spatially-distributed interconnections. This is typically calculated by hemodynamic-based correlation in the dynamic activity between two brain regions. EEG offers the advantage of the millisecond-range temporal resolution. Correlations between the electrical activity expressed as waveform patterns (amplitude and frequencies) among different electrode scalp locations is one way to estimate presumed connectivity among the relevant cortical brain locations. Correlations could be simple (simple coherence measures) or take into consideration the dynamic propagation of signals by shifting the signals with respect to one another (sliding window). Correlations could be applied to raw data and to averaged signals (evoked responses) when a stimulus onset is relevant. Another method to estimate connectivity refers to estimations of independent sources. This assumes that interconnected systems acting in conjunction with each other would be expressed by a common EEG source generator, thus if EEG analysis reveals multiple independent sources then it is postulated that many disconnected systems characterize the cortical activity being measured. Imbalances in excitability of neural networks resulting in dissociated and disconnected neuronal brain activity is a leading hypothesis for the emergence of serious mental disorders such as schizophrenia. EEG assessment of connectivity in these patients exemplifies the attempts to study brain connectivity using EEG.