Full text of DOI:10.1016/S0010-9452(08)70545-8

PREDICTING HAND PREFERENCE WITH PERFORMANCE
ON MOTOR TASKS
W.J. Triggs1, R. Calvanio2, M. Levine2, R.K. Heaton3 and K.M. Heilman1
1
2
(From the Department of Neurology, University of Florida, Gainesville, the Department
3
of Neuropsychology, Spaulding Rehabilitation Hospital, Boston, and the Department of
Psychiatry, University of California, San Diego, USA)
ABSTRACT
Handedness may be defined as preference or hand-differences in task performance. The
strength and significance of the relationship between hand preference and hand performance
asymmetries have been contested. To evaluate this relationship, we administered the
Edinburgh Handedness Inventory and measured asymmetries in finger tapping, Purdue
Pegboard, and grip strength in 30 subjects who prefer their right hand and 30 subjects who
prefer their left hand. Hand asymmetries in finger tapping, Purdue Pegboard, and grip
strength each predicted hand preference scores. However, a multiple regression equation
best predicted hand preference by using performance of each task. Hand asymmetries in
finger tapping correlated strongly with asymmetries in Purdue Pegboard performance, but
neither of these asymmetries correlated strongly with asymmetries in grip strength. These
findings indicate that hand preference and asymmetries in motor proficiency are strongly
related, but suggest that preference and proficiency for different aspects of motor
performance may be independently lateralized.
INTRODUCTION
Handedness is the most obvious human behavioral asymmetry. The term
handedness, however, may refer either to hand preference or to the asymmetrical
performance of manual tasks (Woo and Pearson, 1927; Barnsley and
Rabinovitch, 1970; Provins and Cunliffe, 1972; Kimura and Davidson, 1975;
Annett, 1976; Peters and Durding, 1978; Johnstone, Galin and Herron, 1979;
McManus, Kemp and Grant, 1986; Harrison and Pauly, 1990; Shimoyama,
Ninchoji and Uemura, 1990; Steinmetz, Volkmann, Jancke et al., 1991; Provins
and Magliaro, 1993). Whereas there is evidence that preference and relative
manual proficiency are directly related, the relationship between these two
measures of handedness remains controversial. When subjects are grouped
according to the strength of hand preference, a strong correlation has been
repeatedly demonstrated between hand preference classification and hand-
differences in the performance of a peg-moving task (Annett, 1970b, 1976,
1985). A similar relationship exists between hand preference and relative
proficiency in finger tapping (Peters and Durding, 1978, 1979). These
associations, and the fact that the distributions of relative manual proficiency
were found to be unchanged during childhood (Annett, 1970a; Peters and
Durding, 1978), led Annett (1985) to propose that one hand may be preferred
over the other because it is more adept. Annett (1992) has since verified the
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relationship between hand preference classification and peg moving asymmetry
using a series of pen and paper tasks designed to resemble peg moving. Annett’s
position, however, has been challenged (Flowers, 1975; Todor and Doane, 1977;
Johnstone et al., 1979; Borod, Caron and Koff, 1984; Porac and Coren, 1981;
Provins and Magliaro, 1993; Bryden, Ardila and Ardila, 1993; Peters, 1995).
Porac and Coren (1981) suggested that preference and asymmetrical task
proficiency are fundamentally different entities. These authors based this position
on two observations. First, they noted that correlations between hand preference
and hand performance asymmetries are often of only modest size. Second, they
emphasized that preference and proficiency have distinct population distributions.
Whereas the population distribution of hand preference scores is best described
by a bimodal J-shaped distribution (Annett, 1970b), relative manual proficiency
is typically distributed normally with a mean shift towards superior performance
of the right hand (Woo and Pearson, 1927; Annett, 1972). However, Annett
(1972, 1985) has indicated that the J-shaped distribution of preference can be
superimposed on the normal distribution of proficiency asymmetry when the
distributions are accurately represented [compare Figure 2.1 of Porac and Coren
(1981) and Figure 13.4 (a) of Annett (1985)].
Bishop (1989) examined the relationship between preference and task
proficiency with mathematical modeling. By assuming that hand preference is
exponentially related to relative manual proficiency, Bishop developed a model
that accounted for the modest size of correlations between preference and
asymmetry in motor proficiency, as well as the differences in the distribution
patterns of hand preference and asymmetrical proficiency noted by Porac and
Coren (1981). Bishop (1989) concluded, however, that different aspects of motor
proficiency (i.e. speed, strength, etc.) may have differential importance in
determining hand preference for different manual tasks.
