From the earliest drawings of neurons1
, to the identification of families of voltage-gated ion channels 2
, a central theme of neuroscience has been the remarkable intrinsic variety of cells. While catalogues of types of neurons
continue to grow 3
, the importance of intrinsic diversity within neurons of a single type
for neuronal coding has been largely ignored. Differences in channel expression and morphology 4, 5
can diversify spike outputs, even among cells of a single identified type 6
. Alternatively, spiking properties can be equivalent among neurons having channel densities in different proportions6
. Intrinsic variability therefore seems to play multiple roles in mechanisms of spike generation. The extent to which these individual differences in cells are relevant to neural coding is however, less well understood.
Intrinsic diversity could play a critical role in neuronal coding, for example by reducing pairwise spike train correlations and reducing redundancy across populations of neurons, perhaps in conjunction with connectivity 7, 8
. Such decreases would afford populations of highly diverse neurons additional bandwidth with which to code for stimuli, as suggested by theoretical studies 9, 10
. But in noisy neural systems, where trial-to-trial variability is large11
, how the tradeoff between redundancy and bandwidth is balanced remains unexplored. At one extreme, biophysical differences may simply be the product of the imprecision of biology. For example, mosaic of neuronal properties may only reflect the probabilistic nature of gene expression among different cells. Alternatively, this diversity may be a functionally significant adaptation, whereby the noise of stochastic gene expression is harnessed in service of neuronal coding. Thus, understanding the effects of intrinsic diversity on neural responses and neuronal coding is essential for linking the cell biology of neurons with their functional role in information coding in the context of neuronal circuits. Heterogeneity in responses can arise from numerous sources, including anatomical differences and differences in inputs, but here we choose to focus on the mitral cells of the main olfactory bulb, where input correlations in mitral cells connected to the same glomerulus are high 12
, and the anatomy is highly stereotypic.
Here we demonstrate that intrinsic biophysical diversity affects neuronal coding by reducing correlations in the population code while simultaneously increasing the information encoded by the population. We report two-fold increases in the coding capacity of populations of biophysically heterogeneous cells as compared to their homogeneous counterparts. This enhancement was seen both for random noisy inputs and for physiologically relevant stimuli modulated by oscillations corresponding to the frequency of sniffing. Additionally, we show that the spike triggered average (STA) can be used as one way to quantify neuronal diversity. Taken together, these data imply that biophysical heterogeneity is an important mechanism of robust population coding, not the unavoidable consequence of biology's imprecision.