TMS Dissertation 2013

Neurophysiology
UoB | APRIL 2013 | Neurophysiology
The influence of intensity on mapping parameters of a clinically relevant paradigm of
Transcranial Magnetic Stimulation
Neuroplasticity and Neurorehabilitation Laboratory; University of Birmingham
Michael Grey
26 April 2013
HIGHLIGHTS
 Within session reliability of mapping parameters was strong
 Significant intensity-dependency was established for area and volume measures
 Shape and CoG were not significantly displaced in any of the trials
ABSTRACT
Background | The use of Transcranial Magnetic Stimulation (TMS) to investigate cortio-spinal
excitability and motor control has popularized substantially since it’s advent in 1985. However, it’s
clinical use remains self-limited by the lengthy protocol inherent in conventional methodology |
Purpose | The aim of the present study was to evaluate the effect of intensity on cortical excitability
maps resulting from a novel TMS protocol | Method | Eighty, continuous, single-pulse stimulations
(inter-stimulus intervals of 1.5 seconds (0.67Hz)) were administered in three trials at each of three
intensities (110%, 120% and 130% of resting motor threshold (RMT)) to 12 young, healthy
subjects. Motor Evoked Potentials (MEPs) were measured from the first dorsal interosseous (FDI)
and abductor digiti minimi (ADM), and simultaneously amplified, filtered, and recorded for offline
analysis. During data collection, MEPs generated from each trial were compiled to generate
excitability maps. Four map parameters were assessed; map size (both volume and area), shape, and
the amplitude-weighted mean of MEP amplitudes (center of gravity; CoG). | Results | Map volume
and area showed significant positive relationships with intensity, but reliability was high within all
intensities. Both coordinates of CoG were un-effected by stimulus intensity (FDI xCoG p = 0.25,
yCoG p = 0.33; ADM xCoG p = 0.99, yCoG p = 0.61). Map shape was also independent of
intensity. | Conclusion | The reproduction of established relationships demonstrates validity of the

UoB | 26 APRIL 2013 | Neurophysiology
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new method while stability of map parameters across trials suggests it’s reliability. These findings
promote the clinical use of the novel protocol.
The ability to detect fine changes in cortical organization requires careful consideration of
the specifics of the protocol employed (Brasil-Neto et al., 1992).
1. Introduction
Transcranial Magnetic Stimulation has become an increasingly popular resource among
neuroscientists; it is distinguished by its safe and non-invasive nature as an investigative tool in the
progression of knowledge surrounding cortico-spinal excitability and motor control (Hoogendam,
J., Ramakers, G., & Lazzaro, V., 2010; Eisen et al., 1994).
1.1 Uses of TMS
The administration of TMS has expanded beyond it’s original use in neurophysiology labs; as a
focal intervention, TMS has abundant clinical applications including diagnosis, evaluation of drugs
and physiological interventions, and treatment itself (Barker et al., 1985; Berardelli et al., 2002;
Cohen et al., 1998). Via monitoring the progression of, and projecting the discourse of a disease,
TMS promises value in the decisions surrounding treatment selection, monitoring treatment effects,
and in research surrounding optimal evidence-based treatments (Berardelli et al., 2002; Crupain et
al., 2002; Hallet, 2000). Unfortunately, conventional methodology hinders the usefulness of TMS in
clinical settings, due to the lengthy duration of its protocol. One study looking into various methods
of administering TMS for treatment of Chronic Tinnitus concluded that further research was needed
to “improve insights into possible mechanisms of different TMS protocols” before it may be used as
a treatment method (Langguth et al., 2010).
1.2 Conventional methodology in a clinical setting
The clinical setting demands two criteria of TMS; first, its reliability must be well established,
next, the validated protocol must be made easy to administer and time effective (Eisen et al., 1994).
Previous research, using conventional methods, has satisfied the first criteria by testing the
reproducibility of maps from various muscles (Boroojerdi et al., 1999; Cohen et al., 1992; Cohen &

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Hallett, 1988; Eisen et al., 1994; Gonzalez et al., 2006; Amassian et al., 1991; Littmann et al., 2013;
Mastaglia et al., 1993; McMillan et al., 1998; Uy et al., 2002; Mortifee et al., 1993; Uy et al 2003;
Cohen et al., 1992). Validity of maps has been confirmed by the stability of CoG position,
compared against results from functional magnetic resonance imaging (fMRI) (Boroojerdi et al.,
1999). The second criterion has been addressed as the topic of this experiment. Conventional
methods use fixed grids, whose dimensions reflect the estimated size of cortical representation of
the muscles; this area can range from 3cm by 3cm (Jones-Lush et al., 2010) to 7cm by 7cm
(Classen et al., 1998). A sequence of magnetic impulses is elicited systematically across the 15
(Littmann et al., 2013) to 24 pre-plotted points spaced 1cm apart on scalp (Adams et al., 2013) or,
on a snug swim cap (Uy et al., 2013). These methods result in protocol times ranging from fifteen
minutes, upwards of an hour (Cramer et al., 2007). This is not a practical duration for clinical
settings. Variability of the muscle response (motor evoked potentials; MEPs) is made more
vulnerable to fluctuating alertness as duration increases (Littmann et al., 2013; Wassermann &
Zimmerman, 2012). Therefore, a long procedure may also be insufficient to capture short-term
responses to an intervention. Moreover, the belabored duration of the conventional method is the
product of several unvalidated assumptions: first, that a finite number of repeated same-site
stimulations will provide a reliable representation of maximal response from that cortical area, and
also that pre-determination of evenly spaced stimuli is advantageous for reliability of the map.
1.3 Evolution of the TMS Paradigm
Data acquisition time can be addressed by evaluating three components of the conventional
protocol; the number of same-site stimulations, the inter-stimulus interval, and stimulus placement.
The number of stimulations elicited per sight in conventional methodology, is arbitrary;
comprehensive mapping requires hundreds of stimulations from all active sites on the cortex (Butler
et al., 2005; Bassi et al., 1997; Butler et al., 2005). The range of stimuli per site used by
conventional methodology (4-6) originated as a safety precaution near the inception of TMS, and is
assumed to be a reasonable compromise between reliability and feasibility (Barker et al., 1988).

