Physiology & Behavior, Vol. 66, No. 1, pp. 63–72, 1999
© 1999 Elsevier Science Inc.
Printed in the USA. All rights reserved
0031-9384/99/$–see front matter
PII S0031-9384(99)00026-8
Imagery Quality Estimated by Autonomic
Response Is Correlated to Sporting
Performance Enhancement
R. ROURE,* C. COLLET,* C. DESCHAUMES-MOLINARO,* G. DELHOMME,†
A. DITTMAR† AND E. VERNET-MAURY*
*Université Lyon I. Emotion et Vigilance, Gis C.N.R.S. Sciences de la cognition, and
†Microcapteurs Microsystèmes Biomédicaux, C.N.R.S. L.P.M., INSA Lyon, Bâtiment 401,
20 avenue Albert Einstein, F. 69621 Villeurbanne Cedex, France
Received 8 June 1997; Accepted 3 September 1998
ROURE, R., C. DESCHAUMES-MOLINARO, C. COLLET, G. DELHOMME, A. DITTMAR AND E. VERNETMAURY. Imagery quality estimated by autonomic response is correlated to sporting performance enhancement. PHYSIOL
BEHAV 66(1) 63–72, 1999.—It is now well established that mental imagery practice improves motor skills, but performance
efficiency depends on many factors: the main one being individual differences. The aim of this study is to evaluate performance improvement with imagery quality estimated during ANS recording. Volleyball training (“receiving serve”) afforded
us the experimental paradigm. Subjects were required to pass an opponent’s serve to a given team mate. The receiver’s performance was evaluated from the accuracy of his pass to the targeted team mate. From these first test results, subjects were
divided into two equivalent groups: imagers and controls. After mental practice the two groups were submitted to a posttest
similar to the first one. During the pretest, posttest actual practice as well as the last session of corresponding mental rehearsal, six autonomic parameters were continuously recorded. Furthermore, and for the first time, a grade obtained from
four different aspects of this response permits qualitative evaluation of each subject’s mental imagery. This estimation, based
on the well-established link between performance and autonomic response, is validated by the fact that good correlation was
obtained between this grade and the performance improvement of each of the “imager” group subjects. © 1999 Elsevier
Science Inc.
Autonomic nervous system
Mental practice
Performance improvement
analogy in information processing between imagery and perception (22,23,37,38,51). Visual imagery and visual perception
activate the same cognitive processes; this could explain the
interferences observed in subjective experiments (19). Many
blood-flow studies show an increase in regional cerebral
blood flow (rCBF) in the superior occipital and in the parietal
cortex during visual imagery tasks (28). During motor imagery, rCBF increase is measured in the prefrontal cortex and
the supplementary motor area (33,47). Results from Yue and
Cole (68) add to existing evidence for the neural origin of
strength increases that occur before muscle hypertrophy.
From these authors these force gains appear to result from
practice effects on central motor planning/programming. This
proposal has been developed by Jeannerod (34) and con-
MOST behavioral cognitive correlates of motor imagery
(M.I.), so-called mental practice in sports, show that M.I. enhances motor learning and motor skills (21). Various empirical and theoretical explanations on how imagery facilitates
performance have been advanced in literature.These cases include positive responses; the image will be more vivid and
controllable, and should result in psychophysiological changes
in the body and, thus improve performance. What is known
about these changes?
Several studies agree that imagery activity causes a break
in alpha waves (26). The occipital and temporal regions become active during motor imagery (19). Moreover, corresponding centers are activated when a visual cue or movement is imagined (20). Several authors accept functional
Requests for reprints should be addressed to Dr. E. Vernet-Maury, Microcapteurs Microsystèmes Biomédicaux, INSA Lyon, Bâtiment 401, 20
avenue Albert Einstein, 69621 Villeurbanne Cedex , France.
63
64
ROURE ET AL.
firmed by Vogt (65). Evidence that motor imagery and motor
control share some modality-specific, neural representations
are clearly supported by tomography measurements of cerebral blood flow (10). Neverthless, research dealing with mental imagery improvement concomitant to physiological responses is still scarce, and Murphy’s review (42) stated that it
is presently difficult to find studies in the sport psychology literature that include physiological measurements.
Since Lang (40) in his “bioinformational theory of emotional imagery,” it has been well known that autonomic nervous system (ANS) effectors are also activated by imagery.
Vegetative activation may occur in many situations involving
cognitive or affective arousal, including mental imagery and
also motor imagery. Jones and Johnson (35) objectivate that
autonomic effectors are also activated by imagery: heart activity increases during mental effort. Decety et al. (9) showed
that cardiac and respiratory activity increase during mental
simulation of locomotion; this measurement revealed a covaration of heart and pulmonary ventilation with the degree of
imagined effort. Deschaumes-Molinaro et al. (13,14) objectivated a correlation between mental imagery and autonomic
nervous system response patterns during real shooting, mental concentration before shooting, and mental imagery shooting. These results evidenced that the ratio between real and
imagined autonomic responses is correlated to skill performance value.
Methodological and conceptual progress on the autonomic
nervous system (ANS) functioning as a reactive and specific
system (18,39,58,66), enables this to be considered a useful
tool in the analysis of the cognitive process (46) on performing, for example, a motor skill. Original sensors and indices
developed by the Vernet-Maury/Dittmar team (17) have
made it possible to apprehend ANS functioning in real time.
