Abstract:
:Multi electrode recordings of neuronal activity provide an overwhelming amount of data that is often difficult to analyze and interpret. Although various methods exist for treating multielectrode datasets quantitatively, there is a particularly prominent lack of techniques that enable a quick visual exploration of such datasets. Here, by using Kohonen self-organizing maps, we propose a simple technique that allows for the representation of multiple spike trains through a sequence of color-coded population activity vectors. When multiple color sequences are grouped according to a certain criterion, e.g., by stimulation condition or recording time, one can inspect an entire dataset visually and extract quickly information about the identity, stimulus-locking and temporal distribution of multi-neuron activity patterns. Color sequences can be computed on various time scales revealing different aspects of the temporal dynamics and can emphasize high-order correlation patterns that are not detectable with pairwise techniques. Furthermore, this technique is useful for determining the stability of neuronal responses during a recording session. Due to its simplicity and reliance on perceptual grouping, the method is useful for both quick on-line visualization of incoming data and for more detailed post hoc analyses.
journal_name
J Neurophysioljournal_title
Journal of neurophysiologyauthors
Jurjut OF,Nikolić D,Pipa G,Singer W,Metzler D,Mureşan RCdoi
10.1152/jn.00758.2009subject
Has Abstractpub_date
2009-12-01 00:00:00pages
3766-78issue
6eissn
0022-3077issn
1522-1598pii
00758.2009journal_volume
102pub_type
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