A functional clustering algorithm for the analysis of dynamic network data

Details A functional clustering algorithm for the analysis of dynamic network data A functional clustering algorithm for the analysis of dynamic network data

2008-03-20

arxiv.org/abs/0803.3047v3

Biology

Quantitative Biology

Neurons and Cognition

19 pages, 7 figures, significant changes to structure of paper, added methods sections and new measures

Scientific paper

We formulate a novel technique for the detection of functional clusters in discrete event data. The advantage of this algorithm is that no prior knowledge of the number of functional groups is needed, as our procedure progressively combines data traces and derives the optimal clustering cutoff in a simple and intuitive manner through the use of surrogate data sets. In order to demonstrate the power of this algorithm to detect changes in network dynamics and connectivity, we apply it to both simulated neural spike train data and real neural data obtained from the mouse hippocampus during exploration and slow-wave sleep. Using the simulated data, we show that our algorithm performs better than existing methods. In the experimental data, we observe state-dependent clustering patterns consistent with known neurophysiological processes involved in memory consolidation.

Affiliated with

Also associated with

No associations

Rating

A functional clustering algorithm for the analysis of dynamic network data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A functional clustering algorithm for the analysis of dynamic network data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A functional clustering algorithm for the analysis of dynamic network data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-578339