Neuronal connectivity is fundamental to information processing in the brain. Understanding the mechanisms of sensory processing, therefore, requires uncovering how connection patterns between neurons relate to their function. On a coarse scale long range projections can preferentially link cortical regions with similar responses to sensory stimuli1-4. But on the local scale, where dendrites and axons overlap substantially, the functional specificity of connections remains unknown. Here we determine synaptic connectivity between nearby layer 2/3 pyramidal neurons in vitro whose response properties were first characterized in mouse visual cortex in vivo. We found that connection probability was related to the similarity of visually driven neuronal activity. Neurons with the same preference for oriented stimuli connected at twice the rate of neurons with orthogonal orientation preferences. Neurons responding similarly to naturalistic stimuli formed connections at much higher rates than those with uncorrelated responses. Bidirectional synaptic connections were found more frequently between neuronal pairs with strongly correlated visual responses. Our results reveal the deg of functional specificity of local synaptic connections in visual cortex, and point to the existence of fine-scale subnetworks dedicated to processing related sensory information.

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.

Sensory processing occurs in neocortical microcircuits in which synaptic connectivity is highly structured1–4 and excitatory neurons form subnetworks that process related sensory information5,6. However, the developmental mechanisms underlying the formation of functionally organized connectivity in cortical microcircuits remain unknown. Here we directly related patterns of excitatory synaptic connectivity to visual response properties of neighbouring layer 2/3 pyramidal neurons in mouse visual cortex at different postnatal ages, using two-photon calcium imaging in vivo and multiple whole-cell recordings in vitro. Although neural responses were highly selective for visual stimuli already at eye opening, neurons responding to similar visual features were not yet preferentially connected, indicating that the emergence of feature selectivity does not depend on the precise arrangement of local synaptic connections. After eye opening, local connectivity reorganised extensively, as more connections formed selectively between neurons with similar visual responses, and connections were eliminated between visually unresponsive neurons, while the overall connectivity rate did not change. We propose a unified model of cortical microcircuit development based on activity-dependent mechanisms of plasticity: neurons first acquire feature preference by selecting feedforward inputs before the onset of sensory experience – a process that may be facilitated by early electrical coupling between neuronal subsets7–9 – after which patterned input drives the formation of functional subnetworks through a redistribution of recurrent synaptic connections.