Correction: Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer.

[This corrects the article DOI: 10.1371/journal.pcbi.1005754.].

Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer.

The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. Patterned mossy fiber activity induces rhythmic Golgi cell activity that is synchronized by shared parallel fiber input and by gap junctions. This leads to long distance synchrony of Golgi cells along the transverse axis, powerfully regulating granule cell firing by imposing inhibition during a specific time window. The essential network mechanisms, including tunable Golgi cell oscillations, on-beam inhibition and NMDA receptors causing first winner keeps winning of granule cells, illustrate how fundamental properties of the granule layer operate in tandem to produce (1) well timed and spatially bound output, (2) a wide dynamic range of granule cell firing and (3) transient and coherent gating oscillations. These results substantially enrich our understanding of granule cell layer processing, which seems to promote spatial group selection of granule cell activity as a function of timing of mossy fiber input.

The periglomerular cell of the olfactory bulb and its role in controlling mitral cell spiking: a computational model.

Interneurons in the olfactory bulb are key elements of odor processing but their roles have not yet being fully understood. Two types of inhibitory interneurons, periglomerular and granule cells, act at two different levels within the olfactory bulb and may have different roles in coordinating the spiking of mitral cells, which are the principal output neurons of the olfactory bulb. In this work we introduce a reduced compartmental model of the periglomerular cell and use it to investigate its role on mitral cell spiking in a model of an elementary cell triad composed of these two cell types plus a granule cell. Our simulation results show that the periglomerular cell is more effective in inhibiting the mitral cell than the granule cell. Based on our results we predict that periglomerular and granule cells have different roles in the control of mitral cell spiking. The periglomerular cell would be the only one capable of completely inhibiting the mitral cell, and the activity decrease of the mitral cell through this inhibitory action would occur in a stepwise fashion depending on parameters of the periglomerular and granule cells as well as on the relative times of arrival of external stimuli to the three cells. The major role of the granule cell would be to facilitate the inhibitory action of the periglomerular cell by enlarging the range of parameters of the periglomerular cell which correspond to complete inhibition of the mitral cell. The combined action of the two interneurons would thus provide an efficient way of controling the instantaneous value of the firing rate of the mitral cell.

Dynamic range of vertebrate retina ganglion cells: importance of active dendrites and coupling by electrical synapses.

The vertebrate retina has a very high dynamic range. This is due to the concerted action of its diverse cell types. Ganglion cells, which are the output cells of the retina, have to preserve this high dynamic range to convey it to higher brain areas. Experimental evidence shows that the firing response of ganglion cells is strongly correlated with their total dendritic area and only weakly correlated with their dendritic branching complexity. On the other hand, theoretical studies with simple neuron models claim that active and large dendritic trees enhance the dynamic range of single neurons. Theoretical models also claim that electrical coupling between ganglion cells via gap junctions enhances their collective dynamic range. In this work we use morphologically reconstructed multi-compartmental ganglion cell models to perform two studies. In the first study we investigate the relationship between single ganglion cell dynamic range and number of dendritic branches/total dendritic area for both active and passive dendrites. Our results support the claim that large and active dendrites enhance the dynamic range of a single ganglion cell and show that total dendritic area has stronger correlation with dynamic range than with number of dendritic branches. In the second study we investigate the dynamic range of a square array of ganglion cells with passive or active dendritic trees coupled with each other via dendrodendritic gap junctions. Our results suggest that electrical coupling between active dendritic trees enhances the dynamic range of the ganglion cell array in comparison with both the uncoupled case and the coupled case with cells with passive dendrites. The results from our detailed computational modeling studies suggest that the key properties of the ganglion cells that endow them with a large dynamic range are large and active dendritic trees and electrical coupling via gap junctions.

A computational study on the role of gap junctions and rod Ih conductance in the enhancement of the dynamic range of the retina.

Recent works suggest that one of the roles of gap junctions in sensory systems is to enhance their dynamic range by avoiding early saturation in the first processing stages. In this work, we use a minimal conductance-based model of the ON rod pathways in the vertebrate retina to study the effects of electrical synaptic coupling via gap junctions among rods and among AII amacrine cells on the dynamic range of the retina. The model is also used to study the effects of the maximum conductance of rod hyperpolarization activated current I(h) on the dynamic range of the retina, allowing a study of the interrelations between this intrinsic membrane parameter with those two retina connectivity characteristics. Our results show that for realistic values of I(h) conductance the dynamic range is enhanced by rod-rod coupling, and that AII-AII coupling is less relevant to dynamic range amplification in comparison with receptor coupling. Furthermore, a plot of the retina output response versus input intensity for the optimal parameter configuration is well fitted by a power law with exponent approximately 0.5. The results are consistent with predictions of more theoretical works and suggest that the earliest expression of gap junctions along the rod pathways, together with appropriate values of rod I(h) conductance, has the highest impact on vertebrate retina dynamic range enhancement.