The Resting Motor Threshold – Restless or Resting? A Repeated Threshold Hunting Technique to Track Dynamic Changes in Resting Motor Threshold

Karabanov, Anke Ninija; Raffin, Estelle; Siebner, Hartwig R.

doi:10.1016/j.brs.2015.07.001

Cited by 15 publications

(18 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By using the adaptive hunting threshold single-pulse TMS technique, we found that the minimum TS intensity required to elicit the MEPtarget was lower during MI when compared to rest. This result replicates and extends earlier findings showing that corticospinal excitability is higher during MI (Karabanov et al, 2015;Grosprêtre et al, 2016;Ruffino et al, 2017), regardless of the MEPtarget amplitude.…”

Section: Corticospinal Excitability Increase During MIsupporting

confidence: 92%

“…The latter have the potential to override the inhibitory system and are known to contribute to the short interval intracortical facilitation (SICF) phenomenon (Ilić et al, 2002;Kossev et al, 2003;Peurala et al, 2008;Vucic et al, 2009;Wagle-Shukla et al, 2009). Importantly, it must be pointed out that rMT is not a static but rather a state-dependent measure that is subject to the excitability of several cortical and spinal elements excited by the TMS pulse (Groppa et al, 2012;Karabanov et al, 2015). For example, MI decreases the rMT (Facchini et al, 2002;Li, 2007;Grosprêtre et al, 2016) and enhances MEP amplitude (Kasai et al, 1997;Yahagi and Kasai, 1998;Lebon et al, 2012;Grosprêtre et al, 2016) when 3 compared to rest.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Unravelling the modulation of intracortical inhibition during motor imagery: An adaptive threshold-hunting study

Neige

Rannaud-Monany

Stinear

et al. 2019

Preprint

View full text Add to dashboard Cite

Motor imagery (MI) is the mental simulation of an action without any apparent muscular contraction. By means of transcranial magnetic stimulation, few studies revealed a decrease of short-interval intracortical inhibition (SICI) within the primary motor cortex. However, this decrease is ambiguous, as one would expect greater inhibition during MI to prevent overt motor output. The current study investigated the extent of SICI modulation during MI through a methodological and a conceptual reconsideration of i) the importance of parameters to assess SICI (Exp.1) and ii) the inhibitory process within the primary motor cortex as an inherent feature of MI (Exp.2). Participants performed two tasks: 1) rest and 2) imagery of isometric abduction of the right index finger. Using transcranial magnetic stimulation, motor evoked potentials were elicited in the right first dorsal interosseous muscle. An adaptive threshold-hunting paradigm was used, where the stimulus intensity required to maintain a fixed motor evoked potential amplitude was quantified.To test SICI, we conditioned the test stimulus with a conditioning stimulus (CS) of different intensities. Results revealed an Intensity by Task interaction showing that SICI decreased during MI as compared to rest only for the higher CS intensity (Exp.1). At the lowest CS intensities, a Task main effect revealed that SICI increased during MI (Exp.2). SICI modulation during MI depends critically on the CS intensity. By optimising CS intensity, we have shown that SICI circuits may increase during MI, revealing a potential mechanism to prevent the production of a movement while the motor system is activated.

show abstract

Section: Corticospinal Excitability Increase During MIsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Unravelling the modulation of intracortical inhibition during motor imagery: An adaptive threshold-hunting study

Neige

Rannaud-Monany

Stinear

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Further, due to the rapid acquisition of RMT/AMT using adaptive threshold hunting, this technique is ideally suited to monitor state-dependent changes that occur following plasticity-inducing interventions. For example, threshold hunting can detect rapid changes in RMT that occur with changes in visual attention and motor imagery [ 20 ]. In conclusion, accumulating evidence suggests that the use of adaptive threshold hunting methods of MT estimation benefit researchers in that fewer stimuli are required while providing similar outcomes obtained by traditional methods.…”