Continuous and simultaneous measurement of ANS effectors within the same group of subjects during two situations
bearing on physical practice and imagination of this practice
will make it possible to bring out the impact of imagery on
overall autonomic responses. As autonomic response is noninvasive and may be continuously recorded, it may give information on the quality of imagery practice. Indeed, mental
practice efficacy depends on the nature of the task (52), the
skill-learning level (1,50), and on individual capacities (12,29,
32). The latter factor is difficult to characterize, unlike the
first. For this reason, individual imagery quality has to be estimated. We hypothesize that ANS responses recorded in real
time during mental practice may help to objectivate the quality of mental practice. The aim of this study is to correlate performance improvement with imagery ability estimated during
ANS recording.
Volleyball training (“receiving serve”) afforded us the experimental paradigm and will help us to answer the following
questions: Is it possible to follow the impact of imagery during
mental practice sessions? Could imagery quality estimated
through autonomic response be correlated to performance
improvement? This study is concerned with individual differences in the ability to evoke ANS responses in mental practice, particularly those that are known to vary in a motor task
(4,14,49).
METHOD
Protocol—Experimental Paradigm: A Theee-Stage Study
The first real experiment: the “pretest.” Twenty-four students,
9 females, and 15 males, aged between 20 and 32 years (mean
23), during physical training (volleyball) had to perform a
task that was part of the game. Subjects were intermediatelevel volleyball players.
Subject A receives the ball from server B, and has to pass it
to player C (target) standing about 5 meters in front of him.
The operator gives the start signal when the recording apparatus is ready. Player C moves to a “neutral point.” This student, who sits outside the game area between two trials,
moves in and stands close to the net. Player B serves in a standardized movement (“low serve”) trying to reach a virtual
point between the net and receiver A.
After the serve, the target player must be motionless when
coming into contact with the ball from the receiver. He may
be considered a “setter” in volleyball terms.
Movement imagery questionnaire (MIQ). Before the first
test (pretest), the 24 subjects answer the M.I.Q. (Movement
Imagery Questionnaire) of Hall and Pongrac (30). The M.I.Q.
measures individual differences in both visual and kinesthetic
imagery of movement: this is considered a suitable instrument
for measuring imagery ability (24).
Mental practice. Twenty-four subjects were randomly assigned to the first and second groups, which contained in
equal numbers “high” and “low imagers” (from M.I.Q. results) and “skilled and less-skilled players” (from the results
in the volleyball pretest). The first group was called “imagers,” and the second, “nonimagers.” The 12 subjects of the latter were worked at a neutral task during the period (about 2
months) between the pre- and posttests. This task consisted of
“social” relationships with the experimentalist: a 30-min conversation in a school room. Imagers’ practice was submitted
to a 30-min session, three times a week during the 2 months
between the two tests. These 12 imagers listened to a taperecording that contained the remaining imagery and these
were practiced through 20 mental rehearsal sessions. Imagery
assessments were conducted collectively in a school room.
Subjects were seated in comfortable chairs and listened to
prerecorded instructions from an audio tape. More upon and
after a brief overview of procedures, subjects heard the amplified sound of the volleyball serve strike through 12 trials. The
mental instruction consisted of “seeing” and “feeling” themself intercepting the ball using the forearm strike technique,
directed above the net and toward the “target player.” Serve
strikes occurred at intervals of 40 s, reproducing the lapse of
time between two real trials during physical tests. Twenty
mental rehearsal sessions took place between the two tests.
During the last session, before the posttest, autonomic nervous system recordings of 12 mental practice trials were carried out for each imager.
The last real experiment: the “posttest.” The 24 students performed under the same conditions as during the first experiment (“pretest”).
After the pretest, the 24 subjects are classified according to
their volleyball ability levels: “skilled players” are those who
are successful in the task: between 50 and 75% successful trials; “less-skilled players” are those who only perform between
20 and 50% successful trials.
Pre- and posttest: performance estimation. Four different
ways of receiving serve make it possible to quantify subject
A’s performance (scores from 0 to 3). “3” is a perfect reception: the target-player receives the ball easily at eye level, like
a setter in the volleyball game. “2” is a moderate reception:
the setter has to make an arm movement to reach the ball. “1”
is a poor reception: the target player has to make a step to receive the ball. “0” is an unsuccessful trial: the setter cannot
reach the ball.
AUTONOMIC RESPONSE AND SPORTING PERFORMANCE
Each subject performs 30 trials. Each trial is separated
from the next by a break that is never less than 20 s. The overall experiment lasts around 50 min.
Correction coefficient: subjects’ varying levels of skill
meant that we had to balance results (in a way to obtain a
weighted index) to take into account their success rating during the pretest. It is a fact that meaningful enhancement is difficult to obtain when starting from an already high level of
success (around 70%), while it is easy to reach high enhancement in cases of weak initial performance (around 10%).
This being so, the performance (i.e., enhancement in the
number of successful passes between the two tests) of subjects
obtaining lower than 30% success scores in comparison with
the pretest, was divided by 2.
Subjects with average performance (30 and 60% successful
passes) in comparison with the pretest were granted their actual scores.
Enhancement of already high scores (over 60% good
passes during the pretest) was multiplied by 2.
This definition of a correction coefficient resulted in the
formation of four subject groups: 1) subjects 1 and 2 strongly
enhanced their performance between the two tests (around
50%); 2) subjects 3, 4, 5, and 6 did better by some 30%; 3)
subjects 7 and 8 enhanced by 20%; and 4) subjects 9, 10, 11,
and 12 raised performance by a mean 5%.
Recapitulative Table 1 takes account of this weighting operation, showing each subject’s score, initial and multiplied.
