Cortical areas are discrete regions of the cerebral cortex with distinct functional, architectural, and connectivity properties. These areas are organized in a hierarchical structure, with areas interacting to form large-scale systems. Understanding cortical areas is crucial for interpreting neuroimaging data, as many studies have overlooked the principles of arealization, leading to misinterpretations. The principles of cortical organization, including function, architectonics, connectivity, and topography, define cortical areas. These principles are supported by studies in non-human primates and have implications for human neuroimaging. Cortical areas are formed through developmental processes involving signaling gradients and thalamocortical inputs. They interact through feedforward, feedback, and lateral connections, forming functional systems. Neuroimaging studies should consider these principles to better interpret data, as current methods may not fully capture the discrete nature of cortical areas. Functional connectivity studies using resting-state fMRI have identified large-scale networks, but these correlations may not reflect direct anatomical connections. Neuroimaging should assume the presence of discrete areal boundaries and temporally invariant areas, as changes in correlations can occur on short timescales due to synaptic plasticity. The stability of cortical areas is supported by anatomical substrates, and neuroimaging methods should align with these principles to ensure accurate interpretations.Cortical areas are discrete regions of the cerebral cortex with distinct functional, architectural, and connectivity properties. These areas are organized in a hierarchical structure, with areas interacting to form large-scale systems. Understanding cortical areas is crucial for interpreting neuroimaging data, as many studies have overlooked the principles of arealization, leading to misinterpretations. The principles of cortical organization, including function, architectonics, connectivity, and topography, define cortical areas. These principles are supported by studies in non-human primates and have implications for human neuroimaging. Cortical areas are formed through developmental processes involving signaling gradients and thalamocortical inputs. They interact through feedforward, feedback, and lateral connections, forming functional systems. Neuroimaging studies should consider these principles to better interpret data, as current methods may not fully capture the discrete nature of cortical areas. Functional connectivity studies using resting-state fMRI have identified large-scale networks, but these correlations may not reflect direct anatomical connections. Neuroimaging should assume the presence of discrete areal boundaries and temporally invariant areas, as changes in correlations can occur on short timescales due to synaptic plasticity. The stability of cortical areas is supported by anatomical substrates, and neuroimaging methods should align with these principles to ensure accurate interpretations.