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A model of propagating waves in cerebral cortex across network states
BMC Neuroscience volume 12, Article number: P67 (2011)
Propagating waves of activity have been measured in cerebral cortex in various experimental preparations, and show different propagation speed or patterns. Using network models, we investigated whether the “state” of the network can explain these differences. We used a modified version of a previous model, in which neuronal adaptation can facilitate the transition from activated, asynchronous irregular (AI) states to quiescence in random networks.  With a proper re-ignition mechanism, these networks can transition between UP/DOWN and AI states with different levels of adaptation. Here, we have studied the occurrence of propagating waves during this transition from UP/DOWN to self-sustained activated states in topographic spiking neural network models and compared these results to voltage-sensitive dye imaging data from the visual cortex, as well as to other known experimental results. The addition of local connections with realistic synaptic delays in these topographic spiking neural network models allows for the possibility of propagating slow waves in some network states. Further, while it is generally thought that the large, low-frequency propagation evoked by sensory stimulation during heavily anesthetized states gives way to a bump attractor during waking, activated states, we demonstrate the possibility that propagating activity exists throughout the whole spectrum of network activation and shifts from low frequency (predominantly controlled by adaptation) to high frequency (predominantly controlled by E/I interactions) as the level of network activation increases. With these results from network modeling, we aim to account both for observed effects of anesthesia on the spread of cortical activity in voltage-sensitive dye and electrophysiological experiments [2–4] and for the observation of traveling high-frequency oscillations in vitro  and in awake monkeys [6, 7].
Destexhe A: Self-sustained asynchronous irregular states and Up—Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons. Journal of Computational Neuroscience. 2009, 27: 493-506. 10.1007/s10827-009-0164-4.
Ferezou I, Bolea S, Petersen CCH: Visualizing the Cortical Representation of Whisker Touch: Voltage-Sensitive Dye Imaging in Freely Moving Mice. Neuron. 2006, 50: 617-629. 10.1016/j.neuron.2006.03.043.
Nauhaus I, Busse L, Carandini M, Ringach DL: Stimulus contrast modulates functional connectivity in visual cortex. Nat Neurosci. 2008, 12: 70-76. 10.1038/nn.2232.
Mohajerani MH, McVea DA, Fingas M, Murphy TH: Mirrored Bilateral Slow-Wave Cortical Activity within Local Circuits Revealed by Fast Bihemispheric Voltage-Sensitive Dye Imaging in Anesthetized and Awake Mice. J Neurosci. 2010, 30: 3745-3751. 10.1523/JNEUROSCI.6437-09.2010.
Metherate R, Cruikshank SJ: Thalamocortical inputs trigger a propagating envelope of gamma-band activity in auditory cortex in vitro. Exp Brain Res. 1999, 126: 160-174. 10.1007/s002210050726.
Rubino D, Robbins KA, Hatsopoulos NG: Propagating waves mediate information transfer in the motor cortex. Nat Neurosci. 2006, 9: 1549-1557. 10.1038/nn1802.
Gabriel A, Eckhorn R: A multi-channel correlation method detects traveling gamma-waves in monkey visual cortex. J Neurosci Methods. 2003, 131: 171-184. 10.1016/j.jneumeth.2003.08.008.
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Muller, L.E., Destexhe, A. A model of propagating waves in cerebral cortex across network states. BMC Neurosci 12, P67 (2011) doi:10.1186/1471-2202-12-S1-P67
- Cerebral Cortex
- Visual Cortex
- Neural Network Model
- Slow Wave
- Network State