Hand preference has traditionally been measured using handedness
inventories, quantifying hand preference for the performance of a variety of
manual tasks. Since preferences for different types of manual tasks may be
independently lateralized (Healey, Liederman and Geschwind, 1986; Steenhuis
and Bryden, 1989), we posited that the correlation between hand preference and
performance asymmetry would be increased by measuring asymmetries in
multiple manual tasks. Therefore, we examined the strength of the correlation
between hand preference and hand-differences in multiple manual tasks (finger
tapping, pegboard dexterity and grip strength) using regression analysis.
To determine if performance asymmetries may be related to shared neural
substrates, we also examined relationships between the performance of different
manual tasks. For example, Lawrence and Kuypers (1968) demonstrated in
monkeys that the corticospinal system is critical for performing independent
finger movements. Finger tapping and picking up a peg require some degree of
independent finger movement precision. Therefore, hand asymmetries associated
with these two tasks may be related to asymmetries of the corticospinal system
(Triggs, Calvanio and Levine, 1997). Because hand-differences in both of these
tasks may be based in part on corticospinal asymmetries, we predicted that
asymmetries in finger tapping speed would correlate more strongly with
asymmetries in pegboard dexterity than they would with strength asymmetries.

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681
MATERIALS AND METHODS
Subjects
The subjects of this investigation were 60 healthy volunteers between 21 and 57 (mean
37 ± 9) years of age recruited according to preferred writing hand to include 30 right-
handers without prior history of left-handedness and 30 left-handers. These subjects were
used in a previous publication (Triggs et al., 1997). The two groups contained equal
numbers of men and women and most subjects were recruited from hospital staff. None of
these subjects had a history of brain injury or any medical condition (e.g. musculoskeletal
injury, arthritis) expected to affect performance on the study tasks. All subjects had
completed high school, and most had completed at least 4 years of college. Each subject
participated after giving informed consent.
Tests and Procedure
Hand Preference
We quantified hand preference using the Annett Handedness Inventory, as modified by
Briggs and Nebes (1975), and the Edinburgh Handedness Inventory (Oldfield, 1971). These
inventories record self-reported hand preference for a series of motor tasks as ‘always right’,
‘usually right’, ‘either’, ‘usually left’, and ‘always left’. Scores on Briggs and Nebes (1975)
version of Annett’s Handedness Inventory range from – 24 (all left) to + 24 (all right). Scores
on the Edinburgh Handedness Inventory range from – 100 (all left) to + 100 (all right). In a
previous report, Triggs et al. (1997) excluded from analysis the Edinburgh Inventory question
regarding the hand held at the top of a broom while sweeping for purposes of classifying
subjects as having consistent or nonconsistent hand preference. In the present report, we
quantified hand preference using raw inventory scores. However, we verified that in no
instance would removing the broom item have altered interpretation of the results.
Wrist-Finger Speed
We measured wrist-finger speed by asking subjects to use their index finger to tap the
‘7’ key of an IBM-compatible computer (Gateway 2000, North Sioux City, SD) running
WordPerfect (WordPerfect Corporation, Orem, UT). Subjects were asked to tap as rapidly
as possible during three 10 s trials with each hand. We derived right hand and left hand
scores from the total number of ‘7’s’ tapped correctly with each hand over the three trials.
Subjects were prevented from seeing the score of each hand on this task.
Finger Precision
We measured the precision of finger movements using the Purdue Pegboard (Tiffin,
1968). Subjects were asked to remove small metal pegs from a well and place them, one
by one, into a vertically oriented row of holes. Subjects practiced the task with each hand
prior to testing. Subjects were then asked to place as many pegs as possible during three 30
s trials with each hand. We derived right hand and left hand scores from the total number
of pegs placed correctly with each hand over the three trials.
Static Strength
We measured static strength with a hand-held dynamometer. Subjects were given three
trials with each hand. We derived right hand and left hand scores from the mean peak grip
force reached by each hand over the three trials.
Data Analyses
We transformed performance measures (finger tapping, pegboard, and grip strength
scores) into hand-difference scores for each subject’s right and left hands. Hand-difference
scores for motor performance are not necessarily independent of the overall level of

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performance. However, in no instance did correcting hand-difference scores to account for
the overall level of performance alter interpretation of the results. We used linear multiple
regression modeling to examine the relationships between hand-differences in manual
performance and preference. We used Pearson-product moment correlation coefficients to
examine the relationships among hand-differences in manual performance.
