Kaneko2014 Cognition

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Differential reliance of chimpanzees and humans on automatic

and deliberate control of motor actions

Takaaki Kaneko ⇑, Masaki Tomonaga

Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan

a r t i c l e i n f o

Article history:

Received 5 June 2013

Revised 4 February 2014

Accepted 12 February 2014

Available online 15 March 2014

Keywords:

Self-monitoring

Chimpanzees

Agency

Voluntary action

Imitation

Mirror system

a b s t r a c t

Humans are often unaware of how they control their limb motor movements. People pay

attention to their own motor movements only when their usual motor routines encounter

errors. Yet little is known about the extent to which voluntary actions rely on automatic

control and when automatic control shifts to deliberate control in nonhuman primates.

In this study, we demonstrate that chimpanzees and humans showed similar limb motor

adjustment in response to feedback error during reaching actions, whereas attentional allo-

cation inferred from gaze behavior differed. We found that humans shifted attention to

their own motor kinematics as errors were induced in motor trajectory feedback regardless

of whether the errors actually disrupted their reaching their action goals. In contrast, chim-

panzees shifted attention to motor execution only when errors actually interfered with

their achieving a planned action goal. These results indicate that the species differed in

their criteria for shifting from automatic to deliberate control of motor actions. It is widely

accepted that sophisticated motor repertoires have evolved in humans. Our results suggest

that the deliberate monitoring of one’s own motor kinematics may have evolved in the

human lineage.

2014 Elsevier B.V. All rights reserved.

1. Introduction

To what extent do nonhuman primates intentionally

control their motor actions? This is an important question

for understanding the evolutionary origin of intentional

and deliberate control of motor actions. However, experi-

mental studies comparing humans and nonhuman prima-

tes in this regard are scarce.

Humans automatically adjust their limb movements

according to the degree of discrepancy between the pre-

dicted results of actions and actual feedback, even when

they are unaware of the error (Fourneret & Jeannerod,

1998; Knoblich & Kircher, 2004; Musseler & Sutter,

2009). For example, when one moves a cursor to an icon

using a computer mouse, the contingency between mouse

movement and cursor action can often change due to con-

ditions affecting the mouse (e.g., desk surface structure).

Motor corrections occur automatically and humans are

unaware of errors unless an error reaches a certain thresh-

old. Several behavioral experiments have demonstrated

that primate species, including both humans and nonhu-

mans, dedicate distinctive systems to conceptual represen-

tations of action goals and execution of actual motor

kinematics to achieve the goal (Glover, 2004; Nakayama,

Yamagata, Tanji, & Hoshi, 2008; Yamagata, Nakayama,

Tanji, & Hoshi, 2009). Humans perceptually represent sim-

ple goals of their actions, and the corresponding actual mo-

tor action is automatically activated (Mechsner, Kerzel,

Knoblich, & Prinz, 2001). Norman and Shallice (1986) ar-

gued that motor systems need to recruit attentional re-

sources only when they face a novel and unpredictable

situation where routine solutions are not efficient.

http://dx.doi.org/10.1016/j.cognition.2014.02.002

0010-0277/ 2014 Elsevier B.V. All rights reserved.

⇑ Corresponding author. Current Address: Department of Psychology,

Kyoto University, Yoshida-Honmachi, Kyoto 606-8501, Japan. Tel.: +81 75

753 2442.

E-mail address: [email protected] (T. Kaneko).

Cognition 131 (2014) 355–366

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Cognition

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On the other hand, accumulating evidence suggests that

perception of others’ actions is closely related to execution

of one’s own actions. It has been proposed that perception

and understanding of others’ actions shares the same neu-

ral circuits with execution of one’s own actions through

the mirror-neuron system (Kanakogi & Itakura, 2011;

Myowa-Yamakoshi, Kawakita, Okanda, & Takeshita, 2011;

Rizzolatti & Craighero, 2004; Sommerville, Woodward, &

Needham, 2005). Interestingly, mirror systems in humans

and non-human primates have one distinct difference.