ANS Recordings
Phasic ANS responses. Six autonomic parameters of three
different kinds were selected to be quantified: 1) electrodermal response: skin potential and resistance; 2) thermovascular
parameters: skin blood flow and skin temperature; and 3) cardiorespiratory parameters: instantaneous heart rate and respiratory frequency.
65
Potential responses. Skin potential was recorded using
Beckman self adhesive 78 mm2 electrodes. Electrode positioning was in compliance with traditional recommendations (25).
The active electrode was placed on the hypothenar eminence
of the subject’s nondominant hand, after alcohol–ether cleaning of the skin. The reference electrode was placed 10 cm
higher on the wrist. Signal processing for electrodermal potential variations was carried out using the SYDER code (16),
which permitted classification of elementary responses, according to their form, sign (positive or negative), and duration. As far as potential variations were concerned, only this
index was used, the others being less satisfactory or even redundant with simultaneously recorded indices. According to
this code, three positive and three negative skin potential
forms were considered.
Resistance responses. The conductance method (constant
voltage) is mainly used, but we chose resistance (constant current), which needs less amplification; this fact being especially
advantageous in field multiparametric recordings (3). Cutaneous resistance was recorded using 50 mm2 unpolarizable
round Capsulex electrodes placed on the second phalanx of
the index and of the third digit of the nondominant hand, held
by adhesive tape. Resistance was measured with 15 mA DC
current. A new temporal index was defined because response
amplitude depends on the prestimulation value (67). A concomitant observation of thermovascular indices (59) made it
possible to define the time during which the subject “responds” to stimuli without referring to the initial value (or
tonic level). This Ohmic Perturbation Duration or O.P.D. index of skin resistance reveals the emotional load of stimulation (61). Moreover, as far as this temporal index is used, it
was demonstrated that no difference emerge between constant current vs. voltage method (63). To eliminate any interference between skin potential and resistance and other artefacts, parameters were recorded by means of a high-rate
common-rejection mode differential “isolation” amplifier
TABLE 1
PERFORMANCE ENHANCEMENT AND
AUTONOMIC ACTIVITY SCORE
Subjects
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
Number of
ANS Responses
Vigilance
Level
Anxiety
Level
Focalized
Attention
ANS Responses
Score
Performance
Improvement
10
11
11
9
9
11
8
7
6
4
4
10
10
5
10
5
5
5
0
5
210
210
0
0
0
0
22
22
0
22
22
22
0
0
22
25
0
0
1
0
0
0
1
0
0
0
0
0
20
16
20
12
14
14
7
10
24
26
2
5
12
16
8
6
8
10
6
6
3
2
1
1
S1 to S12 5 Subjects. The number of autonomie (ANS) responses are counted from skin
potential, resistance, or blood flow response: 0 5 no response; 12 5 one response to each trial.
Vigilance level: 10 5 increased activation by steps; 5 5 Regular activation; 0 5 no adjustments; 210 5 subject relaxed throughout testing. Anxiety level: 0 5 no spontaneous electrodermal activity (SA); 22 5 average SA; 25 5 high SA. Focalized attention: 2 5 sinus arythmia decrements at each response; 1 5 50% response; 0 5 no change. ANS response score:
sum of the four preceeding marks. Performance improvement: difference between post- and
pretest scores (during actual practice) taking subjects’ correction coefficient into account.
66
(Analog Devices AD 293 B). Likewise, recorder inputs were
in a different mode, and resistance circuit supply was of the
floating type. Skin resistance measurement current passed between the index and the third digit, while skin potential was
measured between the hypothenar eminence and the inner
side of the forearm (44).
Superficial skin blood flow. This was assessed using the
original Hematron patented sensor (Dittmar, C.N.R.S./
A.N.V.A.R., 1985, Brevet 85 15932). The noninvasive sensor
was placed on the skin, on the thenar eminence of the nondominant hand, with adhesive tape.
The transducer consisted of a disc 25 mm in diameter and
4 mm thick. The measuring surface in contact with the skin
was made up of two parts: the reference area at the periphery
of the disc and the measurement area, at the center of the
disc. The temperature difference between these two areas was
measured using 16 thermocouple junctions. A very low thermal-inertia flat heater was located in the central part of the
disc. A proportional, integral, and derivative device controlled the heating power in order to maintain a constant temperature difference of 28C between the central area and the
periphery. The size and shape of the heater were designed in
such a manner that a thermal field was induced in the capillary network. The power necessary to maintain the temperature difference constant depends on skin blood flow: heat was
transferred through the skin and washed out by the blood
flow. At all times, electric power was proportional to the heat
evacuated by the tissue blood flow (15). Skin blood flow variations were measured: (a) by the difference (positive or negative) between the pre- and poststimulation values expressed
in mW?cm218C21; and (b) by the duration of the oscillation
perturbation expressed in seconds.
Superficial skin temperature. This was measured by a low
inertia thermistor (10 K3 MC D2 Betatherm). A 4 mm2 sensor
was placed on the middle of the palm of the nondominant
hand with noncaustic glue. A phasic variation of less than
one-hundreath of a degree can be detected under such conditions independantly of tonic evolution resulting from outside
conditions. The amplitude and duration of responses were
measured (11).
Instantaneous heart rate. This was recorded from three silver electrodes in the precordial position. The D2 derivation
signal (the interval between two consecutive R waves) was
processed and delivered in the form of instantaneous heart
frequency. The smallest appreciable variation was 0.5 of a
beat per minute and the calibrated scale ranged from 0 to 200
beats per minute. In this way, heart rate frequency increase or
decrease is easily evidenced, and the relationship between the
stimulus impact and heart rate instantaneous response established (56).
