Higher order Synchrony Predictability in Somatosensory Cortex during Spontaneous Activity
2010; Frontiers Media; Volume: 4; Linguagem: Inglês
10.3389/conf.fncom.2010.51.00140
ISSN1662-5188
Autores Tópico(s)EEG and Brain-Computer Interfaces
ResumoEvent Abstract Back to Event Higher order Synchrony Predictability in Somatosensory Cortex during Spontaneous Activity Antonio G. Zippo1, 2*, Riccardo Storchi2, 3, Lin Jianyi1, Giancarlo Caramenti4, Maurizio Valente2 and Gabriele E. M Biella2 1 Università degli Studi di Milano, Department of Mathematics, Italy 2 Istituto di Bioimmagini e Fisiologia Molecolare, CNR, Italy 3 Università degli Studi di Modena e Reggio, Department Biological Sciences, Italy 4 Istituto di Tecnologie Biomediche, CNR, Italy The cerebral cortex exhibits highly complex dynamic regimes during spontaneous activity. A plethora of parameters were tried to capture this complexity focusing on different features. One of the most relevant, showed by the spontaneously running cortical networks, is represented by synchronies. While the instantaneous higher order interactions, that incorporate also higher order synchronies, have been well described by weak pairwise correlations [1], their temporal dynamics has not yet been thoroughly analyzed. In a previous paper we showed that multiunit firing activity exhibits intermittent chaotic behavior [2]. We therefore focused on predictability of higher order loose synchronies (LSs), i.e. firing events jointly occurring within 30-50ms temporal windows. We analyzed extracellular simultaneous multiple recordings of spontaneously active Somatosensory Primary cortices of lightly gas-anesthetized rats. We first developed a statistical method based on a hypothesis test combined to a data clustering to extract and classify synchronous and non-synchronous events. The resulting symbolic sequence represents the multiunit spiking activity where some symbols are associated with LSs and others with non-synchronous events. We approximated the Kolmogorov complexity of these sequences within fixed length sliding windows by the compressed sequence length (CSL) computed with a set of Unix compressors (zip, gzip, bzip2) [3]. On comparing the real sequences (RS) with surrogate sequences obtained through random permutations, we found long strings of significantly low CLS regions in comparison with the surrogated sequences (SS) (Fig A). The rate of LS occurrences showed high positive correlation with CLS values. LS predictability was analyzed with Variable Order Markov Model techniques estimating both short and long range sequence dependencies [4]. We found that the LSs in RS were 10 to 100% more predictable than LSs in SS, only the last 5 to 15 symbols were relevant for prediction (Fig B). Unexpectedly, the rate of correct LS predictions wasn’t significantly correlated with CLS. Finally, the rate of LS prediction and the rate of LS occurrence resulted positively correlated. These results deliver important cues on the events leading to the occurrence of LS. The high variability in predictions suggests that the cortical LSs may potentially endorse diverse tasks merged in the shared functional state of spontaneous activity. Figure 1 References 1) E. Schneidman et al (2006) Nature, 440:1007-1012. 2) Storchi et al, submitted to “The IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications”, September 2010. 3) H. Bennett et al (1998) IEEE Transactions on Information Theory, 44:1407-1423. 4) R. Begleiter et al (2004) Journal of Artificial Intelligence Research, 22:385-421. Keywords: computational neuroscience Conference: Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010. Presentation Type: Presentation Topic: Bernstein Conference on Computational Neuroscience Citation: Zippo A, Storchi R, Jianyi L, Caramenti G, Valente M and M Biella GE (2010). Higher order Synchrony Predictability in Somatosensory Cortex during Spontaneous Activity. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00140 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 24 Sep 2010; Published Online: 24 Sep 2010. * Correspondence: Dr. Antonio G. Zippo, Università degli Studi di Milano, Department of Mathematics, Milan, Italy, antonio.zippo@unimi.it Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Antonio G. Zippo Riccardo Storchi Lin Jianyi Giancarlo Caramenti Maurizio Valente Gabriele E M Biella Google Antonio G. Zippo Riccardo Storchi Lin Jianyi Giancarlo Caramenti Maurizio Valente Gabriele E M Biella Google Scholar Antonio G. Zippo Riccardo Storchi Lin Jianyi Giancarlo Caramenti Maurizio Valente Gabriele E M Biella PubMed Antonio G. Zippo Riccardo Storchi Lin Jianyi Giancarlo Caramenti Maurizio Valente Gabriele E M Biella Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.
Referência(s)