Morel, Pierre

[["dc.bibliographiccitation.artnumber","016002"],["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.lastpage","15"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Morel, Pierre"],["dc.contributor.author","Ferrea, Enrico"],["dc.contributor.author","Taghizadeh-Sarshouri, Bahareh"],["dc.contributor.author","Audí, Josep Marcel Cardona"],["dc.contributor.author","Ruff, Roman"],["dc.contributor.author","Hoffmann, Klaus-Peter"],["dc.contributor.author","Lewis, Sören"],["dc.contributor.author","Russold, Michael"],["dc.contributor.author","Dietl, Hans"],["dc.contributor.author","Abu-Saleh, Lait"],["dc.contributor.author","Schroeder, Dietmar"],["dc.contributor.author","Krautschneider, Wolfgang"],["dc.contributor.author","Meiners, Thomas"],["dc.contributor.author","Gail, Alexander"],["dc.date.accessioned","2017-09-07T11:47:44Z"],["dc.date.available","2017-09-07T11:47:44Z"],["dc.date.issued","2015"],["dc.description.abstract","OBJECTIVE:The ease of use and number of degrees of freedom of current myoelectric hand prostheses is limited by the information content and reliability of the surface electromyography (sEMG) signals used to control them. For example, cross-talk limits the capacity to pick up signals from small or deep muscles, such as the forearm muscles for distal arm amputations, or sites of targeted muscle reinnervation (TMR) for proximal amputations. Here we test if signals recorded from the fully implanted, induction-powered wireless Myoplant system allow long-term decoding of continuous as well as discrete movement parameters with better reliability than equivalent sEMG recordings. The Myoplant system uses a centralized implant to transmit broadband EMG activity from four distributed bipolar epimysial electrodes.APPROACH:Two Rhesus macaques received implants in their backs, while electrodes were placed in their upper arm. One of the monkeys was trained to do a cursor task via a haptic robot, allowing us to control the forces exerted by the animal during arm movements. The second animal was trained to perform a center-out reaching task on a touchscreen. We compared the implanted system with concurrent sEMG recordings by evaluating our ability to decode time-varying force in one animal and discrete reach directions in the other from multiple features extracted from the raw EMG signals.MAIN RESULTS:In both cases, data from the implant allowed a decoder trained with data from a single day to maintain an accurate decoding performance during the following months, which was not the case for concurrent surface EMG recordings conducted simultaneously over the same muscles.SIGNIFICANCE:These results show that a fully implantable, centralized wireless EMG system is particularly suited for long-term stable decoding of dynamic movements in demanding applications such as advanced forelimb prosthetics in a wide range of configurations (distal amputations, TMR)."],["dc.identifier.doi","10.1088/1741-2560/13/1/016002"],["dc.identifier.gro","3150711"],["dc.identifier.pmid","26643959"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14153"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7498"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.relation.issn","1741-2560"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0"],["dc.title","Long-term decoding of movement force and direction with a wireless myoelectric implant"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Ferrea, E."],["dc.contributor.author","Franke, J."],["dc.contributor.author","Morel, P."],["dc.contributor.author","Gail, A."],["dc.date.accessioned","2022-07-01T07:34:52Z"],["dc.date.available","2022-07-01T07:34:52Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract Neurorehabilitation in patients suffering from motor deficits relies on relearning or re-adapting motor skills. Yet our understanding of motor learning is based mostly on results from one or two-dimensional experimental paradigms with highly confined movements. Since everyday movements are conducted in three-dimensional space, it is important to further our understanding about the effect that gravitational forces or perceptual anisotropy might or might not have on motor learning along all different dimensions relative to the body. Here we test how well existing concepts of motor learning generalize to movements in 3D. We ask how a subject’s variability in movement planning and sensory perception influences motor adaptation along three different body axes. To extract variability and relate it to adaptation rate, we employed a novel hierarchical two-state space model using Bayesian modeling via Hamiltonian Monte Carlo procedures. Our results show that differences in adaptation rate occur between the coronal, sagittal and horizontal planes and can be explained by the Kalman gain, i.e., a statistically optimal solution integrating planning and sensory information weighted by the inverse of their variability. This indicates that optimal integration theory for error correction holds for 3D movements and explains adaptation rate variation between movements in different planes."],["dc.description.sponsorship"," Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659"],["dc.description.sponsorship","Federal Ministry for Education and Research, Germany"],["dc.description.sponsorship","Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung"],["dc.identifier.doi","10.1038/s41598-022-13866-y"],["dc.identifier.pii","13866"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112030"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-581"],["dc.relation.eissn","2045-2322"],["dc.relation.haserratum","/handle/2/113626"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Statistical determinants of visuomotor adaptation