Instantaneous respiratory frequency. This was recorded from
a low inertia thermistor (10 K3 MC D2 Betatherm), placed at
the entrance of the left nostril with hypoallergenic adhesive
tape. This thermistor was self-heated (several degrees above
ambient temperature) by its measuring current (0.5 mA). The
exhaled air cools the thermistor at each respiratory cycle. The
same signal processing as that for heart rate was used for recording instantaneous respiratory frequency. Here again,
variability was well evidenced, and unlike instantaneous heart
rate response, respiratory frequency variation was increased
by different kinds of stimuli.
Recording apparatus. This was made up of a YTSE 460
type BBC (Brown Boveri) six-channel potentiometric DC recorder fitted with an event tracer, and of an automatic synchronization appliance which cancels out temporal differ-
ROURE ET AL.
ences between the six markers. Paper width was 250 mm, and
unwinding speed was 0.001 m?s21.
A special software package was designed and developed
for rapid analysis and processing of the recorded data. The interactive software makes it possible to calculate all indices
(including waveform pattern recognition of skin potential
responses). The software features other utilities such as amplification or attenuation of signals and zooming. A digital
signal-processing library of functions was designed and added
to the software in order to allow processing of all sorts of artefacts and to filter random noise whenever present in the recorded signals (44).
ANS tonic responses. The six autonomic parameters were
recorded continuously with the same apparatus. All parameters were quantified by measurement of the prestimulation
level (just before the stimulation), and the evolution of this
value during mental practice by means of six uniformly spaced
in-time measurements.
Estimation of spontaneous activity. Electrodermal activity
evidenced between stimuli with a characteristic shape: sudden
deviation from the base line and slow return, reaching an amplitude equal to or higher than 0.2 mV (54) were counted.
Mental Imagery Quality Estimated by Autonomic Activity
Prior to mental practice recordings, subjects were observed at
rest to identify their basal levels for the six parameters under
study.
The efficacy of mental practice was evaluated from four
criteria (62) established by analysis of each individual autonomic recording as refered to overall team results, by comparing this response to the best and the poorest performances
(4,13,14,17,44,62).
The number of ANS responses in mental imagery order
represents the initial factor. Since Wallin and Fagius (66),
ANS response specificity has been widely demonstrated. The
fact that individuals generate mental images identified by an
ANS response pattern constitutes the first quantitive factor of
imagery skill. It is considered that subjects produce a mental
image if a response follows a signal within less than a second,
and has an amplitude or duration at least double that observed during their spontaneous activity while at rest (14).
This number is evaluated for a subject’s preferred variable
(39,58), and is situated on a 0–12 scale: 0 relates to no autonomic
response corresponding to an image induction; 12 indicates
that each instruction is followed by an ANS response. To be sure
that autonomic response does not correspond to the instruction, the habituation phenomenon is eliminated by recording
the autonomic activity during the very last imagery session.
Vigilance level is assessed on the basis of tonic evolution of
the four parameters (skin potential, skin resistance, skin temperature, and skin blood flow). Lindsley (41) suggested that
behavior could be regarded as varying along a continuum of
intensity, from deep sleep to extreme excitation. Arousal is a
multifaced phenomenon, including physiological but also psychological interpretations, both in actual trials and mental
imagery. The measurement of arousal (excitation level) is
shown through autonomic responses. Preferentially, skin resistance is an autonomic variable well known to be a reliable
index in predicting activation variations (6). The arousal/performance relationship is objectivated by electrodermal autonomic level fluctuation during mental imagery. Previous research conducted by the team with other models, for example,
relaxation induction (45) and with other sports disciplines
(6,60) permitted identification of conditions associated with
AUTONOMIC RESPONSE AND SPORTING PERFORMANCE
67
better performance: an adjusted and stabilized activation level
for skin potential and skin resitance, and restricted relaxation
for skin temperature and skin blood flow. To confer equal importance upon the initial factor and this one, we graded evolution between: 210—subject very relaxed according to all indications; imagery supposed ineffective. 25—subject relaxed
for one-half of test time; imagery performance supposed very
poor. 0—subject not relaxed, but his/her activation level remains stable during test time; this level should correspond to
average imagery quality. 15—subject adjusts his/her activation level at least once in the course of the imagery session
(skin resistance decrement and/or skin potential increment;
some relaxation at the thermovascular level); this should produce good quality imagery. 110: subject accentuates his/her
previous activation level by readjusting several times in the
course of the session; conditions are thus optimal for excellent
imagery quality (17).
Situational anxiety level is evaluated by the extent of spontaneous skin potential and skin resistance spontaneous activity (8) demonstrated a positive linear relationship between
spontaneous electrodermal activity and anxious moods. The
extent of heart rate and respiratory frequency response (intensity and irregularity of instantaneous frequencies) are also
taken estimated. To account for the relation between performance and arousal, new theories, as possible alternatives to
the inverted U-curve hypothesis, have recently emerged: the
catastrophe theory (31) contends that performance is determined by the complex interaction of physiological arousal or
cognitive anxiety. Cognitive anxiety is defined as the athlete’s
cognitive interpretation of this physiological arousal. A catastrophic drop in performance may occur when both physiological arousal and cognitive anxiety are high. Hardy and
Parfitt (31) found that the performance in basketball players
and bowlers dramatically deteriored under conditions of increasing physiological arousal and high cognitive anxiety. The
same performance decrements were not found under conditions of low cognitive anxiety.