Section: Discussionmentioning

confidence: 99%

Active and resting motor threshold are efficiently obtained with adaptive threshold hunting

et al. 2017

View full text Add to dashboard Cite

Transcranial magnetic studies typically rely on measures of active and resting motor threshold (i.e. AMT, RMT). Previous work has demonstrated that adaptive threshold hunting approaches are efficient for estimating RMT. To date, no study has compared motor threshold estimation approaches for measures of AMT, yet this measure is fundamental in transcranial magnetic stimulation (TMS) studies that probe intracortical circuits. The present study compared two methods for acquiring AMT and RMT: the Rossini-Rothwell (R-R) relative-frequency estimation method and an adaptive threshold-hunting method based on maximum-likelihood parameter estimation by sequential testing (ML-PEST). AMT and RMT were quantified via the R-R and ML-PEST methods in 15 healthy right-handed participants in an experimenter-blinded within-subject study design. AMT and RMT estimations obtained with both the R-R and ML-PEST approaches were not different, with strong intraclass correlation and good limits of agreement. However, ML-PEST required 17 and 15 fewer stimuli than the R-R method for the AMT and RMT estimation, respectively. ML-PEST is effective in reducing the number of TMS pulses required to estimate AMT and RMT without compromising the accuracy of these estimates. Using ML-PEST to estimate AMT and RMT increases the efficiency of the TMS experiment as it reduces the number of pulses to acquire these measures without compromising accuracy. The benefits of using the ML-PEST approach are amplified when multiple target muscles are tested within a session.

show abstract

“…have to be considered as well as situational determinants. Those include the hours of sleep, the time of the day, but also fast-fluctuating neurobiological factors (Bergmann and others 2009; Kamke and others 2014; Karabanov and others 2015). Figure 2 illustrates the factors that might increase variability to NIBS, relevant for stroke recovery.…”

Section: From Established Treatments To Emerging Solutions For Motor mentioning

confidence: 99%

Restoring Motor Functions After Stroke: Multiple Approaches and Opportunities

Raffin

Hummel

2017

Neuroscientist

Self Cite

View full text Add to dashboard Cite

More than 1.5 million people suffer a stroke in Europe per year and more than 70% of stroke survivors experience limited functional recovery of their upper limb, resulting in diminished quality of life. Therefore, interventions to address upper-limb impairment are a priority for stroke survivors and clinicians. While a significant body of evidence supports the use of conventional treatments, such as intensive motor training or constraint-induced movement therapy, the limited and heterogeneous improvements they allow are, for most patients, usually not sufficient to return to full autonomy. Various innovative neurorehabilitation strategies are emerging in order to enhance beneficial plasticity and improve motor recovery. Among them, robotic technologies, brain-computer interfaces, or noninvasive brain stimulation (NIBS) are showing encouraging results. These innovative interventions, such as NIBS, will only provide maximized effects, if the field moves away from the "one-fits all" approach toward a "patient-tailored" approach. After summarizing the most commonly used rehabilitation approaches, we will focus on NIBS and highlight the factors that limit its widespread use in clinical settings. Subsequently, we will propose potential biomarkers that might help to stratify stroke patients in order to identify the individualized optimal therapy. We will discuss future methodological developments, which could open new avenues for poststroke rehabilitation, toward more patient-tailored precision medicine approaches and pathophysiologically motivated strategies.

show abstract

The Resting Motor Threshold – Restless or Resting? A Repeated Threshold Hunting Technique to Track Dynamic Changes in Resting Motor Threshold

Cited by 15 publications

References 32 publications

Unravelling the modulation of intracortical inhibition during motor imagery: An adaptive threshold-hunting study

Unravelling the modulation of intracortical inhibition during motor imagery: An adaptive threshold-hunting study

Active and resting motor threshold are efficiently obtained with adaptive threshold hunting

Restoring Motor Functions After Stroke: Multiple Approaches and Opportunities

Contact Info

Product

Resources

About