A biophysical signature of network affiliation and sensory processing in mitral cells

One defining characteristic of the mammalian brain is its neuronal diversity1. For a given region, substructure or layer and even cell type2, variability in neuronal morphology and connectivity2-5 persists. While it is well established that such cellular properties vary considerably according to neuronal type, the significant biophysical diversity of neurons of the same morphological class is typically averaged out and ignored. Here we show that the amplitude of hyperpolarization-evoked membrane potential sag recorded in olfactory bulb mitral cells is an emergent, homotypic property of local networks and sensory information processing. Simultaneous whole-cell recordings from pairs of cells reveal that the amount of hyperpolarization-evoked sag potential and current6 is stereotypic for mitral cells belonging to the same glomerular circuit. This is corroborated by a mosaic, glomerulus-based pattern of expression of the HCN2 subunit of the hyperpolarization-activated current (Ih) channel. Furthermore, inter-glomerular differences in both membrane potential sag and HCN2 protein are diminished when sensory input to glomeruli is genetically and globally altered so only one type of odorant receptor is universally expressed7. We therefore suggest that population diversity in the intrinsic profile of mitral cells reflect functional adaptations of distinct local circuits dedicated to processing subtly different odor-related information.


Paired Recordings and Electrical Coupling
We used electrical coupling to unambiguously determine whether or not the tufts of two mitral cells share the same glomerulus 1-3 . By alternating injections of large hyperpolarizing current steps into the two cells, we could determine the SPA and coupling co-efficient in each direction 1 . Among intra-glomerular pairs we observe there to be extremely non-uniform coupling (ie coupling in one direction can be 5-10 fold greater that in the other 1 ). As such, no correlation was observed between the strength of coupling and the difference in sag potential amplitude recorded in the two cells (r = 0.017, n = 26 pairs). Moreover, the largest coefficient recorded was 0.22 (n = 125 pairs; including 1 ) where the mean is 0.05. Thus hyperpolarizing to -90mV from -50mV in one cell does not produce more than a couple of mV hyperpolarization in the second cell and cannot significantly evoke I h (V ½ max = -88 mV; 4 ). Importantly, sag was never simultaneously probed in the two cells meaning that electrical coupling cannot contribute directly to the similarity in SPA recorded in intra-glomerular pairs.
Following recordings, DAB staining was performed as previously described 1 .
Consistent with previous observations 1, 3 all recovered pairs that were observed to be electrically coupled were found to project their apical dendrites to the same glomerulus and never to different glomeruli 1 .

Sag analysis
The I h sag potential was measured as the difference between the peak voltage and the

Morphological reconstruction
To obtain the morphologies of the cells we recorded from, biocytin (0.4% weight/volume) was included in the patch-pipette solution. Each slice was fixed in 4% PFA immediately after the experiment and stained the day after using the Avidin-Biotin-peroxidase Complex for amplification (ABC kit, Vector Labs) and DAB (1 mg/ml) for visualization 7 . The cells of Figures 1 and 3 were 3D digitally reconstructed by tracing all biocytin-stained arborizations using a Neurolucida system (Microbrightfield Inc.) under 100x magnification.

Immunohistochemistry
All mice (P28-P35) used for immunohistochemistry were anesthetized using intraperitoneally-administered pentobarbital and subsequently perfusion-fixed in 4% PFA, pH 7.2. The brains were removed and post-fixed in the same fixative overnight.
HCN2-DAB images were analyzed for homogeneity across glomeruli using ImageJ  To eliminate user bias, the threshold was set independently for each of the three channels. Given these conditions, co-localization (overlap) was calculated (using the Classification module) and visualized using the 3D-rendering function (using the Visualization module). Image-editing software (Adobe Photoshop and Adobe Illustrator; Adobe Systems, San Jose, CA) was used to combine the obtained images into plates.