The mirror system in humans is activated to observe

intransitive meaningless movements, in contrast to that

in non-human primates, which is activated only with

regard to others’ actions with an explicit action goal but

not to gross movements (Ferrari, Gallese, Rizzolatti, &

Fogassi, 2003; Rizzolatti & Craighero, 2004). Furthermore,

a growing body of research indicates differences in the

way humans and chimpanzees copy others’ actions. It is

well known that chimpanzees are capable of sophisticated

social learning (Tomasello, Davis-Dasilva, Camak, & Bard,

1987; Whiten, Custance, Gomez, Teixidor, & Bard, 1996;

Whiten et al., 1999). However, social learning by great

apes, including chimpanzees, is limited to emulation,

which is defined as reproducing the action-goal of an

observed action, and does not include imitation, which is

defined as copying the kinematic aspects of the action

(Call, 2001; Call, Carpenter, & Tomasello, 2005;

Myowa-Yamakoshi & Matsuzawa, 1999; Myowa-

Yamakoshi & Matsuzawa, 2000; Nagell, Olguin, &

Tomasello, 1993; Tennie, Call, & Tomasello, 2006;

Tomasello et al., 1987). Many studies have emphasized

differences in how chimpanzees and humans perceive

others’ actions. Yet similarities and dissimilarities between

the two species in the execution and perception of one’s

own actions have rarely been investigated (Kaneko &

Tomonaga, 2011; Kaneko & Tomonaga, 2012).

This species difference in copying action may reflect

species differences in the execution of one’s own actions.

Specifically, it is possible that control of motor kinematics

in chimpanzees is highly dependent on the automatic

aspects of motor control, as chimpanzees, find it difficult

to imitate a motor action without an explicit action goal

(Call, 2001; Myowa-Yamakoshi & Matsuzawa, 1999). This

view is also congruent with our previous study, which

showed that chimpanzees have a bias toward monitoring

goals when monitoring their own action, whereas humans

monitor kinematic information and goal representation

equally (Kaneko & Tomonaga, 2012). The monitoring of

own-action occurs hierarchically; that is, it entails an

automatic and implicit sensorimotor process and an expli-

cit conceptual process. However, in that study, we could

not empirically determine to what extent implicit versus

explicit monitoring was involved.

In the present study, we investigated possible differ-

ences in reliance on automatic motor control between

the two species and examined when and to what extent

they paid attention to their own motor kinematics. We

hypothesized that humans and chimpanzees are compara-

ble in conceptual representation of an action goal but may

differ in the extent and timing of the selective attentionthat they allocate to controlling detailed motor kinematics

of their own actions. We compared the two species by

applying an equivalent behavioral task. The participants

manipulated a trackball device and moved a cursor to hit

a target shown on the computer display (Fig. 1a). The con-

tingency between the trackball manipulation and the cur-

sor action was stable in two-thirds of the trials. In the

remaining trials, the spatial mapping between the trackball

manipulation and the cursor action was distorted; thus,

the participants’ expectations for visual feedback of their

movements were inconsistent with the feedback received,

and they had to adjust their limb motor movements to the

novel mapping. The details of this distortion are described

later.

The extent to which motor control relies on automatic

operation can be inferred from the gaze behavior of partic-

ipants (Fig. 2 and Supplemental Movies 1 and 2). While

performing a reaching action, humans generally continue

to fixate on the goal (target location) of the reaching action,

and the action kinematics of their own limb (or cursor

trajectory) is observed only in their peripheral vision.

However, once contingency between one’s own actions

and visual feedback is altered and the usual motor routines

do not work, then humans shift their gaze from the action

target to the action kinematic (Sailer, Flanagan, &

Johansson, 2005). Thus, by measuring gaze shifts from

the goal (target) to the action kinematic (cursor trajectory),

it is possible to infer when participants rely on overt atten-

tion to adjust a motor limb.

