# Good Neighbors, Bad Neighbors: The Frequent Network Neighborhood Mapping of the Hippocampus Enlightens Several Structural Factors of the Human Intelligence on a 414-Subject Cohort

## TL;DR

This study maps the frequent network neighborhoods of the hippocampus in 414 human brains, revealing structural factors that correlate with intelligence and memory performance, using advanced graph analysis techniques.

## Contribution

It introduces the Frequent Network Neighborhood mapping method to identify hippocampal neighbor sets linked to psychological traits in a large cohort.

## Key findings

- Identified hippocampal neighbor sets associated with high intelligence scores.
- Found neighbor sets correlated with low memory test scores.
- Demonstrated the utility of advanced graph analysis in connectomics research.

## Abstract

The human connectome has become the very frequent subject of study of brain-scientists, psychologists, and imaging experts in the last decade. With diffusion magnetic resonance imaging techniques, unified with advanced data processing algorithms, today we are able to compute braingraphs with several hundred, anatomically identified nodes and thousands of edges, corresponding to the anatomical connections of the brain. The analysis of these graphs without refined mathematical tools is hopeless. These tools need to address the high error rate of the MRI processing workflow, and need to find structural causes or at least correlations of psychological properties and cerebral connections. Until now, structural connectomics was only rarely able identifying such causes or correlations. In the present work, we study the frequent neighbor sets of the most deeply investigated brain area, the hippocampus. By applying the Frequent Network Neighborhood mapping method, we identified frequent neighbor-sets of the hippocampus, which may influence numerous psychological parameters, including intelligence-related ones. We have found neighbor sets, which have significantly higher frequency in subjects with high-scored Penn Matrix tests, and with low-scored Penn Word Memory tests. Our study utilizes the braingraphs, computed from the imaging data of the Human Connectome Project's 414 subjects, each with 463 anatomically identified nodes.