Threshold Hunting Research Articles

Wrist proprioceptive acuity is linked to fine motor function in children undergoing piano training.

Playing the piano involves rapid and precise upper limb movements, which require seamless integration of the proprioceptive and motor systems. In this study, we comprehensively assessed active and passive proprioception and different domains of motor function in young pianists, aiming to understand how their proprioceptive and motor functions are improved. Fifty-seven participants, including seventeen 11- to 12-yr-old (young) pianists, 20 children, and 20 adults, were included. The children in the pianist group had received piano training for 6 yr, whereas the children and adults in the control groups had no previous experience with instrumental training. All participants performed a psychophysical discrimination threshold hunting task and an ipsilateral joint position reproduction task, both of which measured the position sense acuity of the wrist. Their motor function was evaluated by the Movement Assessment Battery for Children, 2nd edition. The results revealed that the young pianists showed a significantly lower position sense discrimination threshold (31%) and fewer joint position reproduction errors (49%) than the nontrained children. Second, a higher level of manual dexterity, but not of ball skills or balance, was found in the young pianist group. Third, a higher proprioceptive acuity (i.e., decreased position sense discrimination threshold) significantly correlated with higher manual dexterity. This study documents that a high wrist position sense is a common characteristic among young pianists. The increased upper limb position sense acuity is correlated with better manual dexterity, suggesting that piano practice may benefit untrained fine motor skills in children.NEW & NOTEWORTHY We document that improved proprioceptive acuity is a common feature in young pianists. This proprioceptive improvement is associated with both proprioceptive processing and proprioceptive-motor integration. Higher wrist proprioceptive acuity in young pianists is linked to enhanced manual dexterity, which suggests that intensive piano training may improve untrained fine motor skills.

Probing interhemispheric dorsal premotor-primary motor cortex interactions with threshold hunting transcranial magnetic stimulation

ObjectiveTo characterise the effect of altering transcranial magnetic stimulation parameters on the magnitude of interhemispheric inhibition (IHI) from dorsal premotor (PMd) to primary motor cortex (M1). MethodWe used a fully automated adaptive threshold hunting paradigm to quantify PMd-M1 IHI across a range of conditioning stimulus (CS) intensities (90%, 110%, 130% of resting motor threshold, rMT) and interstimulus intervals (ISIs) (8, 10, 40 ms). M1-M1 IHI was examined with CS intensities of 110%, 120%, and 130% rMT and ISIs of 10 and 40 ms. Two test coil orientations (inducing posterior-anterior or anterior-posterior current) were used. ResultsPMd-M1 IHI was obtained consistently with posterior-anterior (but not anterior-posterior) test stimuli and increased with CS intensity. M1-M1 IHI was expressed across all conditions and increased with CS intensity when posterior-anterior but not anterior-posterior induced current was used. ConclusionsThe expression of PMd-M1 IHI is contingent on test coil orientation (requiring posterior-anterior induced current) and increases as a function of CS intensity. The expression of M1-M1 IHI is not dependent on test coil orientation. SignificanceWe defined a range of parameters that elicit reliable PMd-M1 IHI. This (threshold hunting) methodology may provide a means to quantify premotor-motor pathology and reveal novel quantitative biomarkers.

Spatiotemporal Dynamics of a Diffusive Predator–Prey System with Allee Effect and Threshold Hunting

In this paper, we study a diffusive predator–prey system with the Allee effect and threshold hunting. First, the number of interior equilibrium points is determined by discussing the relation of parameters. Then, preliminary analysis on the local asymptotic stability and bifurcations of non-spatial system based on ordinary differential equations is presented. It is noted that four stable equilibrium points coexist due to the Allee effect and threshold hunting. The stability of interior equilibrium points and the existence of Turing instability induced by the diffusion, spatially homogeneous and inhomogeneous Hopf bifurcation, Turing–Hopf bifurcation are studied by analyzing the corresponding characteristic equation for spatial system. By constructing generalized Jacobian matrix, we analyze the stability of interior equilibrium point where u-component is equal to the threshold of functional response. These results show that the Allee effect, threshold hunting and diffusion have significant impacts on the dynamics. Last, we present some numerical simulations that supplement the analytic results.

Mobile Application for Adaptive Threshold Hunting in Transcranial Magnetic Stimulation.

