Timing of mirror system activation when inferring the intentions of others

The Reaching Phase of Feeding and Self-Care Actions Optimizes Action Observation Effects in Chronic Stroke Subjects

BACKGROUND

The Action Observation Therapy (AOT) is a well-established post-stroke rehabilitation treatment based on the theoretical framework of the Mirror Neuron System (MNS) activation. However, AOT protocols are still heterogeneous in terms of video contents of observed actions.

OBJECTIVE

The aim of this study was to analyze electroencephalographic (EEG) recordings in stroke patients during the observation of different videos of task-specific upper limb movements, and to define which category of actions can elicit a stronger cortical activation in the observer's brain.

METHODS

Signals were analyzed from 19 chronic stroke subjects observing customized videos that represented 3 different categories of upper limb actions: Finalized Actions, Non-Finalized Actions, and Control Videos. The Event-Related Desynchronization in the µ and β bands was chosen to identify the involvement of the cerebral cortex: the area of the normalized power spectral density was calculated for each category and, deepening, for the reaching and completion sub-phases of Finalized Actions. For descriptive purposes, the time course of averaged signal power was described. The Kruskal-Wallis test (P < .05) was applied.

RESULTS

The analysis showed a greater desynchronization when subjects observed Finalized Actions with respect to Non-Finalized in all recorded areas; Control videos provoked a synchronization in the same areas and frequency bands. The reaching phase of feeding and self-care actions evoked a greater suppression both in µ and β bands.

CONCLUSIONS

The observation of finalized arm movements seems to elicit the strongest activation of the MNS in chronic stroke patients. This finding may help the clinicians to design future AOT-based stroke rehabilitation protocols.

CLINICAL TRIAL REGISTRATION

Clinical Trial Registration-URL: http://www.clinicaltrials.gov. Unique identifier: NCT04047134.

Perspectives on Rehabilitation Using Non-invasive Brain Stimulation Based on Second-Person Neuroscience of Teaching-Learning Interactions

Recent advances in second-person neuroscience have allowed the underlying neural mechanisms involved in teaching-learning interactions to be better understood. Teaching is not merely a one-way transfer of information from teacher to student; it is a complex interaction that requires metacognitive and mentalizing skills to understand others’ intentions and integrate information regarding oneself and others. Physiotherapy involving therapists instructing patients on how to improve their motor skills is a clinical field in which teaching-learning interactions play a central role. Accumulating evidence suggests that non-invasive brain stimulation (NIBS) modulates cognitive functions; however, NIBS approaches to teaching-learning interactions are yet to be utilized in rehabilitation. In this review, I evaluate the present research into NIBS and its role in enhancing metacognitive and mentalizing abilities; I then review hyperscanning studies of teaching-learning interactions and explore the potential clinical applications of NIBS in rehabilitation. Dual-brain stimulation using NIBS has been developed based on findings of brain-to-brain synchrony in hyperscanning studies, and it is delivered simultaneously to two individuals to increase inter-brain synchronized oscillations at the stimulated frequency. Artificial induction of brain-to-brain synchrony has the potential to promote instruction-based learning. The brain-to-brain interface, which induces inter-brain synchronization by adjusting the patient’s brain activity, using NIBS, to the therapist’s brain activity, could have a positive effect on both therapist-patient interactions and rehabilitation outcomes. NIBS based on second-person neuroscience has the potential to serve as a useful addition to the current neuroscientific methods used in complementary interventions for rehabilitation.

[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.

Weighted Brain Network Metrics for Decoding Action Intention Understanding Based on EEG

Background: Understanding the action intentions of others is important for social and human-robot interactions. Recently, many state-of-the-art approaches have been proposed for decoding action intention understanding. Although these methods have some advantages, it is still necessary to design other tools that can more efficiently classify the action intention understanding signals.

New Method: Based on EEG, we first applied phase lag index (PLI) and weighted phase lag index (WPLI) to construct functional connectivity matrices in five frequency bands and 63 micro-time windows, then calculated nine graph metrics from these matrices and subsequently used the network metrics as features to classify different brain signals related to action intention understanding.

Results: Compared with the single methods (PLI or WPLI), the combination method (PLI+WPLI) demonstrates some overwhelming victories. Most of the average classification accuracies exceed 70%, and some of them approach 80%. In statistical tests of brain network, many significantly different edges appear in the frontal, occipital, parietal, and temporal regions.

Conclusions: Weighted brain networks can effectively retain data information. The integrated method proposed in this study is extremely effective for investigating action intention understanding. Both the mirror neuron and mentalizing systems participate as collaborators in the process of action intention understanding.

Investigating Mirror System (MS) Activity in Adults with ASD When Inferring Others' Intentions Using Both TMS and EEG

ASD is associated with mentalizing deficits that may correspond with atypical mirror system (MS) activation. We investigated MS activity in adults with and without ASD when inferring others' intentions using TMS-induced motor evoked potentials (MEPs) and mu suppression measured by EEG. Autistic traits were measured for all participants. Our EEG data show, high levels of autistic traits predicted reduced right mu (8-10 Hz) suppression when mentalizing. Higher left mu (8-10 Hz) suppression was associated with superior mentalizing performances. Eye-tracking and TMS data showed no differences associated with autistic traits. Our data suggest ASD is associated with reduced right MS activity when mentalizing, TMS-induced MEPs and mu suppression measure different aspects of MS functioning and the MS is directly involved in inferring intentions.