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JoVE Journal Neuroscience

Neuroscience

Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning

Published: April 21, 2023 doi: 10.3791/65212
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*1, *1, 1
1Department of Kinesiology and Health Sciences, University of Waterloo
* These authors contributed equally

Summary

Short-latency afferent inhibition (SAI) is a transcranial magnetic stimulation protocol to probe sensorimotor integration. This article describes how SAI can be used to study the convergent sensorimotor loops in the motor cortex during sensorimotor behavior.

Abstract

Skilled motor ability depends on efficiently integrating sensory afference into the appropriate motor commands. Afferent inhibition provides a valuable tool to probe the procedural and declarative influence over sensorimotor integration during skilled motor actions. This manuscript describes the methodology and contributions of short-latency afferent inhibition (SAI) for understanding sensorimotor integration. SAI quantifies the effect of a convergent afferent volley on the corticospinal motor output evoked by transcranial magnetic stimulation (TMS). The afferent volley is triggered by the electrical stimulation of a peripheral nerve. The TMS stimulus is delivered to a location over the primary motor cortex that elicits a reliable motor-evoked response in a muscle served by that afferent nerve. The extent of inhibition in the motor-evoked response reflects the magnitude of the afferent volley converging on the motor cortex and involves central GABAergic and cholinergic contributions. The cholinergic involvement in SAI makes SAI a possible marker of declarative-procedural interactions in sensorimotor performance and learning. More recently, studies have begun manipulating the TMS current direction in SAI to tease apart the functional significance of distinct sensorimotor circuits in the primary motor cortex for skilled motor actions. The ability to control additional pulse parameters (e.g., the pulse width) with state-of-the-art controllable pulse parameter TMS (cTMS) has enhanced the selectivity of the sensorimotor circuits probed by the TMS stimulus and provided an opportunity to create more refined models of sensorimotor control and learning. Therefore, the current manuscript focuses on SAI assessment using cTMS. However, the principles outlined here also apply to SAI assessed using conventional fixed pulse width TMS stimulators and other forms of afferent inhibition, such as long-latency afferent inhibition (LAI).

Introduction

Multiple sensorimotor loops converge in the motor cortex to shape pyramidal tract projections to spinal motor neurons and interneurons1. However, how these sensorimotor loops interact to shape corticospinal projections and motor behavior remains an open question. Short-latency afferent inhibition (SAI) provides a tool to probe the functional properties of convergent sensorimotor loops in motor cortex output. SAI combines motor cortical transcranial magnetic stimulation (TMS) with electrical stimulation of the corresponding peripheral afferent nerve.

TMS is a non-invasive method to safely stimulate pyramidal motor neurons trans-synaptically in the human brain2,3. TMS involves passing a large, transient electric current through a coiled wire placed on the scalp. The transient nature of the electrical current creates a rapidly changing magnetic field that induces an electric current in the brain4. In the case of a single TMS stimulus, the induced current activates a series of excitatory inputs to the pyramidal motor neurons5-7. If the strength of the generated excitatory inputs is sufficient, the descending activity elicits a contralateral muscular response known as the motor-evoked potential (MEP). The latency of the MEP reflects the corticomotor conduction time8. The amplitude of the MEP indexes the excitability of the corticospinal neurons9. The single TMS stimulus that elicits the MEP can also be preceded by a conditioning stimulus10,11,12. These paired-pulse paradigms can be used to index the effects of various interneuron pools on the corticospinal output. In the case of SAI, the peripheral electrical conditioning stimulus is used to probe the impact of the afferent volley on the motor cortical excitability11,13,14,15. The relative timing of the TMS stimulus and peripheral electrical stimulation aligns the action of the TMS stimulus on the motor cortex with the arrival of the afferent projections to the motor cortex. For SAI in the distal upper limb muscles, the median nerve stimulus typically precedes the TMS stimulus by 18-24 ms11,13,15,16. At the same time, SAI increases as the strength of the afferent volley induced by the peripheral stimulus increases13,17,18.

Despite its strong association with the extrinsic properties of the afferent projection to the motor cortex, SAI is a malleable phenomenon implicated in many motor control processes. For example, SAI is reduced in task-relevant muscles before an impending movement19,20,21 but is maintained in adjacent task-irrelevant motor representations19,20,22. The sensitivity to task relevancy is hypothesized to reflect a surround inhibition mechanism23 that aims to reduce unwanted effector recruitment. More recently, it was proposed that the reduction in SAI in the task-relevant effector may reflect a movement-related gating phenomenon designed to suppress expected sensory afference21 and facilitate corrections during sensorimotor planning and execution24. Regardless of the specific functional role, SAI is correlated with reductions in manual dexterity and processing efficiency25. Altered SAI is also associated with an increased risk of falling in older adults26 and compromised sensorimotor function in Parkinson's disease26,27,28 and individuals with focal hand dystonia29.

Clinical and pharmacological evidence indicates that the inhibitory pathways mediating SAI are sensitive to central cholinergic modulation30. For example, administering the muscarinic acetylcholine receptor antagonist scopolamine reduces SAI31. In contrast, increasing the half-life of acetylcholine via acetylcholinesterase inhibitors enhances SAI32,33. Consistent with pharmacological evidence, SAI is sensitive to several cognitive processes with central cholinergic involvement, including arousal34, reward35, the allocation of attention21,36,37, and memory38,39,40. SAI is also altered in clinical populations with cognitive deficits associated with the loss of cholinergic neurons, such as Alzheimer's disease41,42,43,44,45,46,47, Parkinson's disease (with mild cognitive impairment)48,49,50, and mild cognitive impairment47,51,52. The differential modulation of SAI by various benzodiazepines with differential affinities for various γ-aminobutyric acid type A (GABAA) receptor subunit types suggests that the SAI inhibitory pathways are distinct from pathways mediating other forms of paired-pulse inhibition30. For example, lorazepam decreases SAI but enhances short-interval cortical inhibition (SICI)53. Zolpidem reduces SAI but has little effect on SICI53. Diazepam increases SICI but has little impact on SAI53. The reduction in SAI by these positive allosteric modulators of GABAA receptor function, coupled with the observation that GABA controls the release of acetylcholine in the brain stem and cortex54, has led to the hypothesis that GABA modulates the cholinergic pathway that projects to the sensorimotor cortex to influence SAI55.

Recently, SAI has been used to investigate interactions between the sensorimotor loops that set procedural motor control processes and those that align procedural processes to explicit top-down goals and cognitive control processes21,36,37,38. The central cholinergic involvement in SAI31 suggests that SAI may index an executive influence over procedural sensorimotor control and learning. Importantly, these studies have begun to identify the unique effects of cognition on specific sensorimotor circuits by assessing SAI using different TMS current directions. SAI studies typically employ posterior-anterior (PA) induced current, while only a handful of SAI studies have employed anterior-posterior (AP) induced current55. However, using TMS to induce AP compared with PA current during SAI assessment recruits distinct sensorimotor circuits16,56. For example, AP-sensitive, but not PA-sensitive, sensorimotor circuits are altered by cerebellar modulation37,56. Furthermore, AP-sensitive, but not PA-sensitive, sensorimotor circuits are modulated by attention load36. Finally, attention and cerebellar influences may converge on the same AP-sensitive sensorimotor circuits, leading to maladaptive alterations in these circuits37.

Advances in TMS technology provide additional flexibility to manipulate the configuration of the TMS stimulus employed during single-pulse, paired-pulse, and repetitive applications57,58. Controllable pulse parameter TMS (cTMS) stimulators are now commercially available for research use worldwide, and these provide flexible control over the pulse width and shape57. The increased flexibility arises from controlling the discharge duration of two independent capacitors, each responsible for a separate phase of the TMS stimulus. The biphasic or monophasic nature of the stimulus is governed by the relative discharge amplitude from each capacitor, a parameter called the M-ratio. cTMS studies have combined pulse width manipulation with different current directions to demonstrate that the fixed pulse widths used by conventional TMS stimulators (70-82 µs)59,60 likely recruit a mix of functionally distinct sensorimotor circuits during SAI56. Therefore, cTMS is an exciting tool to disentangle further the functional significance of various convergent sensorimotor loops in sensorimotor performance and learning.

