Predicting recovery for patients with disorders of consciousness (DoC) remains exceptionally difficult due to the vast differences in injury causes and demographic backgrounds. Therefore, it is critical to investigate how these clinical variables associate with large-scale brain network reorganization and whether such connectivity patterns ultimately relate to long-term outcomes.

On October 20, 2026, a research team from the Institute of Biophysics of the Chinese Academy of Sciences, and Beijing Tiantan Hospital, Capital Medical University, published a study in The Innovation Life revealing the connection between clinical characteristics (etiology, age, and time since injury) and brain network connectivity, as well as their crucial role in patients' functional recovery.

Clinical assessment results showed that patients with traumatic brain injury (TBI) exhibited higher consciousness levels and better long-term functional recovery than those with anoxic brain injury. Additionally, younger age was associated with higher consciousness levels and better recovery outcomes. Among the patients included in this study who were at least 28 days post-injury, the time since injury showed no significant correlation with either of these two indicators.

The researchers analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from 128 patients with disorders of consciousness (DoC) and 40 healthy controls, examining the functional connectivity among 22 cortical regions across six major brain networks, including the default mode network (DMN).

By combining rs-fMRI with clinical assessments, the study found that different clinical characteristics correspond to distinct brain network connectivity patterns. Specifically, etiology-related internetwork connectivity is closely associated with functional recovery.

Functional connectivity associated with etiology, age, and time since injury was distributed across different brain networks with minimal overlap. In a machine learning model designed to distinguish the three etiologies, the connectivity features of the DMN contributed the most.

Further analysis revealed that among etiology-related connections, functionally recovered patients exhibited stronger positive intranetwork correlations and more pronounced negative internetwork correlations compared to non-recovered patients. This suggests that the preservation of modular network organization may be linked to recovery potential.

Statistical mediation analysis indicated that internetwork functional connectivity could statistically account for the recovery advantage observed in TBI patients compared to those with anoxic injuries. However, age and time since injury did not show similar significant indirect effects.

These findings link etiology-related brain network connectivity to long-term functional recovery, offering insights into the varying recovery trajectories among patients with different etiologies.

Notably, the aforementioned mediation effects reflect statistical correlations rather than causal relationships; therefore, further verification through longitudinal studies and interventional trials remains necessary.

Figure 1: Relationship between brain network connectivity and clinical characteristics

Figure 2: Associations of intra- and inter-network functional connectivity with consciousness level and functional recovery

(Image by YANG Yan's group)

Article link: https://doi.org/10.59717/j.xinn-life.2026.100266

Contact: YANG Yang

Institute of Biophysics, Chinese Academy of Sciences

Beijing 100101, China

E-mail: yyang@ibp.ac.cn

(Reported by Prof. YANG Yan's group)