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However, it is acknowledged that an infinite number of stimuli are required to guarantee the largest
response (and therefore the most accuracte excitability representation) be elicited at a single
stimulation site. Therefore, the threat of inconsistency is maintained despite repetitive on-sight
stimulations (Calne et al., 1991); the finite number of same-site stimulations is acquiesced, due to
impracticality of the alternative. While 20 stimuli was initially suggested to be required to elicit the
maximum MEP from low intensity stimulation (Calne et al., 1991), Littman et al. have recently
validated the use of 5 stimuli (2013). Littmann’s results have been further challenged showing that
mapping characteristics are not significantly altered by the use of as little as one stimulation “per
site”, even where sites are generated spontaneously and in random sequence (unpublished results).
Regarding stimuli placement, Brasil-Neto et al. note that variance decreases as width
between marked points decreases (1992). Further research surrounding the effect of stimuli
placement on map has illustrated high correlation between mapping parameters generated by
systematic (conventional) and random placement (novel) methods; CoG correlated with a
coefficient greater than 8. The novel method provides an approximately even distribution of stimuli,
which reduces the average space between stimulation sites compared to repeated on-site
stimulations. The result is elimination of the time requirement to manually prepare grids, as well as
the requirement of bootstrapping to determine optimal spacing widths for positioning.
The third method by which the novel protocol reduces data acquisition time is by reducing
the inter response intervals (ISIs). While conventional methods employ ISIs between 2 seconds
(0.5Hz) (Adams et al., 2013) and 10 seconds (0.1Hz) (Eisen et al., 1994), map parameters have
shown to be unaffected by ISIs as small as 1.5 seconds (0.67Hz) (unpublished results).
The purpose of this study was to contribute to the evaluation of the appropriateness of the
novel TMS protocol for clinical use, by examining the effect of intensity on several mapping
parameters. It was anticipated that our results would reflect those established by similar research
using the conventional method; it was hypothesized that the positive relationship between both of
area and volume would result, but that these changes in MEP amplitude resulting from intensity

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would not influence the shape of maps produced, and therefore that CoG would also remain stable.
2. Methods
2.1 Frameless Neuronavigation system
A magnetic resonance imaging (MRI) prototype was generated from one healthy participant
prior to experimentation, and served as a template of the cortex for each participant. This was
favorable for time of testing, but primarily resulted fom restricted access to MRI equipment. An
infrared light receptor, suspended overhead, was used to digitize the subject’s skull by registering
eight anatomical points on the head (3 points on each ear, nose bridge and nose tip) with reference
to the infrared reflective markers secured to a headband worn by the subject. This computed a 3D
representation of the subject’s head in space, paired to the pre-generated MRI on the Brainsight
program. Stimulation grids were overlaid onto the 3D cortical representation, via frameless
stereotactic navigation technology, and used to guide stimulation throughout the session on a
computer screen.
2.2 Subjects
Twelve healthy subjects (including the author) provided written, informed consent before
participation. Subjects were asked to refrain from alcohol, caffeine, and exhaustive exercise 24
hours prior to the session. All subjects were right handed, and had batwing generated motor
thresholds under 60% of stimulator output. See Appendix A for Exclusion criteria
Subject was sat comfortably, with their right arm supinated atop a table where it was velcroed to
prevent movement. To minimize impedance, skin overlying the FDI and AMD of the right hand
were prepared for electrodes with abrasion tape, and without alcohol (as per unpublished results).
Electrodes were then applied in a bipolar configuration over the m. first dorsal interosseous (FDI)
and abductor digiti minimi (ADM) of the right hand. These muscles were selected for three reasons;
(1) distal arm muscles have been shown to have larger representation on the cortex, making the
“hand area” easy to locate and thereby reducing experimentation time (Cohen et al., 1992), (2) as a
superficial cortical control area, this areas tends to exhibit lower thresholds, contributing to

