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From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks
Univ Freiburg, Fac Biol, Freiburg, Germany.;Univ Freiburg, Bernstein Ctr Freiburg, Freiburg, Germany..
Univ Freiburg, Fac Biol, Freiburg, Germany.;Univ Freiburg, Bernstein Ctr Freiburg, Freiburg, Germany..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0002-8044-9195
2019 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, no 10, article id e1007432Article in journal (Refereed) Published
Abstract [en]

Spatio-temporal sequences of neuronal activity are observed in many brain regions in a variety of tasks and are thought to form the basis of meaningful behavior. However, mechanisms by which a neuronal network can generate spatio-temporal activity sequences have remained obscure. Existing models are biologically untenable because they either require manual embedding of a feedforward network within a random network or supervised learning to train the connectivity of a network to generate sequences. Here, we propose a biologically plausible, generative rule to create spatio-temporal activity sequences in a network model of spiking neurons with distance-dependent connectivity. We show that the emergence of spatio-temporal activity sequences requires: (1) individual neurons preferentially project a small fraction of their axons in a specific direction, and (2) the preferential projection direction of neighboring neurons is similar. Thus, an anisotropic but correlated connectivity of neuron groups suffices to generate spatio-temporal activity sequences in an otherwise random neuronal network model. Author summary Here we propose a biologically plausible mechanism to generate temporal sequences of neuronal activity in network of spiking neurons. We show that neuronal networks exhibit temporal sequences of activity when (1) neurons do not connect in all directions with equal probability (asymmetry), and (2) neighboring neurons have similar connection preference (spatial correlations). This mechanism precludes supervised learning or manual wiring to generate network connectivity to produce temporal sequences. Connection asymmetry is consistent with the experimental findings that axonal and dendritic arbors are spatially asymmetric. We predict that networks exhibiting temporal sequences of neuronal activity should have spatially asymmetric but correlated connectivity. Finally, we argue how neuromodulators can play a role in rapid switching among different temporal sequences.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2019. Vol. 15, no 10, article id e1007432
National Category
Basic Medicine
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URN: urn:nbn:se:kth:diva-266318DOI: 10.1371/journal.pcbi.1007432ISI: 000500776600055PubMedID: 31652259Scopus ID: 2-s2.0-85074674864OAI: oai:DiVA.org:kth-266318DiVA, id: diva2:1383019
Note

QC 20200107

Available from: 2020-01-07 Created: 2020-01-07 Last updated: 2020-01-13Bibliographically approved

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