This manuscript details a unique SAI approach to studying sensorimotor integration that integrates peripheral electrical stimulation with cTMS during sensorimotor behaviors. This approach improves on the typical SAI approach by assessing the effect of afferent projections on select interneuron populations in the motor cortex that govern the corticospinal output during ongoing sensorimotor behavior. Although relatively new, cTMS provides a distinct advantage in studying sensorimotor integration in typical and clinical populations. Furthermore, the current approach can be easily adapted for use with conventional TMS stimulators and to quantify other forms of afferent inhibition and facilitation, such as long-latency afferent inhibition (LAI)13 or short-latency afferent facilitation (SAF)15.

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Protocol

The following protocol can be applied to various experiments. The information provided details an experiment in which SAI is used to quantify sensorimotor integration during a finger response to a validly or invalidly cued probe. In this protocol, SAI is assessed without a task, then concurrently during the cued sensorimotor task, and then again without a task. The cTMS stimulator can be replaced by any commercially available conventional TMS stimulator. However, the pulse width of the conventional TMS stimulator would be fixed between 70-82 µs depending on the specific hardware59,60. This study was approved by the University of Waterloo's Office of Research Ethics. All participants provided written informed consent.

1. Hardware/software requirements

NOTE: Figure 1 displays a schematic of the hardware requirements to integrate the peripheral electrical and TMS stimulators with a computer-controlled sensorimotor task. Figure 2A depicts the setup for SAI for PA-induced and AP-induced current. Figure 2B illustrates the sequence of events for the cued sensorimotor task and the relative timing of the SAI assessment. A stereotactic guidance system to track the TMS coil orientation relative to the participant is strongly recommended to reduce trial-by-trial variability in the physiological response associated with variation in coil position and trajectory61.

Figure 1
Figure 1: A schematic of the hardware used to assess SAI at rest and during concurrent sensorimotor behavior. PC1, which is used to control the sensorimotor task and the timing of the cTMS stimulus/peripheral electrical stimulation, is connected to a digital-to-analog converter capable of generating a 5 V TTL output trigger via a USB cable. For unconditioned trials, the trigger from digital input-output channel 1 is sent to the cTMS stimulator via a BNC cable. For conditioned trials, the trigger from digital input-output channel 1, which is sent to the cTMS stimulator, is preceded by a trigger from digital input-output channel 2 to the peripheral electrical stimulator. A BNC cable from the trigger out channel on the cTMS unit is sent to the EMG system analog-to-digital board to trigger the EMG amplifier recording and the display/saving of the data by the EMG acquisition software on PC2. An optional BNC cable from the cTMS trigger out is also sent to the stereotactic guidance system to record the coil position and trajectory at the time of the cTMS stimulus. Abbreviations: PC = personal computer; USB = universal serial bus; TTL = transistor-transistor logic trigger cable; BNC = Bayonet Neill-Concelman connector; cTMS = controllable pulse parameter transcranial magnetic stimulator; TMS = transcranial magnetic stimulation; A/D = analog-digital; EMG = electromyography. Please click here to view a larger version of this figure.

Figure 2
Figure 2: SAI setup and the sensorimotor task. (A) A schematic of the setup for the assessment of SAI in the FDI muscle. Of note, the induced current in the brain is opposite to the direction of the current in the TMS coil. (B) A depiction of a valid index finger cue (top) and invalid index finger cue (bottom) trial. The cue is always depicted as the top stimulus (highlighted by the dashed circle). The cue color corresponds to a specific finger response. The participants were instructed to respond to the probe color as fast and accurately as possible. Cues and probes could be any color. The probability of a valid cue was 70%. Invalid cues occurred in 30% of trials. Abbreviations: SAI = short-latency afferent inhibition; PA = posterior-anterior; AP = anterior-posterior; FDI = first dorsal interosseous; EMG = electromyography; MNS = median nerve stimulus. Please click here to view a larger version of this figure.

  1. Equip one personal computer (PC1) with software to control the sensorimotor task via a USB (or serial port) digital-analog board with two digital output channels.
  2. Set up a no-task software routine to control the order of the unconditioned cTMS stimuli and cTMS stimuli that will be conditioned by peripheral electrical stimulation with an interstimulus interval (ISI) of 21 ms. Randomize the interval between any two stimuli (e.g., conditioned or unconditioned) using a rectangular distribution with a duration between 5-8 s.
    1. Ensure that the routine sends one digital output trigger to the trigger in the port of the cTMS unit for the unconditioned stimuli. Ensure that the routine sends separate digital outputs to the cTMS unit and the peripheral electrical stimulator for the conditioned stimuli.
    2. Ensure the trigger to the peripheral stimulator precedes the cTMS trigger by 21 ms. Ensure the number of unconditioned and conditioned stimuli is between 8 and 24. Ideally, the order of the unconditioned and conditioned trials should be randomized.
  3. Set up a software routine to control the sensorimotor task. Ensure this software also time-locks the digital output triggers sent to the cTMS and peripheral electrical stimulators to a specific point(s) during the behavior.
    NOTE: The outlined experiment used a cued sensorimotor task (Figure 2B). The triggers to the peripheral stimulator and cTMS stimulator were timed to occur 225-275 ms after the response cue onset using a rectangular distribution. The purpose of this timing was to assess changes in sensorimotor integration based on the validity between the response cue and the prior preparation cue, which was valid in 70% of all trials.
  4. Equip a second personal computer (PC2) with a two-channel electromyography (EMG) amplifier connected to an analog-digital converter. Ensure that the digital-analog converter has a digital input channel to time-lock the EMG to the TMS stimulus. Ensure PC2 is equipped with EMG data acquisition software to record the TMS-evoked muscle responses.
    NOTE: PC1 can be used to control the sensorimotor task and record the EMG. However, researchers should independently verify the timing of the triggers to the TMS stimulator, peripheral stimulator, and EMG system. Multiple devices connected to a single PC increase the potential for central processor conflicts, leading to instability in the relative timing of the event markers.
  5. Set up the EMG data acquisition software with the following settings: three recording channels, 2 EMG, one input trigger, triggered recordings with an epoch of −0.3 s to 0.5 s around the TTL trigger, an EMG amplification factor of 1,000x, a sampling rate of 4,000 Hz, a bandpass filter of 3 Hz to 1 kHz, and a mains filter (optional).
    ​NOTE: The current protocol uses an epoched recording method. The EMG acquisition software continuously monitors the EMG signal. However, only epoched data time-locked to the TMS stimulus are displayed and recorded.
  6. Connect one digital output channel from PC1 to the trigger input on the cTMS stimulator. Connect the second digital output channel from PC1 to the trigger input on the peripheral electrical stimulator. When using the PC's operating system, independently confirm the relative timing of the two digital outputs from PC1.
  7. Connect the trigger output to the digital input of the EMG system. If using a stereotactic guidance system, it may be possible to split the trigger output to the guidance system to record the trial by trial position of the cTMS coil at the time of the cTMS stimulus.

2. Participant screening and informed consent

  1. Screen the participant for contraindications to TMS9,62,63,64,65.
  2. Inform the participant about the study objectives and procedures. Review the risks outlined in the institution's ethics review board-approved consent document. Answer any questions about the potential risks. Obtain written informed consent before beginning any study procedures.