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participant comfort by enabling lower stimulation intensities (Berardelli et al., 2002; Cowan et al.,
1987), and (3) conventional methods has been biased towards the use of these muscles, facilitating
the comparison of results, and providing well established reliability for the response of this area
(critical in order to establish intensity-related changes) (Adams, 2013). Since control of FDI and
AMD are so closely associated on the cortex, we were able to generate maps from both in the same
trial. Subject alertness was monitored between trials with verbal communication.
2.3 Magnetic Stimulation
Magnetic Stimulation was delivered using a Magstim Rapid 2.0 stimulator (Magstim Co. Ltd,
Sheffield, UK) through a figure-of-eight batwinged coil. This stimulator was selected based on it’s
ability to stimulate at high frequencies, a critical element of reducing protocol time (Gonzalez et al.,
2006; Chiappa et al., 1993). The angle of the coil was maintained at 45 degrees from the midsagittal
line of the skull, with the handle pointing backward to create a posterior to anterior current flow.
This angle has been associated with optimal responses in the hand muscles (Mills et al., 1992;
Alway et al., 1994). Coil orientation was monitored by Polaris, with respect to the 3D
representation of the subject’s head on the computer screen. The center of the coil remained
constantly in contact with the scalp, unimpeded by friction from the swim cap.
2.4 Localization of the “hot spot”
Stimulations were administered over the area of the primary motor cortex, wherein
corticospinal cells were expected to project to FDI, until the point was located which most
consistently generated the largest amplitude MEPs. This optimal stimulation location was termed
the “hot spot”. This spot became the center of the 6cm by 6cm grid. These dimensions were
selected because of the high reproducibility of MEPs within this area (Littermann et al., 2013).
2.5 Resting Threshold
Resting threshold was defined as the minimum stimulus intensity required to elicit a
50microvolt MEP from five out of 10 consecutive trials delivered at the hot spot (Cohen et al.,
1992). Each subject’s threshold was calibrated relative to their specific anatomy, supra threshold

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stimulation intensities were administered repeatedly at the hotspot, and intensity was incrementally
reduced until the defining criteria were met. The threshold at the center point (hot spot) was used to
calibrate stimulation intensity for the entire grid.
2.6 Protocol
Stimuli were placed randomly, within the grid. The use of as few as 75 stimuli has been
validated for map generation (Littmann et al., 2013), therefore 80 stimuli were employed, leaving
room for potential exclusions. Stimuli were elicited with an ISI of 1.5seconds (0.67Hz). Stimulus
intensity was threshold-adjusted by expression as a percentage of the absolute value. Three
conditions of intensity commonly seen in conventional methods were examined; 10% (Uy et al.,
2013), 20% (Littmann et al., 2013), and 30% (Brasil-Neto et al., 1992) above resting threshold.
MEPs were recorded from the FDI and ADM during full voluntary relaxation of the hand. Muscle
relaxation was monitored by visual feedback on a computer screen, which turned color during
voluntary or involuntary contraction; subjects were told to attempt to keep the screen from turning
color. The electro-myographic responses were amplified (0.5 - 1k), and twice filtered (first from
50Hz to 300Hz, and then by Hum Bug for the 50Hz output frequency which is in the range of the
main content of the time signal). Responses were simultaneously digitized for recording on
MrKICK. The recorded electrical muscle responses (motor evoked potentials; MEPs) can then be
compiled to produce excitability maps. Each two-minute trial was performed in a pseudorandom
order, for a total of three trials per intensity. All 9 trials were performed consecutively, separated
only by short rest periods (1-2mins). Head marker and electrodes were not removed until the end of
the session. The room was kept air conditioned below 19 degrees, and coil was cooled with an ice
pack between sessions, to prevent it from reaching it’s set temperature limit.
2.7 Peripheral nerve, electrical stimulation
At the end of each experiment, before electrodes were removed, supramaximal peripheral
nerve stimulation (PNS) was used to determine the maximal amplitude response in the FDI and
ADM. Electrical stimulus was administered repeatedly, near the elbow, until a plateau was

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observed in the peak-to-peak measurement. MEPs were normalized to this max involuntary
contraction generated in order to standardize inter-subject results for comparison.
2.8 Data Analysis
MEP recordings were statistically analyzed using repeated measures ANOVA. The alpha
level to assess significance was set at 0.05. Nine maps were generated from the recordings of each
of the 12 subjects. Reliability of the protocol was evaluated by comparison of map characteristics
derived from the novel protocol, against those from conventional methods. Four parameters were
considered; volume, area, shape and CoG. Volume was presented as the sum of the MEP
amplitudes derived from electrical traces. The area of muscle representation on the cortex was
distinguished by inclusion of all points from which responses were induced. CoG was defined as
the amplitude weighted mean of the map, and it’s reliability analyses was divided into both medial-
lateral and anterior-posterior coordinates using the following formula from Uy et al (2002):
xi=anterior–posterior distance from intraural line; yi= medial-lateral distance; vi=MEP peak-to-peak area
3.0 Results
None of the subjects
reported adverse effects
following stimulation. Map
characteristics varied
between individuals, but
trends were observed.
3.1 Center of Gravity No significance existed for intensity-related displacement of CoG in either
direction (xCoG, p = 0.25; yCoG, p = 0.33) (Fig 1). Furthermore, there was no relationship between
intensity and either of the amount, or direction, of displacement of CoG (Fig 1).
Fig. 1 Stability of the average position of both coordinates of CoG from the FDI
as a function of intensity; (a) anterior-posterior position, and (b) medial-lateral
position. CoG was determined as the physical location representing the mean
amplitude of MEPs from all stimuli used to create the map, and normalized to
120%RMT to eliminate inter-individual anatomical differences. mm = millimeters

