Negro, Francesco

[["dc.bibliographiccitation.firstpage","1699"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Journal of Neurophysiology"],["dc.bibliographiccitation.lastpage","1706"],["dc.bibliographiccitation.volume","119"],["dc.contributor.author","Yavuz, Utku Ş."],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Diedrichs, Robin"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2019-02-06T11:53:32Z"],["dc.date.available","2019-02-06T11:53:32Z"],["dc.date.issued","2018"],["dc.description.abstract","Motor neurons innervating antagonist muscles receive reciprocal inhibitory afferent inputs to facilitate the joint movement in the two directions. The present study investigates the mutual transmission of reciprocal inhibitory afferent inputs between the tibialis anterior (TA) and triceps surae (soleus and medial gastrocnemius) motor units. We assessed this mutual mechanism in large populations of motor units for building a statistical distribution of the inhibition amplitudes during standardized input to the motor neuron pools to minimize the effect of modulatory pathways. Single motor unit activities were identified using high-density surface electromyography (HDsEMG) recorded from the TA, soleus (Sol), and medial gastrocnemius (GM) muscles during isometric dorsi- and plantarflexion. Reciprocal inhibition on the antagonist muscle was elicited by electrical stimulation of the tibial (TN) or common peroneal nerves (CPN). The probability density distributions of reflex strength for each muscle were estimated to examine the strength of mutual transmission of reciprocal inhibitory input. The results showed that the strength of reciprocal inhibition in the TA motor units was fourfold greater than for the GM and the Sol motor units. This suggests an asymmetric transmission of reciprocal inhibition between ankle extensor and flexor muscles. This asymmetry cannot be explained by differences in motor unit type composition between the investigated muscles since we sampled low-threshold motor units in all cases. Therefore, the differences observed for the strength of inhibition are presumably due to a differential reciprocal spindle afferent input and the relative contribution of nonreciprocal inhibitory pathways. NEW & NOTEWORTHY We investigated the mutual transmission of reciprocal inhibition in large samples of motor units using a standardized input (electrical stimulation) to the motor neurons. The results demonstrated that the disynaptic reciprocal inhibition exerted between ankle flexor and extensor muscles is asymmetric. The functional implication of asymmetric transmission may be associated with the neural strategies of postural control."],["dc.identifier.doi","10.1152/jn.00424.2017"],["dc.identifier.pmid","29384455"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/57534"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eissn","1522-1598"],["dc.title","Reciprocal inhibition between motor neurons of the tibialis anterior and triceps surae in humans"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","37"],["dc.bibliographiccitation.journal","Acta Physiologica"],["dc.bibliographiccitation.lastpage","38"],["dc.bibliographiccitation.volume","215"],["dc.contributor.author","Yavuz, Utku Suekrue"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Sebik, Oguz"],["dc.contributor.author","Holobar, Ales"],["dc.contributor.author","Froemmel, Cornelius"],["dc.contributor.author","Turker, Kemal S."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:49:23Z"],["dc.date.available","2018-11-07T09:49:23Z"],["dc.date.issued","2015"],["dc.identifier.isi","000364786400081"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35500"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.publisher.place","Hoboken"],["dc.relation.issn","1748-1716"],["dc.relation.issn","1748-1708"],["dc.title","The new technique for accurate estimation of the spinal cord circuitry: recording reflex responses of large motor unit populations"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","189"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","198"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Stango, Antonietta"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T10:00:16Z"],["dc.date.available","2018-11-07T10:00:16Z"],["dc.date.issued","2015"],["dc.description.abstract","Research on pattern recognition for myoelectric control has usually focused on a small number of electromyography (EMG) channels because of better clinical acceptability and low computational load with respect to multi-channel EMG. However, recently, high density (HD) EMG technology has substantially improved, also in practical usability, and can thus be applied in myocontrol. HD EMG provides several closely spaced recordings in multiple locations over the skin surface. This study considered the use of HD EMG for controlling upper limb prostheses, based on pattern recognition. In general, robustness and reliability of classical pattern recognition systems are influenced by electrode shift in dons and doff, and by the presence of malfunctioning channels. The aim of this study is to propose a new approach to attenuate these issues. The HD EMG grid of electrodes is an ensemble of sensors that records data spatially correlated. The experimental variogram, which is a measure of the degree of spatial correlation, was used as feature for classification, contrary to previous approaches that are based on temporal or frequency features. The classification based on the variogram was tested on seven able-bodied subjects and one subject with amputation, for the classification of nine and seven classes, respectively. The performance of the proposed approach was comparable with the classic methods based on time-domain and autoregressive features (average classification accuracy over all methods similar to 95% for nine classes). However, the new spatial features demonstrated lower sensitivity to electrode shift (+/- 1 cm) with respect to the classic features (p<0.05). When even just one channel was noisy, the classification accuracy dropped by similar to 10% for all methods. However, the new method could be applied without any retraining to a subset of high-quality channels whereas the classic methods require retraining when some channels are omitted. In conclusion, the new spatial feature space proposed in this study improved the robustness to electrode number and shift in myocontrol with respect to previous approaches."],["dc.description.sponsorship","ERC AdvancedGrant DE-MOVE [267888]"],["dc.identifier.doi","10.1109/TNSRE.2014.2366752"],["dc.identifier.isi","000351365100005"],["dc.identifier.pmid","25389242"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37767"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Ieee-inst Electrical Electronics Engineers Inc"],["dc.relation.issn","1558-0210"],["dc.relation.issn","1534-4320"],["dc.title","Spatial Correlation of High Density EMG Signals Provides Features Robust to Electrode Number and Shift in Pattern Recognition for Myocontrol"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","244"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","251"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Kapelner, Tamas"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Aszmann, Oskar C."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2020-12-10T18:26:21Z"],["dc.date.available","2020-12-10T18:26:21Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1109/TNSRE.2017.2766360"],["dc.identifier.eissn","1558-0210"],["dc.identifier.issn","1534-4320"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76053"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Decoding Motor Unit Activity From Forearm Muscles: Perspectives for Myoelectric Control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","4305"],["dc.bibliographiccitation.issue","19"],["dc.bibliographiccitation.journal","The Journal of Physiology"],["dc.bibliographiccitation.lastpage","4318"],["dc.bibliographiccitation.volume","593"],["dc.contributor.author","Yavuz, Utku Suekrue"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Sebik, Oguz"],["dc.contributor.author","Holobar, Ales"],["dc.contributor.author","Froemmel, Cornelius"],["dc.contributor.author","Turker, Kemal S."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:50:51Z"],["dc.date.available","2018-11-07T09:50:51Z"],["dc.date.issued","2015"],["dc.description.abstract","We propose and validate a non-invasive method that enables accurate detection of the discharge times of a relatively large number of motor units during excitatory and inhibitory reflex stimulations. High-density surface electromyography (HDsEMG) and intramuscular EMG (iEMG) were recorded from the tibialis anterior muscle during ankle dorsiflexions performed at 5%, 10% and 20% of the maximum voluntary contraction (MVC) force, in nine healthy subjects. The tibial nerve (inhibitory reflex) and the peroneal nerve (excitatory reflex) were stimulated with constant current stimuli. In total, 416 motor units were identified from the automatic decomposition of the HDsEMG. The iEMG was decomposed using a state-of-the-art decomposition tool and provided 84 motor units (average of two recording sites). The reflex responses of the detected motor units were analysed using the peri-stimulus time histogram (PSTH) and the peri-stimulus frequencygram (PSF). The reflex responses of the common motor units identified concurrently from the HDsEMG and the iEMG signals showed an average disagreement (the difference between number of observed spikes in each bin relative to the mean) of 8.2 +/- 2.2% (5% MVC), 6.8 +/- 1.0% (10% MVC) and 7.5 +/- 2.2% (20% MVC), for reflex inhibition, and 6.5 +/- 4.1%, 12.0 +/- 1.8% and 13.9 +/- 2.4%, for reflex excitation. There was no significant difference between the characteristics of the reflex responses, such as latency, amplitude and duration, for the motor units identified by both techniques. Finally, reflex responses could be identified at higher force (4 of the 9 subjects performed contraction up to 50% MVC) using HDsEMG but not iEMG, because of the difficulty in decomposing the iEMG at high forces. In conclusion, single motor unit reflex responses can be estimated accurately and non-invasively in relatively large populations of motor units using HDsEMG. This non-invasive approach may enable a more thorough investigation of the synaptic input distribution on active motor units at various force levels."],["dc.description.sponsorship","European Research Council (ERC) [267888]"],["dc.identifier.doi","10.1113/JP270635"],["dc.identifier.isi","000363090500002"],["dc.identifier.pmid","26115007"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35792"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1469-7793"],["dc.relation.issn","0022-3751"],["dc.title","Estimating reflex responses in large populations of motor units by decomposition of the high-density surface electromyogram"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3789"],["dc.bibliographiccitation.issue","17"],["dc.bibliographiccitation.journal","The Journal of Physiology"],["dc.bibliographiccitation.lastpage","3804"],["dc.bibliographiccitation.volume","593"],["dc.contributor.author","Muceli, Silvia"],["dc.contributor.author","Poppendieck, Wigand"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Yoshida, Ken"],["dc.contributor.author","Hoffmann, Klaus P."],["dc.contributor.author","Butler, Jane E."],["dc.contributor.author","Gandevia, Simon C."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:52:40Z"],["dc.date.available","2018-11-07T09:52:40Z"],["dc.date.issued","2015"],["dc.description.abstract","We describe the design, fabrication and testing of a novel multi-channel thin-film electrode for detection of the output of motoneurones in vivo and in humans, through muscle signals. The structure includes a linear array of 16 detection sites that can sample intramuscular electromyographic activity from the entire muscle cross-section. The structure was tested in two superficial muscles (the abductor digiti minimi (ADM) and the tibialis anterior (TA)) and a deep muscle (the genioglossus (GG)) during contractions at various forces. Moreover, surface electromyogram (EMG) signals were concurrently detected from the TA muscle with a grid of 64 electrodes. Surface and intramuscular signals were decomposed into the constituent motor unit (MU) action potential trains. With the intramuscular electrode, up to 31 MUs were identified from the ADM muscle during an isometric contraction at 15% of the maximal force (MVC) and 50 MUs were identified for a 30% MVC contraction of TA. The new electrode detects different sources from a surface EMG system, as only one MU spike train was found to be common in the decomposition of the intramuscular and surface signals acquired from the TA. The system also allowed access to the GG muscle, which cannot be analysed with surface EMG, with successful identification of MU activity. With respect to classic detection systems, the presented thin-film structure enables recording from large populations of active MUs of deep and superficial muscles and thus can provide a faithful representation of the neural drive sent to a muscle."],["dc.identifier.doi","10.1113/JP270902"],["dc.identifier.isi","000360769900009"],["dc.identifier.pmid","26174910"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36177"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1469-7793"],["dc.relation.issn","0022-3751"],["dc.title","Accurate and representative decoding of the neural drive to muscles in humans with multi-channel intramuscular thin-film electrodes"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Nature Biomedical Engineering"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Vujaklija, Ivan"],["dc.contributor.author","Sartori, Massimo"],["dc.contributor.author","Kapelner, Tamás"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Jiang, Ning"],["dc.contributor.author","Bergmeister, Konstantin"],["dc.contributor.author","Andalib, Arash"],["dc.contributor.author","Principe, Jose"],["dc.contributor.author","Aszmann, Oskar C."],["dc.date.accessioned","2020-12-10T18:09:54Z"],["dc.date.available","2020-12-10T18:09:54Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1038/s41551-016-0025"],["dc.identifier.eissn","2157-846X"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73794"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1479"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","The Journal of Physiology"],["dc.bibliographiccitation.lastpage","1496"],["dc.bibliographiccitation.volume","595"],["dc.contributor.author","Negro, F."],["dc.contributor.author","Laine, C. M."],["dc.contributor.author","Mayer, F."],["dc.contributor.author","Martinez-Valdes, Eduardo"],["dc.contributor.author","Falla, Deborah"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2020-12-10T18:36:34Z"],["dc.date.available","2020-12-10T18:36:34Z"],["dc.date.issued","2017"],["dc.description.abstract","A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre-post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63-0.99 and 0.39-0.95, respectively). In Experiment II, similar to 40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders."],["dc.identifier.doi","10.1113/JP273662"],["dc.identifier.isi","000398112300016"],["dc.identifier.issn","0022-3751"],["dc.identifier.pmid","28032343"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76674"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Wiley"],["dc.relation.issn","1469-7793"],["dc.relation.issn","0022-3751"],["dc.title","Tracking motor units longitudinally across experimental sessions with high-density surface electromyography"],["dc.title.alternative","Motor unit tracking with high-density EMG"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1337"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","Journal of Applied Physiology"],["dc.bibliographiccitation.lastpage","1346"],["dc.bibliographiccitation.volume","119"],["dc.contributor.author","Castronovo, Anna Margherita"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Conforto, Silvia"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:48:29Z"],["dc.date.available","2018-11-07T09:48:29Z"],["dc.date.issued","2015"],["dc.description.abstract","alpha-Motor neurons receive synaptic inputs from spinal and supraspinal centers that comprise components either common to the motor neuron pool or independent. The input shared by motor neurons-common input-determines force control. The aim of the study was to investigate the changes in the strength of common synaptic input delivered to motor neurons with changes in force and with fatigue, two conditions that underlie an increase in the net excitatory drive to the motor neurons. High-density surface electromyogram (EMG) signals were recorded from the tibialis anterior muscle during contractions at 20, 50, and 75% of the maximal voluntary contraction force (in 3 sessions separated by at least 2 days), all sustained until task failure. EMG signal decomposition identified the activity of a total of 1,245 motor units. The coherence values between cumulative motor unit spike trains increased with increasing force, especially for low frequencies. This increase in coherence was not observed when comparing two subsets of motor units having different recruitment thresholds, but detected at the same force level. Moreover, the coherence values for frequencies <5 Hz increased at task failure with respect to the beginning of the contractions for all force levels. In conclusion, the results indicated that the relative strength of common synaptic input to motor neurons increases with respect to independent input when the net excitatory drive to motor neurons increases as a consequence of a change in force and fatigue."],["dc.description.sponsorship","European Research Council Advanced Grant DEMOVE [267888]"],["dc.identifier.doi","10.1152/japplphysiol.00255.2015"],["dc.identifier.isi","000365907800011"],["dc.identifier.pmid","26404614"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35317"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Physiological Soc"],["dc.relation.issn","1522-1601"],["dc.relation.issn","8750-7587"],["dc.title","The proportion of common synaptic input to motor neurons increases with an increase in net excitatory input"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1895"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Journal of Neurophysiology"],["dc.bibliographiccitation.lastpage","1911"],["dc.bibliographiccitation.volume","114"],["dc.contributor.author","Dideriksen, Jakob Lund"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:52:18Z"],["dc.date.available","2018-11-07T09:52:18Z"],["dc.date.issued","2015"],["dc.description.abstract","Increasing joint stiffness by cocontraction of antagonist muscles and compensatory reflexes are neural strategies to minimize the impact of unexpected perturbations on movement. Combining these strategies, however, may compromise steadiness, as elements of the afferent input to motor pools innervating antagonist muscles are inherently negatively correlated. Consequently, a high afferent gain and active contractions of both muscles may imply negatively correlated neural drives to the muscles and thus an unstable limb position. This hypothesis was systematically explored with a novel computational model of the peripheral nervous system and the mechanics of one limb. Two populations of motor neurons received synaptic input from descending drive, spinal interneurons, and afferent feedback. Muscle force, simulated based on motor unit activity, determined limb movement that gave rise to afferent feedback from muscle spindles and Golgi tendon organs. The results indicated that optimal steadiness was achieved with low synaptic gain of the afferent feedback. High afferent gains during cocontraction implied increased levels of common drive in the motor neuron outputs, which were negatively correlated across the two populations, constraining instability of the limb. Increasing the force acting on the joint and the afferent gain both effectively minimized the impact of an external perturbation, and suboptimal adjustment of the afferent gain could be compensated by muscle cocontraction. These observations show that selection of the strategy for a given contraction implies a compromise between steadiness and effectiveness of compensations to perturbations. This indicates that a task-dependent selection of neural strategy for steadiness is necessary when acting in different environments."],["dc.description.sponsorship","EU Commission through the project NeuroTREMOR [287739]"],["dc.identifier.doi","10.1152/jn.00247.2015"],["dc.identifier.isi","000362045100049"],["dc.identifier.pmid","26203102"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36094"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Physiological Soc"],["dc.relation.issn","1522-1598"],["dc.relation.issn","0022-3077"],["dc.title","The optimal neural strategy for a stable motor task requires a compromise between level of muscle cocontraction and synaptic gain of afferent feedback"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]