3. Electromyography (EMG) electrode placement

  1. Instruct the participant to sit in the experimental chair with their elbows resting on the arms of the chair and bent to allow the wrist/hand to rest comfortably on the desk workspace. Adjust the height of the chair and desk workspace as needed.
  2. Clean the skin over the first dorsal interosseous (FDI), abductor pollicis brevis (APB), and the ulnar styloid process using a mildly abrasive cream placed on a round cotton pad. Wipe any residue away using an alcohol prep pad.
  3. For each muscle, place one disposable Ag-AgCl adhesive electrode over the muscle belly. Place a second electrode on a nearby bony landmark as a reference. Finally, place one additional Ag-AgCl adhesive electrode on the ulnar styloid process to serve as a ground.
    NOTE: A common FDI reference site is the bony prominence at the base of the second proximal phalanx on the radial side of the hand. A common APB reference site is the proximal phalanx's bony prominence on the thumb's radial side.
  4. Connect each pair of electrodes and the ground to the EMG amplifier and data acquisition system. Use channel 1 for the FDI and channel 2 for the APB.

4. Peripheral electrical stimulator electrode placement

  1. Connect the digital output trigger of the peripheral stimulator to the trigger input channel on the EMG system to trigger EMG recording when the peripheral stimulus is delivered.
  2. Use a mildly abrasive cream to clean the skin on the inside of the forearm. Start from the wrist flexion crease and extend to ~6 cm proximal. Extend cleaning to the area starting from the wrist midline to the radial side of the forearm. Wipe away any residue using an alcohol prep pad.
  3. Apply conducting gel to a reusable stimulating bar electrode. Use just enough gel to cover the metal disks of the anodal and cathodal contact points. Place the stimulating electrode over the skin on the palmar side of the wrist with the cathode proximal to the anode. Place the cathode slightly medial and proximal to the radial styloid process.
    1. Do not use excessive gel. If the gel creates a bridge between the anode and cathode terminals, clean the electrode to remove all the gel, and reapply. A gel bridge between the anode and cathode will divert substantial currents along the skin, making it difficult to stimulate the median nerve.
  4. On the peripheral stimulator, set the stimulus type selector to monophasic, set the stimulus duration to 200 µs, and select an appropriate voltage and amperage, double-checking any multiplication factors. The voltage (Vmax) was set to 200 V for the hardware used here, with an initial amperage of 0.05 x 10 mA.
  5. While holding the stimulating electrode, deliver a single electrical stimulus by depressing the trigger switch on the constant current stimulator. Then, visually inspect the APB muscle and the EMG display (channel 2) for evidence of a muscle contraction. The muscle contraction, known as the M-wave, is elicited by direct activation of the motor axon by the electrical stimulus and should occur between 6-9 ms after the peripheral electrical stimulus artifact.
  6. If there is no evidence of a muscle contraction, then ask the participant if they felt a tingling sensation radiating toward the fingers or immediately underneath the electrode. The optimal position will be the electrode position that elicits the most significant APB muscle contraction at the current stimulus intensity.
    1. If no sensation is reported or the sensation is restricted to the skin immediately below the electrode, then increase the amperage in increments of 0.05 (multiplied by a factor of 10) until the participant reports a tingling sensation radiating up to the fingers/thumb. If a radiating sensation is reported in a digit other than the thumb, reposition the electrode by moving the electrode radially until the feeling radiates to the thumb.
  7. Once the optimal position of the stimulating electrode has been determined, secure the electrode to the wrist using three pieces of tape. Position the first piece over the middle of the electrode, and then use the second and third pieces to secure the top and bottom of the electrode.
    NOTE: Based on experience, it is suggested to first secure the band of tape to the back of the electrode and then run the tape down the side of the electrode to the skin. This approach seems to secure the electrode and minimizes the potential for lateral movement during the experiment.
  8. After securing the electrode, ask the participant to assume the desired limb orientation to be used during TMS stimulation. Check to make sure a thumb twitch is still elicited.

5. Determination of the median nerve stimulus intensity

  1. Determine the peripheral stimulus threshold by adjusting the amperage of the peripheral stimulus intensity until an M-wave of 0.2 mV is elicited37,56. If the M-wave exceeds the desired 0.2 mV target amplitude on three successive stimuli, then decrease the amperage. If the M-wave is below the desired 0.2 mV target amplitude on three subsequent stimuli, increase the amperage. The threshold is the first amperage value where the M-wave exceeds 0.2 mV.
    NOTE: A common alternative is to set the intensity to either 3x the perceptual sensory threshold or 1x the motor threshold11,16,17,66,67,68. The sensory threshold is the stimulus intensity at which participants correctly report a sensation on 5 of 10 electrical stimuli. The motor threshold is the stimulus intensity at which a visible twitch is elicited on 5 of 10 stimuli.

6. Determination of the optimal coil trajectory for transcranial magnetic stimulation

  1. Use a template magnetic resonance image (MRI) file to create a new stereotactic guidance system project file to monitor the participant's position and coil orientation. Then, connect the digital output trigger from the TMS stimulator to the trigger input channel on the EMG system to trigger the EMG recording when the TMS stimulus is delivered.
    NOTE: When available, a subject-specific MRI may be used. However, the MEP is sufficient to determine the optimal coil position for motor cortex stimulation studies.
  2. Affix the guidance system's coil tracking tool to the PA TMS coil. Use the coil calibration tool to calibrate the orientation of the coil tracking tool to the midpoint of the TMS coil. Repeat this step using a second coil tracking tool for an AP coil with identical geometry to the PA coil.
  3. Affix the guidance system's subject-tracking tool to the forehead of the participant using two EMG electrodes. Use a fine-tip dry-erase marker or eye-liner applicator to place markings on the middle of the nose tip, the nasion, and the left and right preauricular pits. Use the guidance system's subject calibration tool to touch and record the position of each marker.
  4. Set an initial coil position by placing the coil on the participant's head and recording the coil trajectory. Ensure the center surface of the coil is tangential to the scalp. Align the midline of the coil at 45° to the mid-sagittal plane of the participant's head.
    1. To obtain a starting approximation of the motor cortex hotspot, imagine a tangential line connecting a point 5 cm anterior to the vertex and 5 cm lateral to the vertex, and place a 70 mm coil at approximately 2 cm from the anterior point along the tangential line.
      NOTE: An alternate approach to approximate the cortical motor hotspot for the distal muscles of the contralateral hand is for the experimenter to place their left index finger (if stimulating over the participant's left motor cortex) on the head vertex and the thumb of the left hand on the preauricular point of the left ear. The position of the index finger metacarpophalangeal joint can be used to visualize an approximate position at which to place the coil center.
  5. On the cTMS stimulator, set the pulse type selector to Monophasic-Positive to induce a PA current in the underlying neural tissue. Next, set the M-ratio to 0.2 and the stimulus intensity (also known as the power) to 30% of the maximal stimulator output. Finally, set the pulse width (also known as the positive phase duration) to 120 µs (the longest pulse width used in the study).
    NOTE: The coil position and trajectory determined using the PA-induced current will be employed for the AP-induced current16,36,37,38,56,69.
  6. Deliver three to five TMS stimuli while the participant maintains a slight contraction of the FDI muscle (~5%-10% of maximum voluntary contraction). If no motor-evoked potential (MEP) is elicited, increase the stimulator intensity by 10%, and deliver three to five additional TMS stimuli.
  7. Repeat the previous step until an MEP of at least 0.2 mV is consistently elicited to every stimulus, or until the stimulator intensity reaches 60%-70% of the maximal stimulator output. If no reliable MEP is elicited, keep the stimulation parameters constant, and move the TMS stimulator in a circle with ~2 cm diameter around the original stimulation site. Increase the circle's diameter by 1 cm if a reliable MEP is still not elicited at any point in the original circle.
  8. Once a reliable MEP is elicited, confirm the FDI motor hotspot by keeping the stimulation parameters constant and moving the TMS stimulator 2 cm north, east, south, and west of the current coil location. Deliver three to five TMS stimuli at each location70. Record the new coil position and trajectory if a consistently larger MEP is elicited at any of the four quadrants. Use the new coil position and trajectory as the cortical motor hotspot.

