Plasticity of face-hand sensorimotor circuits after a traumatic brachial plexus injury.

Background: Interactions between the somatosensory and motor cortices are of fundamental importance for motor control. Although physically distant, face and hand representations are side by side in the sensorimotor cortex and interact functionally. Traumatic brachial plexus injury (TBPI) interferes with upper limb sensorimotor function, causes bilateral cortical reorganization, and is associated with chronic pain. Thus, TBPI may affect sensorimotor interactions between face and hand representations. Objective: The aim of this study was to investigate changes in hand-hand and face-hand sensorimotor integration in TBPI patients using an afferent inhibition (AI) paradigm. Method: The experimental design consisted of electrical stimulation (ES) applied to the hand or face followed by transcranial magnetic stimulation (TMS) to the primary motor cortex to activate a hand muscle representation. In the AI paradigm, the motor evoked potential (MEP) in a target muscle is significantly reduced when preceded by an ES at short-latency (SAI) or long-latency (LAI) interstimulus intervals. We tested 18 healthy adults (control group, CG), evaluated on the dominant upper limb, and nine TBPI patients, evaluated on the injured or the uninjured limb. A detailed clinical evaluation complemented the physiological investigation. Results: Although hand-hand SAI was present in both the CG and the TBPI groups, hand-hand LAI was present in the CG only. Moreover, less AI was observed in TBPI patients than the CG both for face-hand SAI and LAI. Conclusion: Our results indicate that sensorimotor integration involving both hand and face sensorimotor representations is affected by TBPI.

Effect of muscle length in a handgrip task on corticomotor excitability of extrinsic and intrinsic hand muscles under resting and submaximal contraction conditions.

The neurophysiological mechanisms underlying muscle force control for different wrist postures still need to be better understood. To further elucidate these mechanisms, the present study aimed to investigate the effects of wrist posture on the corticospinal excitability by transcranial magnetic stimulation (TMS) of extrinsic (flexor [FCR] and extensor carpi radialis [ECR]) and intrinsic (flexor pollicis brevis (FPB)) muscles at rest and during a submaximal handgrip strength task. Fourteen subjects (24.06 ± 2.28 years) without neurological or motor disorders were included. We assessed how the wrist posture (neutral: 0°; flexed: +45°; extended: -45°) affects maximal handgrip strength (HGSmax ) and the motor evoked potentials (MEP) amplitudes during rest and active muscle contractions. HGSmax was higher at 0° (133%) than at -45° (93.6%; p < 0.001) and +45° (73.9%; p < 0.001). MEP amplitudes were higher for the FCR at +45° (83.6%) than at -45° (45.2%; p = 0.019) and at +45° (156%; p < 0.001) and 0° (146%; p = 0.014) than at -45° (106%) at rest and active condition, respectively. Regarding the ECR, the MEP amplitudes were higher at -45° (113%) than at +45° (60.8%; p < 0.001) and 0° (72.6%; p = 0.008), and at -45° (138%) than +45° (96.7%; p = 0.007) also at rest and active conditions, respectively. In contrast, the FPB did not reveal any difference among wrist postures and conditions. Although extrinsic and intrinsic hand muscles exhibit overlapping cortical representations and partially share the same innervation, they can be modulated differently depending on the biomechanical constraints.

Spectral detection of nematodes in soybean at flowering growth stage using unmanned aerial vehicles / Detecção espectral de nematóides na soja em estádio de florescimento por meio de veículos aéreos não-tripulados

ABSTRACT: Soybean is one of the main crop species grown in the world. However, there is a decline in productivity due to the various types of stress, including the nematodes Heterodera glycines and Pratylenchus brachyurus. The objectives were to determine the best spectral band for detecting H. glycines and P. brachyurus at the beginning of flowering (R1). Soil and root sampling was conducted at nine sampling sites in each of the five nematode-infested regions, totaling 45 sampling points. Flights were made at all regions using Phantom 4 Advanced, Sequoia and 14-band customized Sentera. For H. glycines, the red spectral band best explained the variability on soil and root nematode counts as well as the second stage of juveniles in soil. For P. brachyurus, Sentera RedEdge best explained the variability in root nematode counts and Sequoia NIR best explained soil juveniles. A multiple linear regression model using spectral data for detecting P. brachyurus and H. glycines improved R² compared to simple linear regressions. At flowering growth stage (R1), soybean spectral reflectance was associated with the number of H. glycines and P. brachyurus on soil and roots using low-cost and multispectral sensors.

RESUMO: A soja é uma das principais espécies de planta cultivadas no mundo. Todavia, perdas de produtividade são ocasionadas por vários tipos de estresses, incluindo os nematoides H. glycines e P. brachyurus. Como objetivo, buscou-se determinar a melhor banda espectral para a detecção do H. glycines e P. brachyurus com o uso de modelos de regressões lineares simples e definir um modelo matemático de regressão linear múltiplo para sua detecção, no início do florescimento (R1). Para isto, foram definidos nove pontos de coleta em cinco reboleiras, totalizando 45 pontos. As coletas foram feitas em um padrão específico de distâncias, de forma a ter amostras com tipos variados de populações de nematoides. Foram realizados voos com o Phantom 4 Advanced, Sequoia e Sentera sobre cada uma das reboleiras. O comprimento de onda do vermelho melhor explicou a variabilidade dos dados para H. glycines no solo e na raiz, bem como dos juvenis de segundo estádio no solo. Para P. brachyurus, a RedEdge da Sentera foi a que explicou melhor a variabilidade dos dados para nematoide na raiz e a NIR da Sequoia a que melhor explicou para juvenis no solo. Quando se utilizou um modelo matemático para a detecção do P. brachyurus e H. glycines, percebe-se uma grande melhora no R² e p-valor com relação às regressões lineares simples. No início da floração (R1), a refletância espectral da soja foi associada ao número de H. glycines e P. brachyurus no solo e nas raízes, usando sensores de baixo custo e multiespectrais.