Functional magnetic resonance imaging (fMRI) neurofeedback targeting areas such as the amygdala or insula for depression or anxiety symptoms leads to significant improvements [1]. However, there are barriers to widespread access to fMRI neurofeedback, including the necessary infrastructure and high costs of MRI data acquisition. Accordingly, recent studies have proposed neurofeedback protocols based on scalp-read signatures of deep brain activity, also known as fingerprinting neurofeedback (FP-NF) [2]. FP-NF could allow for more widely accessible or even mobile protocols. As it depends on less expensive and potentially more widely available electroencephalography or functional near-infrared spectroscopy, it provides more democratic access to this technology “in the wild”.

FP-NF patterns likely result from signal transmission from the neurofeedback target to structurally connected surface regions. Therefore, delineating the anatomical connections to and from the neurofeedback targets can provide insights into identifying accessible targets. To date, tract-tracing experiments in non-human primates (NHP) are considered the gold-standard method for mapping anatomic connections and pathways. This approach has higher resolution and reliability than in vivo structural imaging methods such as diffusion MRI (dMRI); dMRI has several limitations in its ability to accurately reproduce tracts (e.g., those arising from crossing, branching, and turning fibers), which are evident when directly comparing the connections mapped using tracing methods and dMRI in the same NHP brain [3]. Importantly, connectomes from NHP tract tracing data have moderate to strong correlations with those computed using fMRI functional connectivity within and across species [4].