Application of transcranial magnetic stimulation (TMS) is expanding with many studies applying adaptive threshold hunting to determine a motor threshold (MT). In addition to being a measure of corticospinal excitability, the MT is used as a baseline stimulation intensity (SI) to which following investigative or modulatory SIs are referenced to. Currently available tools for determining MTs include system-integrated tools and third-party stand-alone software. System-integrated MT-tools are still rarely available and the stand-alone software usually demand a separate computer, and hence possess additional space-requirements. I introduce and validate a free Android-based mobile application ("ATH-tool") for adaptive threshold hunting of the MT. The objective is to allow for a simple and validated recording of MTs with sharing capabilities for logs. For comparison, I applied Motor Threshold Assessment Tool 2.0, to compare the MT-values determined with the new application, as it applies closely the same routine. Computational validation with known true threshold values confirmed that the new application captured the true MT at high precision (error ≤ 0.9%). Previously published data on motor evoked potentials (MEPs) were used to simulate realistic response occurrence by considering experimental data from 15 healthy subjects at different stimulation intensities. The MTs of the different methods agreed well (ICC ≥ 0.971, ). There was no significant difference between the MTs determined with the different methods ( p ≥ 0.151 ). The novel mobile application should make it easier for researchers and clinicians to determine MTs and log the results.

P42-F New mobile application for adaptive threshold hunting in transcranial magnetic stimulation

Background Use of transcranial magnetic stimulation (TMS) in clinical neurophysiology has expanded as navigated TMS and repetitive TMS therapies have gained popularity. Clinical applications and scientific studies often apply adaptive threshold hunting (ATH) to determine motor threshold (MT). MT expresses corticospinal excitability, and it is used as a baseline stimulation intensity (SI) for modulatory, therapeutic and mapping procedures. Currently available tools for ATH are system-integrated tools and stand-alone software. System-integrated tools are rare, and the available stand-alone software require a dedicated computer adding to laboratory space-requirements. Material and methods I programmed an Android-based “bestPEST” mobile application for ATH to allow for a simple recording of MTs with sharing capabilities and logging. The application applies parameter estimation by sequential testing and was named after Pentlands BestPEST-routine ( Pentland , 1980 ). The application is free through Google Play. For comparison I applied Motor Threshold Assessment Tool 2.0 ( Awiszus and Borckardt, 2012 ) as a reference method. I used data gathered from 15 healthy volunteers to simulate realistic motor evoked potentials (MEPs) utilizing random generator which considered the experimentally measured individual mean MEP amplitude and variation at different SIs ( Kallioniemi et al., 2018 ). Results The MTs of the different methods agreed well (ICC ⩾ 0.989, p Conclusions The bestPEST application produced similar MTs with the reference method, and will help investigators to determine MTs and to log results.

Adaptive threshold hunting reveals differences in interhemispheric inhibition between young and older adults.

Interhemispheric inhibition between bilateral motor cortices is important for the performance of unimanual activities and may be compromised with advancing age. Conventionally, interhemispheric inhibition is assessed using paired-pulse transcranial magnetic stimulation (TMS) with constant conditioning and test stimulation parameters. Adaptive threshold hunting TMS, whereby a target motor-evoked potential amplitude is maintained in the presence of the conditioning, may provide an alternative means of assessment. Furthermore, interhemispheric inhibition may suppress late indirect-waves more so than early indirect-waves which can be preferentially elicited using anterior-posterior (AP) and posterior-anterior (PA) induced currents, respectively. The aim of this study was to assess age-related effects on interhemispheric inhibition using both conventional and threshold hunting techniques with PA- and AP-induced current. In 15 young and 15 older adults, short (10ms) and long (40ms) interval interhemispheric inhibition was examined in the nondominant extensor carpi radialis muscle at rest and during voluntary extension of the contralateral wrist. With the conventional technique, there were no age-related differences in short-interval interhemispheric inhibition. With threshold hunting and AP-induced current, young adults exhibited greater short-interval interhemispheric inhibition during contralateral activation compared with rest and compared with older adults. Furthermore, long-interval interhemispheric inhibition was greater in older adults compared with young for both conventional and threshold hunting techniques. Age-related differences in interhemispheric inhibition are evident with threshold hunting using PA- and AP-induced current.

Adaptive threshold hunting for the effects of transcranial direct current stimulation on primary motor cortex inhibition.