This factor is assessed on the basis of a scale graduated between: 0—no spontaneous activity, cardiovascular response
average value: subject not anxious; 22—low spontaneous ac-
tivity, cardiovascular response above average value: subjects
anxiety average; 25—high spontaneous activity, excessive
cardiovascular response (values exceeding mean 1 standard
deviation): subjects anxiety detrimental to imagery quality.
Focused attention is characterized by the presence of
bradycardia and/or sinus arrythmia. Focused attention, characteristic of good performance, is objectivated by a drop in
the sinus arrythmia of the heart rate observed in instantaneous frequency form; such a decrement is often associated
with a mean-value variation in this frequency. This measurement was put forward as early as 1971 by Kalsbeek (36), as offering a mean for evaluation of mental load. Instantaneous
respiratory frequency also shows variabilities, these being (or
not being) associated with apnea (55,60).
Heart rate amplitude and variability drop by at least half
the subject’s basal level at the time of the signal. This factor is
graduated between: 0—no bradycardia or arrythmia; 11—the
presence of both is noted during 50% of responses (0 through
6); 12—the presence of both is noted during more than 50%
of responses (6 through 12).
The overall grade, “Vernet-Maury score” (62) indicating
the quality of mental imagery, is obtained from the algebraic
sum of each of the subjects’ four scores. This total is then
compared with each subject’s weighted performance grade
(correction coefficient), this being obtained by comparison of
scores between the two tests.
FIG. 1. Results of the 12 “imager” subjects. Total number of fully or
partially successful pre- and posttests (testing carried out prior to and
after equivalent activity sessions). 1–12 5 subjects’ numbers. R 5
moderate reception (score 2/3—partially successful tests); RR 5 perfect reception (successful tests, score 5 3).
FIG. 2. Results of the 12 “nonimager” subjects. Total number of
fully or partially successful pre- and posttests (testing carried out
prior to and after equivalent activity sessions). 1–12 5 subjects’ numbers; R 5 moderate reception (score 2/3—partially successful tests);
RR 5 perfect reception (successful tests, score 5 3).
RESULTS
Evolution of Performance Between Pre- and Posttests
“Imager”group. A very high difference was found between the two tests, invariably tending toward enhancement
during the second test: x2 5 20.89, p , 0.00001 (see Fig. 1).
“Nonimager” group. There was no significant difference
between the two tests: x2 5 0.71, p NS 0.8 (see Fig. 2).
Estimation of Performance Quality
By the number of ANS responses. The 12 “Imager” subjects show markedly different abilities in their production of
68
ROURE ET AL.
FIG. 3. “High imager” subject. A response is perceived at each mental induction order as observed on the subject’s preferential channel: skin potential responses here are still clear on skin resistance recordings. On the basis of this parameter, it
can be seen that tonic level (activation) changes four times during this session (trials No. 1, 5, 8, 11); skin temperature
declines then increments (trial No. 4): this subject can relax through thermovascular response. At this recording speed,
sinus arythmia and bradycardia changes are not easily evidenced (see, however, trials No. 1, 4, and 6) in instantaneous heart
rate and respiratory frequency. y-axis: time in minute.
AUTONOMIC RESPONSE AND SPORTING PERFORMANCE
69
FIG. 4. “Poor imager” subject. Only during trials No. 1, 2, and 5 are responses evidenced on skin potential recordings. Skin resistance recording
evidences an increment in tonic level from trial No. 2 and especially between trials No. 5–13: subjects are relaxed. Skin temperature recording
evidences the opposite tonic response to that observed in “high imager” subjects. Values increment initially (trials No. 1–7) then no longer
change. No sinus arythmia and no bradycardia are observed in instantaneous heart rate. y-axis: time in minutes.
70
ROURE ET AL.
characteristic ANS responses at each signal. From 12 inductions, between 4 and 11 responses are obtained (mean 6 sd 5
8.2 6 2.7).
By the vigilance and activation level. Two groups of subjects were obvious. Highly aroused subjects (score 5 to 10) undergo a decrease in skin resistance level during mental sessions and an increase in skin potential level (or another
autonomic parameter—skin temperature or skin blood flow—
according to the concept of preferential channel (39),
throughout the test (two subjects) or according to two or
three ajustments (five subjects). Subjects with low arousal
(score 0 to 210), conversely undergo an increase in skin resistance level and a decrease in skin potential level (five subjects).
By the anxiety level. In this group of subjects, the anxiety
level is low or average (mean 6 5 21.4 6 1.5) except the subject 12 (m 5 5).
By the focused attention level. The latter remained stable
(mean 6 5 0. 16 6 0. 4) in our experiment, with the exception
of two subjects: subject 1, m 5 1, subject 2, m 5 1. For this
group of intermediate level players, this index is weakly discriminant in the qualitative definition of imagery.
Correlation Between Imagery Quality and Performance
Performance is strongly correlated to ANS response: r 5
0.79, p 5 0.0019.
Overall results are summarized in Table 1. Figures 3 and 4
illustrate a “high” (grade 5 120) and a “poor” (grade 5 24)
autonomic recording imager.
DISCUSSION
These results can be considered an objective demonstration of the proposal submitted by Vealey and Walter (57): if
imagery is considered a skill, we can say that sportsmen differ
in their ability to develop “vivid” and “controllable” images.
Just as sportsmen differ in physical skills, they will differ in
their ability to develop “vivid and controllable” images. Although autonomic measurements were proposed to characterize specific behavioral aspects, for instance, Fowles et al. (25)
have argued that heart rate is a better measure of behavioral
activation while skin conductance is better as a measure of
behavioral inhibition. Up to this time, it was not possible to
evaluate these individual differences: now, neurovegetative
transcribing of cognitive processes (5) makes it possible to understand response characteristics and to assess their quality.
