Numerous studies argue that cortical reorganization may contribute to the restoration of motor function following stroke. However, the evolution of changes during the post-stroke reorganization has been little studied. This study sought to identify dynamic changes in the functional organization, particularly topological characteristics, of the motor execution network during the stroke recovery process. Ten patients (nine male and one female) with subcortical infarctions were assessed by neurological examination and scanned with resting-state functional magnetic resonance imaging across five consecutive time points in a single year. The motor execution network of each subject was constructed using a functional connectivity matrix between 21 brain regions and subsequently analysed using graph theoretical approaches. Dynamic changes in topological configuration of the network during the process of recovery were evaluated by a mixed model. We found that the motor execution network gradually shifted towards a random mode during the recovery process, which suggests that a less optimized reorganization is involved in regaining function in the affected limbs. Significantly increased regional centralities within the network were observed in the ipsilesional primary motor area and contralesional cerebellum, whereas the ipsilesional cerebellum showed decreased regional centrality. Functional connectivity to these brain regions demonstrated consistent alterations over time. Notably, these measures correlated with different clinical variables, which provided support that the findings may reflect the adaptive reorganization of the motor execution network in stroke patients. In conclusion, the study expands our understanding of the spectrum of changes occurring in the brain after stroke and provides a new avenue for investigating lesion-induced network plasticity.

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.

As a promising non-invasive neuroimaging technique, functional near-infrared spectroscopy (fNIRS) has seen increasing use in neuroscientific studies over the last decades.^{1 – 3} Compared to other neuroimaging techniques, fNIRS has several specific advantages: acceptable spatial resolution; lower cost, silent, higher temporal resolution, lower sensitivity to head motion, and fewer physical constraints compared to functional magnetic resonance imaging (fMRI); portability/mobility and few restrictions on use location. These advantages make it an ideal alternative for detecting human brain activity in both healthy people (from newborns to the elderly) and patients with neurological or psychiatric conditions, in both laboratory and natural contexts. Validation studies using simultaneous fNIRS and fMRI scanning have shown fNIRS to be effective for both task-driven activation detection^{4 – 8} and resting-state brain function research.^9,10 FNIRS has been successfully applied to various neuroscience domains, including areas such as motor-related studies with large bodily movements, social cognitive neuroscience, and neurodevelopment.^{11 – 15} In addition to task-evoked activation studies, fNIRS has also seen increasing use in detecting spontaneous brain activity absent of external stimuli during resting state,^{16 – 20} which is particularly useful for several special populations who cannot perform complicated tasks, such as infants and patients with certain deficits.