Epilepsy is a debilitating neurological disease characterized by recurrent spontaneous seizures. Despite the development of over 40 anti-seizure medications and other types of therapies, between 15 – 30 percent of patients continue to experience uncontrolled seizures. We postulate that the reason for such a disconnect between the increasing availability of therapies and the lack of change in the percentage of patients with refractory seizures is due to limitations in our understanding of the mechanistic basis behind seizures. In my thesis, we take a multi-pronged approach to develop technologies that expand our understanding of seizure dynamics and enhance the etiological relevance of disease models used in screening therapies. First, we improve our understanding of the cellular dynamics of seizures by developing a transparent graphene microelectrode. Simultaneous two-photon imaging and electrographic recording reveal that seizures tend to follow a stereotyped local propagation pattern. Seizure dynamics, such as speed and directionality, can be accurately predicted by machine learning models trained on processing the multimodal data. Next, we visualize hemisphere-wide dynamics of seizure spread using transparent MXene microelectrodes. Simultaneous widefield single-photon imaging and electrographic recording over a 7.5 mm2 area of the cortex show how the ictal wavefront spreads across the cortex from the seizure initiation zone. Analysis of ictal activity by non-negative matrix factorization, a dimensionality reduction measure, reveal that the most common type of seizures changed during the recording, suggesting a brain state shift in the animal over time. Then, we harness our understanding of seizure dynamics to create an etiologically relevant model for screening epilepsy therapies. In this model, we optogenetically excite a population of neurons that are highly active during seizures to induce seizures on demand. On demand seizures can be used to screen multiple types of therapies and can accelerate evaluation of new therapeutics in chronically epileptic mice. In all, our investigation into seizure dynamics covers the cellular, hemisphere, and whole organism levels. By integrating new tools that inform the development and predict the efficacy of seizure treatments, my thesis takes us one step closer to accomplishing our ultimate goal – improving the quality of life for epilepsy patients everywhere.