Combined action observation and imagery facilitates corticospinal excitability.

Observation and imagery of movement both activate similar brain regions to those involved in movement execution. As such, both are recommended as techniques for aiding the recovery of motor function following stroke. Traditionally, action observation and movement imagery (MI) have been considered as independent intervention techniques. Researchers have however begun to consider the possibility of combining the two techniques into a single intervention strategy. This study investigated the effect of combined action observation and MI on corticospinal excitability, in comparison to either observation or imagery alone. Single-pulse transcranial magnetic stimulation (TMS) was delivered to the hand representation of the left motor cortex during combined action observation and MI, passive observation (PO), or MI of right index finger abduction-adduction movements or control conditions. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles of the right hand. The combined action observation and MI condition produced MEPs of larger amplitude than were obtained during PO and control conditions. This effect was only present in the FDI muscle, indicating the facilitation of corticospinal excitability during the combined condition was specific to the muscles involved in the observed/imagined task. These findings have implications for stroke rehabilitation, where combined action observation and MI interventions may prove to be more effective than observation or imagery alone

Motor imagery during action observation: A brief review of evidence, theory and future research opportunities

Motor imagery (MI) and action observation (AO) have traditionally been viewed as two separate techniques, which can both be used alongside physical practice to enhance motor learning and rehabilitation. Their independent use has been shown to be effective, and there is clear evidence that the two processes can elicit similar activity in the motor system. Building on these well-established findings, research has now turned to investigate the effects of their combined use. In this article, we first review the available neurophysiological and behavioral evidence for the effects of combined action observation and motor imagery (‘AO+MI’) on motor processes. We next describe a conceptual framework for their combined use, and then discuss several areas for future research into AO+MI processes. In this review, we advocate a more integrated approach to AO+MI techniques than has previously been adopted by movement scientists and practitioners alike. We hope this early review of an emergent body of research, along with a related set of research questions, can inspire new work in this area. We are optimistic that future research will further confirm if, how, and when this combined approach to AO+MI can be more effective in motor learning and rehabilitation settings, relative to the more traditional application of AO or MI independently

Depression uncouples brain hate circuit

It is increasingly recognized that we need a better understanding of how mental disorders such as depression alter the brain's functional connections to improve both early diagnosis and therapy. A new holistic approach has been used to investigate functional connectivity changes in the brains of patients suffering from major depression using resting-state functional magnetic resonance imaging (fMRI) data. A canonical template of connectivity in 90 different brain regions was constructed from healthy control subjects and this identified a six-community structure with each network corresponding to a different functional system. This template was compared with functional networks derived from fMRI scans of both first-episode and longer-term, drug resistant, patients suffering from severe depression. The greatest change in both groups of depressed patients was uncoupling of the so-called ‘hate circuit’ involving the superior frontal gyrus, insula and putamen. Other major changes occurred in circuits related to risk and action responses, reward and emotion, attention and memory processing. A voxel-based morphometry analysis was also carried out but this revealed no evidence in the depressed patients for altered gray or white matter densities in the regions showing altered functional connectivity. This is the first evidence for the involvement of the ‘hate circuit’ in depression and suggests a potential reappraisal of the key neural circuitry involved. We have hypothesized that this may reflect reduced cognitive control over negative feelings toward both self and others

Decoding collective communications using information theory tools

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective