English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Optimal feedback control theory (OFCT) has been verysuccessful in explaining human motor coordination in aprincipled manner [1,2]. OFCT derives motor controlpolicies from the minimization of a cost function, whichpredicts a large variety of movement data [3]. However,very little is known about the nature of this cost func-tion. From the many proposed costs (which take thesame mathematical form) two stand out as being moti-vated in a principled manner: noise [4,5] and“effort”(incl. muscle fatigue and metabolic demand [6]). Thesetwo cost are evolutionarily sensible as they maximize anorganism’s fitness: increasing task-relevant precision andenergy efficiency. It was recently suggested [6] thatnoise and effort are weighed against each other whendetermining motor coordination. However, the neuronalimplementation or representation of such costs in thebrain remains unclear [7]. We test the hypothesis thatthis trade-off may be directly affected by our internalmetabolic state (e.g. blood glucose level). We test thehypothesis if a subject’s internal metabolic state has animpact on the strategy for motor control. Specifically,low metabolic levels could bias motor coordinationacross redundant muscle groups from larger, metaboli-cally more costly muscles towards smaller muscles toincrease efficiency.We performed preliminary experiments by conductingreaching experiments under a dietary regime. 5 right-handed participants 21-27 years old performed reachingmovements in a virtual reality arm movement-trackingrig (visual stimuli were projected via a mirror systemonto the plane of hand movement). Air sleds ona surrounding table supported the participant’sarmtoallow frictionless movement. The task began whenparticipants moved their hand to a visual workspacecentre; then a 1.5cm radius target sphere appeared15cm away in one of 8 directions (total of 800 trials,randomly ordered directions). Subjects chose when tostart reaching towards the target, having to come to astop within the target sphere within movement dura-tions of 75 to 125ms. Feedback was given in the form ofa score that increased for successful trials and decreasedconversely. Each experiment involved two morning ses-sions on separate days. 3 subjects followed their normaleating/drinking routine for the first session then fastedfrom 8.00pm the evening before the second session andvice versa for the 2 other subjects. Blood glucose mea-surements were taken before and after each sessionusing a personal blood glucose monitoring system.Our preliminary data suggests a systematic shift in thecoordination of muscle groups acting on each jointbased on available energy levels. We found statisticallysignificant changes in shoulder and elbow joint utilisa-tion (integrated absolute change in joint angle) in all 5subjects and in up to 5 out of 8 target directionsdepending on the metabolic state. Moreover, we canmodel the subject’s reaching trajectories under bothmetabolic conditions using OFCT by a change in theweight of the metabolic cost term as a function of inter-nal metabolic state. Our preliminary findings are impor-tant as we link for the first time metabolic state toneuronal computations underlying motor control.

Does the cost function of human motor control depend on the internal metabolic state?