Cortico-Cortical Evoked Potentials to Probe Neuroplasticity: Methodological Considerations and Contextualization

Abstract

Neuroplasticity is the set of processes that allow the brain to adapt to changing conditions, needs, and inputs. It is fundamentally important for learning, memory formation, habit formation, and recovery after a brain injury. While neuroplasticity has been characterized at the cellular level, much remains to be discovered about neuroplasticity in the living, human brain. The more we understand about neuroplasticity, the better equipped we will be to leverage neuroplasticity as a clinical tool for recovery after ischemic strokes and other injuries. To study neuroplasticity in living humans, we need a way to measure connections in the brain and changes to those connections over time. Cortico-cortical evoked potentials (CCEPs) are one possible metric. CCEPs are stereotyped waveforms that can be recorded throughout the cortex in response to electrical stimulation at a single cortical site. They are a metric of effective connectivity and are interpreted as the sum of monosynaptic and polysynaptic inputs from a stimulated site to the neurons at a recording site. This makes them a useful tool for causal, directional inference about neural pathways. More directly, CCEPs measure the brain’s response to electrical stimulation. Electrical stimulation is a proposed method for inducing neuroplasticity in the aftermath of a stroke, and as a stimulation response metric, CCEPs may be particularly useful in tracking the efficacy of such treatments. However, much remains unknown about the physiological underpinnings of CCEPs and the relationship between CCEPs and the functional and behavioral outputs of the brain. This limits conclusions that can be drawn from CCEP results. In this thesis, I address some basic, unanswered questions about CCEPs. I collected CCEP data in consenting human patients implanted with stereo-electroencephalography (sEEG), electrocorticography (ECoG), and/or deep brain stimulation (DBS) electrodes for intractable epilepsy or Parkinson’s Disease. I quantitatively examine methodological considerations when choosing a data collection and analysis strategy. I also use other metrics of brain connectivity to contextualize CCEPs and work towards a clearer interpretation of their mechanisms and roles. I found that sEEG CCEP results can be influenced by methodological choices including data processing techniques, the number of trials of data collected, the quantification approach, and the period over which CCEPs are collected. This work collectively demonstrates the importance of carefully considering and fully reporting all CCEP methodology. Additionally, I found that CCEPs are not always stable between recording sessions on multiple days, indicating that long-term studies utilizing CCEPs will need to account for potential variability and supporting the hypothesis that CCEPs may be brain state dependent. I also found little similarity between CCEPs and various established metrics of resting state functional connectivity (rsFC), which suggests that CCEPs measure network processes not captured by traditional rsFC analysis. This dissertation aims to advance our understanding of CCEP mechanisms and functional significance by systematically approaching basic questions of methodological considerations and context that have often been overlooked. By more fully characterizing CCEPs, I also aim to lay the groundwork for studies to use CCEPs to measure neuroplasticity.