RESULTS
Hand Preference
In right-handed subjects, scores on the Annett Handedness Inventory ranged
from + 10 to + 24 (mean + 20 ± SD 4) and scores on the Edinburgh Handedness
Inventory ranged from + 50 to + 100 (mean + 90 ± SD 13) In left-handed
subjects, scores on the Annett Handedness Inventory ranged from – 24 to + 20
(mean – 14 ± SD 11) and scores on the Edinburgh Handedness Inventory ranged
from – 100 to + 60 (mean – 68 ± SD 38). Scores on the two hand preference
inventories were strongly correlated (r = 0.98; p < 0.0001).
Analysis of Handedness Effects on Task Performance
The results of evaluation of handedness effects on task performance in these
subjects has been reported previously (Triggs et al., 1997). In brief, analysis of
variance for each task showed a highly significant two-way interaction between
the hand tested and handedness, such that the right hand performed better than
the left hand in right-handers and the left hand performed better than the right
hand in left-handers (p < 0.0001 for each task). Details of the effects of
handedness on task performance are provided in Table I.
TABLE I
Effects of Handedness on Task Performance
Left-handers
(n = 30)
Right-handers
(n = 30)
Left
hand
Right
hand
Left
hand
Right
hand
Motor task
Finger-tapping
Purdue Pegboard
Grip Strength
197 ± 22
50 ± 5
23 ± 6
186 ± 20
46 ± 5
22 ± 6
191 ± 26
47 ± 5
22 ± 6
206 ± 23
51 ± 4
23 ± 6
Note. This table contains Finger Tapping scores expressed as the sum of taps in three 10 second trials, Purdue
Pegboard scores expressed as the sum of pegs placed in three 30 second trials, and Grip Strength scores expressed as
mean peak force (kg) reached over three trials. All data are expressed as mean ± standard deviation.
To examine the relationship between hand preference and asymmetrical task
performance, we computed the correlations which appear in Table II. The table
is divided into two sections and illustrates the results using scores on both the
Annett and Edinburgh Handedness Inventories as separate dependent variables.
The first row of each section of the table shows the Pearson-product moment
correlation coefficients for the relationships between hand preference and hand
asymmetries in the performance of each of the three tasks, using handedness

Motor performance predicts hand preference
683
TABLE II
Predicting Preference from Performance
Finger
Tapping
Purdue
Pegboard
Grip
Strength
Predictors
R
Annett Handedness Inventory
(Briggs and Nebes, 1975)
r
β
0.69‡
0.302*
0.69‡
0.314*
0.60‡
—
0.348†
0.80‡
Edinburgh Handedness Inventory
(Oldfield, 1971)
r
β
0.70‡
0.286*
0.73‡
0.58‡
—
0.377†
0.309†
0.81‡
Note. This analyses used each subject’s scores on the Annett and Edinburgh Hand Preference Inventories as dependent
variables. Independent variables included the difference in the performance of each subject’s right and left hands in
each manual task. The table shows the Pearson-product moment correlation coefficient (r) for the correlation of
preference with asymmetry in the performance of each motor task. The table contrasts the results of simple regression
analyses with the correlation coefficient (R) and standard coefficients (β) obtained with multiple regression analysis
using asymmetries in all three motor tasks as independent variables.
* = p < 0.03; † = p < 0.005; ‡ = p < 0.0001.
inventory (Annett or Edinburgh) scores as the dependent variable and
performance asymmetries in Finger Tapping, Purdue Pegboard, and Grip
Strength as independent variables. For each of the two handedness inventories,
each of the three correlations is significant and all are of about the same
magnitude. The second row of each section of the table shows the multiple
regression equation in which the dependent variable, Handedness Inventory
(Annett or Edinburgh) scores, is related to hand asymmetries in Finger Tapping,
Purdue Pegboard, and Grip strength as simultaneously entered independent
variables. The standardized coefficients (β) for all three proficiency asymmetry
measures proved to be significant and of approximately the same magnitude.
The resulting multiple regression equation accounted for R2 = 64% (Annett
Inventory) and 66% (Edinburgh Inventory) of the variance in hand preference
for all subjects combined. When this regression equation was used to predict
scores on the Annett Handedness Inventory, 26 of 30 (87%) left-handers and 27
of 30 (90%) right-handers (88% of all subjects) were classified correctly. For the
Edinburgh Handedness Inventory, 27 of 30 (90%) left-handers and 28 of 30
(93%) right-handers (92% of all subjects) were classified correctly.
