Cortical similarity networks in the rat brain: Postnatal development and sensitivity to early life stress

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Authors: Rachel L. Smith, Stephen J. Sawiak, Lena Dorfschmidt, Ethan G. Dutcher, Jolyon A. Jones, Joel D. Hahn, Olaf Sporns, Larry W. Swanson, Paul A. Taylor, Daniel Glen, Jeffrey W. Dalley, Francis J. McMahon
+3 more Armin Raznahan, Petra E. Vértes, Edward Thomas Bullmore
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Abstract

Abstract Network models are a key tool in human neuroscience, and translation into animal models is essential for interrogating mechanistic drivers of network organization. Using magnetic resonance imaging (MRI), we present the first in vivo network representation of the individual rat brain, a key animal model in neuroscience. We measured magnetization transfer ratio (MTR) at each of 53 distinct cortical areas and estimated a cortical similarity network for each scan across two independent cohorts. We characterized normative network development in rats scanned repeatedly between postnatal days 20 (weanling) and 290 (mid-adulthood; N = 47) and then contrasted these findings with a cohort exposed to early life stress (repeated maternal separation [RMS]; N = 40). The normative rat cortical similarity network exhibited biologically meaningful organization, consistent with cytoarchitectonic and tract-tracing data, and displayed complex topological features. Developmental analyses revealed increasing interregional similarity during early postnatal and adolescent periods, followed by divergence in mid-adulthood, particularly within fronto-hippocampal systems. RMS disrupted these trajectories, especially between frontal and parahippocampal regions that were also most dynamic during development and aging. These findings introduce a new network-based methodology for studying cortical organization in a model organism, providing a translational framework to understand how environmental risk factors alter brain network development.

Fields of Study & Subjects

Functional Brain Connectivity Studies Advanced Neuroimaging Techniques and Applications Advanced MRI Techniques and Applications

Publication details

Journal / source
Network Neuroscience
Volume
10
Issue
2
Pages
418–443
Publication date
1 January 2026
Language
EN