Primary motor cortex excitability can be modulated by anodal and cathodal transcranial direct current stimulation (tDCS). These neuromodulatory effects may, in part, be dependent on modulation within gamma-aminobutyric acid (GABA)-mediated inhibitory networks. GABAergic function can be quantified non-invasively using adaptive threshold hunting paired-pulse transcranial magnetic stimulation (TMS). The previous studies have used TMS with posterior-anterior (PA) induced current to assess tDCS effects on inhibition. However, TMS with anterior-posterior (AP) induced current in the brain provides a more robust measure of GABA-mediated inhibition. The aim of the present study was to assess the modulation of corticomotor excitability and inhibition after anodal and cathodal tDCS using TMS with PA- and AP-induced current. In 16 young adults (26 ± 1years), we investigated the response to anodal, cathodal, and sham tDCS in a repeated-measures double-blinded crossover design. Adaptive threshold hunting paired-pulse TMS with PA- and AP-induced current was used to examine separate interneuronal populations within M1 and their influence on corticomotor excitability and short- and long-interval inhibition (SICI and LICI) for up to 60min after tDCS. Unexpectedly, cathodal tDCS increased corticomotor excitability assessed with AP (P = 0.047) but not PA stimulation (P = 0.74). SICIAP was reduced after anodal tDCS compared with sham (P = 0.040). Pearson's correlations indicated that SICIAP and LICIAP modulation was associated with corticomotor excitability after anodal (P = 0.027) and cathodal tDCS (P = 0.042). The after-effects of tDCS on corticomotor excitability may depend on the direction of the TMS-induced current used to make assessments, and on modulation within GABA-mediated inhibitory circuits.

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

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.

P101 Impact of coil rotation on TMS threshold

Introduction Conflicting results have been reported on the importance of optimal TMS coil rotation. Maintaining a constant coil rotation angle manually remains a challenge. However, the exact impact of rotation angle on resting motor thresholds (RMTs) has not been investigated to date. Objective Using a robot-guided and a fully automated threshold hunting procedure, we aimed at determining the relevance of optimal rotation for determining RMT. Methods FDI hotspot was located with the automated hotspot hunting procedure ( n = 7). RMTs were then determined applying the threshold-hunting algorithm at different rotation angles (360° in steps of 15°, 15 pulses per rotation angle) in a randomized order over all pulses. The coil handle in posterior position was set as 0°. The procedure was repeated with steps of 5° within a 60° range of lowest thresholds of the first session. Threshold values were normalized for individual min and max. Results With 15° steps mean threshold was lowest at angles of 30° and 45°. Using 5° steps revealed a minimum mean threshold at 40° (mean threshold: 29.0; SEM: 0.05). A second minimum was found at the opposite angle. Highest RMTs were observed at angles between 135° and 180° and 285° and 315°. The relation between the rotation angle and deviation of the measured RMTs (from the minimum RMT at the optimal rotation angle) was non-linear with a floor effect between 5° and 15°. Conclusion Optimal coil rotation angle for FDI was found at 40°. Interestingly, within a range between 25° and 55° the effect of different coil rotation angles on the RMTs was not relevant, i.e. lower than the error of the threshold hunting procedure. The results therefore suggest that manual coil positioning at a rotation angle of 40° with little positional errors is uncritical when assessing motor thresholds of the FDI.

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

The resting motor threshold (RMT) is used to individually adjust the intensity of transcranial magnetic stimulation (TMS) intensity and is assumed to be stable. Here we challenge this notion by showing that RMT expresses acute context-dependent fluctuations. In twelve participants, the RMT of the right first dorsal interosseus muscle was repeatedly determined using a threshold-hunting procedure while participants performed motor imagery and visual attention tasks with the right or left hand. Data were analyzed using repeated-measure ANOVA. RMT differed depending on which hand performed the task (P=0.003). RMT of right FDI was lower during motor imagery than during visual attention of the right hand (P=0.002), but did not differ between left-hand tasks (P=0.988). State-dependent changes of RMT occur in absence of overt motor activity and can be captured online by threshold hunting. These fluctuations need to be considered when RMT is used to individually adjust TMS intensity for plasticity-inducing protocols.

Increased Cortical Excitability with Prefrontal High-Frequency Repetitive Transcranial Magnetic Stimulation in Adolescents with Treatment-Resistant Major Depressive Disorder

To examine changes in motor cortical excitability in adolescent subjects receiving 30 sessions of high-frequency prefrontal repetitive transcranial magnetic stimulation (rTMS). Eight adolescents with treatment-resistant major depressive disorder (MDD) enrolled in an open augmentation trial of 10 Hz rTMS. Resting motor thresholds were obtained by the visualization of movement method with a maximum likelihood threshold hunting computer algorithm at baseline and after every five sessions of rTMS. Motor threshold was recorded as the percentage of total machine output at each measurement. Motor threshold data from baseline, weeks 2, 4, and 5 were included in a mixed model repeated measure analysis to examine a change in least square mean effect over time. The omnibus effect did not reach statistical significance (F=1.25, p=0.32). However, multiple comparisons from the overall model demonstrated a decrease in the least square mean motor threshold. The mean contrast from baseline to week 5 approached significance (p=0.07). Moreover, a post-hoc analysis with a Wilcoxon signed ranks test demonstrated a significant decrease at week 5 (p=0.03). This suggests that high-frequency rTMS may increase cortical excitability in adolescents with treatment-resistant MDD.