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3.1 Size
Variability in map size (area and volume) was also substantial
between individuals and within individuals related to changes of
intensity. Intra-individual changes in size of
responsive cortical area demonstrated a strong positive
relationship with intensity of stimulation (p = 0.00), that was consistent
across all participants; each increase in stimulation intensity resulted in a
significant increase in both volume (Fig 2), and area (Fig 3) of FDI and ADM.
The intensity-dependent scaling of volume was proportional across a
map, such that the largest MEP amplitudes were consistently concentrated
near the center of the map surrounded by gradually decreasing amplitudes
with progression towards the periphery of the map.
3.2 Shape
It is apparent that the intensity-dependency of peripheral
responsiveness was proportional, enabling preservation of map shape,
despite scaling of its size (Fig 3). Inter-subject variability in the shape of
topographical representation of the two hand muscles was also observed
(Fig 3).
Intensity(%RMT)
Subject 07
Fig 3. Effect of Intensity on area and shape of the
map. The two dimensional excitability map of FDI
from subject 7 (left) and 10 (right) are the product
of 80 stimulations (0.67Hz) placed randomly over
the FDI area of the cortex. Responses from all
stimulations are included. Intensity of stimulator
output is represented in the rows, progressing
from 110%RMT (top), to 130%RMT (bottom).
Columns represent the effector muscle. With
increasing intensity, the size of the cortical
representation is extended. Shape of
topographical representation is subject-specific,
but is preserved within subject across all
intensities. The pink dot near the center of each
map represents CoG, which is approximately
stable across all within-participant trials.
Significant overlap of representation is apparent
between FDI and ADM. Volume of ADM
representation is reduced overall.
Fig 2. Three dimensional sample
map from subject 7; excitability
maps resulting from 80
stimulations (0.67Hz), at each of
110%, 120%, and 130% RMT,
placed randomly over the FDI
area of the cortex. Responses
from all stimulations are included,
and their strength is represented
in the scale of colors present,
such that red indicates a close to
maximal response, while navy
blue indicates no response. The
intensity-dependency of volume
and area is apparent.
FDI FDIADM ADM
Subject 10

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3.3 ADM vs FDI
Representations of FDI and ADM were highly comparable and largely overlapping (Fig 3).
CoG for the two were not significantly distinguishable, but CoG of ADM was, on average, located
more medial and superior along M1.
3.4 Variability
Although not a significant difference, variability in shape and size were slightly greater from
trials at 110%RMT compared to the higher intensities (Fig 3).
110%RMT110%RMT

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Fig 3. Effects of stimulation strength on variability of MEP response comprising a map from the FDI of
subject no. 11. The 3D representations illustrate the effect of intensity on map size (esp. volume). Variability
of the size of MEP response across trials at each intensity is also apparent in each row. Down the columns it
can be seen that volume of the map increases as intensity is increased. Below the 3D cortical representation
of 110%RMT, a 2D aerial view of the map has been inserted, which depict the stability of shape, and
variability in the map’s size (seen by the grades of blue).
4.0 Discussion
The main purpose of this study was to investigate the influence of intensity on cortical
excitability of the units responsible for motor control of two hand muscles, using the novel TMS
protocol. Characteristics of four mapping parameters were evaluated to discriminate the integrity of
the excitability maps resulting from changes of intensity; shape, and area of cortical representation,
map volume, and it’s amplitude-weighted mean (CoG).
The main findings of this study were: (1) reproduction of the established relationship
between intensity and both of volume and area, as well as the lack of it’s influence on CoG, (2)
establishment of the intensity-independence of the shape of a map’s area, and (3) demonstration that
the variability of CoG and map size across trials from a single intensity was approximately
consistent for all intensities tested.
4.1 Inter-Individual Differences
Substantial differences in size and shape of maps was observed between individuals. Inter-
individual differences in topography are related to intrinsic excitability, or topological factors;
130%RMT120%RMT

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“thickness and shape of the extracerebral structures of curvature of the cortex itself” have been
attributed to these findings (Cohen et al., 1992).
4.2. Intra-Intensity Effects
4.2.1 MEP Amplitude
The notorious variability of MEP amplitude was apparent in our results. Variability of
responses from a single site can be influenced by (1) position of the stimulating coil, (2) excitability
of the cortex and the effector, (3) the coil cortex distance.
Position of the stimulating coil may have influenced the magnitude of MEP independently
from the intensity used (Cowan et al. 1987; Cohen and Hallett 1988; Rossini 1988; Amassian et al.
1989); specifically, variability of MEP amplitude increases as position of coil deviates from optimal
(Brasil-Neto et al., 1992). This is because in optimal positions, consistent stimulation of both large
and small alpha-motorneurons contribute to stability of the response, reducing the notable
variability in MEP (Chiappa et al., 1993), whereas sub-optimal stimulation positions preferentially
stimulate smaller and fewer neurons, resulting in greater variability (Brasil-Neto et al., 1992).
However, coil angle was maintained with caution throughout experimentation (monitored visually),
and minor changes in coil position could not account for variability of the size of a response
(Amassian et al., 1989).
Excitability of the cortex and the effector can also influence MEP amplitude. In an effort to
stabilize mood and minimize these influences, music and television were not permitted during
testing. Trials within a session were also randomized for intensity to avoid influences of systematic
changes in excitability. With regard to effector excitability, variability is also greater for a muscle at
rest than when tonically active (Chiappa et al., 1993). Pre-stimulation muscle activation was
controlled for by use of a visual monitor, as outlined in the protocol.
Finally, influence from the coil-cortex distance was held constant by maintaining contact
between the epicenter of the coil and the surface of the head (Adams et al., 2013). Since the

