The study reveals that synaptic connectivity in local cortical circuits is highly nonrandom, with several key features. Synaptic connections between layer 5 pyramidal neurons in the rat visual cortex show a higher prevalence of bidirectional connections than expected in a random network. Additionally, several three-neuron connectivity patterns are overrepresented, suggesting that connections tend to cluster. Synaptic connection strength, defined by the peak excitatory postsynaptic potential (EPSP) amplitude, follows a lognormal distribution, indicating that synaptic weights are concentrated among a few connections. Strong connections are more clustered than weak ones, implying that the local cortical network can be viewed as a skeleton of stronger connections in a sea of weaker ones. These findings suggest that the network structure plays a crucial role in network dynamics and should be further investigated. The study also shows that synaptic connection strengths are correlated, and that stronger connections are more likely to be reciprocal. The results highlight the importance of nonrandom features in synaptic connectivity for understanding cortical function. The study used statistical methods to analyze a large dataset from hundreds of simultaneous quadruple whole-cell recordings, revealing several nonrandom features in synaptic connectivity. The findings suggest that the local cortical network is not random but has a structured organization that may be important for network dynamics. The study also shows that the distribution of synaptic connection strengths has a heavy tail, indicating that a few strong connections contribute significantly to the overall network activity. The results suggest that the local cortical network is not random but has a structured organization that may be important for network dynamics. The study also shows that synaptic connection strengths are correlated, and that stronger connections are more likely to be reciprocal. The findings highlight the importance of nonrandom features in synaptic connectivity for understanding cortical function.The study reveals that synaptic connectivity in local cortical circuits is highly nonrandom, with several key features. Synaptic connections between layer 5 pyramidal neurons in the rat visual cortex show a higher prevalence of bidirectional connections than expected in a random network. Additionally, several three-neuron connectivity patterns are overrepresented, suggesting that connections tend to cluster. Synaptic connection strength, defined by the peak excitatory postsynaptic potential (EPSP) amplitude, follows a lognormal distribution, indicating that synaptic weights are concentrated among a few connections. Strong connections are more clustered than weak ones, implying that the local cortical network can be viewed as a skeleton of stronger connections in a sea of weaker ones. These findings suggest that the network structure plays a crucial role in network dynamics and should be further investigated. The study also shows that synaptic connection strengths are correlated, and that stronger connections are more likely to be reciprocal. The results highlight the importance of nonrandom features in synaptic connectivity for understanding cortical function. The study used statistical methods to analyze a large dataset from hundreds of simultaneous quadruple whole-cell recordings, revealing several nonrandom features in synaptic connectivity. The findings suggest that the local cortical network is not random but has a structured organization that may be important for network dynamics. The study also shows that the distribution of synaptic connection strengths has a heavy tail, indicating that a few strong connections contribute significantly to the overall network activity. The results suggest that the local cortical network is not random but has a structured organization that may be important for network dynamics. The study also shows that synaptic connection strengths are correlated, and that stronger connections are more likely to be reciprocal. The findings highlight the importance of nonrandom features in synaptic connectivity for understanding cortical function.