Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding
2010 (English)In: Nature Reviews Neuroscience, ISSN 1471-0048, E-ISSN 1471-003X, Vol. 11, no 9, 615-627 p.Article in journal (Refereed) Published
The brain is a highly modular structure. To exploit modularity, it is necessary that spiking activity can propagate from one module to another while preserving the information it carries. Therefore, reliable propagation is one of the key properties of a candidate neural code. Surprisingly, the conditions under which spiking activity can be propagated have received comparatively little attention in the experimental literature. By contrast, several computational studies in the last decade have addressed this issue. Using feedforward networks (FFNs) as a generic network model, they have identified two dynamical activity modes that support the propagation of either asynchronous (rate code) or synchronous (temporal code) spiking. Here, we review the dichotomy of asynchronous and synchronous propagation in FFNs, propose their integration into a single extended conceptual framework and suggest experimental strategies to test our hypothesis.
Place, publisher, year, edition, pages
2010. Vol. 11, no 9, 615-627 p.
Neural Pathways, Action Potentials, Animals, Neural Networks (Computer), Neurons, Humans
IdentifiersURN: urn:nbn:se:kth:diva-154866DOI: 10.1038/nrn2886ISI: 000281122500010ScopusID: 2-s2.0-77955979385OAI: oai:DiVA.org:kth-154866DiVA: diva2:758909
QC 201504292014-10-282014-10-282015-04-29Bibliographically approved