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variance in distance from the cortex to the skill for sites within a 6cm by 6cm area is negligible, it is
unlikely that this factor influenced the results.
The variability of individual MEP responses was greater in the periphery, but did not
significantly influence map size, or shape. Conventional methods have also demonstrated that other
mapping characteristics (ie. area, and CoG) are insensitive to the variability of MEP amplitudes
(Byrnes et al., 1999).
4.2.2 Area
Although not statistically significant, greater variability of area was noted between trials of the
lowest intensity. The positive relationship between intensity and variability of MEP amplitude can
be explained by the functional definition of the threshold-adjusted intensity (ie. the intensity
resulting in a response from approximately half of the stimulations elicited) (Amassian et al., 1989);
since 110%RMT is quite close to resting threshold, the chance of eliciting a null response increases.
Furthermore, low excitory inputs reaching the underlying neurons, makes them more subject to the
effect of “uncontrolled fluctuations in membrane potential”, resulting in greater variability between
trials (Chiappa et al., 1993). This finding should be considered when selecting an intensity for
rehabilitative settings that aim to monitor plasticity, where even mild variability may interfere with
tracking a patient’s progression.
The greatest modulations occurred furthest from the map epicenter, indicating some
inconsistency of peripheral excitability. Liepert et al. claim that the close topographical relation
between areas of inhibition and excitation amplify the effect of intensity in the perimeter, which we
have observed as mild variability of map area (1995). Furthermore, progression from the center of
the map is associated with a reduction in the amount of representative motor neurons (ie. those
projecting to the effector). Therefore stimulation in the periphery is less likely to recruit as many
neurons, resulting in a weaker, and more variable response. While our results sustain that MEP
responses were slightly more variable in the periphery, no significant changes in overall map shape
or size resulted.

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4.2.3 Volume
The overall map volume (sum of MEP amplitudes) was reliable at each intensity. Similar
findings have been confirmed in previous research, suggesting that the coefficient of reliability for
the map’s cumulative volume is sufficiently high to regard it, unaccompanied by other mapping
parameters, as a valid indicator of cortical excitability, validating this paradox found in our results
(Eisen et al., 1994; Littmann et al., 2013).
It was also found that the pattern of MEP amplitudes crossing the map reflected
topographical organization in the appropriate areas (as determined by MRI), mimicking results of
conventional TMS use (Boroojerdi et al., 1999); the MEP amplitudes increased with progression
towards the center of the map, independent of the intensity used. While not a novel insight, this
observation contributes to the validity of the maps produced. The heightened response observed
from the optimal stimulation site, in the center of the map, results from a higher concentrated of
motor units projecting to the effector (Mastaglia et al., 1993). However, to say that the reduced
magnitude of response from peripheral units results solely from reduced motor unit representation,
might over-estimate the responsiveness of those motor units; the response to peripheral stimulation
may not be the sole result of excitation of neurons directly underlying the coil. Weaker stimulation
of more optimal areas resulting from the increased current spread associated with lower intensities
may also contribute to a response. Furthermore, widely distributed neural networks within the
cortex have also been established (Pascual-Leone et al., 2000); these networks maintain that the
magnitude of effector activity may result from the conduction of a stimulation (from a particular
site) through neural networks to a site that is more optimally represented for the effector (Pascual-
Leone, 2000).
Our results for map area, generated from three trials at a single intensity within one testing
session, indicate at least strong short-term reliability. In comparison, only moderate long term
reliability was found by Eisen et al., this discrepency may be explained by: changes in excitability
occurring over time frames lasting longer than one session, and re-placement of electrodes (1994).

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McMillan et al., found maps of masseter muscle were only highly reproducible if electrodes were
left on between testing sessions (1998).
4.2.4 ADM vs FDI
The results from ADM paralleled those from FDI, this similarity suggests the appropriateness of
generalizability of the results and use of the novel method for mapping other muscles. Overall, a
general reduction in volume and area for most trials from ADM compared to FDI was apparent.
This finding can be explained in terms of the functional role of the two hand muscles; research has
suggested that the area of cortical representation increases as a result of use.
Mapped representations of FDI and ADM were largely overlapping as expected based on
results of previous work on hand muscles (Mastaglia et al., 1993; Eisen et al., 1994). It has been
said that the capacity of TMS to distinguish the somatotopy of muscle movement movements
represented within 2mm on the cortex is limited by the current technology (Cohen et al., 1992).
However Mastaglia et al. credited TMS for it’s ability to provide some separation between proximal
control areas for the two muscles of the hand (although results were not statistically significant)
(1993). Similar findings have resulted in this work; although only discretely distinguishable, ADM
was more medial and superior along M1, reflecting the somatotopic pattern determined via MRI
(Boldrey & Penfield, 1937; Gullapalli et al., 2001; Foesrster, 1931). Therefore our results support
the conclusion that while “the distributed character dominates in M1” an integrated and overlapping
somatotopic arrangement exists (Gullapalli et al., 2001).
4.3 Inter-Intensity Effects
4.3.1 Volume
The results of this study reflect the positive relationship between intensity and volume,
which has been established using conventional methods (Eisen et al., 1994). The increase in
amplitude, associated with higher stimulation intensities, is the result of more neurons reaching
their threshold for depolarization. The relative proportion of large and small neurons, as well as the

