An analytical approach to information transmission in the face of up and down states Felix Droste How a single neuron responds to a sensory signal is heavily dependent on the activity of the embedding network [Arieli et al, 1996]. If this network is in a so-called asynchronous-irregular state, its contribution to the input that the neuron receives can be modeled as a Gaussian white noise; for this case, analytical approaches to the neuron's information transmission properties are well established [Brunel et al., 2001, Lindner and Schimansky-Geier, 2001]. However, there is a variety of dynamic states that the network can be in. One possibility, observed mainly during slow-wave sleep, under anesthesia, or during quiet wakefulness, is the transition between so-called up and down states, periods of activity interrupted by collective pauses [Steriade et al., 2001]. Recently, experimental interest in how such an up-down background influences the transmission of a sensory signal has grown [Petersen et al., 2003, Luczak et al., 2013, Zagha et al., 2013], but so far, analytical approaches are still lacking. Here, we model the up-down background using a stochastic two-state process, Markovian dichotomous noise. For a leaky integrate-and-fire neuron that receives such input, we derive analytical expressions for the spontaneous power spectrum and the rate response to an additional weak signal (the sensory input). We then extend the framework to encompass weak fluctuations around the two states, accounting for the shot-noise nature of the input. Using this framework, we compare information transmission with an up-down background to the case of asynchronous-irregular network activity. We find that for low mean input to the cell, an up-down background can be advantageous for information transmission. references: - Arieli, A.; Sterkin, A.; Grinvald, A. & Aertsen, A., Science, 1996, 273, 1868-1871 - Brunel, N.; Chance, F. S.; Fourcaud, N. & Abbott, L. F., Phys. Rev. Lett., 2001, 86, 2186-2189 - Lindner, B. & Schimansky-Geier, L., Phys. Rev. Lett., 2001, 86, 2934-2937 - Steriade, M.; Timofeev, I. & Grenier, F. J. Neurophysiol., 2001, 85, 1969-1985 - Petersen, C. C.; Hahn, T. T.; Mehta, M.; Grinvald, A. & Sakmann, B., Proc. Natl. Acad. Sci., 2003, 100, 13638-13643 - Luczak, A.; Bartho, P. & Harris, K. D., J. Neurosci., 2013, 33, 1684-1695 - Zagha, E.; Casale, A. E.; Sachdev, R. N.; McGinley, M. J. & McCormick, D. A., Neuron, 2013, 79, 567-5781