The strength of synaptic connections fundamentally determines how neurons influence each other's firing. Excitatory connection amplitudes between pairs of cortical neurons vary over two orders of magnitude, comprising only very few strong connections among many weaker ones [1][2][3][4][5][6][7][8][9] . Although this highly skewed distribution of connection strengths is observed in diverse cortical areas 1-9 , its functional significance remains unknown: it is not clear how connection strength relates to neuronal response properties, nor how strong and weak inputs contribute to information processing in local microcircuits. Here we reveal that the strength of connections between layer 2/3 (L2/3) pyramidal neurons in mouse primary visual cortex (V1) obeys a simple rule-the few strong connections occur between neurons with most correlated responses, while only weak connections link neurons with uncorrelated responses. Moreover, we show that strong and reciprocal connections occur between cells with similar spatial receptive field structure. Although weak connections far outnumber strong connections, each neuron receives the majority of its local excitation from a small number of strong inputs provided by the few neurons with similar responses to visual features. By dominating recurrent excitation, these infrequent yet powerful inputs disproportionately contribute to feature preference and selectivity. Therefore, our results show that the apparently complex organization of excitatory connection strength reflects the Reprints and permissions information is available at www.nature.com/reprints.

A large population of neurons can in principle produce an astronomical number of distinct firing patterns. In cortex however, these patterns lie in a space of lower dimension1-4, as if individual neurons were “obedient members of a huge orchestra”5. Here we use recordings from the visual cortex of mouse and monkey to investigate the relationship between individual neurons and the population, and to establish the underlying circuit mechanisms. We show that neighbouring neurons can differ in their coupling to the overall firing of the population, ranging from strongly coupled “choristers” to weakly coupled “soloists”. Population coupling is largely independent of sensory preferences, and it is a fixed cellular attribute, invariant to stimulus conditions. Neurons with high population coupling are more strongly affected by non-sensory behavioural variables such as motor intention. Population coupling reflects a causal relationship, predicting a neuron’s response to optogenetically-driven increases in local activity. Moreover, population coupling indicates synaptic connectivity: a neuron’s population coupling, measured in vivo, predicted subsequent in vitro estimates of the number of synapses received from its neighbours. Finally, population coupling provides a compact summary of population activity: knowledge of the population couplings of N neurons predicts a substantial portion of their N2 pairwise correlations. Population coupling therefore represents a novel, simple measure that characterises each neuron’s relationship to a larger population, explaining seemingly complex network firing patterns in terms of basic circuit variables.

How a sensory stimulus is processed and perceived depends on the surrounding sensory scene. In the visual cortex, contextual signals can be conveyed by an extensive network of intra- and inter-areal excitatory connections that link neurons representing stimulus features separated in visual space1–4. However, the connectional logic of visual contextual inputs remains unknown; it is not clear what information individual neurons receive from different parts of the visual field, nor how this input relates to the visual features a neuron encodes, defined by its spatial receptive field. We determined the organisation of excitatory synaptic inputs responding to different locations in the visual scene by mapping spatial receptive fields in dendritic spines of mouse visual cortex neurons using two-photon calcium imaging. We found that neurons received functionally diverse inputs from extended regions of visual space. Inputs representing similar visual features from the same location in visual space were more likely to cluster on neighbouring spines. Inputs from visual field regions beyond the postsynaptic neuron’s receptive field often synapsed on higher-order dendritic branches. These putative long-range inputs were more frequent and more likely to share the preference for oriented edges with the postsynaptic neuron when the input’s receptive field was spatially displaced along the axis of the postsynaptic neuron’s receptive field orientation. Therefore, the connectivity between neurons with displaced receptive fields obeys a specific rule, whereby they connect preferentially when their receptive fields are co-oriented and co-axially aligned. This organization of synaptic connectivity is ideally suited for amplification of elongated edges, which are enriched in the visual environment, and thus provides a potential substrate for contour integration and object grouping.

In the cerebral cortex, the selectivity of neurons for features of sensory stimuli arises through the interaction of excitatory and inhibitory synaptic inputs. Excitatory neurons receive inhibitory input that closely tracks excitation 1-4 , stabilizing network dynamics 5 while improving efficiency and robustness of the neural code 6-8 . However, how this balance of excitation and inhibition is achieved by cortical circuits is unclear, since inhibitory interneurons are thought to pool the inputs of nearby excitatory cells and provide them with non-specific inhibition proportional to the activity of the local network 9-13 . Here we show that although parvalbumin-expressing (PV) inhibitory cells make connections with the majority of nearby pyramidal cells, the strength of their synaptic connections is structured according to the similarity of the cells' responses. Individual PV cells strongly inhibit those pyramidal cells that provide them with strong excitation and share their visual selectivity. This fine-tuning of synaptic weights supports co-tuning of inhibitory and excitatory inputs onto individual pyramidal cells despite dense connectivity between inhibitory and excitatory neurons. Our results indicate that individual PV cells are preferentially integrated into subnetworks of inter-connected, co-tuned pyramidal cells, stabilising their recurrent dynamics. Conversely, weak but dense inhibitory connectivity between subnetworks is sufficient to support competition between them, de-correlating their output. We suggest that the history and structure of correlated firing adjusts the weights of both inhibitory and excitatory connections, supporting stable amplification and selective recruitment of cortical subnetworks.