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degree of current spread also factor in with intensity. The quantity of larger neurons (requiring
greater stimulations to depolarize), which exceeds that of smaller neurons influences the muscle
response by increasing recruitment’s dependency on intensity to increase the amplitude of response
(Chiappa et al., 1993). The effect of current spread exhibits a positive relationship with intensity of
stimulation; higher intensities induce greater spread, resulting in a larger magnitude response via
recruitment of a larger number of motor units extending to the effector (Wassermann et al., 1993).
The same holds for the inverse; Eisen et al., credited stimulation intensities closer to threshold for a
reduction in current spread (1994). This relationship implies that lower intensities may result in
more accurate representation of control from specific neurons (although not necessarily those
directly underlying the stimulation site), but a decreased magnitude of response, resulting from
reduced recruitment.
The intensity-dependency of volume occurred proportionally across the map, scaling the
map volume without affecting the relative degree of control at a point on the map was preserve.
4.3.2 Area
Findings of this study confirm previous research using conventional methods, which have
found that the number of responsive stimulation sites increased as intensity increased, increasing
map area (Eisen et al., 1994). Cohen et al. show that an absolute intensity preferentially increases
map area in subjects with low MEP thresholds (1992). Similarly, findings of this study demonstrate
that higher threshold-adjusted intensities result in a greater area of activation. The cause of the
positive relationship observed between intensity and map size has been attributed to inhibitory
influences, transient inexcitability, and the concentration of representative motor units, which
predominate in the sub-optimal stimulation area of the periphery.
Inhibitor influences have been noted to surround the excitatory area (Mastaglia et al., 1993);
“at the borders of the area, inhibitory influences might be more prominent, thus preventing a MEP
to be evoked” (Liepert et al., 1995). Sub-optimal stimulation sites in the periphery are also more
prone to transient increases in their resting threshold, making them more difficult to stimulate from

17
lower intensities, and contributing to greater variability of peripheral responses (Eisen et al., 1994).
However, Brasil-Neto et al. have established that changes in area do not depend on changes of the
resting motor threshold for the area within the grid (1993).
Although discrepancies in average RMT within a grid are typically considered negligible for
the purpose of determining threshold-adjusted intensity for a session, groupings of neurons based
on differing thresholds has been disclosed (Kwan et al., 1985; Eisen et al., 1994). While a high
concentration of low threshold neurons has been credited for the excitability of the hot spot, the
organization of surrounding neurons based on variation in their thresholds could not be found
(Cohen et al., 1992). If higher threshold neurons predominate in the periphery, their influence on
the intensity-dependency of map size would be substantial.
The well-established intensity-dependency of area has led Brasil-Neto et al. to suggest the use
of a minimum intensity of 130%RMT to maximize reliability of maps (1992). Although results
from this study acknowledge a mild increase in variability of map size resulting from lower
stimulation intensities, the increase did not appear to be significant. Our findings further refute this
conclusion by demonstrating that the reduction in map size resulting from decreased stimulation
intensity, does not threaten the shape, or CoG of cortical representation. These findings indicate that
reliability is not significantly threatened by the use of intensity as low as 110%RMT. The reliability
of maps generated from lower intensities has also been supported by Uy et al., who used 115% to
establish reliability of their “shortened conventional method” (2002).
4.3.3 Shape
The influence of intensity on MEP amplitude, area, and volume has been well established.
This research, however, contributes to current literature by demonstrating that neither intensity, or
the variability of MEP amplitude significantly influenced the shape of a map.
4.3.4 Center of Gravity
CoG was consistently found near the center of the map, proximal to the cluster of largest
MEPs; it’s location, and the stability of it’s location were both independent of intensity. Following

18
from a proportional intensity-related scaling of volume, and independence of map shape, the
stability of CoG is not surprising. The reliability of the amplitude-weighted “epicenter” for both
upper and lower extremity muscles, despite changes of intensity (from 110% to 120%RMT), and
across mapping occasions has also been observed using conventional methods (Uy, 2002); an
acceptable level of deviation for CoG in hand muscle representations has been considered to be 1-
4mm displacement across trials (Malcolm et al., 82 2006; Miranda et al., 1997; Uy et al., 2002;
Kamen, 2004; Wolf et al., 2004).
The large range of medial-lateral and anterior-posterior coordinates of CoG across
individuals in the raw data indicated subject-specificity, also noted in other research (Eisen et al.,
1994). The stability of CoG was therefore underestimated by the raw data, due to confounding
anatomical factors. Intensit-related deviations were assessed by normalizing within-subject
variability to 120%RMT. Significance was not established for the amount of displacement of CoG
in either the medial-lateral or anterior-posterior positions; displacement was similar across all
intensities tested. Furthermore, the direction of deviation didn’t conform to a particular trend,
suggesting no predictable relationship with intensity.
One study using the conventional method found that while lateral coordinates of CoG
remained constant, anterior-posterior coordinates showed poor reproducibility for the FDI (Khander
et al., 2006). This finding was not supported in our results. The consistency of CoG across trials
indicates at least good short-term reliability.
5.0 Limitations
The accuracy of parameters represented in our results may be underestimated due to the
influence of coil position. Future research may consider the use of fixing devices to minimize (but
not prevent) changes in position during a session (Boroojerdi et al., 1999).

