Mild traumatic brain injury (mTBI) is a sub-type of traumatic brain injury when loss of consciousness and disorientation is shorter than 30 minutes. Though brain imaging with MR and CT often appear normal, the patient sustains long-term cognitive difficulties such as headache, blurry vision, memory problems, attention deficits, mood swings and frustration¹. Empirical evidence suggests that immediately after injury, there is time window when the patient is vulnerable to more serious brain damage should another impact occur². It is critical to know if the patient is out of this vulnerable time window, specifically in sports³ and military⁴. In this study, we want to find functional connectivity biomarkers that are associated with mTBI symptoms with the eventual goal of these biomarkers contributing to predicting mTBI patient’s outcome and recovery.After obtaining informed consent, rs-fMRI was recorded from 78 patients at four time points (3 days, 7 days, 1 month and 3 months) after mTBI and 26 healthy controls (2 sessions, 1 week apart). After eliminating missing and noisy data, we analyzed 184 time points in total. Using GE 3T MRI scanner, multi-band (acceleration factor 3) 2D-EPI, TR/TE = 900/30 ms was acquired for 6 minutes (395 volumes), with 1.875 mm^2 in-plane resolution and 3 mm slice thickness to cover the whole brain. T1-weighted scan (1 mm resolution) was acquired at each time point. All participants filled a neurophysiological self-assessment questionnaire that was used to calculate symptom severity scores⁵. rs-fMRI data were motion corrected, rigid registered to T1-weighted image, non-rigid registered to MNI atlas, nuisance removed using aCompCor⁶, spatial smoothed using Gaussian filter (FWHM 4mm) and temporally band-pass filtered (0.01 -0.1 Hz) using custom built software. 13 seed based functional connectivity maps were extracted for all subjects. MNI seed locations are listed in Table 1. Correlation of each voxel’s connectivity map value to symptom score was computed using SPM multiple regression factorial design. Statistical significance (p<0.05) was estimated after correcting for multiple comparisons using cluster size threshold.Normal appearing functional networks were obtained for all seeds. Correlation with symptom score revealed increased connectivity between left executive control network (LECN) and default mode network (DMN) regions in patients with higher symptom scores (Figure 1a). Motor region (left face area) connectivity to primary visual areas decreased as symptom score increased (Figure 1b). The same motor region’s connections to dorsal motor area including torso area were negatively associated with symptom score (Figure 1 b). Dorsal motor region (left hand knob area) connectivity to DMN (IPL) was positively correlated to symptom score (Figure 1c). Primary visual network connectivity to higher order visual regions was strongly correlated with symptom scores (Figure 1d). We failed to detect significant connectivity associated with symptom scores in other networks.Functional connectivities between LECN, DMN, motor and visual networks seem to be affected by mTBI and are associated with symptom scores. LECN (and other task positive networks) are typically anti-correlated with the DMN^7,8 in health. In mTBI, we notice an increase in the correlation as the symptom score increases perhaps due to a breakdown of the competitiveness between these networks. Connectivity between the primary and secondary visual networks also appears to increase with symptom score. This increase in visual region connectivity has been shown when subjects become aware of stimuli⁹ and top-down attention also has an influence in this connectivity¹⁰; implying mTBI patients with higher scores are perhaps explicitly paying more attention to external stimuli. Motor region seemed to increase connectivity to DMN and decrease connectivity to visual regions as the score increases. This probably shows that motor system is less influenced by external stimuli (from visual network) and more influenced by introspective inputs from the DMN. In the current analysis, correction for multiple measures from the same subject over time was not performed. Using only one session from each subject produces similar results.The work here shows in a large sample, significant correlation between functional connectivity in visual, motor and default mode networks and self-reported symptom scores. Given this association, functional connectivity will be an important contributor to predict mTBI outcome. Future work includes probing visual, motor and attention sub-symptom-scores’ association with the corresponding networks. We are also performing longitudinal analysis of connectivities within each specific patient to enable outcome and recovery prediction.