Corticospinal interaction during isometric compensation for modulated forces with different frequencies

Apigenin Attenuates Functional and Structural Alterations via Targeting NF-kB/Nrf2 Signaling Pathway in LPS-Induced Parkinsonism in Experimental Rats : Apigenin Attenuates LPS-Induced Parkinsonism in Experimental Rats

Parkinson's disease (PD) is a progressive hypokinetic movement disorder caused by selective degeneration of dopaminergic neurons in striatum and dopamine deficiency in a region of the midbrain. LPS is an endotoxin, used as animal model to induce microglial activation, neuroinflammation, oxidative stress, and neurotransmitter alteration with PD-like symptoms. Therefore, to prevent neuroinflammation and neurotransmitter changes and to restore normal brain physiology, we tried apigenin (AGN) alone and in combination with piperine (bioenhancer), in LPS experimental model of rats. In this study, rats were treated with single unilateral intranigral injection of LPS at a dose of 5 μg/5 μl on day 0. The oral administration of AGN (25 and 50 mg/kg; p.o.) alone, AGN (25 mg/kg; p.o.) in combination with piperine (2.5 mg/kg; p.o.), and bromocriptine (10mg/kg; p.o.) started from day 7th once in a day. Intranigral injection of LPS significantly altered body weight and behavioral parameters assessed on weekly basis. Furthermore, the biochemical and neuroinflammatory analysis confirmed (on day 22nd) increased level of nitrite, MDA, SOD, TNF-α, IL-1β, IL-6, and caspase-1, and decreased level of CAT, GSH, and complex-I. Furthermore, altered level of neurotransmitters (DA, GABA, and glutamate) and cellular changes were observed from histopathological and immunohistochemistry (NF-kB and Nrf-2) analysis. Treatment with AGN (25 and 50 mg/kg; p.o.) alone and AGN (25 mg/kg; p.o.) in combination with piperine (2.5 mg/kg; p.o.) significantly attenuated the alteration in body weight, motor impairments, oxidative stress, neuroinflammation, and neurotransmitters in rat brain. The neuroprotective effect of AGN against LPS-induced cell death is attributed by modulating NF-kB and Nrf2 signaling pathway in the striatum.

Primary Sensorimotor Cortex Drives the Common Cortical Network for Gamma Synchronization in Voluntary Hand Movements

Background: Gamma synchronization (GS) may promote the processing between functionally related cortico-subcortical neural populations. Our aim was to identify the sources of GS and to analyze the direction of information flow in cerebral networks at the beginning of phasic movements, and during medium-strength isometric contraction of the hand.

Methods: We measured 64-channel electroencephalography in 11 healthy volunteers (age: 25 ± 8 years; four females); surface electromyography detected the movements of the dominant hand. In Task 1, subjects kept a constant medium-strength contraction of the first dorsal interosseus muscle, and performed a superimposed repetitive voluntary self-paced brisk squeeze of an object. In Task 2, brisk, and in Task 3, constant contractions were performed. Time-frequency analysis of the EEG signal was performed with the multitaper method. GS sources were identified in five frequency bands (30–49, 51–75, 76–99, 101–125, and 126–149 Hz) with beamformer inverse solution dynamic imaging of coherent sources. The direction of information flow was estimated by renormalized partial directed coherence for each frequency band. The data-driven surrogate test, and the time reversal technique were performed to identify significant connections.

Results: In all tasks, we depicted the first three common sources for the studied frequency bands that were as follows: contralateral primary sensorimotor cortex (S1M1), dorsolateral prefrontal cortex (dPFC) and supplementary motor cortex (SMA). GS was detected in narrower low- (∼30–60 Hz) and high-frequency bands (>51–60 Hz) in the contralateral thalamus and ipsilateral cerebellum in all three tasks. The contralateral posterior parietal cortex was activated only in Task 1. In every task, S1M1 had efferent information flow to the SMA and the dPFC while dPFC had no detected afferent connections to the network in the gamma range. Cortical-subcortical information flow captured by the GS was dynamically variable in the narrower frequency bands for the studied movements.

Conclusion: A distinct cortical network was identified for GS in voluntary hand movement tasks. Our study revealed that S1M1 modulated the activity of interconnected cortical areas through GS, while subcortical structures modulated the motor network dynamically, and specifically for the studied movement program.