19
Direct translation of a map onto specific cortical locations is not feasible due to the use of a
single MRI prototype, and the current stimulator technology, which limits the sharpness of
stimulator focus (Eisen et al.1994; Catala et al. 1999).
Our results have established within session reliability of mapping parameters. However, our
single-session protocol prohibits conclusion on the long-term reproducibility. Further research
confirming the test-retest reliability of the novel protocol will promote TMS for use as a “standard
medical tool” (Hallet, 2000).
Lastly, our results reflect the effect of intensity on a healthy population; generalizability may be
limited.
6.0 Significances and Future Considerations
Both the short-term reproducibility of mapping parameters, and the replication of
established intensity-dependent relationships, compliment the robustness of the novel protocol to
generate reliable maps. This promotes it’s use in both clinical and experimental settings.
Previous research indicating transient modulations of cortical output, occurring within
60mins of testing, highlight the significance of the strong, short-term reliability of the novel
protocol established in our results (Chiappa et al., 1993). A protocol resulting in quicker data
acquisition would help reduce subject fatigue (Khander et al., 2006), stabilizing participant arousal
to improve accuracy of representation via minimizing the influence of fluctuations in corticospinal
excitability on the muscle response (Uy et al., 2002; Eisen et al., 1994; Ziemann et al., 1996).
Therefore, by reducing time of testing, the novel protocol may improve the accessibility and
cortical representation of maps produced for the continuation of relevant research.
If the technique is to be used for monitoring plasticity, it must be able to generate consistent
representations of the cortex in order to detect subtle changes in organization. The stability of map
parameters from the novel protocol indicates it’s sensitivity to detect changes in cortical-excitability
resulting in directional shifts in the amplitude weighted mean of the map. The ability to reliably
track area, volume, shape, and CoG, will improve predictions surrounding the course of motor

20
recovery, which will have useful implications in tracking motor recovery, and predicting it’s course
for decisions regarding optimal treatment options. Used along side measures of functional
improvements, TMS will offer consultation in decisions surrounding pursuing, or terminating
treatment; based on the presence of cortical responsiveness despite a lack of functional
improvements. This may open opportunities for recovery that were initially thought to be stagnant
results of an ineffective treatment.
The reliability of our maps also suggests that the “conventional scalp grid” is an
unnecessary protocol; eliminating scalp grid preparation contributes to shortening protocol time.
6.0 Conclusion
The application of TMS have progressed significantly since it’s advent, resulting in growing
pains obstructing its usefulness, as it’s design beginsto limit it’s function. While new paradigms
have been developed to satisfy various opportunities (ie. repetitive stimulation for plasticity), only
recently have the assumptions framing conventional methodology of single-pulse stimulation been
challenged and the proposition of a novel, time-efficient protocol been developed.
Manipulating intensity using the novel protocol did not threaten the efficacy of cortical
excitability maps produced using the novel protocol. Use of the novel protocol resulted in
reproduction of trends established by conventional methods between intensity and various mapping
parameters, supporting the validity, and robustness of the new paradigm. This research also
contributed to current literature by enlightening the stability of map shape. By providing evidences
supporting the reliability of the novel protocol, our results add time efficiency to TMS’s reputation
as a non-invasive, painless and safe method. These finding promote the employment of the novel
protocol for both research and clinical settings.
8.0 Acknowledgements
Mark van de Ruit and Michael Grey

21
Appendix A
Participant Information Sheet
1) Study Outline
This is a study to assess the reliability of a technique to ‘map’ the excitability of brain. This will
allow us to visualize strength of connections between specific brain areas and the muscle it
controls.
2) Invitation
You are being invited to take part in a research study. Before you decide it is important that you
understand why the research is being conducted and what it will involve. Please take time to
carefully read the following information and discuss it with others if you wish. Ask us if there is
anything that is not clear or if you would like more information. Take time to decide whether or not
you wish to participate. Please also be aware that you are free to withdraw from the study at
anytime should you change your mind, including during the study.
3) What is the purpose of the study?
The study’s aim is to test if brain excitability mapping can be reliably used to measure brain
reorganisation. If successful, we will develop the method to enable its use in the assessment of
brain reorganisation during motor learning and during rehabilitation following acquired brain injury
(e.g. stroke and traumatic brain injury).
4) Why have I been chosen?
We are looking for healthy volunteers with no history of neurological disorder in order to study the
reliability of our technique.
5) Do I have to take part?
It is your decision to participate or not. If you do decide to participate you will be asked to sign a
consent form. If you decide to participate you are still free to withdraw at any time without giving a
reason.
6) What will happen to me if I take part?
I.
When you first visit the lab, a member of our team will outline the study and address any
questions you have about the study or the techniques we use. You will have the opportunity
to see a demonstration of the techniques. We will then ask you to complete a consent form
and safety questionnaire (see attached).
II.
Each experimental session will last up to 2 hours. The study uses a technique called
transcranial magnetic stimulation (TMS) to assess the connection between your brain and a
specific muscle. An electromagnetic coil will be placed on your head over the area of your
brain that controls the muscles of the hand. The coil will click and the muscle twitches as a
result. This procedure is non-invasive and painless.
III.
You will be seated comfortably in a chair for the duration of the experiment. We will fix
recording electrodes over the skin of the arm/leg muscle(s) to be examined. You will be
asked to push a lever that controls a cursor on a computer monitor. TMS will be applied for a
maximum of 5 minutes after which time you will rest for approximately 10 minutes. The
experiment is then repeated.
IV.

