Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury

Abstract

For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI.

Significance statement: Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness.

Keywords: acquired brain injury; hub; posterior cingulate cortex/precuneus; prediction; recovery outcome; resting state fMRI.

Figure 1.

A–E, Average FCS maps within the CON (A), PC (B), MCS (C), UWS/VS (D), and coma (E) groups. FCS maps of individual participants were standardized to z-scores and then averaged within each group. A hot color represents higher FCS than the global mean, and a cold color represents lower FCS than the global mean. All of the results were mapped onto the cortical surfaces using in-house BrainNet viewer software (Xia et al., 2013).

Figure 2.

Group differences in FCS. A, Main group effect of FCS among the five groups (p < 0.05 corrected, with uncorrected p < 0.01 for each voxel and a minimum of 84 voxels in each cluster). The largest region was composed of multiple brain areas and was decomposed into several subregions, including the right anterior insula, left inferior temporal gyrus, right inferior temporal gyrus, left medial temporal lobe, right medial temporal lobe, left basal ganglia, right basal ganglia, and right orbital frontal cortex. B, Fingerprint plots of the mean fitted FCS (FCS with covariates such as the age and gender removed) across the five groups for each of the regions that showed main group effects. Regions overlapping the DMN are labeled in blue, while those overlapped with the SN/ECN were labeled in cyan. Other regions that showed increased FCS with decreased consciousness were labeled in red. C–L, Post hoc comparisons of 10 pairs of groups (p < 0.05 corrected). Two-sample t-maps highlighting the difference between PC patients and CONs (C), MCS patients and CONs (D), UWS/VS patients and CONs (E), coma patients and CONs (F), MCS and PC patients (G), UWS/VS and PC patients (H), coma and PC patients (I), UWS/VS and MCS patients (J), coma and MCS patients (K), and coma and UWS/VS patients (L) are shown. To note, there was no significant difference between UWS/VS and MCS patients (J), between coma and MCS patients (K), or between coma and UWS/VS patients (L). LIPL, Left inferior parietal lobule; MPFC, medial prefrontal cortex, LIPS, left intraparietal sulcus; RIPS, right intraparietal sulcus; RINS, right anterior insula; MCC, middle cingulate cortex; LITG, left inferior temporal gyrus; RITG, right inferior temporal gyrus; LMTL, left medial temporal lobe; RMTL, right medial temporal lobe; LBG, left basal ganglia; RBG, right basal ganglia; and ROFC, right orbital frontal cortex.

Figure 3.

A, The relationship between FCS and the GCS score. Six regions showed a significant Spearman's correlation based on voxelwise analysis after correction (p < 0.05). Scatter plots between the mean fitted FCS (FCS with covariates such as age, gender, and time elapsed before fMRI after injury removed) in two representative regions (the PCC/PCU and the left IPL) and the GCS score are shown. B, The relationship between FCS and the CRS-R score. Four regions showed significant correlation based on voxelwise analysis after correction (p < 0.05). Scatter plots between the mean fitted FCS in two representative regions (the PCC/PCU and the left IPL) and the CRS-R score are shown. LIPL, Left inferior parietal lobule.

Figure 4.

FCS predicted recovery outcome. A, Five regions showed significant correlations with the GOS score (p < 0.05 corrected). Scatter plots showing the difference between the mean fitted FCS in two representative regions (the PCC/PCU and the MPFC) and the GOS score are shown. B, Absolute discriminating maps of multivariate support vector machine analysis of UWS/VS plus coma patients to characterize awakened or nonawakened status 3 months after the fMRI scanning using FCS (clusters with at least 84 voxels were shown). The classifier with the LOOCV demonstrated accuracy of 81.25%, a specificity of 88.89%, and a sensitivity of 71.43%. Scatter plot shows that 2 of 18 nonawakened patients (GOS score <3, labeled in blue circle) were incorrectly classified, and 4 of 14 awakened patients (GOS score >2, labeled in red square) were incorrectly classified. MPFC, Medial prefrontal cortex.

