Biology subjects

Farrens, A. J.

Publications and source records attributed to Farrens, A. J..

7 recordsLinked to original sources

bioRxiv2022

Concurrent Contribution of Co-contraction to Error Reduction during Dynamic Adaptation of the Wrist

MRI-compatible robots provide a means of studying brain function involved in complex sensorimotor learning processes, such as adaptation. To properly interpret the neural correlates of behavior measured using MRI-compatible robots, it is critical to validate the measurements of motor performance obtained via such devices. Previously, we characterized adaptation of the wrist in response to a force field applied via an MRI-compatible robot, the MR-SoftWrist. Compared to arm reaching tasks, we observed lower end magnitude of adaptation, and reductions in trajectory errors beyond those explained by adaptation. Thus, we formed two hypotheses: that the observed differences were due to measurement errors of the MR-SoftWrist; or that impedance control plays a significant role in control of wrist movements during dynamic perturbations. To test both hypotheses, we performed a two-session counterbalanced study. In both sessions, participants performed wrist pointing in three force field conditions (zero force, constant, random). Participants used either the MR-SoftWrist or the UDiffWrist, a non-MRI-compatible wrist robot, for task execution in session one, and the other device in session two. To measure anticipatory co-contraction associated with impedance control, we collected surface EMG of four forearm muscles. We found no significant effect of device on behavior, validating the measurements of adaptation obtained with the MR-SoftWrist. EMG measures of co-contraction explained a significant portion of the variance in excess error reduction not attributable to adaptation. These results support the hypothesis that for the wrist, impedance control significantly contributes to reductions in trajectory errors in excess of those explained by adaptation.

bioengineering↗

bioRxiv2021

Changes in resting state functional connectivity associated with dynamic adaptation of wrist movements

Dynamic adaptation is an error-driven process of adjusting planned motor actions to changes in task dynamics (1). Adapted motor plans are consolidated into motor memories that contribute to better performance on re-exposure to the same dynamic condition. In parallel, dynamic perturbations can be compensated for by alternate motor control processes, such as co-contraction, that contribute to error reduction (2). Whether these control strategies share the same neural resources for memory formation is unclear. To address this gap in knowledge, we used a novel fMRI-compatible wrist robot, the MR-SoftWrist (3), to identify neural processes specific to dynamic adaptation and subsequent memory formation. Using the MR-SoftWrist, we acquired fMRI during a motor performance and a dynamic perturbation task to localize brain networks of interest. Resting state fMRI scans were acquired immediately before and after task performance to quantify changes in resting state functional connectivity (rsFC) within these networks. Twenty-four hours later, we assessed behavioral retention of training. A variance decomposition analysis was used to isolate behavior associated with adaptation versus alternate error reduction strategies. Immediately after the dynamic perturbation task, rsFC significantly increased within the corticothalamic-cerebellar network of the trained wrist and decreased interhemispherically within the cortical sensorimotor network. These changes were associated to behavioral measures of initial acquisition and retention, indicative of memory formation. Variance decomposition analysis revealed that increases within the cortico-thalamic-cerebellar network were associated with adaptation, while interhemispheric decreases in rsFC within the sensorimotor network were associated with alternate error reduction processes. Significance StatementMotor memory formation processes have been studied using resting state functional connectivity (rsFC) before and after exposure to adaptation tasks. However, due to technical limitations, previous studies have not investigated rsFC within brain regions localized during task execution, nor quantified rsFC within minutes after task performance. The present study used an fMRI-compatible wrist robot to localize relevant brain regions during dynamic adaptation within the cortico-thalamic-cerebellar network and bilateral sensorimotor network. Immediately following dynamic adaptation, we measured significant changes in rsFC within these networks, that were associated with adaptation behavior and with gains in behavior assessed 24 hours later, indicative of memory formation. Variance decomposition analysis identified distinct rsFC networks associated with adaptation specific processes, and with alternate motor control strategies.

bioengineering↗

bioRxiv2020

Measurement of stretch-evoked brainstem function using fMRI

Knowledge on the organization of motor function in the reticulospinal tract (RST) is limited by the lack of methods for measuring RST function in humans. Behavioral studies suggest the involvement of the RST in long latency responses (LLRs). LLRs, elicited by precisely controlled perturbations, can therefore act as a viable paradigm to measure motor-related RST activity using functional Magnetic Resonance Imaging (fMRI). Here we present StretchfMRI, a novel technique developed to study RST function associated with LLRs. StretchfMRI combines robotic perturbations with electromyography and fMRI to simultaneously quantify muscular and neural activity during stretch-evoked LLRs without loss of reliability. Using StretchfMRI, we established the muscle-specific organization of LLR activity in the brainstem. The observed organization is partially consistent with animal models, with activity primarily in the ipsilateral medulla for flexors and in the contralateral pons for extensors, but also include other areas, such as the midbrain and bilateral pontomedullary contributions.