22
You might be asked to come for three sessions on three different days at approximately the
same time of the day. Every session will begin with a short series of electrical stimuli to
determine the maximal level of contraction of the target muscle. This stimulation is
sometimes uncomfortable and has been described as similar to a bee sting that lasts less
than a second.
7) What do I have to do?
You will need to attend each session in order to participate in the study. However, you may
withdraw at any time during or between experimental sessions should you not wish to continue.
8) What are the possible disadvantages and risks of taking part?
All studies with human participants involve some degree of risk, as outlined below. However, we
take a variety of precautions to ensure this risk is minimised. You will need to complete a safety
screen for the TMS procedure. Whilst on the premises, staff will accompany you. Staff will monitor
the sessions closely whilst TMS is applied
9) Where can I find more information about the methods used in the study?
On the next page you will find additional information on the techniques used during this study. If
any questions remain, please do not hesitate to contact us.
10) Will my taking part in this study be kept confidential?
All information collected about you during the course of the study is kept strictly confidential. All
data will be held and analysed in the School of Sport and Exercise Sciences. All data will be kept
on computers with limited access, using coded filenames. All data will be kept on password-
protected computers with limited physical access (locked office and laboratory rooms) using coded
filenames. Access will be limited to approved and registered members of the research team. All
data is kept for a minimum of 10 years.
11) What will happen to the results of the research study?
They will be presented within the university, and may be used for conference presentations or
publications. You will not be identified in any presentation or publication.
12) Who has reviewed the study?
The Universities ethical review committee have reviewed the study protocol and associated risks.
The School of Sports and Exercise Sciences at the University of Birmingham have reviewed the
study protocol as well.
13) Contacts for further Information
Mark van de Ruit: 0121 414 8743 (MLV195@bham.ac.uk )
Supervisor: Dr. Michael Grey: 0121 414 7242
Transcranial Magnetic Stimulation (TMS)
Transcranial magnetic stimulation is used in clinical neurophysiology to study the nerve fibres that
carry the information about movements from the brain cortex to the spinal cord and the muscles.
TMS is a neurophysiologic technique that allows the induction of a current in the brain using a
magnetic field to pass the scalp and the skull safely and painlessly. In TMS, a current passes
through a coil of copper wire that is encased in plastic and held over the participant’s head. This
coil resembles a paddle or a large spoon and is held in place either by the investigator or by a
mechanical fixation device similar to a microphone pole. As the current passes through the coil it
generates a magnetic field that can penetrate the participant’s scalp and skull and in turn induce a

23
current in the participant’s brain. There is a clicking noise associated with the current passing in the
coil, but the effect of the magnetic field and the induction of current in the brain are not painful.
However, some discomfort may occur from the contraction of scalp muscles or the activation of
nearby nerves.
TMS can be used to study how the brain organizes different functions such as language, memory,
vision, or movement control – by using TMS to alter activity in a given region, we learn about the
functional role of that region. This is the approach that will be used in the current study, which will
use TMS to study how areas of the brain are related to the control of arm and leg muscles.
This technique is safe and is part of standard clinical tests in neurology in many countries
worldwide. TMS does not cause long-term adverse neurological or cognitive effects in healthy
participants. TMS effects are thought to last for less than an hour after the stimulation has been
given, and there are no known longer-lasting effects. The most common side effect is transient
tension headache resulting from contraction of head and neck musculature during the procedure,
and this usually responds to simple analgesia.
This TMS protocol has minimal risk to participants who have no contraindications (see below).
There is a very small risk of seizure associated with magnetic stimulation, however they are only a
handful of cases worldwide where this has happened and the majority of these incidents were in
early studies in which guidelines for TMS were less clear cut. This risk is primarily associated with
people who have a prior history of epilepsy, or other neurological conditions. We will exclude will
exclude you from participating in the study if you have such a history. Our study procedure follows
internationally established safety procedures.
You must not participate in the study if you have any of the following: (i) metal anywhere in the
head (including shrapnel, and screws and clips from surgical procedures) other than dental work,
(ii) cardiac pacemakers, cochlea implants and implanted medication pumps, (iii) electrodes inside
the heart which might provide a low-resistance current path to electrically sensitive tissue.; (iv)
serious heart disease, (v) increased intracranial pressure, as in acute large infarctions or trauma, (v)
a family history of epilepsy, (vi) women who think they may be pregnant.
Peripheral Nerve Stimulation (PNS)
Peripheral nerve stimulation or PNS is an electrophysiological technique used to test reflexes. It
involves electrically stimulating a nerve via surface electrodes. It is a painless technique that has
been in used clinically and in laboratories throughout the world for more than 200 years.
For this test, you will receive small electrical stimulation to your arm just below your wrist. The
stimulation will cause a small reflex contraction of muscles in your hand. This response will be
measured by recording electrode (similar to adhesive stickers) placed over a hand muscle. The area
of your hand where the electrodes will be placed may be cleaned with rubbing alcohol.
This type of stimulation has been compared to feeling a carpet shock (static electricity). The
equipment used for H-reflex testing contains safety devices to limit the chances of injuries from the
stimulation.
More information about the techniques above can be found here:
TMS
http://www.ncbi.nlm.nih.gov/pubmed/19833552
http://www.elsevier.com/locate/ifcn
PNS

24
http://www.patient.co.uk/health/Nerve-Conduction-Studies.htm
http://www.ebme.co.uk/arts/nerve/

25
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