Spike Timing-Dependent Plasticity in the Long-Latency Stretch Reflex Following Paired Stimulation from a Wearable Electronic Device

Foysal, K. M. Riashad; Carvalho, Felipe de; Baker, Stuart N.

doi:10.1523/jneurosci.1414-16.2016

Cited by 29 publications

(30 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, others have reported a reduction in spinal excitability during MI (Oishi et al 1994;Yahagi et al 1996), which may represent the deployment of an inhibitory system intended to prevent the overt manifestation of the imagined movement. Spinal, as well as cortical, circuits are capable of undergoing plastic changes (Lamy et al 2010;Dixon et al 2016;Foysal et al 2016); such spinal plasticity is under cortical control (Chen et al 2006a,b). It is therefore most likely that pairing MI with TMS induces changes at multiple levels of the neuraxis.…”

Section: The Site Of Plasticitymentioning

confidence: 99%

Induction of plasticity in the human motor system by motor imagery and transcranial magnetic stimulation

Foysal

Baker

2020

The Journal of Physiology

Self Cite

View full text Add to dashboard Cite

Key points Delivering transcranial magnetic brain stimulation over the motor cortex during motor imagination leads to enhanced motor output, which is selective for the muscles primarily involved in the imagined movement. This novel protocol may be useful to enhance function after damage to the motor system, such as after stroke. Abstract Several paired stimulation paradigms are known to induce plasticity in the motor cortex, reflected by changes in the motor evoked potential (MEP) following the paired stimulation. Motor imagery (MI) is capable of activating the motor system and affecting cortical excitability. We hypothesized that it might be possible to use MI in conjunction with transcranial magnetic stimulation (TMS) to induce plasticity in the human motor system. TMS was delivered to the motor cortex of healthy human subjects, and baseline MEPs recorded from forearm flexor, forearm extensor and intrinsic hand muscles. Subjects were then asked to imagine either wrist flexion or extension movements during TMS delivery (n = 90 trials). Immediately after this intervention, MEP measurement was repeated. Control protocols tested the impact of imagination or TMS alone. Flexion imagination with TMS increased MEPs in flexors and an intrinsic hand muscle. Extensor imagination with TMS increased MEPs in extensor muscles only. The control paradigms did not produce significant changes. We conclude that delivering TMS during MI is capable of inducing plastic changes in the motor system. This new protocol may find utility to enhance functional rehabilitation after brain injury.

show abstract

Section: The Site Of Plasticitymentioning

confidence: 99%

Induction of plasticity in the human motor system by motor imagery and transcranial magnetic stimulation

Foysal

Baker

2020

The Journal of Physiology

Self Cite

View full text Add to dashboard Cite

show abstract

“…For distal and forearm muscles contributions from M1 to the LLR are well supported, but there is also evidence for subcortical involvement (Soteropoulos et al 2012). For more proximal muscles there is also evidence for both M1 and subcortical contributions (Foysal et al 2016;Herter et al 2015;Omrani et al 2014) but the relative importance of M1 is unclear. Although cells in M1…”

Section: Llr: Beyond a Marker For Cortical Excitability?mentioning

confidence: 99%

Long-latency Responses to a Mechanical Perturbation of the Index Finger Have a Spinal Component

Soteropoulos

Baker

2020

J. Neurosci.

Self Cite

View full text Add to dashboard Cite

In an uncertain external environment, the motor system may need to respond rapidly to an unexpected stimulus. Limb displacement causes muscle stretch; the corrective response has multiple activity bursts, which are suggested to originate from different parts of the neuraxis. The earliest response is so fast, it can only be produced by spinal circuits; this is followed by slower components thought to arise from primary motor cortex (M1) and other supraspinal areas. Spinal cord (SC) contributions to the slower components are rarely considered. To address this, we recorded neural activity in M1 and the cervical SC during a visuomotor tracking task, in which two female macaque monkeys moved their index finger against a resisting motor to track an on-screen target. Following the behavioral trial, an increase in motor torque rapidly returned the finger to its starting position (lever velocity >200°/s). Many cells responded to this passive mechanical perturbation (M1: 148/211 cells, 70%; SC: 67/119 cells, 56%). The neural onset latency was faster for SC compared to M1 cells (21.7±11.2ms vs 25.5±10.7ms respectively, mean ± SD). Using spike triggered averaging, some cells in both regions were identified as likely premotor cells, with monosynaptic connections to motoneurons. Response latencies for these cells were compatible with a contribution to the muscle responses following the perturbation. Comparable fractions of responding neurons in both areas were active up to 100ms after the perturbation, suggesting that both SC circuits and supraspinal centers could contribute to later response components. Significance Statement Following a limb perturbation, multiple reflexes help to restore limb position. Given conduction delays, the earliest part of these reflexes can only arise from spinal circuits. By contrast, long latency reflex components are typically assumed to originate from supraspinal centers. We recorded from both spinal and motor cortical cells in monkeys responding to index finger perturbations. Many spinal interneurons, including those identified as projecting to motoneurons, responded to the perturbation; the timing of responses was compatible with a contribution to both short-and longlatency reflexes. We conclude that spinal circuits also contribute to long latency reflexes in distal and forearm muscles, alongside supraspinal regions such as the motor cortex and brainstem.

