Quantifying Prefrontal-Hippocampal Circuit Engagement Using Scalp EEG and the Paired Associates Learning Task

The hippocampus (HPC)-prefrontal cortical (PFC) circuit, critical for affective processing and cognition, is vulnerable in mental health disorders. Although disrupted HPC-PFC functional connectivity is a common feature of anxiety, schizophrenia, and autism, how local cellular interactions within this circuit manifest as large-scale temporal coordination remains unknown. The objective of this project is to provide novel mechanistic insights into disrupted neural coordination in mental illness by examining the relationship between invasive local field potential (LFP) recordings from the HPC and PFC, and scalp electroencephalogram (EEG) during the Paired Associates Learning (PAL) task. The PAL task measures visuospatial associative memory by requiring animals to learn the stimulus-location pairing of different images on a touchscreen. We have previously shown that manipulations that disrupt HPC-PFC coordination, such as traumatic brain injury and advanced age, lead to PAL performance impairments. Importantly, EEG recordings during PAL performance in human study participants have shown associations between behavioral deficits and altered neural dynamics in schizophrenia and anxiety. We hypothesize that simultaneous LFP and EEG recordings from rats performing the PAL task will reveal highly correlated theta power across brain regions, as well as significant phase relationships among frequencies when compared to rest periods. Preliminary data show correlated increases in theta power in both the LFP and EEG from HPC as well as PFC, and higher power in the theta frequency band during PAL compared to rest periods. Future analyses will determine phase coherence between frequencies within a signal as well as brain regions. Exploring the relationship between invasive neurophysiological measures of the LFP and non-invasive surface EEG signals in the context of a translatable behavioral paradigm could provide new physiological and behavioral biomarkers that may be capable of predicting HPC-PFC coordination and aid the development of therapies for treating mental health disorders. The Evelyn F. McKnight Brain Research Foundation and the NIH/NIMH (grant R01MH126236). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.