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Introduction Focal epilepsies are diseases of neuronal excitability affecting macroscopic networks of cortical and subcortical neural structures. These networks (“epileptogenic networks”) can generate pathological electrophysiological activities during seizures, and also between seizures (interictal period). Many works attempt to describe these networks by using quantification methods, particularly based on the estimation of statistical relationships between signals produced by brain regions, namely functional connectivity (FC). Results FC has been shown to be greatly altered during seizures and in the immediate peri-ictal period. An increasing number of studies have shown that FC is also altered during the interictal period depending on the degree of epileptogenicity of the structures. Furthermore, connectivity values could be correlated with other clinical variables including surgical outcome. Significance This leads to a conceptual change and to consider epileptic areas as both hyperexcitable and abnormally connected. These data open the door to the use of interictal FC as a marker of epileptogenicity and as a complementary tool for predicting the effect of surgery. Aim In this article, we review the available data concerning interictal FC estimated from intracranial electroencephalograhy (EEG) in focal epilepsies and discuss it in the light of data obtained from other modalities (EEG imaging) and modeling studies. Impact statement In this article, we review the concept of the epileptogenic network and explained the basic notions of functional connectivity (FC) and the potential biases when studying it using intracranial EEG (iEEG). We report the current body of published data using iEEG. These data demonstrate that even at temporal distance from epileptic seizures there are differential changes in FC between areas epileptic or not. It appears that the connectivity of epileptic zone remains relatively preserved and higher than the connectivity of the nonepileptic zone (decreased). These data could help in locating epileptic areas and predicting the surgical outcome.