7. Determination of the stimulus intensity for transcranial magnetic stimulation

  1. Launch the freely available TMS motor threshold assessment tool (MTAT 2.1)71,72,73 to determine the stimulus intensity required to elicit an MEP of 1 mV (1 mV threshold)16,67,74. Set the estimation method to Without a priori information, and click on Start.
    NOTE: The current protocol uses a TMS intensity of 1 mV16. However, some studies prefer to set the intensity as 120% of the individual's resting motor threshold. For AP current, a 1 mV MEP may not be obtainable. In such cases, determine the stimulator output that elicits the maximal MEP elicited by the AP stimulus configuration, provided the maximum MEP is at least 0.5 mV.
  2. Determine the maximum stimulator output available for the pulse width of 120 µs. Then, use a conversion chart to rescale the range of the stimulator output from 0 to 100 so that the stimulator output matches the scale of the MTAT 2.1 software.
    NOTE: For the model used in the current study, the maximal stimulator output for a pulse width of 120 µs is 50%. Therefore, the values provided by the MTAT 2.1 software are divided by 2 to determine the value set on the stimulator. For a pulse width of 70 µs, the maximal stimulator output is 66%, so all the values provided by the MTAT 2.1 software are multiplied by 0.66 (and rounded to the nearest 0.5%). For a pulse width of 30 µs, the maximal stimulator output is 100%. Therefore, no scaling adjustment is necessary.
  3. Set the TMS stimulator intensity to the initial percentage of maximal stimulator output indicated by the MTAT 2.1 software and deliver a single TMS stimulus. If the recorded MEP in the 20-50 ms time range after the TMS stimulus exceeds 1 mV, indicate "yes" by pressing the Y key. If the recorded MEP is less than 1 mV, indicate "no" by pressing the N key. Repeat this step until the stimulus intensity displayed by the MTAT software changes from black to green.
    NOTE: The initial value indicated by the MTAT 2.1 software is always 37%. For a pulse width of 120 µs, the actual stimulator value is 18.5%. For a pulse width of 70 µs, the actual stimulator value is 24%. For a pulse width of 30 µs, the stimulator value is 37%.
  4. Repeat for each combination of current direction and stimulus duration. For AP current, rotate the current direction to 180° by physically rotating the coil to induce the PA current by 180°, or utilize a custom coil manufactured to induce AP current.
    ​NOTE: When using multiple TMS current directions and pulse widths, all the thresholds may be determined before the data collection or just before using that specific combination of current direction and pulse width in the protocol.

8. Short-latency afferent inhibition (no task baseline)

  1. Attach the coil that will induce the PA current in the brain to the cTMS stimulator. Set the pulse type to Monophasic-Positive and the M-ratio to 0.2. Set the pulse width to 120 µs. Finally, set the stimulus intensity to the 1 mV threshold determined in step 7.
    NOTE: If using both PA and AP current directions, the order in which step 8 is conducted should be randomized across participants. If using multiple pulse widths, the order in which step 8 is performed should be counterbalanced across participants. PA120 and AP30 were the only current configurations employed in the described experiment.
  2. Set the peripheral electrical stimulus intensity to the intensity determined in step 5. Then, launch the no-task software routine on PC1. Next, set the interstimulus interval between the peripheral electrical and TMS stimuli to 21 ms.
  3. Position the TMS coil over the FDI motor hotspot determined in step 6. Ask the participant to hold a slight contraction of the FDI muscle (~5%-10% of maximum voluntary contraction). Next, run the no-task software on PC1 to trigger both the peripheral and cTMS stimulators.
  4. Repeat the steps for the AP30 current configuration using the coil that induces AP current in the brain.
    ​NOTE: It is recommended that the no-task baseline be repeated at the end of the experiment, time permitting. The pre- and post-no-task SAI assessments are strongly advised in order to provide an SAI baseline and to establish any pre-existing differences between groups (if applicable).

9. Short-latency afferent inhibition (Sensorimotor task)

  1. Attach the PA coil to the cTMS stimulator. Set the pulse type to Monophasic-Positive and the M-ratio to 0.2. Set the pulse width to 120 µs. Finally, set the stimulus intensity to the 1 mV threshold determined in step 7.
    NOTE: When using multiple TMS current configurations (e.g., PA120, AP30), the current configuration employed during the sensorimotor task should be counterbalanced across the participants. Using the same counterbalancing used to determine the order for the no-task baseline assessment is recommended.
  2. Set the peripheral electrical stimulus intensity to the intensity determined in step 5. Then, launch the sensorimotor task software routine on PC1. Set the interstimulus interval between the peripheral electrical and TMS stimuli to 21 ms.
  3. Position the TMS coil over the FDI motor hotspot determined in step 6. Ask the participant to hold a slight contraction of the FDI muscle (~5%-10% of maximum voluntary contraction).
  4. Run the sensorimotor task software routine to control the sensorimotor task and send the behavior-locked digital triggers to the peripheral and cTMS stimulators. Keep the desired number of unconditioned and conditioned trials between 8 and 24 stimuli per condition.
  5. Repeat the steps for the AP30 current configuration using the coil to induce AP current in the brain.

10. Data processing and analysis

  1. Visually inspect the EMG data offline and discard any traces in which the root mean square of the prestimulus EMG (−50 to stimulus onset) exceeds a criterion amplitude. Calculate the root mean square error for each trial as follows:
    Equation 1
    where N is the number of data points between −50 and stimulus onset, and the EMG is the voltage at point n. For SAI conducted with the muscle at rest, use a criterion amplitude of 10-15 µV. For SAI assessed with a slight tonic contraction, use a criterion amplitude that is the average RMSE across all the trials plus two standard deviations, assuming contraction levels were monitored during the study.
  2. For each trial, calculate the peak-to-peak MEP amplitude for the FDI as the difference between the minimum and maximum values in the time window between 20 ms to 50 ms post-TMS stimulus artifact in channel 170.
  3. For the conditioned trials, calculate the peak-to-peak M-wave amplitude for the APB as the peak-to-peak amplitude 5 ms to 15 ms post-peripheral stimulus artifact in channel 2.
    NOTE: Calculating the peak-to-peak M-wave amplitude is a method to confirm that the stimulus intensity did not vary across the conditions throughout the experiment.
  4. Calculate the mean MEP amplitude for the unconditioned and conditioned trials and the mean M-wave for conditioned trials for each combination of TMS current direction, pulse width, and behavioral condition.
  5. Express the conditioned MEP amplitude as a ratio of the unconditioned MEP amplitude for each participant using the equation below11:
    Equation 2
    NOTE: Lower ratios reflect more potent inhibition. Multiplying the ratio by 100% is common to express the conditioned MEP amplitude as a percentage of the unconditioned MEP amplitude.
  6. Calculate the mean across all the participants for each TMS current direction, pulse width, and behavioral condition combination. Report these values. Although mean values are generally reported, demonstrate individual data in figures where possible.

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Representative Results

Figure 3 illustrates examples of unconditioned and conditioned MEPs from a single participant elicited in the FDI muscle during the sensorimotor task using PA120- and AP30- (subscript denotes pulse width) induced current. The bar graphs in the middle column illustrate the raw average peak-to-peak MEP amplitudes for the unconditioned and conditioned trials. The bar graphs to the right show the SAI and MEP onset latencies for the PA120- and AP30-induced current for the same participant.

The average effect of the peripheral electrical conditioning stimulus is to suppress the corticospinal output elicited by the TMS stimulus, as shown by the smaller raw average peak-to-peak MEP amplitudes for the conditioned compared to unconditioned MEPs and SAI ratios of less than 1. The longer MEP onset latency for the AP30 SAI reflects the longer latency of the input to the corticospinal neuron.