Indeed, as previously put to the fore (13,14), these results confirm that it is possible, by inference, to follow mental practice
in real time, through its emotional component estimated by
multiparametric analysis of the autonomic response. Furthermore, and for the first time, a grade obtained from four different aspects of this response permits qualitative evaluation of
each subject’s mental imagery. This estimation based on the
well-established link between performance and autonomic response is validated by the fact that good correlation was obtained between this grade and the performance improvement
of each of the “imager” group subjects. It should be noted
that this performance improvement was not evidenced in the
control group as previously demonstrated (21), but this was
established for the first time on an opened task, thus general-
izing the efficiency of imagery. Although well demonstrated,
this relationship was evidenced as very different from one
subject to another. The qualitative assessment of mental imagery makes it possible to understand these wide individual
differences, as scores obtained range from 26 to 120. It is obvious, in view of the new theory on the importance of bodily
response, that some subjects try to perform imagery but do
not succeed (7): without a peripheral emotional response,
these subjects could not obtain optimal nervous processing
followed by the right decision. In the same way, others, who
are too relaxed during mental practice, cannot succeed, according to Lang’s bioinformational theory (40): for this latter,
propositions concerning physiological and behavioral response provided a prototype for overt behavior, and the processing of response information was associated with somatovisceral arousal. Lang showed that the conceptual structure of
the image and its associated efferent outflow can be modified
directly through instructions and through the shaping of reports of image experience.
As far as this population of volleyball players is concerned,
it seems that the two other factors taken into account to establish the quality of mental practice, i.e., attention and situational anxiety (43) are not so pertinent, but this may differ
with different subjects (14,39,59).
The overall grade testifying to the quality of mental imagery is to be aligned with other well-established indices, as in
medicine: Apgar’s score definited since 1953 by Virginia Apgar (27).
These results contribute experimental arguments to several theoretical attempts to explain neural mechanisms resulting in enhanced performance. The fact that performance
improvement can be described by autonomic responses evidenced the central origin of this phenomenon, and thus bring
arguments to neurocognitive theories testifying of neural pattern of activation that occur during motor programming.
These results altogether suggest that mental representations
during simulation of one’s own actions share common neural
mechanisms with other covert aspects of motor performance
such as planning and programming. Indeed, as Vogt (64) suggested, motor imagery needs preparation also, and motor
preparation involves, to some entend, the same neural substrate (2,53). This confirms the recent proposal from our team
(48) that performance improvement may not be explained by
aspecific motivational factors.
To conclude, the methodology applied permits continuous,
real-time monitoring of neurovegetative adjustments operated by each subject in the course of actual testing and during
imagery sessions. By inference and for each individual, it
leads to an estimation of (a) the ability to generate images,
and (b) the quality of these images. The latter is closely related to the content of the task given. This confirms neurocognitive hypotheses, as all internalized models of the task are reproduced during imagery. It also makes it possible to compare
adjustments at the emotional level (anxiety/vigilance) with
motor execution. Such a virtue of imagery being thus identified, it becomes possible to combine a visceromotor program
with mental evocation. Both these aspects—the cognitive and
the emotional contribute to the qualitative definition of imagery; this being so, they should permit individual elaboration
of performance enhancement.
REFERENCES
1. Adams, J. A.: A closed-loop theory of motor learning. J. Motor
Behav. 3:111–150; 1971.
2. Berthoz, A.: The role of inhibition in the hierarchical gating of executed and imagined movements. Cogn. Brain Res. 3:101–113; 1996.
AUTONOMIC RESPONSE AND SPORTING PERFORMANCE
3. Boucsein, W.: Electrodermal activity. New York: Plenum Press;
1992.
4. Caterini, R.; Delhomme, G.; Dittmar, A.; Economides, S.; Vernet-Maury, E.: A model of sporting performance constructed
from autonomic nervous system responses. Eur. J. Appl. Physiol.
67:250–255; 1993.
5. Collet, C.; Deschaumes-Molinaro, C.; Delhomme, G.; Dittmar,
A.; Vernet-Maury, E.: Les réponses neurovégétatives comme
écho des processus cognitifs dans l’analyse des conduites sensorimotrices complexes. Actes du colloque C.N.R.S. Neurosciences
et Sciences de l’Ingénieur, Chamonix; 1994:91–94.
6. Collet, C.; Roure, R.; Rada, H.; Dittmar, A.; Vernet-Maury, E.:
Relationship between performance and skin resistance evolution
involving various motor skills. Physiol. Behav. 59:953–963; 1996.
7. Damasio, A. R.: L’erreur de Descartes: La raison des émotions.
Paris: O. Jacob; 1995.
8. De Bonis, M.; Freixa I baque, E.: Spontaneous electroderrmal
activity and moods. Neuropsychobiology 4:15–25; 1978.
9. Decety, J.; Jeannerod, M.; Germain, M.; Pastene, J.: Vegetative
response during imagined movement is proportional to mental
effort. Behav. Brain Res. 42:1–5; 1991.
10. Decety, J.; Jeannerod, M.: L’imagerie et son substrat neurologique. Rev. Neurol. 151:474–479; 1995.
11. Delhomme, G.; Dittmar, A.; Pauchard, T.: Linearizing of resistive thermal sensors. Medical bioelectric and thermal surface sensors. Innovat. Technol. Biol. Med. 12:174–182; 1991.
12. Denis, M.: Visual imagery and the use of mental practice in the
developement of motor skills. Can. J. Appl. Sport Sci. 10:4s–16s;
1985.
