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Markov Stability partitioning shows spectrally dependent community structure amongst thalamocortical neural ensembles
BMC Neuroscience volume 16, Article number: P222 (2015)
The processing of information through the spatiotemporal coordination of neuronal activity is still poorly understood [1]. Here we analyse local field potential (LFP) signals from multi-electrode recordings in the mouse lateral geniculate nucleus (LGN) and visual cortex (V1), to systematically investigate interactions between neuronal ensembles across the frequency spectrum. Computing mutual information for each pair of electrodes using the k-nearest neighbor method developed by [2], two broad groupings can be discerned among the electrodes (Figure 1A). The same partitioning is found as a stable solution when applying the Markov Stability algorithm developed by Billeh et. al. [3], which uses a Markov diffusion process through the dataset to detect stable groupings (Figure 1B/C). Analysing narrowband filtered LFP signals, neuronal groupings were found to change between low (1-40 Hz) and high (>40Hz) frequency bands. One particular neural ensemble was found to participate in different groupings across low and high frequency bands, with differing interaction partners and mechanisms as assessed by phase-phase and phase-amplitude correlation measures, both within and across areas. This frequency-specific interaction pattern may allow for the simultaneous coordination of information transmission across different timescales.
References
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Martin, CD., Ardila-Jimenez, S. & Schultz, S. Markov Stability partitioning shows spectrally dependent community structure amongst thalamocortical neural ensembles. BMC Neurosci 16 (Suppl 1), P222 (2015). https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2202-16-S1-P222
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DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2202-16-S1-P222