Figure 3
Figure 3: Exemplar MEP traces and peak-to-peak amplitudes for unconditioned (solid trace) and conditioned (dashed trace) stimuli using PA120- (top) and AP30- (bottom) induced current. (A) Examples of the raw MEP waveforms elicited by PA120- and AP30-induced current during a validly cued index finger trial. (B) The average peak-to-peak amplitude of the unconditioned and conditioned MEPs for PA120- and AP30-induced current during a validly cued index finger trial. The error bars represent the standard error. (C) Top: The conditioned to unconditioned MEP amplitude ratio (e.g., SAI) for PA120- and AP30-induced current during a validly cued index finger trial. Bottom: The onset latencies of the unconditioned MEPs elicited by PA120- and AP30-induced current during a validly cued index finger trial. The MEP onset latency is not impacted by the cue validity. Abbreviations: TMS = transcranial magnetic stimulation; MNS = median nerve stimulus; MEP = motor-evoked potential; SAI = short-latency afferent inhibition; PA = posterior-anterior; AP = anterior-posterior. Please click here to view a larger version of this figure.

Figure 4 demonstrates the differential effects of a conditioning stimulus for the PA120 and AP30 TMS stimuli based on the validity of the informational cue for a single participant. The top-left and top-right panels depict the PA120 SAI and AP30 SAI during a validly cued index finger response and an invalidly cued index finger response in which the participants had to remap their response to a non-index finger. The bottom left and bottom panels depict the PA120 SAI and AP30 SAI during a validly cued non-index finger response and an invalidly cued non-index finger response in which the participants had to remap their response to the index finger.

In this participant, the PA120 SAI was similarly enhanced for an index finger response regardless of whether the participant was cued to the index finger (top left panel) or required to remap their response to the index finger following an invalid cue to a non-index finger (bottom left panel). In contrast, the AP30 SAI appears to be differentially modulated based on whether the invalid cue required a remap away (top-right panel) or toward the index finger (bottom-right panel).

Figure 4
Figure 4: SAI for valid and invalid cue types depending upon the cued finger (index vs. non-index) separated by PA120- and AP30-induced current. Top left: PA120 SAI for a correctly cued index finger response and an incorrectly cued response that required remapping to respond using a non-index finger. Top right: AP30 SAI for a correctly cued index finger response and an incorrectly cued response that required remapping to respond using a non-index finger. Bottom left: PA120 SAI for a correctly cued non-index finger response and an incorrectly cued response that required remapping to respond with the index finger. Bottom right: AP30 SAI for a correctly cued non-index finger response and an incorrectly cued response that required remapping to respond with the index finger. Abbreviations: SAI = short-latency afferent inhibition; PA = posterior-anterior; AP = anterior-posterior. Please click here to view a larger version of this figure.

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Discussion

The SAI method described here probes a subset of neural pathways that play a role in sensorimotor performance and learning. Assessing SAI while participants perform controlled sensorimotor tasks is critical for disentangling the complex contributions of the numerous sensorimotor loops that converge on the motor corticospinal neurons to shape the motor output in healthy and clinical populations. For example, a similar methodology has been used to identify the cerebellar influence over procedural motor control processes37,56 and the specific targets by which the declarative memory system may influence procedural motor control and learning in healthy21,36,37,38 and previously concussed populations75.

The are several advantages to the assessment of sensorimotor integration outlined here. First, the protocol moves beyond the standard evaluation of SAI using PA-induced current. SAI studies have almost exclusively employed PA-induced current when assessing SAI55,76. However, PA-induced current likely only recruits a subset of sensorimotor circuits in the motor cortex36,37,56,77, thus yielding an incomplete picture of the ongoing sensorimotor processes and the brain-behavior associations55. Second, the protocol employs variable pulse widths to enhance the specificity of the interneuron population recruited by the TMS stimulus77. The fixed pulse widths of conventional monophasic TMS stimulators, typically between 70-82 µs59,60, can recruit a mix of sensorimotor circuits within a particular current direction56,77,78. Using cTMS to manipulate the pulse width during SAI assessments can enhance the understanding of the functional significance of the different sensorimotor loops that govern corticospinal output in healthy56,78,79 and clinical populations75. Lastly, in this work, the SAI assessments were conducted at rest and were time-locked to a specific process during a concurrent behavior. Such an approach is relatively rare in the sensorimotor control and learning SAI literature14,19,20,21,36,37,80. More common is to assess SAI and sensorimotor performance/learning separately34,81,82,83,84,85,86. However, resting assessments of SAI rely on the correlation of behavior and physiological measurements measured at different points in time. Further, assessing the influences on cortical spinal output at rest likely does not capture their task-related significance. Assessing SAI at rest may only make sense for quantifying baseline differences between groups or evaluating the effects of a fundamental change in brain structure/function in a clinical population, such as in individuals with Parkinson's disease26,27,28, Alzheimer's disease87,88, and focal hand dystonia29.

Users should also carefully consider several critical elements of the described SAI protocol. First, the stimulus intensity required to elicit a 1mV MEP using AP current with a given pulse width is consistently higher than the equivalent PA current16,36,37,38,56. Higher thresholds increase the probability that the stimulus intensity required to achieve a 1 mV MEP exceeds the stimulator ability for a subset of individuals, especially when using AP current with short pulse widths59. In such cases, the researcher must decide whether to exclude the participant or determine another stable threshold. For a conventional stimulator with a fixed pulse width of ~80 µs, the magnitude of the AP SAI is not influenced by test stimulus MEP amplitudes ranging from 0.5 mV to 2 mV16. Second, the protocol outlined above requires participants to maintain a minimal contraction (5%-10% of maximal voluntary contraction) of the FDI. The slight contraction enhances the selectivity of the interneuron population recruited by various AP pulse widths by reducing the required stimulus intensity56,78. However, whether a slight contraction should be employed for PA-induced currents is questionable. Slight contraction does not enhance the selectivity of PA-induced currents of varying pulse widths78, and contraction-related sensory gating89 could mask other functional contributions of the PA-sensitive circuits during some task states. Moving forward, it may make sense to assess PA SAI at rest but AP SAI, especially at short pulse widths, with a slight contraction. Finally, the external validity of the reductionist approach of the SAI protocol described here is debatable. The described protocol targets one task-relevant muscle in a controlled task involving selective finger responses. The reductionist approach outlined here can provide substantial insight into the specific mechanisms at a given point of a sensorimotor behavior. However, the association between SAI in a specific motor representation and the sensorimotor behavior may vary across different elements of a complex task (e.g., planning versus motor execution). Further, the association between SAI and behavior may be less apparent as the complexity of the sensorimotor behavior increases. Assessing SAI across many muscles in a multivariate approach may be necessary to account for interactions between adjacent agonist, synergist, and antagonist motor representations as the task complexity increases.

Conventional TMS assessments have linked SAI to several movement and psychiatric disorders. The increased selectivity of cTMS-SAI could facilitate the identification of increasingly reliable biomarkers of sensorimotor and psychiatric disorders. A preliminary report highlighted the potential of cTMS, suggesting that AP30 SAI may be a marker of persistent latent cognitive-motor abnormalities in young adults with a concussion history75. However, the diagnostic utility of cTMS-SAI in movement and psychiatric disorders such as chronic concussion, Parkinson's disease, Alzheimer's disease, mild cognitive impairment, dystonia, and stroke is yet to be explored. One significant limitation to the clinical application of cTMS-SAI in the movement disorder domain is the need for larger scale studies to establish the reliability and normative ranges, as has been done for SAI assessed with a fixed width PA pulse90,91,92,93. Further, clinical applications would benefit from an enhanced understanding of how the different sensorimotor loops probed by cTMS-SAI interact with other facilitatory and inhibitory pathways converging on the motor cortical pyramidal neurons. For example, conventional TMS studies of SAI suggest that the probed sensorimotor loops may complement the function of short-interval cortical facilitation (SICF)74, SICI66,94, and long-interval cortical inhibition (LICI)67 inhibitory pathways. However, the functional significance of such interactions is not clear.

