Attractor dynamics of network UP states in the neocortex
- PMID: 12748641
- DOI: 10.1038/nature01614
Attractor dynamics of network UP states in the neocortex
Abstract
The cerebral cortex receives input from lower brain regions, and its function is traditionally considered to be processing that input through successive stages to reach an appropriate output. However, the cortical circuit contains many interconnections, including those feeding back from higher centres, and is continuously active even in the absence of sensory inputs. Such spontaneous firing has a structure that reflects the coordinated activity of specific groups of neurons. Moreover, the membrane potential of cortical neurons fluctuates spontaneously between a resting (DOWN) and a depolarized (UP) state, which may also be coordinated. The elevated firing rate in the UP state follows sensory stimulation and provides a substrate for persistent activity, a network state that might mediate working memory. Using two-photon calcium imaging, we reconstructed the dynamics of spontaneous activity of up to 1,400 neurons in slices of mouse visual cortex. Here we report the occurrence of synchronized UP state transitions ('cortical flashes') that occur in spatially organized ensembles involving small numbers of neurons. Because of their stereotyped spatiotemporal dynamics, we conclude that network UP states are circuit attractors--emergent features of feedback neural networks that could implement memory states or solutions to computational problems.
Similar articles
-
Internal dynamics determine the cortical response to thalamic stimulation.Neuron. 2005 Dec 8;48(5):811-23. doi: 10.1016/j.neuron.2005.09.035. Neuron. 2005. PMID: 16337918
-
Imaging input and output of neocortical networks in vivo.Proc Natl Acad Sci U S A. 2005 Sep 27;102(39):14063-8. doi: 10.1073/pnas.0506029102. Epub 2005 Sep 12. Proc Natl Acad Sci U S A. 2005. PMID: 16157876 Free PMC article.
-
Analysis of ongoing dynamics in neural networks.Neurosci Res. 2009 Jun;64(2):177-84. doi: 10.1016/j.neures.2009.02.011. Epub 2009 Mar 9. Neurosci Res. 2009. PMID: 19428698
-
Electrophysiological classes of neocortical neurons.Neural Netw. 2004 Jun-Jul;17(5-6):633-46. doi: 10.1016/j.neunet.2004.04.003. Neural Netw. 2004. PMID: 15288889 Review.
-
Beyond bistability: biophysics and temporal dynamics of working memory.Neuroscience. 2006 Apr 28;139(1):119-33. doi: 10.1016/j.neuroscience.2005.06.094. Epub 2005 Dec 2. Neuroscience. 2006. PMID: 16326020 Review.
Cited by
-
Fast inference in generalized linear models via expected log-likelihoods.J Comput Neurosci. 2014 Apr;36(2):215-34. doi: 10.1007/s10827-013-0466-4. Epub 2013 Jul 6. J Comput Neurosci. 2014. PMID: 23832289 Free PMC article.
-
Chronic electrical stimulation homeostatically decreases spontaneous activity, but paradoxically increases evoked network activity.J Neurophysiol. 2013 Apr;109(7):1824-36. doi: 10.1152/jn.00612.2012. Epub 2013 Jan 16. J Neurophysiol. 2013. PMID: 23324317 Free PMC article.
-
Stochastic amplification of fluctuations in cortical up-states.PLoS One. 2012;7(8):e40710. doi: 10.1371/journal.pone.0040710. Epub 2012 Aug 7. PLoS One. 2012. PMID: 22879879 Free PMC article.
-
How can we study reasoning in the brain?Front Hum Neurosci. 2015 Apr 24;9:222. doi: 10.3389/fnhum.2015.00222. eCollection 2015. Front Hum Neurosci. 2015. PMID: 25964755 Free PMC article.
-
Two-photon calcium imaging of neuronal activity.Nat Rev Methods Primers. 2022;2(1):67. doi: 10.1038/s43586-022-00147-1. Epub 2022 Sep 1. Nat Rev Methods Primers. 2022. PMID: 38124998 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Miscellaneous