Figure 5.

A–E, The PCC/PCU resting-state functional connectivity (RSFC) maps of the CON (A), PC (B), MCS (C), UWS/VS (D), and coma (E) groups.

Figure 6.

Group differences in the PCC/PCU resting-state functional connectivity (RSFC). A, Main group effect of the PCC/PCU RSFC among the five groups (p < 0.05 corrected). B, Fingerprint plots of the mean fitted RSFCs of each region that showed a significant main effect across the five groups. Regions overlapped with the DMN are labeled in blue, while those overlapped with the SN/ECN are labeled in red. C–L, Post hoc comparisons of 10 pairs of groups (p < 0.05 corrected); two-sample t-maps between PC patients and CONs (C), MCS patients and CONs (D), UWS/VS patients and CONs (E), coma patients and CONs (F), MCS and PC patients (G), UWS/VS and PC patients (H), coma and PC patients (I), UWS/VS and MCS patients (J), coma and MCS patients (K), and between coma and UWS/VS patients (L) were shown. Of note, there was no significant difference between UWS/VS and MCS patients (J), between coma and MCS patients (K), or between coma and UWS/VS patients (L). MPFC/SFG, Medial prefrontal cortex extending to the bilateral superior frontal gyrus; LIPL, left inferior parietal lobule; RIPL, right inferior parietal lobule; LaITG, left anterior inferior temporal gyrus; RaITG, right anterior inferior temporal gyrus; LFP, left frontoparietal regions, including the intraparietal sulcus, insula, middle and inferior frontal gyrus; RaFP, right anterior regions of FP, including the insula, middle and inferior frontal gyrus; MCC, middle cingulate cortex; RIPS, right intraparietal sulcus; LpITG, left posterior temporal gyrus; RMFG, right middle frontal gyrus.

Figure 7.

The relationship between PCC/PCU resting-state functional connectivity (RSFC), consciousness level, and recovery outcome. A, Correlation between the PCC/PCU RSFC and consciousness level indexed by the GCS and CRS-R scores (p < 0.05 corrected). B, Prediction of the GOS score across the four acquired brain injury groups (left, p < 0.05 corrected) and absolute discriminative maps of multivariate support vector machine analysis (clusters with at least 84 voxels are shown) of the UWS/VS plus coma patients to characterize awakened or nonawakened status (right) 3 months after the fMRI scanning based on the PCC/PCU RSFC.

Figure 8.

A–C, Scatter plots demonstrate the relationship between PCC/PCU resting-state functional connectivity (RSFC) and clinical indices, including GCS score (A), CRS-R score (B), and GOS score (C). Figure 7 demonstrates that the regions that negatively correlated with clinical indices are located in the SN/ECN, while those that positively correlated with clinical indices are in the DMN. Thus, for each clinical index, all the voxels that positively correlated with that clinical index are defined as DMN, while those that negatively correlated with that clinical index are defined as SN/ECN. Scatter plots between clinical indices and mean fitted PCC/PCU RSFC (with covariates such as age, gender, and time of fMRI after injury removed) of the DMN are shown in the left column. Similarly, scatter plots between clinical indices and the mean fitted PCC/PCU RSFC of the SN/ECN are shown in the right column.

Figure 9.

Validation of the FCS findings. A–G, Main group effect of FCS, and correlations between FCS and GCS, CRS-R, and GOS scores (p < 0.05 corrected) calculated by weighted network (our main findings; A), binary network (B), weighted network with shortest data length (number of TRs = 135; C), weighted network with only positive connections considered (D), weighted network without global signal removal (GSR; E), weighted network without local connections (excluded local connections that were within 20 mm; F), and weighted network with TBI only (G).

Figure 10.

Frequencies of spatial overlap among the results of different preprocessing procedures in Figure 9.