One exciting prospect is combining cTMS-SAI with electroencephalography (EEG). EEG can be used to quantify the effect of afferent projections on the pyramidal output evoked by TMS over motor77,95 and non-motor areas95, known as TMS-evoked potentials (TEP). Assessing SAI in the frontal cortex, rather than the motor cortex, provides a unique opportunity to directly evaluate the integrity of cholinergic function in the neural substrates that mediate cognitive function. For example, reductions in the afferent inhibition of the N100 TEP elicited by conventional TMS over the prefrontal cortex correlate with reduced executive function in older adults96 and schizophrenic patients97. Employing cTMS-SAI with EEG could help determine if the cholinergic profile of executive function decline in healthy aging and neuropsychiatric disorders involves the same prefrontal circuitry.

cTMS is still a relatively nascent technology. Like any new technique, there are limitations and unknowns. However, the early evidence from cTMS-SAI studies that vary induced current direction and pulse widths demonstrate exciting possibilities for better understanding the functional significance of various convergent sensorimotor circuits in ongoing behaviors in healthy and clinical populations.

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Disclosures

The authors have nothing to disclose.

Acknowledgments

The authors acknowledge funding from the Natural Sciences and Engineering Research Council (NSERC), the Canada Foundation for Innovation (CFI), and the Ontario Research Fund (ORF) awarded to S.K.M.

Materials

Name Company Catalog Number Comments
Acquisition software (for EMG) AD Instruments, Colorado Springs, CO, USA PL3504/P LabChart Pro version 8
Alcohol prep pads Medline Canada Corporation, Mississauga, ON, Canada 211-MM-05507 Alliance Sterile Medium, Antiseptic Isopropyl Alcohol Pad (200 per box)
Amplifier (for EMG) AD Instruments, Colorado Springs, CO, USA FE234 Quad Bio Amp
Cotton round Cliganic, San Francisco, CA, USA ‎CL-BE-019-6PK Premium Cotton Rounds (6-pack, 90 per package)
cTMS coils Rogue Research, Montréal, QC, Canada COIL70F80301 70 mm Medium Inductance Figure-8 coil
cTMS coils Rogue Research, Montréal, QC, Canada COIL70F80301-IC 70 mm Medium Inductance Figure-8 coil (Inverted Current)
cTMS stimulator Rogue Research, Montréal, QC, Canada CTMSMU0101 Elevate cTMS stimulator
Data acquisition board (for EMG) AD Instruments, Colorado Springs, CO, USA PL3504 PowerLab 4/35
Digital to analog board National Instruments, Austin, TX, USA 782251-01 NI USB-6341, X Series DAQ Device with BNC Termination
Dispoable adhesive electrodes (for EMG) Covidien, Dublin, Ireland 31112496 Kendal 130 Foam Electrodes
Electrogel Electrodestore.com E9 Electro-Gel for Electro-Cap (16 oz jar)
Nuprep Weaver and Company, Aurora, CO, USA 10-30 Nuprep skin prep gel (3-pack of 4 oz tubes) 
Peripheral electrical stimulator Digitimer, Hertfordshire, UK DS7R  DS7R High Voltage Constant Current Stimulator
Reusable bar electrode Electrodestore.com DDA-30 Black Bar Electrode, Flat, Cathode Distal
Software (for behaviour and stimulator triggering) National Instruments, Austin, TX, USA 784503-35 Labview 2020
TMS stereotactic coil guidance system Rogue Research, Montréal, QC, Canada KITBSF0404 BrainSight Neuronavigation System
Transpore tape 3M, Saint Paul, MN, USA 50707387794571 Transpore Medical Tape (1 in x 10 yds)

