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To elucidate the association between recurrent concussion and subconcussive head impacts andb the efficiency of resting state neural networks in retired American football athletes.Cross-sectional.32 former college football athletes and 32 former professional football athletes matched on age, position, and self-reported concussion history (age: 58.5±3.6 y). Of those, 61 subjects had quality imaging data (31 College, 30 Professional). Subjects were stratified by concussion history (High, 3+, N=31; Low, 0–1, N=30).IVs: Concussion history (Low/High) and football exposure (College/Professional). DVs: Mean local efficiency (LE) and clustering coefficients (CC) for seven anatomically defined neural subnetworks: frontal, temporal, occipital, medial temporal, subcortical, parietal, and cerebellar. Outcomes were analysed across several correlational thresholds (r=0–0.9).The high concussion group had lower frontal LE and CC than the low concussion group (Effect size range: 0.260 – 0.437, P<0.05). A crossover history-by-exposure interaction was observed in the cerebellar network (P=0.0063), such that former college athletes with high concussion history demonstrated lower LE and CC than college athletes with low concussion history. Interestingly, professional athletes with high concussion history demonstrated greater LE and CC than those with low concussion history. No other associations were observed across the five remaining neural networks.These data challenge the notion that subconcussive head impact exposure is linked to long-term neurological dysfunction. Our data point to a potential heightened cerebellar network resiliency among retired professional athletes with a high number of concussions. Subconcussive head impact exposure alone does not appear to affect widespread cortical and cerebellar network function among retired American football athletes.None.Member of the Mackey-White committee of the NFL Players Association and member of the Head, Neck, and Spine Committee of the NFL.