Engagement of the rat hindlimb motor cortex across natural locomotor behaviors

Contrary to cats and primates, cortical contribution to hindlimb locomotor movements is not critical in rats. However, the importance of the motor cortex to regain locomotion after neurological disorders in rats suggests that cortical engagement in hindlimb motor control may depend on the behavioral context. To investigate this possibility, we recorded whole-body kinematics, muscle synergies, and hindlimb motor cortex modulation in freely moving rats performing a range of natural locomotor procedures. We found that the activation of hindlimb motor cortex preceded gait initiation. During overground locomotion, the motor cortex exhibited consistent neuronal population responses that were synchronized with the spatiotemporal activation of hindlimb motoneurons. Behaviors requiring enhanced muscle activity or skilled paw placement correlated with substantial adjustment in neuronal population responses. In contrast, all rats exhibited a reduction of cortical activity during more automated behavior, such as stepping on a treadmill. Despite the facultative role of the motor cortex in the production of locomotion in rats, these results show that the encoding of hindlimb features in motor cortex dynamics is comparable in rats and cats. However, the extent of motor cortex modulations appears linked to the degree of volitional engagement and complexity of the task, reemphasizing the importance of goal-directed behaviors for motor control studies, rehabilitation, and neuroprosthetics. © 2016 the authors

Decoding Information From Neural Signals Recorded Using Intraneural Electrodes: Toward the Development of a Neurocontrolled Hand Prosthesis

The possibility of controlling dexterous hand prostheses by using a direct connection with the nervous system is particularly interesting for the significant improvement of the quality of life of patients, which can derive from this achievement. Among the various approaches, peripheral nerve based intrafascicular electrodes are excellent neural interface candidates, representing an excellent compromise between high selectivity and relatively low invasiveness. Moreover, this approach has undergone preliminary testing in human volunteers and has shown promise. In this paper, we investigate whether the use of intrafascicular electrodes can be used to decode multiple sensory and motor information channels with the aim to develop a finite state algorithm that may be employed to control neuroprostheses and neurocontrolled hand prostheses. The results achieved both in animal and human experiments show that the combination of multiple sites recordings and advanced signal processing techniques (such as wavelet denoising and spike sorting algorithms) can be used to identify both sensory stimuli (in animal models) and motor commands (in a human volunteer). These findings have interesting implications, which should be investigated in future experiments. © 2006 IEEE

Analysis of balance, rapidity, force and reaction times of soccer players at different levels of competition

In the present study we analyzed 12 physical parameters, namely force, static and dynamic balance (both quantified by means of 4 parameters each), rapidity, visual reaction times and acoustic reaction times, over 185 subjects. 170 of them played soccer in teams enrolled in all the ten different Italian soccer leagues. Results show that 6 parameters (out of the 12 analyzed) permit to identify and discriminate top-level players, among those showing the same training frequency. The other parameters are strictly related to training frequency or do not discriminate among players or control subjects (non-athletes), such as visual and acoustic reaction times. Principal component analysis permits to identify 4 clusters of subjects with similar performances, thus representing a useful instrument to characterize the overall ability of players in terms of athletic characteristics, on the basis of their location on the principal component parameters plane

Hypergravity effects on proliferation and differentiation of C2C12 muscle-like cells

This study aimed at the investigation of muscle-like cell behaviour in conditions of altered gravity. C2C12 cells underwent stimulations by different hypergravity intensities (5, 10, 20 g) in the Large Diameter Centrifuge of the European Space Agency (ESA), and their features in terms of proliferation and differentiation were compared to control cultures carried out at normal earth gravity force. Proliferation was investigated determining the DNA content in the cultures. A positive correlation between DNA concentration (and therefore cell proliferation) and g values was found. Moreover, actin staining allowed for a qualitative study of the cytoskeleton rearrangement following hypergravity exposure. Differentiation was evaluated on confluent cultures treated with analogous protocol. Also in this case, hypergravity seems to positively affect the differentiation process of C2C12 cells and their fusion in myotubes. The evaluation of myosin expression by immunocytochemistry suggested an accelerated differentiation process following exposure of cells to different g values

Hypergravity effects on myoblast proliferation and differentiation

This study aimed at the investigation of behavior of myoblasts in conditions of altered gravity. C2C12 cells underwent stimulations by different hypergravity intensities (2 h at 5g, 10g, and 20g) in the Large Diameter Centrifuge of the European Space Agency (ESA), highlighting positive effects on both proliferation and differentiation

Neuro-fuzzy decoding of sensory information from ensembles of simultaneously recorded dorsal root ganglion neurons for functional electrical stimulation applications

Functional electrical stimulation (FES) is used to improve motor function after injury to the central nervous system. Some FES systems use artificial sensors to switch between finite control states. To optimize FES control of the complex behavior of the musculo-skeletal system in activities of daily life, it is highly desirable to implement feedback control. In theory, sensory neural signals could provide the required control signals. Recent studies have demonstrated the feasibility of deriving limb-state estimates from the firing rates of primary afferent neurons recorded in dorsal root ganglia (DRG). These studies used multiple linear regression (MLR) methods to generate estimates of limb position and velocity based on a weighted sum of firing rates in an ensemble of simultaneously recorded DRG neurons. The aim of this study was to test whether the use of a neuro-fuzzy (NF) algorithm (the generalized dynamic fuzzy neural networks (GD-FNN)) could improve the performance, robustness and ability to generalize from training to test sets compared to the MLR technique. NF and MLR decoding methods were applied to ensemble DRG recordings obtained during passive and active limb movements in anesthetized and freely moving cats. The GD-FNN model provided more accurate estimates of limb state and generalized better to novel movement patterns. Future efforts will focus on implementing these neural recording and decoding methods in real time to provide closed-loop control of FES using the information extracted from sensory neurons