Effects of the differences in mental states on the mirror system activities when observing hand actions

Beta-band differences in primary motor cortex between media and non-media professionals when watching motor actions in movies

To watch a person doing an activity has an impact on the viewer. In fact, the film industry hinges on viewers looking at characters doing all sorts of narrative activities. From previous works, we know that media and non-media professionals perceive differently audiovisuals with cuts. Media professionals present a lower eye-blink rate, a lower activity in frontal and central cortical areas, and a more organized functional brain connectivity when watching audiovisual cuts. Here, we aimed to determine how audiovisuals with no formal interruptions such as cuts were perceived by media and non-media professionals. Moreover, we wondered how motor actions of characters in films would have an impact on the brain activities of the two groups of observers. We presented a narrative with 24 motor actions in a one-shot movie in wide shot with no cuts to 40 participants. We recorded the electroencephalographic (EEG) activity of the participants and analyzed it for the periods corresponding to the 24 motor actions (24 actions × 40 participants = 960 potential trials). In accordance with collected results, we observed differences in the EEG activity of the left primary motor cortex. A spectral analysis of recorded EEG traces indicated the presence of significant differences in the beta band between the two groups after the onset of the motor activities, while no such differences were found in the alpha band. We concluded that media expertise is related with the beta band identified in the EEG activity of the left primary motor cortex and the observation of motor actions in videos.

[Mirror neurons, neural substrate of action understanding?]

In 1992, the Laboratory of Human Physiology at the University of Parma (Italy) publish a study describing "mirror" neurons in the macaque that activate both when the monkey performs an action and when it observes an experimenter performing the same action. The research team behind this discovery postulates that the mirror neurons system is the neural basis of our ability to understand the actions of others, through the motor mapping of the observed action on the observer's motor repertory (direct-matching hypothesis). Nevertheless, this conception met serious criticism. These critics attempt to relativize their function by placing them within a network of neurocognitive and sensory interdependencies. In short, the essential characteristic of these neurons is to combine the processing of sensory information, especially visual, with that of motor information. Their elementary function would be to provide a motor simulation of the observed action, based on visual information from it. They can contribute, with other non-mirror areas, to the identification/prediction of the action goal and to the interpretation of the intention of the actor performing it. Studying the connectivity and high frequency synchronizations of the different brain areas involved in action observation would likely provide important information about the dynamic contribution of mirror neurons to "action understanding". The aim of this review is to provide an up-to-date analysis of the scientific evidence related to mirror neurons and their elementary functions, as well as to shed light on the contribution of these neurons to our ability to interpret and understand others' actions.

Neurobiological Bases of Social Networks

A social network is a web that integrates multiple levels of interindividual social relationships and has direct associations with an individual’s health and well-being. Previous research has mainly focused on how brain and social network structures (structural properties) act on each other and on how the brain supports the spread of ideas and behaviors within social networks (functional properties). The structure of the social network is correlated with activity in the amygdala, which links decoding and interpreting social signals and social values. The structure also relies on the mentalizing network, which is central to an individual’s ability to infer the mental states of others. Network functional properties depend on multilayer brain-social networks, indicating that information transmission is supported by the default mode system, the valuation system, and the mentalizing system. From the perspective of neuroendocrinology, overwhelming evidence shows that variations in oxytocin, β-endorphin and dopamine receptor genes, including oxytocin receptor (OXTR), mu opioid receptor 1 (OPRM1) and dopamine receptor 2 (DRD2), predict an individual’s social network structure, whereas oxytocin also contributes to improved transmission of emotional and behavioral information from person to person. Overall, previous studies have comprehensively revealed the effects of the brain, endocrine system, and genes on social networks. Future studies are required to determine the effects of cognitive abilities, such as memory, on social networks, the characteristics and neural mechanism of social networks in mental illness and how social networks change over time through the use of longitudinal methods.

A study of EEG mu neurofeedback during action observation

The mirror system is a brain network that gets activated during action performance and observation. Brain mu waves have been used as a mirror system activity index; however, mu rhythm is prone to contamination by occipital alpha wave activity, thus raising a concern regarding its reliability as an index of the mirror system activity. In this study, we investigated whether mu suppression can be used as an index of neurofeedback training, which influences mirror system activities. Participants observed videos of hand movement under three different conditions: central mu feedback (muFB), occipital alpha feedback (aFB), and simple observation without any feedback (OBS). Results showed that at the 4-5 min mark, mu wave was most significantly suppressed in the central site at muFB. We thus demonstrated the possibility of increasing mu wave suppression in feedback training using a specific stimulus such as motion observation.

Electroencephalographic Functional Connectivity With the Tacit Learning System Prosthetic Hand: A Case Series Using Motor Imagery

We previously created a prosthetic hand with a tacit learning system (TLS) that automatically supports the control of forearm pronosupination. This myoelectric prosthetic hand enables sensory feedback and flexible motor output, which allows users to move efficiently with minimal burden. In this study, we investigated whether electroencephalography can be used to analyze the influence of the auxiliary function of the TLS on brain function. Three male participants who had sustained below-elbow amputations and were myoelectric prosthesis users performed a series of physical movement trials with the TLS inactivated and activated. Trials were video recorded and a sequence of videos was prepared to represent each individual's own use while the system was inactivated and activated. In a subsequent motor imagery phase during which electroencephalography (EEG) signals were collected, each participant was asked to watch both videos of themself while actively imagining the physical movement depicted. Differences in mean cortical current and amplitude envelope correlation (AEC) values between supplementary motor areas (SMA) and each vertex were calculated. For all participants, there were differences in the mean cortical current generated by the motor imagery tasks when the TLS inactivated and activated conditions were compared. The AEC values were higher during the movement imagery task with TLS activation, although their distribution on the cortex varied between the three individuals. In both S1 and other brain areas, AEC values increased in conditions with the TLS activated. Evidence from this case series indicates that, in addition to motor control, TLS may change sensory stimulus recognition.