There is a consensus that motor recovery post-stroke primarily depends on the degree of the initial connectivity of the ipsilesional corticospinal tract (CST). Indeed, if the residual CST connectivity is sufficient to convey motor commands, the neuromotor system continues to dominantly use the CST, and motor function recovers up to 80%. In contrast, if the residual CST connectivity is insufficient, hand/arm dexterity barely recovers, even as the phases of stroke progress. Instead, functional upregulation of the reticulospinal tract (RST) often occurs. In this study, we construct a computational model that reproduces the dependence of post-stroke motor recovery on initial CST connectivity. The model emulates biologically plausible evolutions of primary motor descending tracts, based on activity-dependent or use-dependent plasticity and the preferential use of more strongly connected neural circuits. The model replicates several segments of the empirical evidence presented by Fugl-Meyer subscores, which presumably change differently depending on the degree of initial CST connectivity post-stroke, providing several insights into the interactive dynamics of primary descending motor tracts. We discuss findings from the proposed model along with the well-known proportional recovery rule. This modeling study is expected to benefit the design of therapies for post-stroke recovery.

While stroke survivors with moderate or mild impairment are typically able to open their hand at will, those with severe impairment are not. Abnormal synergies govern the arm and hand in stoke survivors with severe impairment, so hand opening, which is required to overcome the working synergy, is a task extremely difficult for them to achieve. It is universally accepted that alternative tracts including the cortico-reticulospinal tract (CRST), employed in the case that the corticospinal tract (CST) is damaged by stroke, brings about such abnormal synergies. Here we note that hand closing is enabled by alternative tracts as well as the CST, and raise a research question: does motor characteristics while closing the hand depend on the integrity of the CST? In this study, we evaluate the ability of 17 stroke survivors to flex and relax the metacarpophalangeal (MCP) joints and investigate whether motor characteristics can be distinguished based on CST integrity which is estimated using upper-extremity Fugl-Meyer (UEFM). UEFM scores have been perceived as an indirect indicator of CST integrity. We found that participants with the UEFM score above a certain value, who are assumed to use the CST, moves the MCP joints more smoothly (p<0.05) and activates the flexor to flex the joints faster (p<0.05), in comparison to participants with low UEFM scores, who are assumed to use alternative tracts. The results present evidence that use of alternative tracts (i.e. the CRST) results in a degradation in movement smoothness and slow activation of the MCP flexor.

It is necessary to control contact force through modulation of joint stiffness in addition to the position of our limb when manipulating an object. This is achieved by contracting the agonist muscles in an appropriate magnitude, as well as, balancing it with contraction of the antagonist muscles. Here we develop a decoding technique that estimates both the position and torque of a joint of the limb in interaction with an environment based on activities of the agonist-antagonistic muscle pairs using electromyography in real time. The long short-term memory (LSTM) network that is capable of learning time series of a long-time span with varying time lags is employed as the core processor of the proposed technique. We tested both the unidirectional LSTM network and bidirectional LSTM network. A validation was conducted on the wrist joint moving along a given trajectory under resistance generated by a robot. The decoding approach provided an agreement of greater than 93% in kinetics (i.e. torque) estimation and an agreement of greater than 83% in kinematics (i.e. angle) estimation, between the actual and estimated variables, during interactions with an environment. We found no significant differences in performance between the unidirectional LSTM and bidirectional LSTM as the learning device of the proposed decoding method.

While perturbation training is known to be effective in reducing fall risk, it is unclear whether the interval of perturbations affects motor response. We investigate postural responses that could vary with the interval of perturbations, probably leading to different contributions of relevant learning substrates. A total of 12 male volunteers with no neurological deficits (age: 33.33±3.12 S.D.) experienced two sequences of perturbations. Two sequences of perturbations were designed and administered in turn: the first sequence consisted of 24-time repeated perturbations with an interval of 5 seconds, while the second sequence consisted of ones with an interval of 2.5 seconds. A perturbation of a smaller magnitude was inserted into each sequence as a catch trial. Perturbations were given by a force plate moving in the anterior-posterior direction. The magnitude of the excursions of the center of pressure (COP) and ankle angle in response to perturbations with a longer interval is greater in comparison to that with a shorter interval (P < 0.05). A difference in responses to the perturbation following the catch trial appears in COP (P < 0.05), not in ankle angle (P > 0.05). These results suggest that while contraction of agonist muscles and co-contraction of antagonistic muscle pairs across the ankle joint for stability operate independently of each other, the refinement of the neuromotor system for a newly trained response can be modulated with stimulus intervals. The dependency of postural responses on the interval could imply that the strength of the learning effect varies with stimulus intervals.

Yet, little is known about the direction of abnormal coupling in conjunction with its degree between joints—muscles—of interest. In this study, we address the directionality of pathological neural couplings between joints, and variability in the degree of them, in the  upper  extremity  post  stroke.  To  evaluate  the  direction  of interjoint  coupling,  joint  motion  and  muscle  activity  in  an involuntary mode while another joint—muscle—was voluntarily activated were assessed in comparison to those made in a volitional mode, focusing on the shoulder, elbow and wrist joints. Overall, involuntary activation of the wrist flexor in the stroke group is observed  when  muscles  of  a  more  proximal  joint  voluntarily activate (p < 0.1 and p <0.05), while activation of the wrist flexor does not lead to involuntary activation of the shoulder muscles and elbow flexor, in comparison to the healthy group. In particular, in the  stroke  group  who  is  assumed  to  have  a  severe  loss  of  the corticospinal system, the wrist extensor is subordinately activated by those about the other joints voluntarily activated (p < 0.05) while it does not cause activations of those about the other joints. These findings indicate that stroke-caused synergies could be directional.

Damage in the corticospinal system following stroke produces imbalance between flexors and extensors in the upper extremity including the fingers, eventually leading to flexion-favored postures. The substitution of the reticospinal tract for the damaged corticospinal tract is known to excessively activate flexors of the fingers while the fingers are voluntarily being extended. Here, we questioned whether the cortical source or/and neural pathways of the flexors and extensors of the fingers are coupled and what factor of impairment influences finger movement. In this study, a total of 7 male participants with hemiplegic stroke conducted isometric flexion and extension at the MCP joints in response to auditory tones. We measured activation and de-activation delays of the flexor and extensor of the MCP joints on the paretic side, as well as, force generation and co-contraction between the flexor and extensor. All participants generated greater torque in the direction of flexion (p=0.017). Regarding co-contraction, coupled activation of the extensor is also made during flexion in the similar way to coupled activation of the flexor made during extension. As opposite to our expectation, we observed that during extension, the extensor showed marginally significantly faster activation (p=0.66) while it showed faster de-activation (p=0.038), in comparison to activation and de-activation of the flexor during flexion. But movement smoothness was not affected by those factors. Our results imply that the cortical source and neural pathway for the extensors of the MCP joints are not coupled with those for the flexors of the MCP joints and extensor weakness mainly contributes to the asymmetry between flexors and extensors.