13. Deschaumes-Molinaro, C.; Dittmar, A.; Vernet-Maury, E.: Relationship between mental imagery and sporting performance.
Behav. Brain Res. 45:29–36; 1991.
14. Deschaumes-Molinaro, C.; Dittmar, A.; Vernet-Maury, E.: Autonomic nervous system response patterns correlate with mental
imagery. Physiol. Behav. 51:1021–1026; 1992.
15. Dittmar, A.: Skin thermal conductivity. In: Leveque, J. L., ed.
Cutaneous investigations in health and desease. New York: Marcel Dekker Inc.; 1989:323–358.
16. Dittmar, A.; Delhomme, G.; Caterini, R.; Vernet-Maury, E.:
Analysis of skin potential response using a novel feature code for
the study of the emotional response. Proc. Annu. Int. Conf.
I.E.E.E., Eng. Med. Biol. Soc.13:427–428; 1991.
17. Dittmar, A.; Rada, H.; Delhomme, G.; Vernet-Maury, E.; Collet,
C.; Roure, R.; Unterreiner, R.; Robini, M.; Delemer, K.: A multisensor system for the non-invasive measurement of the activity of
the autonomic nervous system. Sensors Actuators B 26–27:461–
464; 1995.
18. Ekman, P.; Levenson, R. W.; Friesen, W. V.: Autonomic nervous
system activity distinguishes among emotions. Science 221:1208–
1210; 1983.
19. Farah, M. J.: The neurological basis of mental imagery. Cognition
18:245–272; 1984.
20. Farah, M. J.; Peronnet, F.; Gonon, M. A.; Giard, M. H.: Electrophysiological evidence for a shared representational medium for visual
images and visual percepts. J. Exp. Psychol. 117:248–257; 1988.
21. Feltz, D. L.; Landers, D. M.: The effects of mental practice on
motor skill learning and performance: A meta-analysis. J. Sport
Psychol. 5:25–57; 1983.
22. Finke, R. A.: Theories relating mental imagery to perception.
Psychol. Bull. 98:236–259; 1985.
23. Finke, R. A.: Principles of mental imagery. Cambridge, MA: MIT
Press; 1989.
24. Fishburne, G. J.; Hall, C .R.: Visual and kinesthesic imagery ability in children: Implications for teaching motor skills. In: Barrette, G. T.; Feingold, R. S.; Rees, C. R.; Pieron, M., eds. Myths,
models and methods in sport pedagogy. Champaign, IL: Human
Kinetics Publishers; 1985.
25. Fowles, D. C.; Christie, M. J.; Edelberg, R.: Publication recommendations for electrodermal measurements. Psychophysiology
18:232–239; 1981.
26. Gale, A.; Morris, P. E.; Lucas, B.: Types of imagery and imagery
types: An EEG study. Br. J. Psychol. 63:523–531; 1972.
71
27. Garnier, M.; Delamare, J.: Dictionnaire des termes de médecine.
Paris: Maloine; 1989.
28. Goldenberg, G.; Podreka, I.; Steiner, M.; Willmes, K.: Patterns of
cerebral blood flow related to memorising of high and low imagery words: An emission computer tomography study. Neuropsychology 25:473–485; 1987.
29. Hall, C. R.: The role of mental practice and imagery ability in
motor skill performance. Can. J. Appl. Sport Sci. 12s–19s; 1985.
30. Hall, C. R.; Pongrac, J.: Movement imagery questionnaire. London, Ontario: Departement of Physical Education, University of
Western Ontario; 1983.
31. Hardy, L.; Parfitt, G.: A catastrophe model of anxiety and performance. Brit. J. Med. Psychol. 82:163–168; 1991.
32. Housner, L.; Hoffman, S. J.: Imagery ability in recall of distance
and location information. J. Motor Behav. 13:207–223; 1981.
33. Ingvar, D. H.; Philipon, L.: Distribution of cerebral blood flow in
the dominant hemisphere during motor ideation and motor performance. Ann. Neurol. 2:230–237; 1977.
34. Jeannerod, M.: The representating brain: Neural correlates of
motor intention and imagery. Behav. Brain Sci. 17:187–243; 1994.
35. Jones, G. E.; Johnson, H. J.: Heart rate and somatic concomitants
of mental imagery. Psychophysiology 17:339–447; 1980.
36. Kalsbeek, J. W. H.: Sinus arrhythmia and the dual task method in
measuring mental load. In: Singleson, W. T.; Fox, J. G.; Whitfield,
D., eds. Measurement of man at work. London: Taylor and Francis; 1971:101–113.
37. Kosslyn, S. M.; Ball, T. M.; Reiser, B. J.: Visual images preserve
metric spatial information: Evidence from studies of image scanning. J. Exp. Psychol. 4:47–60; 1978.
38. Kosslyn, S. M.; Brunn, J.; Cave, K. R.; Wallach, R. W.: Individual
differences in mental imagery: A computational analysis. Cognition 18:195–243; 1984.
39. Lacey, J. I.; Bateman, D. E.; Vanlehn, R.: Autonomic response
specificity. Psychosom. Med. 15:8–21; 1953.
40. Lang, P. J.: A bio-informational theory of emotional imagery.
Psychophysiology 16:495–512; 1979.
41. Lindsley, D. B.: Emotion. In: Stevens, S. S., ed. Handbook of
experimental psychology. New York: John Wiley; 1951:473–517.
42. Murphy, S. M.: Imagery interventions in sport. Med. Sci. Sport
Exerc. 26:486–494; 1994.
