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| Home > Publications database > Relating the orientation of cortical traveling waves and co-occurring spike patterns |
| Poster (After Call) | FZJ-2023-01605 |
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2023
Abstract: To study information processing in the cerebral cortex, multiple complementary approaches exist to characterize the coordinated population dynamics. One approach is to investigate the correlated spiking activity of individual neurons. Another approach is to analyze the local field potential (LFP) as an aggregate signature of the neuronal population dynamics. However, it is an open question how these two scales of observation relate to each other.The LFP activity in the motor cortex exhibits functionally relevant oscillations in the beta frequency band (e.g. [1]). It has been shown that the phases of beta oscillations typically form propagating waves [2, 3]. These are commonly observed as planar waves that travel across the primary motor cortex, preferably on a rostral-caudal axis [3]. Significant patterns of precise synchronous spiking (on a ms scale) that have been identified in the motor cortex [4] also display a preferred spatial orientation [5]. Indeed, estimated functional connectivity measured from spike trains using a Granger causality approach occurs in a directed manner that aligns with the mean propagation axis of LFP waves [6]. These findings raise the question of a direct relation between a single spike pattern and a co-occurring LFP wave.To investigate this question, we analyzed multi-electrode-array (Utah array) recordings of the motor cortex (MI/PMd) from a macaque monkey during an instructed reach-to-grasp task [7]. In the beta-band LFP recordings (15-25 Hz), we identified wave directions and planarity based on the gradient of the instantaneous phase using an automated analysis pipeline approach (Cobrawap) [8,9]. Independently, we detected all repeating synchronous spike patterns in the same data sets using the SPADE method [10, 11]. We identified the dominant spatial axis of the synchronous spike pattern as the first eigenvector of a principal component analysis (PCA) over the electrode grid coordinates of the involved neurons. We show that this axis tends to be perpendicular to the propagation direction of simultaneously occurring planar waves (cf. Fig.). This relationship does not only appear on average as suggested by previous work [5,6] but also on a pattern-by-pattern basis. Finally, we discuss extensions of this analysis approach to non-synchronous spike patterns.References:[1]: Kilavik et al. (2012). doi:10.1093/cercor/bhr299[2]: Denker et al. (2018). doi:10.1038/s41598-018-22990-7[3]: Rubino et al. (2006). doi:10.1038/nn1802[4]: Riehle et al. (1997). doi:10.1126/science.278.5345.1950[5]: Torre et al. (2016). doi:10.1523/JNEUROSCI.4375-15.2016[6]: Takahashi et al. (2015). doi:10.1038/ncomms8169[7]: Brochier et al. (2018). doi:10.1038/sdata.2018.55[8]: Gutzen et al. (2021). doi:10.12751/NNCN.BC2020.0030[9]: Capone et al. (2022). doi:10.48550/arXiv.2104.07445[10]: Torre et al. (2013). doi:10.3389/fncom.2013.00132[11]: Stella et al. (2022). doi:10.1523/ENEURO.0505-21.2022Acknowledgements:Founded by EU Grant 785907 (HBP SGA2), EU Grant 945539 (HBP SGA3), ANR Grant GRASP (France), Helmholtz IVF Grant ZT-I-0003 (HAF), and the Joint-Lab “Supercomputing and Modeling for the Human Brain”.
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