# Characterizing Individuals' Cognitive Maps of their Village Social Networks > **NIH NIH R01** · YALE UNIVERSITY · 2023 · $697,939 ## Abstract The pattern of social connections within a population (whether a school, firm, village, or online group) is mentally perceived by those embedded within it. Such “cognitive social networks” (the mental maps people make of the social world around them) are relevant to people’s social, mental, and physical well-being. More formally, a sociocentric social network defines a set of dyadic relationships between individuals in a defined population and can be represented by a 𝑁 × 𝑁 matrix A where each element Aij represents a tie between individuals i and j, e.g., reported by individual i. But individuals not only form mental representations of their own relationships, they also cognize relationships between others. For instance, an individual k may have a perception of the relationship between i and j, say, that i is a friend of j. This yields a three-dimensional network structure with entries 𝑖, 𝑗, 𝑘 ∈ 𝑁 × 𝑁 × 𝑁, where i is the “sender,” j the “receiver,” and k the “perceiver” of the relationship. Humans are innately interested in tracking relationships, despite the cognitive burden. Such knoweldge is often the basis for introductions, strategic information disclosure, and accessing social support. In an ongoing longitudinal cohort involving 24,862 people aged 12-93 in 176 villages in rural Honduras, we have mapped real, face-to-face network ties. Pertinently, we have 4,589 participants older than 50 at baseline (in 2016). Here, in new work involving an ongoing subset of 136 villages, we will assess how people form such cognitive social maps, how these maps vary, and how these perceptions might matter. We have four specific aims. In Aim 1, we ascertain the actual and perceived ties among individuals in the networks of 136 villages. We will ask each resident, in every village, about their perceptions of the connections that might exist among 40 randomly chosen other pairs of people in their village. In Aim 2, we compare the actual ties seen in village- level social networks to the ties perceived by members of the village. Our primary hypotheses are that ties geodesically further away from individuals will be assessed less accurately; that more socially connected individuals will be more accurate; and that older, male, or cognitively impaired individuals will be less accurate. In Aim 3, we assess how the accuracy of perception depends on the characteristics of the perceived tie. Our primary hypotheses are that ties between older individuals or ties involving fewer public displays of connection will be less well perceived by others. In Aim 4, taking advantage of a randomized experiment, we evaluate if being better able to accurately perceive social connections in one’s village is associated with one’s ability to spread novel information, including health information. Our primary hypothesis is that more socially perceptive individuals will have a greater ability to spread exogenously introduced information. Our results have fundamental implications not only... ## Key facts - **NIH application ID:** 10651157 - **Project number:** 1R01AG081814-01 - **Recipient organization:** YALE UNIVERSITY - **Principal Investigator:** NICHOLAS A CHRISTAKIS - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $697,939 - **Award type:** 1 - **Project period:** 2023-06-01 → 2027-02-28 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10651157 ## Citation > US National Institutes of Health, RePORTER application 10651157, Characterizing Individuals' Cognitive Maps of their Village Social Networks (1R01AG081814-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10651157. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*