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References

  1. Bizzi, E., Ajemian, R. From motor planning to execution: a sensorimotor loop perspective. Journal of Neurophysiology. 124 (6), 1815-1823 (2020).
  2. Chen, R. Studies of human motor physiology with transcranial magnetic stimulation. Muscle & Nerve Supplement. 9, S26-S32 (2000).
  3. Hallett, M. Transcranial magnetic stimulation: A primer. Neuron. 55 (2), 187-199 (2007).
  4. Hallett, M. Transcranial magnetic stimulation and the human brain. Nature. 406 (6792), 147-150 (2000).
  5. Day, B. L., et al. Electric and magnetic stimulation of human motor cortex - Surface EMG and single motor unit responses. Journal of Physiology. 412, 449-473 (1989).
  6. Di Lazzaro, V., et al. Comparison of descending volleys evoked by transcranial magnetic and electric stimulation in conscious humans. Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control. 109 (5), 397-401 (1998).
  7. Di Lazzaro, V., Rothwell, J. C. Corticospinal activity evoked and modulated by non-invasive stimulation of the intact human motor cortex. Journal of Physiology. 592 (19), 4115-4128 (2014).
  8. Chen, R., et al. The clinical diagnostic utility of transcranial magnetic stimulation: Report of an IFCN committee. Clinical Neurophysiology. 119 (3), 504-532 (2008).
  9. Rossini, P. M. Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee. Clinical Neurophysiology. 126 (6), 1071-1107 (2015).
  10. Kujirai, T., et al. Corticocortical inhibition in human motor cortex. The Journal of Physiology. 471, 501-519 (1993).
  11. Tokimura, H., et al. Short latency inhibition of human hand motor cortex by somatosensory input from the hand. The Journal of Physiology. 523, 503-513 (2000).
  12. Nakamura, H., Kitagawa, H., Kawaguchi, Y., Tsuji, H. Intracortical facilitation and inhibition after transcranial magnetic stimulation in conscious humans. The Journal of Physiology. 498, 817-823 (1997).
  13. Chen, R., Corwell, B., Hallett, M. Modulation of motor cortex excitability by median nerve and digit stimulation. Experimental Brain Research. 129 (1), 77-86 (1999).
  14. Asmussen, M. J., Jacobs, M. F., Lee, K. G., Zapallow, C. M., Nelson, A. J. Short-latency afferent inhibition modulation during finger movement. PLoS One. 8 (4), e60496 (2013).
  15. Devanne, H. Afferent-induced facilitation of primary motor cortex excitability in the region controlling hand muscles in humans. European Journal of Neuroscience. 30 (3), 439-448 (2009).
  16. Ni, Z., et al. Transcranial magnetic stimulation in different current directions activates separate cortical circuits. Journal of Neurophysiology. 105 (2), 749-756 (2011).
  17. Bailey, A. Z., Asmussen, M. J., Nelson, A. J. Short-latency afferent inhibition determined by the sensory afferent volley. Journal of Neurophysiology. 116 (2), 637-644 (2016).
  18. Fischer, M., Orth, M. Short-latency sensory afferent inhibition: conditioning stimulus intensity, recording site, and effects of 1 Hz repetitive TMS. Brain Stimulation. 4 (4), 202-209 (2011).
  19. Voller, B., et al. Short-latency afferent inhibition during selective finger movement. Experimental Brain Research. 169 (2), 226-231 (2006).
  20. Asmussen, M. J., et al. Modulation of short-latency afferent inhibition depends on digit and task-relevance. PLoS One. 9 (8), e104807 (2014).
  21. Suzuki, L. Y., Meehan, S. K. Attention focus modulates afferent input to motor cortex during skilled action. Human Movement Science. 74, 102716 (2020).
  22. Bonassi, G., et al. Selective sensorimotor modulation operates during cognitive representation of movement. Neuroscience. 409, 16-25 (2019).
  23. Beck, S., Hallett, M. Surround inhibition in the motor system. Experimental Brain Research. 210 (2), 165-172 (2011).
  24. Seki, K., Fetz, E. E. Gating of sensory input at spinal and cortical levels during preparation and execution of voluntary movement. Journal of Neuroscience. 32 (3), 890-902 (2012).
  25. Young-Bernier, M., Davidson, P. S., Tremblay, F. Paired-pulse afferent modulation of TMS responses reveals a selective decrease in short latency afferent inhibition with age. Neurobiology of Aging. 33 (4), 1-11 (2012).
  26. Pelosin, E., et al. Attentional control of gait and falls: Is cholinergic dysfunction a common substrate in the elderly and Parkinson's disease. Frontiers in Aging Neuroscience. 8, 104 (2016).
  27. Dubbioso, R., Manganelli, F., Siebner, H. R., Di Lazzaro, V. Fast intracortical sensory-motor integration: A window into the pathophysiology of Parkinson's disease. Frontiers in Human Neuroscience. 13, 111 (2019).
  28. Oh, E., et al. Olfactory dysfunction in early Parkinson's disease is associated with short latency afferent inhibition reflecting central cholinergic dysfunction. Clinical Neurophysiology. 128 (6), 1061-1068 (2017).
  29. Richardson, S. P., et al. Changes in short afferent inhibition during phasic movement in focal dystonia. Muscle & Nerve. 37 (3), 358-363 (2008).
  30. Ziemann, U., et al. TMS and drugs revisited 2014. Clinical Neurophysiology. 126 (10), 1847-1868 (2015).
  31. Di Lazzaro, V. Muscarinic receptor blockade has differential effects on the excitability of intracortical circuits in the human motor cortex. Experimental Brain Research. 135 (4), 455-461 (2000).
  32. Di Lazzaro, V., et al. Neurophysiological predictors of long term response to AChE inhibitors in AD patients. Journal of Neurology, Neurosurgery and Psychiatry. 76 (8), 1064-1069 (2005).
  33. Fujiki, M., Hikawa, T., Abe, T., Ishii, K., Kobayashi, H. Reduced short latency afferent inhibition in diffuse axonal injury patients with memory impairment. Neuroscience Letters. 405 (3), 226-230 (2006).
  34. Koizume, Y., Hirano, M., Kubota, S., Tanaka, S., Funase, K. Relationship between the changes in M1 excitability after motor learning and arousal state as assessed by short-latency afferent inhibition. Behavioral Brain Research. 330, 56-62 (2017).
  35. Thabit, M. N., et al. Momentary reward induce changes in excitability of primary motor cortex. Clinical Neurophysiology. 122 (9), 1764-1770 (2011).
  36. Mirdamadi, J. L., Suzuki, L. Y., Meehan, S. K. Attention modulates specific motor cortical circuits recruited by transcranial magnetic stimulation. Neuroscience. 359, 151-158 (2017).
  37. Mirdamadi, J. L., Meehan, S. K. Specific sensorimotor interneuron circuits are sensitive to cerebellar-attention interactions. Frontiers in Human Neuroscience. 16, 920526 (2022).
  38. Suzuki, L. Y., Meehan, S. K. Verbal working memory modulates afferent circuits in motor cortex. European Journal of Neuroscience. 48 (10), 3117-3125 (2018).
  39. Mineo, L., et al. Modulation of sensorimotor circuits during retrieval of negative autobiographical memories: Exploring the impact of personality dimensions. Neuropsychologia. 110, 190-196 (2018).
  40. Bonnì, S., Ponzo, V., Di Lorenzo, F., Caltagirone, C., Koch, G. Real-time activation of central cholinergic circuits during recognition memory. European Journal of Neuroscience. 45 (11), 1485-1489 (2017).
  41. Nardone, R., et al. Abnormal short latency afferent inhibition in early Alzheimer's disease: A transcranial magnetic demonstration. Journal of Neural Transmission. 115 (11), 1557-1562 (2008).
  42. Nardone, R., Bratti, A., Tezzon, F. Motor cortex inhibitory circuits in dementia with Lewy bodies and in Alzheimer's disease. Journal of Neural Transmission. 113 (11), 1679-1684 (2006).
  43. Di Lazzaro, V., et al. In vivo cholinergic circuit evaluation in frontotemporal and Alzheimer dementias. Neurology. 66 (7), 1111-1113 (2006).
  44. Di Lazzaro, V., et al. Functional evaluation of cerebral cortex in dementia with Lewy bodies. NeuroImage. 37 (2), 422-429 (2007).
  45. Di Lazzaro, V., et al. In vivo functional evaluation of central cholinergic circuits in vascular dementia. Clinical Neurophysiology. 119 (11), 2494-2500 (2008).
  46. Marra, C., et al. Central cholinergic dysfunction measured "in vivo" correlates with different behavioral disorders in Alzheimer's disease and dementia with Lewy body. Brain Stimulation. 5 (4), 533-538 (2012).
  47. Mimura, Y., et al. Neurophysiological biomarkers using transcranial magnetic stimulation in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews. 121, 47-59 (2021).
  48. Yarnall, A. J., et al. Short latency afferent inhibition: a biomarker for mild cognitive impairment in Parkinson's disease. Movement Disorders. 28 (9), 1285-1288 (2013).
  49. Celebi, O., Temuçin, C. M., Elibol, B., Saka, E. Short latency afferent inhibition in Parkinson's disease patients with dementia. Movement Disorders. 27 (8), 1052-1055 (2012).
  50. Martin-Rodriguez, J. F., Mir, P. Short-afferent inhibition and cognitive impairment in Parkinson's disease: A quantitative review and challenges. Neuroscience Letters. 719, 133679 (2020).
  51. Nardone, R., et al. Short latency afferent inhibition differs among the subtypes of mild cognitive impairment. Journal of Neural Transmission. 119 (4), 463-471 (2012).
  52. Tsutsumi, R., et al. Reduced interhemispheric inhibition in mild cognitive impairment. Experimental Brain Research. 218 (1), 21-26 (2012).
  53. Di Lazzaro, V., et al. Segregating two inhibitory circuits in human motor cortex at the level of GABAA receptor subtypes: A TMS study. Clinical Neurophysiology. 118 (10), 2207-2214 (2007).
  54. Giorgetti, M., et al. Local GABAergic modulation of acetylcholine release from the cortex of freely moving rats. European Journal of Neuroscience. 12 (6), 1941-1948 (2000).
