How do physical interactions with others change our own motor behavior? Utilizing a novel motor learning paradigm in which the hands of two - individuals are physically connected without their conscious awareness, we investigated how the interaction forces from a partner adapt the motor behavior in physically interacting humans. We observed the motor adaptations during physical interactions to be mutually beneficial such that both the worse and better of the interacting partners improve motor performance during and after interactive practice. We show that these benefits cannot be explained by multi-sensory integration by an individual, but require physical interaction with a reactive partner. Furthermore, the benefits are determined by both the interacting partner's performance and similarity of the partner's behavior to one's own. Our results demonstrate the fundamental neural processes underlying human physical interactions and suggest advantages of interactive paradigms for sport-training and physical rehabilitation.

From a parent helping to guide their child during their first steps, to a therapist 15 supporting a patient, physical assistance enabled by haptic interaction is a fundamental modus 16 for improving motor abilities. However, what movement information is exchanged between 17 partners during haptic interaction, and how this information is used to coordinate and assist 18 others remains unclear 1 . Here, we propose a model where haptic information, provided by touch 19 and proprioception 2 , enables interacting individuals to estimate the partner's movement goal, 20 and to improve their own motor performance. We utilize an empirical physical interaction task 3 21 to show that our model can explain human behaviours better than existing models of interaction 22 in literature [4][5][6][7][8] . Furthermore, we experimentally verify our model by embodying it in a robot 23 partner and checking that it induces the same improvements in motor performance and learning 24 in a human individual as interacting with a human partner. These results promise collaborative 25 robots that provide human-like assistance, and suggest that movement goal exchange is the key 26 to physical assistance. 27 Humans are adept at physically interacting with and assisting one another, from helping 28 children to walk, to the incredible feats of balance in acrobatics, and synchrony during the 29 Tango. For over a decade, physical coupling has been documented to promote partners to adopt 30 specialised roles 9-11 and enable pairs or dyads to improve in many joint tasks 3,9,12,13 . However, 31 the underlying computational principle that enables movement coordination is still unknown 1 . 32 The improvement in interacting partners has been shown not to be due to changes in attention or 33 impedance of the interacting limbs 3 , and is absent when the interaction is not physical 14,15 and 34 when the interacting partners do not fully share control 16 . These results highlight the importance 35 of haptics, the sensory modality related to tactile and proprioceptive senses 2 , during continuous 36 physical interactions, and suggest that individuals jointly coordinate with a partner by 37 exchanging information haptically. However, what information is being exchanged and how it 38 is used to adapt one's behaviour remains unknown. We hypothesised that haptically interacting 39 partners can estimate and exchange sensory information about the task goal and the uncertainty 40 of this information with their partner, and tested this hypothesis against competing models of 41 haptic interaction during an interactive target tracking task. 42 Specifically, we first simulated the mechanical dynamics and control behaviour of 43 2 individual partners during the interactive task. We considered our proposed interpersonal goal 44 integration model against three well-known models of interaction in literature that propose 45 different information being exchanged between the partners. We compared the prediction of 46 these...

Objectives:The objective of this study was to investigate comparatively the influence of proton-pump inhibitors (PPI) administration on three bacterial communities in the oral cavity, stomach, and colon along the alimentary tract.Methods:Forty-five subjects including 18 patients taking PPI were enrolled. Stimulated saliva, gastric fluid (GF), and feces were obtained from each subject for the microbiota analysis through bacterial 16S rRNA gene profiling using the pyrosequencing method.Results:The species richness (alpha diversity) was similar among these three microbiota, whereas the interindividual diversity (beta diversity) was much higher in the fecal microbiota compared with that in the others. The UniFrac analysis indicated that the salivary and GF microbiota were similar to one another; however, both differed greatly from the fecal microbiota in the overall bacterial community structure. In the comparison between PPI-users and PPI-nonusers, a bacterial cell number increase of ~1,000 times was found in the GF of PPI-users using culturing methods, whereas the bacterial number and composition were nearly identical between the two groups using quantitative PCR and a similarity search based on 16S profiling. The beta diversity significantly increased in both the salivary and GF microbiota of PPI-users compared with PPI-nonusers.Conclusions:These results suggest that the GF microbiota has recently moved from the saliva. Bacterial overgrowth in the GF by PPI administration may be due to a lack of killing rather than proliferation of the bacteria in the acid-suppressed stomach. The biological significance of the increase in beta diversity by PPI administration remains unclear.

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