Epilepsy is one of the most common brain disorders characterized by its ability to generate epileptic seizures and various neurobiological and cognitive consequences. Around 30 % of epileptic patients have drug-resistant epilepsy (DRE), which is resistant to multiple pharmacologic therapies. However, resection or laser ablation is not suitable for all DRE patients because some patients don’t have safely removable seizure onset zones. For those patients, neuromodulation is an alternate treatment option. Neuromodulation is currently used to treat kinds of neurological disorders, including Parkinson’s disease, essential tremor, and epilepsy. There are currently three types of neuromodulation approved in the United States, which are responsive neurostimulation (RNS),  vagus nerve stimulation (VNS), and deep brain stimulation (DBS). DBS of the anterior nuclei of the thalamus (ANT), has been shown the ability to reduce seizures. However, studies have shown not all seizure networks significantly involve ANT. Some other regions, such as the centromedian thalamus (CM), pulvinar are also being actively studied as potential targets for epilepsy DBS. Moreover, it is unclear what stimulation parameters could lead to the best stimulation outcome. More investigations need to be done to understand how stimulation targets and parameters influence the brain.

 Epilepsy is well-recognized as a network disorder. Many studies are trying to understand epilepsy from the perspective of brain networks. Three kinds of brain connectivity are usually used to study brain networks. Structural connectivity, which is defined as the anatomical connections between neural elements. Though the information flow within the brain can be inferred based on structural connectivity, functionality or directionality cannot. Functional connectivity is defined as the correlated neural activity among different brain regions. It is able to characterize inter-regional communication in a dynamic fashion. Different from the functional connectivity that only addresses statistical relationships, effective connectivity can help reveal the underlying mechanisms of interaction among neural regions. One emerging method to quantify the effective connectivity is cortico-cortical evoked potential (CCEP). By directly stimulating specific brain regions and recording the response signals in other brain regions, it provides a robust method to map the effective connection from the stimulation targets to the other brain regions.

In our project, we stimulate the ANT with different parameter settings and record the neural activity from the other brain regions. We seek to study the network influence of the brain under thalamus stimulation with different parameters by analyzing the thalamo-cortical evoked potential patterns. Furthermore, we aim to investigate the system-level input-output relationship of thalamic DBS. Our results will provide new references to DBS parameters and target optimization.

Figures: 

1. Coverage of an example patient, with Thalamus (light blue), anterior nuclei of the thalamus (dark blue), Hippocampus (red), and Amygdala (green) highlighted.

2. Example ANT effective connection map. The darker the color, the stronger the connection.