43. Naveteur, J.; Freixa I baque, E.: Individual differences in electrodermal activity as a function of subject’s anxiety. Prog. Brain Res.
85:147–166; 1990.
44. Rada, H.; Dittmar, A.; Delhomme, G.; Collet, C.; Roure, R.; Vernet-Maury, E.; Priez, A.: Bioelectric and microcirculation cutaneous sensors for the study of vigilance and emotional response
during tasks and tests. Biosens. Bioelectron. 10:7–15; 1995.
45. Rameloo, B.: Acupuncture et modifications du système nerveux
autonome au cours d’une série d’épreuves anxiogènes. Thèse de
Doctorat en Médecine, Université C. Bernard, Lyon I. 1988.
46. Rippon, G.: Individual differences in electrodermal and electroencephalographic asymmetries. Int. J. Psychophysiol. 8:309–312;
1990.
47. Roland, P. E.; Friberg, L.: Localization of cortical areas activated
by thinking. J. Neurophysiol. 53:1219–1240; 1985.
48. Roure, R.: Imagerie mentale et performance en habileté ouverte.
Les signes neurovégétatifs comme témoins de l’activité du volleyeur et de la qualité de sa représentation mentale. Thèse
U.C.B.Lyon; 1996.
49. Roure, R.; Collet, C.; Deschaumes-Molinaro, C.; Dittmar, A.;
Rada, H.; Delhomme, G.; Vernet-Maury, E.: Autonomic nervous
system responses correlate with mental rehearsal in volleyball
training. Eur. J. Appl. Physiol. 78:99–108; 1998.
50. Schmidt, R. A.: A schema theory of discrete motor skill learning.
Psychol. Rev. 82:225–260; 1975.
51. Shaw, W. A.: The relation of muscular action potentiels to imaginal weight lifting. Arch. Psychol. 35:1; 1940.
52. Simonet, P.: Apprentissages moteurs. Paris: Vigot; 1986.
53. Stephan, K. M.; Fink, G. R.; Passingham, R. E.; Silbersweig, D.;
Ceballo-Bauman, A. O.; Frith, C. D.; Frackowiack, R. S. J.: Functional anatomy of the mental representation of upper extremity
movements in healthy subjects. J. Neurophysiol. 73:373–386; 1995.
72
54. Survillo, W. W.; Quilter, R. E.: The relation of frequency of spontaneous skin potential responses to vigilance and age. Psychophysiology 1:272–276; 1965.
55. Tursky, B.; Scharitz, G. E.; Crider, A.: Differential patterns of
heart rate and skin resistance during a digit transformation task.
J. Exp. Psychol. 83:451; 1970.
56. Van der Molen, M. W.; Boomsma, D. I.; Jennings, J. R.; Nieuwboer, R. T.: Does the heart know what the eye sees? A cardiac
pupillometric analysis of motor preparation and response execution. Psychophysiology 26:70–80; 1989.
57. Vealey, R. S.; Walter, S. M.: Imagery training for performance
enhancement and personal development. In: Williams, J. M., ed.
Applied sport psychology: Personal growth to peak performance.
London Toronto: Mayfield Publishing Copmany; 1993:200–224.
58. Vernet-Maury, E.; Sicard, G.; Dittmar, A.; Deschaumes-Molinaro, C.: Autonomic nervous system preferential responses. Act
Nerv. Sup. 32:37–38; 1990.
59. Vernet-Maury, E.; Deschaumes-Molinaro, C.; Delhomme, G.;
Dittmar, A.: The relation between bioelectrical and thermovascular skin parameters. Innovat.Technol. Biol. Med. 12:112–120;
1991.
60. Vernet-Maury, E.; Jiang, T.; Dittmar, A.; Delhomme, G.; Khardi,
S.; Olivier, D.; Vallet, M.: Apports des paramètres neurovégétatifs dans la détection des hypovigilances en simulation de conduite automobile. In: Vallet, M.; Khardi, S., eds. Vigilance et
ROURE ET AL.
61.
62.
63.
64.
65.
66.
67.
68.
transports: Aspects fondamentaux, dégradation et prévention.
Lyon: Presses Universitaires; 1995:49–61.
Vernet-Maury, E.; Robin, O.; Dittmar, A.: The ohmic perturbation duration: An original temporal index to quantify electrodermal response. Behav. Brain Res. 67:103–107; 1995.
Vernet-Maury, E.; Dittmar, A.: Imaginer la performance. Pour
Sci. 225:38–39; 1996.
Vernet-Maury, E.; Collet, C.; Rada, H.; Delhomme, G.; Dittmar,
A.: Autonomic ability to distinguish among basic emotion: Comparison of two electrodermal indices. Acts of the 8th world congress of I.O.P., Tampere, Finland, 1996, p. 151.
Vogt, S.: Imagery needs preparation too. Behav. Brain Sci.
17:226–227; 1994.
Vogt, S.: On relation between perceiving, imagining and performing in the learning of cyclical movement sequences. Br. J. Psychol. 86:191–216; 1995.
Wallin, B. G.; Fagius, J.: The sympathetic nervous system in man:
Aspects derived from microelectrode recordings. Trends Neurosci. 9:63–67; 1986.
Wilder, J.: Basimetric approach (law of initial value) to biological
rhythms. Ann. NY Acad. Sci. 98:1211–1228; 1962.
Yue, G.; Cole, K. J.: Strength increases from the motor program:
Comparison of training with maximal voluntary and imagined
muscle contractions. J. Neurophysiol. 67:1114–1123; 1992.