Using guitar learning to probe the Action Observation Network's response to visuomotor familiarity

Abstract

Watching other people move elicits engagement of a collection of sensorimotor brain regions collectively termed the Action Observation Network (AON). An extensive literature documents more robust AON responses when observing or executing familiar compared to unfamiliar actions, as well as a positive correlation between amplitude of AON response and an observer's familiarity with an observed or executed movement. On the other hand, emerging evidence shows patterns of AON activity counter to these findings, whereby in some circumstances, unfamiliar actions lead to greater AON engagement than familiar actions. In an attempt to reconcile these conflicting findings, some have proposed that the relationship between AON response amplitude and action familiarity is nonlinear in nature. In the present study, we used an elaborate guitar training intervention to probe the relationship between movement familiarity and AON engagement during action execution and action observation tasks. Participants underwent fMRI scanning while executing one set of guitar sequences with a scanner-compatible bass guitar and observing a second set of sequences. Participants then acquired further physical practice or observational experience with half of these stimuli outside the scanner across 3 days. Participants then returned for an identical scanning session, wherein they executed and observed equal numbers of familiar (trained) and unfamiliar (untrained) guitar sequences. Via region of interest analyses, we extracted activity within AON regions engaged during both scanning sessions, and then fit linear, quadratic and cubic regression models to these data. The data best support the cubic regression models, suggesting that the response profile within key sensorimotor brain regions associated with the AON respond to action familiarity in a nonlinear manner. Moreover, by probing the subjective nature of the prediction error signal, we show results consistent with a predictive coding account of AON engagement during action observation and execution that also takes into account effects of changes in neural efficiency.

Earlier and More Robust Sensorimotor Discrimination of ASL Signs in Deaf Signers During Imitation

“…In other domains of human action (e.g., dance, grasping), the action experts’ sensorimotor cortex is more active while they see others perform actions with which they have experience, like we see in the current results. However, in the this study, there is a vast discrepancy between the amount of ASL experience that the Deaf Signers and Hearing Non-Signers have, and if we were able to compare sensorimotor reactivity across the full spectrum of ASL experience (e.g., including hearing fluent signers, and intermediate signers), it is very possible that a more complex, non-linear relationship between sign experience and mirroring would emerge (Gardner et al 2017a, 2017b; Gardner et al, 2015).…”

“…Some findings suggest that deaf signers’ neural representations of action processing differ from hearing non-signers’ (Corina et al, 2007; Emmorey, McCullough, Mehta, Ponto, & Grabowski, 2011; Emmorey et al, 2010; Mole & Turner, 2017). It is possible that deaf signers’ communicative action processing is highly efficient, reducing sensorimotor system activity but not disengaging from it, due to their extensive expertise in extracting meaning from complex action (Gardner et al, 2017a, 2017b; Gardner et al, 2015). As well, the consideration of mirroring-like processes in sign language users hinges upon the definition of mirroring (Mole & Turner, 2017).…”

Observing action sequences elicits sequence-specific neural representations in frontoparietal brain regions

“…However, by unpacking the representational structure of frontoparietal cortex in a sequence-specific manner, we are able to show that frontoparietal cortex develops a richer and more widespread representation of observed action sequences, which largely generalises to untrained sequences. Previous research based on averaging activity across voxels has fuelled much debate about the relative contribution of increased or decreased engagement of the motor system in learning (Dayan & Cohen, 2011;Gardner, Aglinskas the code that is hidden within averaged activity can provide an altogether different understanding of brain organisation (Kriegeskorte, 2008;Norman, 2006). Moreover, the results highlight the value of using representational similarity analyses in the context of learning to understand plasticity, which few studies have focussed upon to date (Kriegeskorte & Kievit, 2013).…”

“…Compared to action observation and visual training, considerably more research has investigated neural representations underpinning action execution and physical training (Dayan & Cohen, 2011;Diedrichsen & Kornysheva, 2015;Hardwick et al, 2013;Kelly & Garavan, 2005;Penhune & Steele, 2012). fMRI studies have shown both increases and decreases in frontoparietal cortex following motor learning, with increases argued to reflect recruitment of cortical tissue and decreases suggestive of more efficient neural function (Dayan & Cohen, 2011;Gardner, Aglinskas & Cross, 2017;Steele and Penhune, 2010). However, because conventional fMRI analyses average activity across voxels, they are insensitive to a richness of information that is represented by the pattern of activity across voxels (Kriegeskorte et al, 2008).…”

A neurocognitive investigation of the impact of socialising with a robot on empathy for pain

“…While our data failed to support our primary hypothesis, a number of considerations are worth bearing in mind that might help improve future research efforts along these lines. By mapping changes across two identical fMRI sessions before and after the socialising intervention with a trained (robot) and untrained (human) agents, the current study followed a similar procedure as previous training studies on sensorimotor learning and action observation (e.g., [46,66]). While using a pre-and post-intervention approach already limits the influence of potential confounding factors that might arise if a single scan session is performed post-intervention only, a question could nonetheless arise as to whether the repetition of the task or time between the two fMRI sessions could impact the present results.…”