The emergence of robotic body augmentation provides exciting innovations that will revolutionize the fields of robotics, human-machine interaction and wearable electronics. While augmentative devices like extra robotic arms and fingers are informed by restorative technologies in many ways, they also introduce unique challenges for bidirectional human-machine collaboration. Can humans adapt and learn to operate a new robotic limb collaboratively with their biological limbs, without restricting other physical abilities? To successfully achieve robotic body augmentation, we need to ensure that by giving a user an additional (artificial) limb, we are not trading off the functionalities of an existing (biological) one. In this manuscript, we introduce the "Neural Resource Allocation Problem" and discuss how to allow the effective voluntary control of augmentative devices without compromising the control of the biological body. In reviewing the relevant literature on extra robotic fingers and arms, we critically assess the range of potential solutions available for the Neural Resource Allocation Problem.For this purpose, we combine multiple perspectives from engineering and neuroscience with considerations from human-machine interaction, sensory-motor integration, ethics, and law. Altogether we aim to define common foundations and operating principles for the successful implementation of robotic body augmentation. Introducing robotic body augmentation and the neural resource allocation problemWith robotic body augmentation -the augmentation of humans' physical abilities via robotic systems 1 -we are witnessing the rise of a new class of technologies, which are designed to resemble human limbs in their functionality while being integrated with the users' natural abilities. Traditionally, such devices have been developed to substitute a missing or impaired body function (i.e., restorative technologies), most famously bionic legs and arms for substitution of missing limbs 2,3 or exoskeletons for restoring impaired movement 4 . But from a system design perspective, the same technological foundation that allows a functionality which approximately matches that of a body part to be implemented, can also be exploited for augmenting the sensory and motor capabilities of an able-bodied individual. As such, human body augmentation is no longer science fiction. From the engineering side, a whole spectrum of human body enhancement now exists, ranging from technologies for restoration or compensation of functions in patients with physical limitations (Fig.

In mechanical ventilation, a careful setting of the ventilation parameters in accordance with the current individual state of the lung is crucial to minimize ventilator induced lung injury. Positive end-expiratory pressure (PEEP) has to be set to prevent collapse of the alveoli, however at the same time overdistension should be avoided. Classic approaches of analyzing static respiratory system mechanics fail in particular if lung injury already prevails. A new approach of analyzing dynamic respiratory system mechanics to set PEEP uses the intratidal, volume-dependent compliance which is believed to stay relatively constant during one breath only if neither atelectasis nor overdistension occurs. To test the success of this dynamic approach systematically at bedside or in an animal study, automation of the computing steps is necessary. A decision support system for optimizing PEEP in form of a Graphical User Interface (GUI) was targeted. Respiratory system mechanics were analyzed using the gliding SLICE method. The resulting shapes of the intratidal compliance-volume curve were classified into one of six categories, each associated with a PEEP-suggestion. The GUI should include a graphical representation of the results as well as a quality check to judge the reliability of the suggestion. The implementation of a user-friendly GUI was successfully realized. The agreement between modelled and measured pressure data [expressed as root-mean-square (RMS)] tested during the implementation phase with real respiratory data from two patient studies was below 0.2 mbar for data taken in volume controlled mode and below 0.4 mbar for data taken in pressure controlled mode except for two cases with RMS < 0.6 mbar. Visual inspections showed, that good and medium quality data could be reliably identified. The new GUI allows visualization of intratidal compliance-volume curves on a breath-by-breath basis. The automatic categorisation of curve shape into one of six shape-categories provides the rational decision-making model for PEEP-titration.

Background Major depressive disorder is often associated with maladaptive coping strategies, including rumination and thought suppression. Aims To assess the comparative effect of the selective serotonin reuptake inhibitor escitalopram, and the serotonergic psychedelic psilocybin (COMP360), on rumination and thought suppression in major depressive disorder. Method Based on data derived from a randomised clinical trial (N = 59), we performed exploratory analyses on the impact of escitalopram versus psilocybin (i.e. condition) on rumination and thought suppression from 1 week before to 6 weeks after treatment inception (i.e. time), using mixed analysis of variance. Condition responder versus non-responder subgroup analyses were also done, using the standard definition of ≥50% symptom reduction. Results A time×condition interaction was found for rumination (F(1, 56) = 4.58, P = 0.037) and thought suppression (F(1,57) = 5.88, P = 0.019), with post hoc tests revealing significant decreases exclusively in the psilocybin condition. When analysing via response, a significant time×condition×response interaction for thought suppression (F(1,54) = 8.42, P = 0.005) and a significant time×response interaction for rumination (F(1,54) = 23.50, P < 0.001) were evident. Follow-up tests revealed that decreased thought suppression was exclusive to psilocybin responders, whereas rumination decreased in both responder groups. In the psilocybin arm, decreases in rumination and thought suppression correlated with ego dissolution and session-linked psychological insight. Conclusions These data provide further evidence on the therapeutic mechanisms of psilocybin and escitalopram in the treatment of depression.

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