  55. Turco, C. V., Toepp, S. L., Foglia, S. D., Dans, P. W., Nelson, A. J. Association of short- and long-latency afferent inhibition with human behavior. Clinical Neurophysiology. 132 (7), 1462-1480 (2021).
  56. Hannah, R., Rothwell, J. C. Pulse duration as well as current direction determines the specificity of transcranial magnetic stimulation of motor cortex during contraction. Brain Stimulation. 10 (1), 106-115 (2017).
  57. Peterchev, A. V., D'Ostilio, K., Rothwell, J. C., Murphy, D. L. Controllable pulse parameter transcranial magnetic stimulator with enhanced circuit topology and pulse shaping. Journal of Neural Engineering. 11 (5), 056023 (2014).
  58. Peterchev, A. V., Murphy, D. L., Lisanby, S. H. Repetitive transcranial magnetic stimulator with controllable pulse parameters (cTMS). Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2010, 2922-2926 (2010).
  59. Rothkegel, H., Sommer, M., Paulus, W., Lang, N. Impact of pulse duration in single pulse TMS. Clinical Neurophysiology. 121 (11), 1915-1921 (2010).
  60. MagPro Family User Guide. MagVenture A/S. , Available from: https://tsgdoc.socsci.ru.nl/images/a/ac/Magpro_family.pdf (2022).
  61. Bashir, S., Edwards, D., Pascual-Leone, A. Neuronavigation increases the physiologic and behavioral effects of low-frequency rTMS of primary motor cortex in healthy subjects. Brain Topography. 24 (1), 54-64 (2011).
  62. Rossi, S., Hallett, M., Rossini, P. M., Pascual-Leone, A. Screening questionnaire before TMS: An update. Clinical Neurophysiology. 122 (8), 1686 (2011).
  63. Keel, J. C., Smith, M. J., Wassermann, E. M. A safety screening questionnaire for transcranial magnetic stimulation. Clinical Neurophysiology. 112 (4), 720 (2001).
  64. Wassermann, E. M. Risk and safety of repetitive transcranial magnetic stimulation: report and suggested guidelines from the International Workshop on the Safety of Repetitive Transcranial Magnetic Stimulation, June 5-7, 1996. Electroencephalography and Clinical Neurophysiology. 108 (1), 1-16 (1998).
  65. Rossi, S., et al. Safety and recommendations for TMS use in healthy subjects and patient populations, with updates on training, ethical and regulatory issues: Expert guidelines. Clinical Neurophysiology. 132 (1), 269-306 (2021).
  66. Udupa, K., Ni, Z., Gunraj, C., Chen, R. Effects of short latency afferent inhibition on short interval intracortical inhibition. Journal of Neurophysiology. 111 (6), 1350-1361 (2013).
  67. Udupa, K., Ni, Z., Gunraj, C., Chen, R. Interactions between short latency afferent inhibition and long interval intracortical inhibition. Experimental Brain Research. 199 (2), 177-183 (2009).
  68. Turco, C. V., El-Sayes, J., Fassett, H. J., Chen, R., Nelson, A. J. Modulation of long-latency afferent inhibition by the amplitude of sensory afferent volley. Journal of Neurophysiology. 118 (1), 610-618 (2017).
  69. Sakai, K., et al. Preferential activation of different I waves by transcranial magnetic stimulation with a figure-of-eight-shaped coil. Experimental Brain Research. 113 (1), 24-32 (1997).
  70. Groppa, S., et al. A practical guide to diagnostic transcranial magnetic stimulation: Report of an IFCN committee. Clinical Neurophysiology. 123 (5), 858-882 (2012).
  71. ClinicalResearcher.org. , Available from: https://www.clinicalresearcher.org/software.htm (2022).
  72. Awiszus, F. TMS and threshold hunting. Supplements to Clinical Neurophysiology. 56, 13-23 (2003).
  73. Silbert, B. I., Patterson, H. I., Pevcic, D. D., Windnagel, K. A., Thickbroom, G. W. A comparison of relative-frequency and threshold-hunting methods to determine stimulus intensity in transcranial magnetic stimulation. Clinical Neurophysiology. 124 (4), 708-712 (2013).
  74. Cash, R. F., Isayama, R., Gunraj, C. A., Ni, Z., Chen, R. The influence of sensory afferent input on local motor cortical excitatory circuitry in humans. Journal of Physiology. 593 (7), 1667-1684 (2015).
  75. Hayes, K. D., Khan, M. E. R., Barclay, N. E., Meehan, S. K. The persistent effects of sports-related concussion during adolescence on sensorimotor integration. Canadian Association for Neuroscience Meeting. , Canadian Association for Neuroscience. Victoria, Canada. (2022).
  76. Turco, C. V., et al. Short- and long-latency afferent inhibition; Uses, mechanisms and influencing factors. Brain Stimulation. 11 (1), 59-74 (2018).
  77. Casula, E. P., Rocchi, L., Hannah, R., Rothwell, J. C. Effects of pulse width, waveform and current direction in the cortex: A combined cTMS-EEG study. Brain Stimulation. 11 (5), 1063-1070 (2018).
  78. D'Ostilio, K., et al. Effect of coil orientation on strength-duration time constant and I-wave activation with controllable pulse parameter transcranial magnetic stimulation. Clinical Neurophysiology. 127 (1), 675-683 (2016).
  79. Barclay, N. E., Graham, K. R., Hayes, K. D., Meehan, S. K. Program No. 474.08.The contribution of oscillatory activity to the modulation of different sensorimotor circuits under varying working memory load. Society for Neuroscience Annual Meeting. , Society for Neuroscience. Washington, D.C. (2022).
  80. Dubbioso, R., Raffin, E., Karabanov, A., Thielscher, A., Siebner, H. R. Centre-surround organization of fast sensorimotor integration in human motor hand area. NeuroImage. 158, 37-47 (2017).
  81. Adams, F. C., et al. Tactile sensorimotor training does not alter short- and long-latency afferent inhibition. Neuroreport. 34 (3), 123-127 (2023).
  82. Paparella, G., Rocchi, L., Bologna, M., Berardelli, A., Rothwell, J. Differential effects of motor skill acquisition on the primary motor and sensory cortices in healthy humans. Journal of Physiology. 598 (18), 4031-4045 (2020).
  83. Deveci, S., et al. Effect of the brain-derived neurotrophic factor gene Val66Met polymorphism on sensory-motor integration during a complex motor learning exercise. Brain Research. 1732, 146652 (2020).
  84. Turco, C. V., Locke, M. B., El-Sayes, J., Tommerdahl, M., Nelson, A. J. Exploring behavioral correlates of afferent inhibition. Brain Sciences. 8 (4), 64 (2018).
  85. Mang, C. S., Bergquist, A. J., Roshko, S. M., Collins, D. F. Loss of short-latency afferent inhibition and emergence of afferent facilitation following neuromuscular electrical stimulation. Neuroscience Letters. 529 (1), 80-85 (2012).
  86. Mirdamadi, J. L., Block, H. J. Somatosensory changes associated with motor skill learning. Journal of Neurophysiology. 123 (3), 1052-1062 (2020).
  87. Bologna, M., et al. Bradykinesia in Alzheimer's disease and its neurophysiological substrates. Clinical Neurophysiology. 131 (4), 850-858 (2020).
  88. Schirinzi, T. Amyloid-mediated cholinergic dysfunction in motor impairment related to Alzheimer's disease. Journal of Alzheimer's Disease. 64 (2), 525-532 (2018).
  89. Cohen, L. G., Starr, A. Localization, timing and specificity of gating of somatosensory evoked potentials during active movement in man. Brain. 110 (2), 451-467 (1987).
  90. Brown, K. E., et al. The reliability of commonly used electrophysiology measures Active and resting motor threshold are efficiently obtained with adaptive threshold hunting. Brain Stimulation. 10 (6), 1102-1111 (2017).
  91. Turco, C. V., Pesevski, A., McNicholas, P. D., Beaulieu, L. D., Nelson, A. J. Reliability of transcranial magnetic stimulation measures of afferent inhibition. Brain Research. 1723, 146394 (2019).
  92. Rehsi, R. S., et al. Investigating the intra-session reliability of short and long latency afferent inhibition. Clinical Neurophysiology Practice. 8, 16-23 (2023).
  93. Toepp, S. L., Turco, C. V., Rehsi, R. S., Nelson, A. J. The distribution and reliability of TMS-evoked short- and long-latency afferent interactions. PLoS One. 16 (12), e0260663 (2021).
  94. Alle, H., Heidegger, T., Krivanekova, L., Ziemann, U. Interactions between short-interval intracortical inhibition and short-latency afferent inhibition in human motor cortex. Journal of Physiology-London. 587 (21), 5163-5176 (2009).
  95. Noda, Y., et al. A combined TMS-EEG study of short-latency afferent inhibition in the motor and dorsolateral prefrontal cortex. Journal of Neurophysiology. 116 (3), 938-948 (2016).
  96. Noda, Y. Reduced prefrontal short-latency afferent inhibition in older adults and its relation to executive function: A TMS-EEG study. Frontiers in Aging Neuroscience. 9, 119 (2017).
  97. Noda, Y., et al. Reduced short-latency afferent inhibition in prefrontal but not motor cortex and its association with executive function in schizophrenia: A combined TMS-EEG study. Schizophrenia Bulletin. 44 (1), 193-202 (2018).

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Peripheral Nerve Stimulation Controllable Pulse Parameter Transcranial Magnetic Stimulation Sensorimotor Control Motor Planning Motor Execution Sensory To Motor Pathways Neurological Disorders Motor Scale Acquisition Conscious Declarative Process Subconscious Procedural Process Short Latency Afferent Inhibition Cognition Procedural Sensory Motor Circuits Motor Cortex Healthy Populations Clinical Populations Afferent Inputs Transcranial Magnetic Stimulation Sensory Motor Integration Functional Magnetic Resonance Imaging Electroencephalography Neuronal Populations Global Hemodynamic Responses Skilled Motor Behavior Lock Parameters Traditional Transcranial Magnetic Stimulators
Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning
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Graham, K. R., Hayes, K. D., Meehan, … More

Graham, K. R., Hayes, K. D., Meehan, S. K. Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning. J. Vis. Exp. (194), e65212, doi:10.3791/65212 (2023).

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