neuroscience↗

bioRxiv2020

A Controlled Slip: Training Propulsion via Acceleration of the Trailing Limb

Walking function, which is critical to performing many activities of daily living, is commonly assessed by walking speed. Walking speed is dependent on propulsion, which is governed by ankle moment and the posture of the trailing limb during push-off. Here, we present a new gait training paradigm that utilizes a dual belt treadmill to train both components of propulsion by accelerating the belt of the trailing limb during push off. Accelerations require subjects to produce greater propulsive force to counteract inertial effects, and increase trailing limb angle through increased belt velocity. We hypothesized that exposure to our training p rogram would produce after effects in propulsion mechanics and, consequently, walking speed. We tested our protocol on healthy subjects at two acceleration magnitudes-Perceptible (PE), and Imperceptible, (IM)-and compared their results to a third control group (VC) that walked at a higher velocity during training. Results show that the PE group significantly increased walking speed following training (mean {+/-} s.e.m: 0.073 {+/-} 0.013 m/s, p < 0.001). The change in walking speed in the IM and VC groups was not significant at the group level (IM: 0.032 {+/-} 0.013 m/s; VC: -0.003 {+/-} 0.013 m/s). Responder analysis showed that changes in push-off posture and in neuro-motor control of ankle plantar-flexor muscles contributed to the larger increases in gait speed measured in the PE group compared to the IM and VC groups. Analysis of the effects during and after training suggest that changes in neuromotor coordination are consistent with use-dependent learning.

bioengineering↗

bioRxiv2019

StretchfMRI: a new technique to quantify the contribution of the reticular formation to long-latency responses via fMRI

Increased reticulospinal (RS) function has been observed to cause both positive and negative outcomes in the recovery of motor function after corticospinal lesions such as stroke. Current knowledge of RF function is limited by the lack of accurate, noninvasive methods for measuring RS function. Recent studies suggest that the RS tract may be involved in processing and generating Long Latency Responses (LLRs). LLRs, elicited by applying precisely controlled perturbations, can act as a reliable stimulus to measure LLR-related brainstem function using fMRI with high signal-to-noise ratio.\n\nIn this paper, we present StretchfMRI, a new technique that enables simultaneous recording of neural and muscular activity during motor responses conditioned by velocity-controlled robotic perturbations, which allows for direct investigation of the neural correlates of LLRs using fMRI.\n\nVia preliminary validation experiments, we demonstrate that our technique can reliably elicit and identify LLRs in two wrist muscles-FCR and ECU. Moreover, via a single-subject pilot experiment, we show that the occurrence of an LLR in a flexor and extensor muscle modulates neural activity in distinct regions of the brainstem. The observed somatotopic organization is in agreement with the double reciprocal model of RS function observed in animal models, in which the right medullary and left pontine reticular formation are responsible for control of the motor activity in flexors and extensors, respectively.

neuroscience↗

bioRxiv2019

Identifying the neural representation of fast and slow states in force field adaptation via fMRI

Neurorehabilitation is centered on motor learning and control processes, however our understanding of how the brain learns to control movements is still limited. Motor adaptation is a rapid form of motor learning that is amenable to study in the laboratory setting. Behavioral studies of motor adaptation have coupled clever task design with computational modeling to study the control processes that underlie motor adaptation. These studies provide evidence of fast and slow learning states in the brain that combine to control neuromotor adaptation.\n\nCurrently, the neural representation of these states remains unclear, especially for adaptation to changes in task dynamics, commonly studied using force fields imposed by a robotic device. Our group has developed the MR-Softwrist, a robot capable of executing dynamic adaptation tasks during functional magnetic resonance imaging (fMRI) that can be used to localize these networks in the brain.\n\nWe simulated an fMRI experiment to determine if signal arising from a switching force field adaptation task can localize the neural representations of fast and slow learning states in the brain. Our results show that our task produces reliable behavioral estimates of fast and slow learning states, and distinctly measurable fMRI activations associated with each state under realistic levels of behavioral and measurement noise. Execution of this protocol with the MR-Softwrist will extend our knowledge of how the brain learns to control movement.

bioengineering↗

bioRxiv2019

Training propulsion: Locomotor adaptation to accelerations of the trailing limb

Many stroke survivors suffer from hemiparesis, a condition that results in impaired walking ability. Walking ability is commonly assessed by walking speed, which is dependent on propulsive force both in healthy and stroke populations. Propulsive force is determined by two factors: ankle moment and the posture of the trailing limb during push-off. Recent work has used robotic assistance strategies to modulate propulsive force with some success. However, robotic strategies are limited by their high cost and the technical difficulty of fitting and operating robotic devices with stroke survivors in a clinical setting.\n\nWe present a new paradigm for goal-oriented gait training that utilizes a split belt treadmill to train both components of propulsive force generation, achieved by accelerating the treadmill belt of the trailing limb during push off. Belt accelerations require subjects to produce greater propulsive force to maintain their position on the treadmill and increases trailing limb angle through increased velocity of the accelerated limb.\n\nWe hypothesized that accelerations would cause locomotor adaptation that would result in measurable after effects in the form of increased propulsive force generation. We tested our protocol on healthy subjects at two levels of belt accelerations. Our results show that 79% of subjects significantly increased propulsive force generation, and that larger accelerations translated to larger, more persistent behavioral gains.

bioengineering↗