show abstract

“…Behavioral Results in the supplementary materials. For (1) Ultrasonic motor, (2) output capstan arc, (3) input pulley, (4) tensioning mechanisms, (5) structural bearings, (6) force/torque sensor, (7) hand support; (C) Placement of the electrodes on the forearm; (D) Hardware of the novel apparatus developed for the acquisition of the EMG data during fMRI protocols (E) EMG processing scheme based on Adaptive Noise Cancellation.…”

Section: Stretchfmrimentioning

confidence: 99%

“…Among these secondary pathways, the reticulospinal tract (RST) is especially important for its involvement in locomotion 2 , maintenance of posture 3 , reaching 4 and grasping 5 . The RST is composed of two different pathways that originate from the Reticular Formation (RF), a region in the brainstem composed of a constellation of nuclei 6,7 . Evidence from non-human primate studies suggests a possible organization of motor function in the RF, where excitatory signals are sent to ipsilateral flexors and contralateral extensors, and inhibitory signals are sent to contralateral flexors and ipsilateral extensors [8][9][10] .…”

Section: Introductionmentioning

confidence: 99%

Measurement of stretch-evoked brainstem function using fMRI

Zonnino

Farrens

Ress

et al. 2020

Preprint

View full text Add to dashboard Cite

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 stretchevoked 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. 2/25reference, the mean timeseries of the EMG recorded during Exp 1 and processed using three different filtering pipelines is shown in Fig. 2A. Reliability of stretch-evoked EMG during fMRIWe validated the stretch-evoked EMG collected during fMRI by quantifying agreement between measurements collected inside and outside the MR scanner (see Online Methods). We used two analyses: one based on the mean LLR responses averaged across multiple repetitions for each set of conditions (group-level analysis), and one based on the analysis of EMG measurements of individual perturbations (perturbation-specific analysis). Group level resultsGroup-level analysis was performed using the Bland-Altman (BA) method 13,14 , whose plots are shown in Fig. 2B for the comparisons OUT 2 vs. OUT 1 and IN 1 vs. OUT 1 , for different signal filtering pipelines. The values of bias, positive and negative limits of agreement (LoA), with the respective confidence intervals are reported in Tab. S8 in the supplementary materials.Based on the BA analysis, Adaptive Noise Cancellation (ANC) enables reliable estimation of LLR amplitude during fMRI sessions. In fact, the agreement between LLR amplitudes measured inside and outside the MRI is not worse than the agreement between two OUT sessions. Specifically, the bias estimated for the IN 1 vs. OUT 1 comparison was not significantly different from the one estimated for the OUT 2 vs. OUT 1 comparison (z(72)=0.56, p = 0.57 for stretch, z(72) = 1.70 , p = 0.09 for shortening). Additionally, the 95% confidence intervals of the bias estimated for both comparisons, in both muscle stimulus directions, intersect the zero value indicating that the measurement is unbiased (Fig. 3A). Finally, the overlap between the range defined by the LoA for two repeated OUT experiments and the range of LoA for IN vs. OUT experiment, quantified by the Jaccard coefficient, approached perfect overlap (mean ± s.e.m. J = 0.843 ± 0.001 for stretch, J = 0.783 ± 0.001...

show abstract

Spike Timing-Dependent Plasticity in the Long-Latency Stretch Reflex Following Paired Stimulation from a Wearable Electronic Device

Cited by 29 publications

References 52 publications

Induction of plasticity in the human motor system by motor imagery and transcranial magnetic stimulation

Induction of plasticity in the human motor system by motor imagery and transcranial magnetic stimulation

Long-latency Responses to a Mechanical Perturbation of the Index Finger Have a Spinal Component

Measurement of stretch-evoked brainstem function using fMRI

Contact Info

Product

Resources

About