# Neural Mechanisms of Social Information Processing > **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $829,966 ## Abstract Project Summary To feel, remember and act in a social environment, incoming social stimuli must be processed and represented. Recent advances have revealed several routes of social information flow which converge on the dorsal (d)CA2. Ensembles encoding individual identity have also been found in the dCA2, but how diverse social information is integrated to form coherent social representations remains elusive. Studies in human participants have provided early evidence that the hippocampus tracks two social features, familiarity and hierarchy, jointly. However, it is poorly understood how neural ensembles encode social characteristics and how incoming information instruct the formation of social representations based on those characteristics. To address this major knowledge gap, our overall objective is to bridge circuit and population coding mechanisms to determine the neural basis of social information processing. As familiarity and hierarchy are two factors by which social relationships are evaluated across species, we reason that dissociating their circuit and population coding mechanisms will reveal how social information is structured in the brain. Our preliminary data suggest that the dCA2 is functionally relevant for hierarchy and familiarity behaviors and its activity scales with rank distance. Given that the entorhinal cortex shows grid-like activity in rank representation, we hypothesize that the dCA2 may display place cell-like dynamics to signal familiarity and hierarchy distance on an abstract social cognitive map. We will test this hypothesis in Aim 1 with bulk (fiber photometry) and single-cell imaging (Miniscope) of the dCA2 in response to varied familiarity or hierarchy stimuli. Using the imaging data, we will evaluate predictive models of coding strategy with linear classifiers. In Aim 2 we will assess how social presentations of familiarity and hierarchy arise. We have preliminary evidence that distinct neuromodulator activity in the dCA2 correlates with rank distance. As neuromodulators are mainly released into the dCA2 by the paraventricular nucleus of the hypothalamus (PVH), we hypothesize that specific neuromodulators released by the PVH differentially impacts the geometry of the social characteristics. Thus, we will use novel neuromodulator sensors to monitor their dynamics and manipulate their signaling during Miniscope recordings. Finally, we will test their functional relevance by inhibiting their release from the PVH during hierarchy and familiarity behaviors. The approach detailed in this proposal is highly innovative because it leverages new technological advances (novel neuromodulator sensors) and integrates cutting-edge techniques (manipulation of neuromodulator signaling with Miniscope imaging and computational modeling) to address a major knowledge gap in social cognition. As no unified theories of circuit and population coding mechanisms for social information processing exist, the proposed research is highly si... ## Key facts - **NIH application ID:** 10872396 - **Project number:** 1R01MH136228-01 - **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI - **Principal Investigator:** Xiaoting Wu - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $829,966 - **Award type:** 1 - **Project period:** 2024-08-16 → 2029-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10872396 ## Citation > US National Institutes of Health, RePORTER application 10872396, Neural Mechanisms of Social Information Processing (1R01MH136228-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10872396. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*