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Morphoelectric properties of inhibitory neurons shift gradually and regardless of cell type along the depth of the cerebral cortex
How can we understand the enormous diversity of the GABAergic inhibitory neurons in the cerebral cortex? To address this question, we quantify the electrophysiological and morphological properties of inhibitory neurons across the depth of an entire cortical column in the rat barrel cortex. We find properties that shift gradually with the cortical depth of the cell bodies across all inhibitory neurons, regardless of their cell types. By isolating morphoelectric variations from their shifts along the cortical depth, we find that the same simple relationships between morphoelectric properties distinguish between the four main molecular cell types of inhibitory neurons at any cortical depth, and in both the rat barrel cortex and mouse primary visual cortex. We provide converging evidence from dense electron-microscopic reconstructions of inhibitory neurons in the mouse visual cortex, and observe comparable depth-dependent shifts in additional datasets from the mouse primary motor cortex and the middle temporal gyrus of the human cortex. Our findings indicate that two different sources of morphoelectric variations can account for the diversity of cortical inhibitory neurons. The first source is molecular cell type-specific, but cortical depth-independent. The second source is cortical depth-dependent, but affects inhibitory neurons similarly across all cell types. We propose that intrinsic developmental specification vs. extrinsic environmental modulation leads to such a decoupling of inhibitory type-specific properties from gradual shifts of these properties with cortical depth. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, https://ror.org/0472cxd90, 633428 Deutsche Forschungsgemeinschaft, SFB 1089, SPP 2041, Fe472/2-1 Bundesministerium für Bildung und Forschung, 01GQ1002, 01IS18052 Neuroscience Network North Rhine-Westphalia, iBehave National Institutes of Health, https://ror.org/01cwqze88, R24MH117295 The Kavli Foundation, NeuroData Discovery Award
