# Neural circuit basis of safety learning > **NIH NIH R21** · BOSTON COLLEGE · 2024 · $426,250 ## Abstract ABSTRACT Learning about and using environmental cues for safety is critical for survival and mental wellbeing. Current research on safety signals identifies the basolateral amygdala, insular cortex and infralimbic prefrontal cortex as important components of the neural circuits needed to process safety signals. These structures are anatomically interconnected and the proposed studies will be the first to test whether they work together in response to safety signals to mediate safety learning and fear inhibition. Prior mechanistic and descriptive electrophysiology experiments point to the amygdala and insula as key sites for safety learning but not necessarily for recall. Aim 1 will test the hypothesis that basolateral amygdala neurons that project to the insular cortex convey information about the safety signal and are necessary for safety learning. In contrast, the infralimbic cortex is responsive to already learned safety signals and is thought to be critical for behavioral inhibition during threat. Aim 2 will test the hypothesis that infralimbic neurons which receive input from the insular cortex are critical for fear inhibition by safety signals. The results will help complete our understanding of the neural mechanisms underlying safety learning and provide a basis for understanding abnormal safety related behavior in psychopathology. ## Key facts - **NIH application ID:** 10987376 - **Project number:** 1R21MH135410-01A1 - **Recipient organization:** BOSTON COLLEGE - **Principal Investigator:** John Paul Christianson - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $426,250 - **Award type:** 1 - **Project period:** 2024-07-10 → 2026-07-09 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10987376 ## Citation > US National Institutes of Health, RePORTER application 10987376, Neural circuit basis of safety learning (1R21MH135410-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10987376. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*