along different dimensions during naturalistic 3D reaches"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e2001323"],["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","PLoS Biology"],["dc.bibliographiccitation.lastpage","23"],["dc.bibliographiccitation.volume","15"],["dc.contributor.author","Morel, Pierre"],["dc.contributor.author","Ulbrich, Philipp"],["dc.contributor.author","Gail, Alexander"],["dc.date.accessioned","2017-09-07T11:47:47Z"],["dc.date.available","2017-09-07T11:47:47Z"],["dc.date.issued","2017"],["dc.description.abstract","When deciding between alternative options, a rational agent chooses on the basis of the desirability of each outcome, including associated costs. As different options typically result in different actions, the effort associated with each action is an essential cost parameter. How do humans discount physical effort when deciding between movements? We used an action-selection task to characterize how subjective effort depends on the parameters of arm transport movements and controlled for potential confounding factors such as delay discounting and performance. First, by repeatedly asking subjects to choose between 2 arm movements of different amplitudes or durations, performed against different levels of force, we identified parameter combinations that subjects experienced as identical in effort (isoeffort curves). Movements with a long duration were judged more effortful than short-duration movements against the same force, while movement amplitudes did not influence effort. Biomechanics of the movements also affected effort, as movements towards the body midline were preferred to movements away from it. Second, by introducing movement repetitions, we further determined that the cost function for choosing between effortful movements had a quadratic relationship with force, while choices were made on the basis of the logarithm of these costs. Our results show that effort-based action selection during reaching cannot easily be explained by metabolic costs. Instead, force-loaded reaches, a widely occurring natural behavior, imposed an effort cost for decision making similar to cost functions in motor control. Our results thereby support the idea that motor control and economic choice are governed by partly overlapping optimization principles."],["dc.identifier.doi","10.1371/journal.pbio.2001323"],["dc.identifier.gro","3150720"],["dc.identifier.pmid","28586347"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14559"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7507"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.relation.issn","1545-7885"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Ferrea, E."],["dc.contributor.author","Franke, J."],["dc.contributor.author","Morel, P."],["dc.contributor.author","Gail, A."],["dc.date.accessioned","2022-09-01T09:50:07Z"],["dc.date.available","2022-09-01T09:50:07Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.1038/s41598-022-16148-9"],["dc.identifier.pii","16148"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113626"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-597"],["dc.relation.eissn","2045-2322"],["dc.relation.iserratumof","/handle/2/112030"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Author Correction: Statistical determinants of visuomotor adaptation along different dimensions during naturalistic 3D reaches"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","erratum_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","bhu312"],["dc.bibliographiccitation.firstpage","731"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Cerebral Cortex"],["dc.bibliographiccitation.lastpage","741"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Kuang, Shenbing"],["dc.contributor.author","Morel, Pierre"],["dc.contributor.author","Gail, Alexander"],["dc.date.accessioned","2017-09-07T11:47:44Z"],["dc.date.available","2017-09-07T11:47:44Z"],["dc.date.issued","2015"],["dc.description.abstract","Neurons in the posterior parietal cortex respond selectively for spatial parameters of planned goal-directed movements. Yet, it is still unclear which aspects of the movement the neurons encode: the spatial parameters of the upcoming physical movement (physical goal), or the upcoming visual limb movement (visual goal). To test this, we recorded neuronal activity from the parietal reach region while monkeys planned reaches under either normal or prism-reversed viewing conditions. We found predominant encoding of physical goals while fewer neurons were selective for visual goals during planning. In contrast, local field potentials recorded in the same brain region exhibited predominant visual goal encoding, similar to previous imaging data from humans. The visual goal encoding in individual neurons was neither related to immediate visual input nor to visual memory, but to the future visual movement. Our finding suggests that action planning in parietal cortex is not exclusively a precursor of impending physical movements, as reflected by the predominant physical goal encoding, but also contains spatial kinematic parameters of upcoming visual movement, as reflected by co-existing visual goal encoding in neuronal spiking. The co-existence of visual and physical goals adds a complementary perspective to the current understanding of parietal spatial computations in primates."],["dc.identifier.doi","10.1093/cercor/bhu312"],["dc.identifier.gro","3150714"],["dc.identifier.pmid","25576535"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7501"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.issn","1047-3211"],["dc.title","Planning Movements in Visual and Physical Space in Monkey Posterior Parietal Cortex"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]