Epilepsy is a complex neurological disorder characterized by diverse manifestations and heterogenous pathophysiology. In this thesis we leverage advanced multimodal neuroimaging techniques to explore the structural and functional underpinnings of epilepsy, aiming to enhance our understanding and to identify reliable biomarkers for this disorder. Chapter 1 provides a detailed background to the thesis. Chapter 2 explores unilateral versus bilateral temporal lobe epilepsy (TLE), investigating the balance of functional integration and segregation. It tests the hypothesis that increased network segregation correlates with adverse surgical outcomes. Chapter 3 analyzes the functional gradient in subcortical structures, identifying deviations in TLE patients that suggest increased network heterogeneity and segregation in right TLE. Chapter 4 extends these insights to the piriform cortex, uncovering its diverse connectivity patterns within the epilepsy network. Chapters 5 through 7 explore the utility of ultra-high field 7-Tesla MRI to better understand epilepsy. Chapter 5 demonstrates how hippocampal disconnectivity from the default mode network characterizes TLE, with 7T MRI providing superior lateralization of the seizure onset zone (SOZ) compared to 3T MRI when using this disconnectivity as a biomarker. Chapter 6 utilizes unsupervised clustering to map volumetric changes in the hippocampus and thalamus, revealing distinct atrophy patterns associated with different TLE subtypes and outcomes. Chapter 7 highlights the potential of glutamate imaging (GluCEST) at 7T to distinguish between lesional and non-lesional TLE based on hippocampal glutamate levels. The final chapters (8-10) integrate intracranial electroencephalography (iEEG) with neuroimaging. Chapter 8 introduces iEEG-recon, a tool for precise localization of intracranial electrodes, providing electrode-to-brain region correspondence. Chapter 9 develops Electrode Network Mapping (ENM), which expands electrode-specific data to global brain connectivity analyses. Chapter 10 links transient drops in signal complexity in iEEG data with functional and structural metrics from traditional neuroimaging, offering new insights into neural dynamics, and providing an iEEG metric that can be directly related back to functional MRI. Together, the findings from this thesis not only advance our understanding of epilepsy's heterogeneity but also provide neuroimaging biomarkers that could be leveraged for better diagnosis and management of this complex neurological disorder.