To examine the relationship between asymmetries of task performance, we
computed the correlations which appear in Table III. Figure 1 illustrates these
Pearson-product-moment correlations among hand asymmetries in manual
TABLE III
Correlations of Hand-Differences in Manual Performance
All subjects (n = 60)
Right-handers (n = 30)
Left-handers (n = 30)
Tap
Peg
Tap
Peg
Tap
Peg
Peg
Grip
0.78‡
0.41†
—
Peg
Grip
0.57†
0.40*
—
0.29
Peg
Grip
0.50†
– 0.18
—
– 0.09
0.42†
Note. This table shows levels of correlation (r) among right and left hand differences in Finger Tapping speed (Tap),
Purdue Pegboard performance (Peg) and Grip Strength (Grip).
* = p < 0.03; † = p < 0.005; ‡ = p < 0.0001.

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Fig. 1 – Correlations between hand-differences (right hand – left hand) in Finger Tapping,
Purdue Pegboard and Grip Strength in 30 left-handed (●) and 30 right-handed (❍) subjects. Each
scatterplot shows regression lines for all subjects (solid line), as well as separate regression lines for
left-handed (dashed line) and right-handed (dotted line) subjects. See Table III for correlation
coefficients and significance levels.

Motor performance predicts hand preference
685
performance. Both the table and figure show these correlations for all subjects,
as well as for right-handers and left-handers analyzed separately. These data
illustrate three main findings. First, the data show highly significant correlations
between finger tapping and Purdue pegboard asymmetries scores in all subject
classifications. This association between finger tapping and peg moving
asymmetry is greater than between either of these asymmetries and asymmetry
of grip strength. Second, the data show that grip strength asymmetry is
positively related to finger tapping asymmetry in right-handers. Third, the data
show that grip strength asymmetry is unrelated to finger tapping or peg moving
asymmetry in left-handers.
DISCUSSION
Porac and Coren (1981) reviewed correlations between hand preference and
relative manual proficiency of the size recorded in the top row of Table I – i.e.
correlations around 0.60 – and concluded that preference is at best only
marginally related to proficiency. The variance in hand preference accounted for
by the correlations in the present study ranges from (0.6)2 = 36 to (0.7)2 = 49%.
These authors assumed, however, that hand preference is relatively constant
across different tasks. In contrast, an individual’s preference for performing
different types of manual tasks may vary according to the type of task (Healey et
al., 1986; Steenhuis and Bryden, 1989; Peters and Pang, 1992). In our analysis,
we questioned the assumption that hand preference is unidimensional. Using a
multiple regression model that included hand-differences in three tasks, we were
able to account for almost two thirds of the variance in hand preference inventory
scores. This is a substantial proportion of the variance in hand preference to be
accounted for by asymmetries in the performance of only three tasks.
Furthermore, this multiple regression model used asymmetrical task performance
to correctly classified dichotomized hand preference in nearly 90% of our
subjects. The results of this analysis are inconsistent with the view of Porac and
Coren (1981) that preference and proficiency may be orthogonal dimensions of
handedness. Instead, our results suggest that preference is strongly related to
hand asymmetries in task performance. However, hand asymmetries in finger
tapping, peg moving, and grip strength tasks each contributed independently to
predicting preference inventory scores, suggesting that hand preference may be
related to asymmetries in multiple neural substrates. These results are consistent
with a modification of the hypothesis of Annett (1985), namely that asymmetries
in multiple dimensions of manual proficiency may contribute to the development
of hand preference (Bishop, 1989). Performance of simple tasks such as finger
tapping and peg-placing improves during childhood (Annett, 1970a; Peters and
Durding, 1978; Curt, Maccario and Dellatolas, 1992; Carlier, Dumont, Beau et
al., 1993) and with prolonged practice (Annett, Hudson and Turner, 1974; Peters,
1981), but the relative performance asymmetry between the two hands remains
unchanged, consistent with this hypothesis.
We found that asymmetries of finger tapping and peg moving were highly
correlated. These results appear to be inconsistent with Peters (1995)

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interpretation of the relationship between preference and skill. Peters (1995)
hypothesized that preference induces asymmetry in skill as a result of increased
use of the preferred hand. Peters (1995) suggested that the experience relevant to
the development of skill asymmetry is task-dependent, and therefore predicted a
poor correlation between asymmetries in finger tapping and peg moving. In
contrast to Peters’ prediction, we found that hand asymmetries in finger tapping
and peg-placing were highly correlated. Although this finding may suggest that
hand preference results from, rather than determines, skill asymmetry, it remains
possible that experience is shared across seemingly independent tasks (e.g. finger
tapping and peg moving).
