SUMMARY To understand fine-scale structure and function of single mammalian neuronal networks, we developed and validated a novel strategy to genetically target and trace monosynaptic inputs to a single neuron in vitro and in vivo. The strategy independently targets a neuron and its presynaptic network for specific gene expression and fine-scale labeling, using single-cell electroporation of DNA to target infection and monosynaptic retrograde spread of a genetically modifiable rabies virus. The technique is highly reliable, with transsynaptic labeling occurring in every electroporated neuron infected by the virus. Targeting single neocortical neuronal networks in vivo, we found clusters of both spiny and aspiny neurons surrounding the electroporated neuron in each case, in addition to intricately-labeled distal cortical and subcortical inputs. The broad applicability of this technique to probe and manipulate single neuronal networks with single-cell resolution in vivo may shed new light on fundamental mechanisms underlying circuit development and information processing by neuronal networks throughout the brain.

Orientation and spatial frequency tuning are highly salient properties of neurons in primary visual cortex (V1). The combined organization of these particular tuning properties in the cortical space will strongly shape the V1 population response to different visual inputs, yet it is poorly understood. In this study, we used two-photon imaging in macaque monkey V1 to provide the first data demonstrating the 3D cell-by-cell layout of both spatial frequency and orientation tuning in large mammals. We first show that spatial frequency tuning is organized into highly structured maps that remain consistent across the depth of layer II/III, similar to orientation. Next, we show that orientation and spatial frequency maps are intimately related at the fine spatial scale observed with two-photon imaging. We find that not only do the map gradients have a striking tendency toward orthogonality, but they also co-vary negatively from cell-to-cell at the spatial scale of cortical columns.

The primary visual cortex (V1) encodes a diverse set of visual features, including orientation, ocular dominance (OD) and spatial frequency (SF), whose joint organization must be precisely structured to optimize coverage within the retinotopic map. Prior experiments have only identified efficient coverage based on orthogonal maps. Here, we used two-photon calcium imaging to reveal an alternative arrangement for OD and SF maps in macaque V1; their gradients run parallel but with unique spatial periods, whereby low SF regions coincide with monocular regions. Next, we mapped receptive fields and find surprisingly precise micro-retinotopy that yields a smaller point-image and requires more efficient inter-map geometry, thus underscoring the significance of map relationships. While smooth retinotopy is constraining, studies suggest that it improves both wiring economy and the V1 population code read downstream. Altogether, these data indicate that connectivity within V1 is finely tuned and precise at the level of individual neurons.

Neurons in the inferior temporal (IT) cortex respond selectively to complex objects, and maintain their selectivity despite partial occlusion. However, relatively little is known about how the occlusion of different shape parts influences responses in the IT cortex. Here, we determine experimentally which parts of complex objects monkeys are relying on in a discrimination task. We then study the effect of occlusion of parts with different behavioral relevance on neural responses in the IT cortex at the level of spiking activity and local field potentials (LFPs). For both spiking activity and LFPs, we found that the diagnostic object parts, which were important for behavioral judgments, were preferentially represented in the IT cortex. Our data show that the effects of diagnosticity grew systematically stronger along a posterior-anterior axis for LFPs, but were evenly distributed for single units, suggesting that diagnosticity is first encoded in the posterior IT cortex. Our findings highlight the power of combined analysis of field potentials and spiking activity for mapping structure to computational function in the brain.

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