Including prior knowledge for accurate and fast motor threshold estimation

Accurately estimating motor threshold (MT) is important in transcranial magnetic stimulation (TMS), because the MT is used as a reference to adjust individual subject’s machine output intensity. 1 Hallett M. Transcranial magnetic stimulation: a primer. Neuron. 2007; 55: 187-199 Abstract Full Text Full Text PDF PubMed Scopus (1072) Google Scholar MT is defined as the minimum TMS output intensity that can induce reliable motor evoked potentionals (MEPs) (usually > 100 μV), with a probability of 50%. The Parameter Estimation in Sequential Test (PEST) method, which is based on maximum likelihood regression, has previously been proposed to speed up MT estimation. 2 Awiszus F. TMS and threshold hunting. Suppl Clin Neurophysiol. 2003; 56: 13-23 Crossref PubMed Scopus (263) Google Scholar We recently proposed a new Bayesian PEST method that modifies the previous PEST method in two ways. 3 Qi F, Wu AD, Schweighofer N. Fast estimation of transcranial magnetic stimulation motor threshold. Brain Stimulation. [Epub ahead of print]. Google Scholar First, we used prior knowledge, in the form of a probabilistic model, to facilitate MT estimation. Second, we used the probability interval of the estimated MT distribution to control the estimation error. Specifically, the width of 95% of the area under the curve of MTs probability density function was taken as a measure of the estimation precision. We experimentally tested the accuracy, and hence safety, of our Bayesian method in 10 healthy subjects. 3 Qi F, Wu AD, Schweighofer N. Fast estimation of transcranial magnetic stimulation motor threshold. Brain Stimulation. [Epub ahead of print]. Google Scholar

Threshold curves for transcranial magnetic stimulation to improve reliability of motor pathway status assessment

Objective To provide a new protocol for a simple determination of resting motor threshold (MT) and assessment of excitation-inhibition balance in motor cortex and pathways. Methods Navigated TMS was used to map cortical representation area of the FDI muscle bilaterally in ten healthy subjects. Reference MTs were determined using a threshold hunting paradigm. Subsequently, a novel stimulation protocol was applied which included 70 stimuli (7 intensities, sub- and suprathreshold). The “MT-curve” was constructed by computing the MTs with several threshold amplitudes with the novel protocol. The measurements were repeated. Sensitivity of the MT-curve to stimulus location was also tested. Results The reference MTs agreed with those determined with the novel protocol ( R = 0.96–0.99, p < 0.001). Based on coefficient of repeatability derived from non-parametric one-way ANOVA, the repeatability was good ( ρ AO = 0.929, p < 0.05). Generally, the mean difference between the repeated MT-curves was <3% of the maximum stimulator output. Coil movement 10 mm medially from the optimal stimulus location increased that difference to >7%. Conclusions The MTs derived using the MT-curve protocol concurred with the reference MTs. The MT-curve is highly reproducible and sensitive to the exact cortical location of stimulation. Significance The MT-curves provide a simple way to assess motor pathway status using a single stimulation train. This may be useful in the follow-up and monitoring of motor pathway recovery e.g. from stroke or trauma.

Characterization of human joint proprioception by means of a threshold hunting paradigm

A method has been developed to measure the proprioceptive performance of movement detection in human joints, with the threshold hunting paradigm commonly used in other sensory modalities. Methods applied in former studies regarding movement detection were very time consuming (hours), making them not applicable to patients. Using the threshold hunting paradigm, the subject changes the parameter value continuously around the threshold producing a threshold hunting curve, which itself might be valuable for investigation of movement detection performance. The method presented here, is very quick compared to other studies in this field, especially when velocity is hunted and the threshold values are very low. The threshold parameter value is stable since there is a control at any time over the subject's stimulus perception. Furthermore, a Monte Carlo simulation showed that hunting curves can clearly be distinguished from guessing. Also reliability is given. All these points allow to use the method to evaluate the proprioceptive performance of a single individual. Considering the results, the method described may be useful for basic and clinical investigations regarding the proprioceptive performance limits of movement detection aspects.