Stam%20etal%202007%20supplemental

Stam etal 2007%2 - different brain regions In this study they want to see if the cluster coefficient and path length change with Alzheimer’s

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Stam et al., 2006 Electroencephalography (EEG) is the measurement of brain activity and is divided in frequency bands. The frequency bands indicate how fast the EEG is changing. In this study, they focus on the beta-band. They used 21 locations on the brain to measure the EEG (figure 3a in the article). The synchronization likelihood calculates the correlation between two locations. That is, how much the signal at one of the 21 locations is similar to the signal at one of the other 21 locations. You don’t need to know how they calculate it, just note that they use two measures: the cluster coefficient and path length. Figure 1 in the article explains the cluster coefficient (C) and path length (L). Take home message is that optimal systems are characterized by a high C and a low L; such systems are designated small-world networks (Watts and Strogatz, 1998). This may be optimal for synchronizing neural activity between
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Unformatted text preview: different brain regions. In this study they want to see if the cluster coefficient and path length change with Alzheimer’s Disease. They expect a lower C and a higher L in the Alzheimer’s group compared to the control group, which would mean that there is less synchronization between different brain regions. You don’t need to read the ‘Computation of SL’ and ‘Computation of the Cluster Coefficient C and Characteristic Path Length L’ paragraphs. Also, the appendix is not necessary. There are a lot of complicated topics in the results, but read it once. You might not be able to get everything they say, but you can pick up several things. The discussion is more straightforward. Figure 3 is an important figure and can help you understand their findings....
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This note was uploaded on 02/17/2011 for the course HK 490 taught by Professor Reidtky during the Fall '10 term at Purdue University-West Lafayette.

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