Research

I am interested in finding out how can brains process information through spatiotemporal spike patterns. To this end I am developing methods for the analysis and visualization of such spike patterns. My work follows two different, but complementary, approaches. The first has a more qualitative nature and aims to provide researchers with intuitive ways of visualizing multivariate data, in particular multielectrode spike trains. The second approach is more quantitative and tries to relate properties of spatiotemporal spike patterns to features of external stimuli, with the help of classifiers.

Visualizing Multineuronal Activity Patterns

Spike rastergrams are a simple and efficient tool for visualizing the activity of simultaneously recorded neurons. However, the visual detection of multineuronal spike patterns in these plots is largely dependent on the arrangement of the neurons in the rastergram. This happens because of Gestalt principles that govern our visual system. If neurons that form a particular spike pattern are not neighbors in the rastergram, the detection of that pattern can become difficult due to the activity of the other neurons.

To enable the visual identification of multineuronal spike patterns, defined within a time window, we devised a method to color them based on their reciprocal similarity. For example, if pattern A is similar to pattern B but different from pattern C, then pattern A and B will be assigned similar colors (e.g., red and orange) while pattern C will be assigned a different color (e.g., blue). This way, color becomes a signature of pattern identity and the occurrences of similar patterns can be easily visualized across entire recording sessions.

Figure. Transforming simultaneously recorded spike trains into color sequences. For each time window, the spiking activity of all neurons is assessed and then mapped onto a color space using Kohonen maps.

The labeling of spike patterns with colors enables the visualization of each trial as a sequence of colors. Grouping several color sequences by a certain criterion (e.g., stimulus, time of recording) can reveal regions in which similar patterns (colors) occur consecutively along the trial and/or consistently around the same time points across different trials.

Figure. Color sequences corresponding to trials recorded with the same stimulus (a drifting sinusoidal grating). The three yellow stripes indicate the presence of similar activity patterns at specific time points across all trials.

This method enables the intuitive visualization of neuronal population dynamics and enables the identification of periods of interest, which can be further subjected to more quantitative analyses. Although it was designed for the visualization of multielectrode spike trains, the method could be applied also to simultaneously recorded continuous signals (e.g., LFP, EEG, MEG).

Article links:

[abstract]

[pdf]

[source code]

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Timescale of Informative Multineuronal Activity Patterns

In development ...