Nonlinear Frequency-Domain Analysis of the Transformation of Cortical Inputs by a Motoneuron Pool-Muscle Complex

Corticomotor coherence in the beta and/or gamma bands has been described in different motor tasks, but the role of descending brain oscillations on force control has been elusive. Large-scale computational models of a motoneuron pool and the muscle it innervates have been used as tools to advance the knowledge of how neural elements may influence force control. Here, we present a frequency domain analysis of a NARX model fitted to a large-scale neuromuscular model by the means of generalized frequency response functions (GFRF). The results of such procedures indicated that the computational neuromuscular model was capable of transforming an oscillatory synaptic input (e.g., at 20 Hz) into a constant mean muscle force output. The nonlinearity uncovered by the GFRFs of the NARX model was responsible for the demodulation of an oscillatory input (e.g., a beta band oscillation coming from the brain and forming the input to the motoneuron pool). This suggests a manner by which brain rhythms descending as command signals to the spinal cord and acting on a motoneuron pool can regulate a maintained muscle force. In addition to the scientific aspects of these results, they provide new interpretations that may further neural engineering applications associated with quantitative neurological diagnoses and robotic systems for artificial limbs.

The influence of unilateral contraction of hand muscles on the contralateral corticomuscular coherence during bimanual motor tasks

The mechanisms behind how muscle contractions in one hand influence corticomuscular coherence in the opposite hand are still undetermined. Twenty-two subjects were recruited to finish bimanual and unimanual motor tasks. In the unimanual tasks, subjects performed precision grip using their right hand with visual feedback of exerted forces. The bimanual tasks involved simultaneous finger abduction of their left hand with visual feedback and precision grip of their right hand. They were divided into four conditions according to the two contraction levels of the left-hand muscles and whether visual feedback existed for the right hand. Measures of coherence and power spectrum were calculated from EEG and EMG data and statistically analyzed to identify changes in corticomuscular coupling and oscillatory activity. Results showed that compared with the unimanual task, a significant increase in the mean corticomuscular coherence of the right hand was found when left-hand muscles contracted at 5% of the maximal isometric voluntary contraction (MVC). No significant changes were found when the contraction level was 50% of the MVC. Furthermore, both the increase of muscle contraction levels and the elimination of visual feedback for right hand can significantly decrease the corticomuscular coupling in right hand during bimanual tasks. In summary, the involvement of moderate left-hand muscle contractions resulted in an increase tendency of corticomuscular coherence in right hand while strong left-hand muscle contractions eliminated it. We speculated that the perturbation of activities in one corticospinal tract resulted from the movement of the opposite hand can enhance the corticomuscular coupling when attention distraction is limited.

Fast Oscillatory Commands from the Motor Cortex Can Be Decoded by the Spinal Cord for Force Control

Oscillations in the beta and gamma bands (13-30 Hz; 35-70 Hz) have often been observed in motor cortical outputs that reach the spinal cord, acting on motoneurons and interneurons. However, the frequencies of these oscillations are above the muscle force frequency range. A current view is that the transformation of the motoneuron pool inputs into force is linear. For this reason possible roles for these oscillations are unclear, since if this transformation is linear, the high frequencies in the motoneuron inputs (e.g., 20 Hz from pyramidal tract neurons) would be filtered out by the muscle and have no effect on force control. A biologically inspired mathematical model of the neuromuscular system was used to investigate the impact of high-frequency cortical oscillatory activity on force control. The model simulation results evidenced that a typical motoneuron pool has a nonlinear behavior that enables the decoding of a high-frequency oscillatory input. An input at a single frequency (e.g., beta band) leads to an increase in the steady-state force generated by the muscle. When the input oscillation was amplitude modulated at a given low frequency, the force oscillated at this frequency. In both cases, the mechanism relies on the recruitment and derecruitment of motor units in response to the oscillatory descending drive. Therefore, the results from this study suggest a potential role in force control for cortical oscillations at frequencies at or above the beta band, despite the low-pass behavior of the muscles.

SIGNIFICANCE STATEMENT

The role of cortical oscillations in motor control has been a long-standing question, one view being that they are an epiphenomenon. Fast oscillations are known to reach the spinal cord, and hence they have been thought to affect muscle behavior. However, experimental limitations have hampered further advances to explain how they could influence muscle force. An approach for such a challenge was adopted in the present research: to study the problem through computer simulations of an advanced biologically compatible mathematical model. Using such a model, we found that the well-known mechanism of recruitment and derecruitment of the spinal cord motoneurons can allow the muscle to respond to cortical oscillations, suggesting that these oscillations are not epiphenomena in motor control.

