HighlightsAn interaction between warfarin and cannabidiol is describedThe mechanisms of cannabidiol and warfarin metabolism are reviewedMechanism of the interaction is proposedINR should be monitored in patients when cannabinoids are introduced

Objective: To further evaluate the relationship between the clinical profiles and limbic and motor brain regions and their connecting pathways in psychogenic nonepileptic seizures (PNES). Neurite Orientation Dispersion and Density Indices (NODDI) multicompartment modeling was used to test the relationships between tissue alterations in patients with traumatic brain injury (TBI) and multiple psychiatric symptoms. Methods: The sample included participants with prior TBI (TBI; N = 37) but no PNES, and with TBI and PNES (TBI + PNES; N = 34). Participants completed 3T Siemens Prisma MRI high angular resolution imaging diffusion protocol. Statistical maps, including fractional anisotropy (FA), mean diffusivity (MD), neurite dispersion [orientation dispersion index (ODI)] and density [intracellular volume fraction (ICVF), and free water (i.e., isotropic) volume fraction (V-ISO)] signal intensity, were generated for each participant. Linear mixed-effects models identified clusters of between-group differences in indices of white matter changes. Pearson's r correlation tests assessed any relationship between signal intensity and psychiatric symptoms. Results: Compared to TBI, TBI + PNES revealed decreases in FA, ICVF, and V-ISO and increases in MD for clusters within cingulum bundle, uncinate fasciculus, fornix/stria terminalis, and corticospinal tract pathways (cluster threshold a = 0.05). Indices of white matter changes for these clusters correlated with depressive, anxiety, PTSD, psychoticism, and somatization symptom severity (FDR threshold a = 0.05). A follow-up within-group analysis revealed that these correlations failed to reach the criteria for significance in the TBI + PNES group alone. Interpretation: The results expand support for the hypothesis that alterations in pathways comprising the specific PNES network correspond to patient profiles. These findings implicate myelin-specific changes as possible contributors to PNES, thus introducing novel potential treatment targets.

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