Intracortical Dynamics Underlying Repetitive Stimulation Predicts Changes in Network Connectivity

Targeted stimulation can be used to modulate the activity of brain networks. Previously we demonstrated that direct electrical stimulation produces predictable poststimulation changes in brain excitability. However, understanding the neural dynamics during stimulation and its relationship to poststimulation effects is limited but critical for treatment optimization. Here, we applied 10 Hz direct electrical stimulation across several cortical regions in 14 human subjects (6 males) implanted with intracranial electrodes for seizure monitoring. The stimulation train was characterized by a consistent increase in high gamma (70–170 Hz) power. Immediately post-train, low-frequency (1–8 Hz) power increased, resulting in an evoked response that was highly correlated with the neural response during stimulation. Using two measures of network connectivity, corticocortical evoked potentials (indexing effective connectivity), and theta coherence (indexing functional connectivity), we found a stronger response to stimulation in regions that were highly connected to the stimulation site. In these regions, repeated cycles of stimulation trains and rest progressively altered the stimulation response. Finally, after just 2 min (∼10%) of repetitive stimulation, we were able to predict poststimulation connectivity changes with high discriminability. Together, this work reveals a relationship between stimulation dynamics and poststimulation connectivity changes in humans. Thus, measuring neural activity during stimulation can inform future plasticity-inducing protocols. SIGNIFICANCE STATEMENT Brain stimulation tools have the potential to revolutionize the treatment of neuropsychiatric disorders. Despite the widespread use of brain stimulation techniques such as transcranial magnetic stimulation, the therapeutic efficacy of these technologies remains suboptimal. This is in part because of a lack of understanding of the dynamic neural changes that occur during stimulation. In this study, we provide the first detailed characterization of neural activity during plasticity induction through intracranial electrode stimulation and recording in 14 medication-resistant epilepsy patients. These results fill a missing gap in our understanding of stimulation-induced plasticity in humans. In the longer-term, these data will also guide our translational efforts toward non-invasive, personalized, closed-loop neuromodulation therapy for neurological and psychiatric disorders in humans.