There is no a priori reason to expect that hand asymmetries in finger tapping
would be related to hand asymmetries in pegboard dexterity, and these two types
of manual tasks have been identified through factor analysis of individual
differences as independent dimensions of manual proficiency (Fleishman and
Hempel, 1954). Whereas a high correlation between hand asymmetries in finger
tapping and pegboard performance would not be anticipated, the high correlation
we observed suggests that both tasks may depend in part on a common neural
substrate. Finger tapping of one key and peg moving may depend upon
independent finger movements and precision of finger movement, respectively.
Since the corticospinal tract is a critical substrate for independent finger
movement (Lawrence and Kuypers, 1968) and for precision grip (Muir and
Lemon, 1983), we speculate that asymmetries in finger tapping and pegboard
dexterity are related, at least in part, to asymmetry in the corticospinal system.
Support for this postulate comes from the observation that in these same
subjects, Triggs et al. (1997) found a high correlation between hand asymmetries
in both finger tapping and peg moving tasks with hand asymmetries in the
threshold for corticospinal activation with transcranial magnetic stimulation.
Although lateralized asymmetries in finger tapping, pegboard dexterity and
grip strength each correlated significantly with preference inventory scores, grip
strength, in contrast to finger tapping and peg-placing tasks, does not require
independent or precise control of the fingers. Thus, the corticospinal system is
probably not an important substrate for synergistic flexion of the fingers in a
power grip. For example, Lawrence and Kuypers (1968) reported that monkeys
lost the ability to make independent finger movements after pyramidotomy, but
could still flex the digits together strongly in a power grip. Furthermore, large
cortical motoneurones may be active during application of low levels of finely
controlled force (e.g. during a precision grip), but may become paradoxically
inactive during a power grip (Muir and Lemon, 1983) or at high force levels
(Fetz and Cheney, 1987). We speculate that hand asymmetries in grip strength
were less strongly correlated with hand asymmetries in either finger tapping
speed or finger precision because hand asymmetries in grip strength are
independent of asymmetry in the corticospinal system.
Annett (1985) has proposed that the normally distributed continuous
differences in the strength and skill of the right and left hands are the result of
numerous small accidental influences on the development of the two sides of the
body (e.g. larger muscles, more efficient neuromuscular coordination). Annett
has hypothesized that superimposed on this distribution of manual differences is

Motor performance predicts hand preference
687
an underlying genetic influence producing a systematic bias towards increased
strength and skill on the right side of the body (the Right Shift). In contrast,
Annett has hypothesized that there exists no such systematic bias favoring the
development of strength and skill on the left side. The present results appear
consistent with Annett’s hypotheses. We have suggested that finger tapping and
peg moving asymmetries are strongly associated because they depend in part on
corticospinal asymmetry as a common neural substrate. However, we found that
grip strength asymmetry was still significantly associated with finger tapping
asymmetry in right-handers, but was unrelated to finger tapping asymmetry in
left-handers. To the extent that asymmetries of strength and finger tapping
reflect functional asymmetries in distinct neural substrates (Lawrence and
Kuypers, 1968), the present findings provide support for the existence of an
underlying bias favoring the development of the right hand in right-handers and
the absence of such a bias favoring the left hand in left-handers.
The idea that performance asymmetry may influence the development of
hand preference does not reduce the possibility that hand preference is
multifactorial in origin. Our finding that behavioral asymmetries strongly
correlate with preference does not preclude other factors from being important in
the development of hand preference. For example, Liederman (1983) suggested
that “[handedness in the infant] is due to the conjoint influence of many factors
that themselves can operate relatively independently, rather than a single
mechanism that reveals itself over time.” We postulate that relatively lower-
order structures may provide the substrates of asymmetries in simple manual
abilities (Triggs, Calvanio, Macdonell et al., 1994). In contrast, mechanisms
residing in higher-order structures undoubtedly contribute to the development of
asymmetries in more complicated tasks or skills: activities which entail the
synthesis of elementary manual abilities through practice and learning (Schmidt,
1988). Activity in such higher-order substrates may be particularly likely during
the acquisition of new skills (Pascual-Leone, Grafman and Hallett, 1994).
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William J. Triggs, MD, Department of Neurology, Box 100236 UFHSC, Gainesville, FL 32610-0236, USA.
E-mail: triggswj@medmac.ufl.edu
(Received 22 October 1999; accepted 24 March 2000)