Characterization of information-based learning benefits with submovement dynamics and muscular rhythmicity

For skill advancement, motor variability must be optimized based on target information during practice sessions. This study investigated structural changes in kinematic variability by characterizing submovement dynamics and muscular oscillations after practice with visuomotor tracking under different target conditions. Thirty-six participants were randomly assigned to one of three groups (simple, complex, and random). Each group practiced tracking visual targets with trajectories of varying complexity. The velocity trajectory of tracking was decomposed into 1) a primary contraction spectrally identical to the target rate and 2) an intermittent submovement profile. The learning benefits and submovement dynamics were conditional upon experimental manipulation of the target information. Only the simple and complex groups improved their skills with practice. The size of the submovements was most greatly reduced by practice with the least target information (simple > complex > random). Submovement complexity changed in parallel with learning benefits, with the most remarkable increase in practice under a moderate amount of target information (complex > simple > random). In the simple and complex protocols, skill improvements were associated with a significant decline in alpha (8–12 Hz) muscular oscillation but a potentiation of gamma (35–50 Hz) muscular oscillation. However, the random group showed no significant change in tracking skill or submovement dynamics, except that alpha muscular oscillation was reduced. In conclusion, submovement and gamma muscular oscillation are biological markers of learning benefits. Effective learning with an appropriate amount of target information reduces the size of submovements. In accordance with the challenge point hypothesis, changes in submovement complexity in response to target information had an inverted-U function, pertaining to an abundant trajectory-tuning strategy with target exactness.

Functional corticospinal projections from human supplementary motor area revealed by corticomuscular coherence during precise grip force control

The purpose of the present study was to investigate whether corticospinal projections from human supplementary motor area (SMA) are functional during precise force control with the precision grip (thumb-index opposition). Since beta band corticomuscular coherence (CMC) is well-accepted to reflect efferent corticospinal transmission, we analyzed the beta band CMC obtained with simultaneous recording of electroencephalographic (EEG) and electromyographic (EMG) signals. Subjects performed a bimanual precise visuomotor force tracking task by applying isometric low grip forces with their right hand precision grip on a custom device with strain gauges. Concurrently, they held the device with their left hand precision grip, producing similar grip forces but without any precision constraints, to relieve the right hand. Some subjects also participated in a unimanual control condition in which they performed the task with only the right hand precision grip while the device was held by a mechanical grip. We analyzed whole scalp topographies of beta band CMC between 64 EEG channels and 4 EMG intrinsic hand muscles, 2 for each hand. To compare the different topographies, we performed non-parametric statistical tests based on spatio-spectral clustering. For the right hand, we obtained significant beta band CMC over the contralateral M1 region as well as over the SMA region during static force contraction periods. For the left hand, however, beta band CMC was only found over the contralateral M1. By comparing unimanual and bimanual conditions for right hand muscles, no significant difference was found on beta band CMC over M1 and SMA. We conclude that the beta band CMC found over SMA for right hand muscles results from the precision constraints and not from the bimanual aspect of the task. The result of the present study strongly suggests that the corticospinal projections from human SMA become functional when high precision force control is required.

The strength of the corticospinal coherence depends on the predictability of modulated isometric forces

Isometric compensation of predictably frequency-modulated low forces is associated with corticomuscular coherence (CMC) in beta and low gamma range. It remains unclear how the CMC is influenced by unpredictably modulated forces, which create a mismatch between expected and actual sensory feedback. We recorded electroencephalography from the contralateral hand motor area, electromyography (EMG), and the motor performance of 16 subjects during a visuomotor task in which they had to isometrically compensate target forces at 8% of the maximum voluntary contraction with their right index finger. The modulated forces were presented with predictable or unpredictable frequencies. We calculated the CMC, the cortical motor alpha-, beta-, and gamma-range spectral powers (SP), and the task-related desynchronization (TRD), as well as the EMG SP and the performance. We found that in the unpredictable condition the CMC was significantly lower and associated with lower cortical motor SP, stronger TRD, higher EMG SP, and worse performance. The findings suggest that due to the mismatch between predicted and actual sensory feedback leading to higher computational load and less stationary motor state, the unpredictable modulation of the force leads to a decrease in corticospinal synchrony, an increase in cortical and muscle activation, and a worse performance.