We introduced two types of distortion to alter the visual

feedback of participants’ actions and to induce an online

motor adjustment (Fig. 1b). One type of distortion dis-

turbed the cursor motion and interfered with reaching

the goal ( goal dissociation), and the other altered the motor

trajectory but had no effect on reaching the goal ( goal

congruent ). Under the goal-dissociation condition, cursor

action was rotated in a clockwise/counter-clockwise direc-

tion relative to the trackball manipulation. Thus, the cursor

could not reach the target unless the participants adjusted

their manipulation to the distorted spatial mapping. Under

the goal-congruent condition, cursor action was also

perturbed by angular rotation. However, the polarity of

rotation was gradually changed to the opposite direction

midway through the reaching action. This resulted in sub-

jects’ not needing to adjust their manipulation to the dis-

torted spatial mapping. Instead, to reach the target, they

needed to manipulate the trackball as if there were no

distortion. Thus, under this condition, distortion had no

effect on reaching the target (i.e., the goal of the action)

but still altered the action trajectory (see details in

Section 2). Under this condition, perceived cursor action

was dissociated from participants’ estimations of the

cursor action with respect to detailed spatiotemporal

parameters, although the cursor effectively reached the

planned action goal at the conceptual level. These distor-

tion techniques were developed by Wolpert, Ghahramani,

and Jordan (1995).

In this experimental setting, we measured limb motor

adjustment in response to feedback errors and gaze shifts

as an indicator of when the feedback error triggered

participants’ overt attention to motor corrections as ameans of testing the possible difference between

356 T. Kaneko, M. Tomonaga / Cognition 131 (2014) 355–366

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chimpanzees and humans in their reliance on automatic

and deliberate control for online motor adjustment.

2. Methods

2.1. Participants

Five chimpanzees living at the Primate Research Insti-tute, Kyoto University, Japan, took part in the experiment

(one male [Ayumu] and four females [Chloe, Cleo, Pal,

and Pan]; aged 10–30 years). These chimpanzees have par-

ticipated in various perceptual and cognitive studies

(Matsuzawa, 2003; Matsuzawa, Tomonaga, & Tanaka,

2006; Tomonaga, 2001). Seven female human participants

performed the experiment (aged 19–27 years). The partic-

ipants were undergraduate and graduate students, caregiv-

ers, and technicians who were unaware of the studyhypothesis. The care and use of animals complied with

the institutional ethical guidelines. The ethics committee

of the institution approved the human experiment.

2.2. Apparatus

Stimuli were presented on a 17-in. LCD monitor (Gunze

AV10226N02W) at a 60-cm viewing distance. The partici-

pants manipulated a trackball device 12 cm in diameter

(Sanwa H55-0300-SET). Eye movements were measured

with an infrared remote eye tracker (Tobii TX300) at

300 Hz. Mean eye-movement and visual-angle tracking er-

rors for each participant ranged from 0.45 to 0.60 forchimpanzees and from 0.58 to 1.14 for humans. Details

of the eye-tracking method and apparatus are described

elsewhere (Kaneko, Sakai, Miyabe-Nishiwaki, & Tomonaga,

2013). A small piece of fruit was delivered to the chimpan-

zee participants using an automated universal feeder (Bio-

medica BUF-310) as a reward at the end of each trial.

2.3. Task

A schematic illustration of the experimental task is

shown in Fig. 1a. An open circle and cursor were presented

on the monitor at the start of a trial (trial initiation pro-cess). The participants were required to move the cursor

Start

Stimulusonset

Hit

Goal Dissociation Goal Congruent

Defaultaction

(b)

(c)δP

P

D

L

(a)

Angular rotation

Alteredaction

Fig. 1. Schematic diagram of the behavioral task and design. (a) Task. The trial required the subject to hit three different locations of a target consecutively.Here, only one target is shown for simplicity. (b) Test conditions. Two types of perturbations were used. The typical time course of angular rotation is shown

for each condition. (c) Schematic illustration of the goal-congruent distortion algorithm. The rectangle and circle represent the target and the cursor,

respectively. The dotted circle at left represents the initial location of the cursor. The dotted circle in the middle shows the invisible cursor (see Section 2 for

details).

11

2

3

4

1

3

2

6

7

6

7

(b)(a)

5

Fig. 2. Automatic and deliberate control of action inferred from gaze

behavior. Examples of trials performed by chimpanzees with (b) and

without (a) distortion. Open green rectangles show the target location.

(Each target was shown successively but not simultaneously in an actual

trial). Solid lines represent cursor trajectory, and black arrows indicate

the direction of movement. Red crosses represent fixation, and adjacent

numbers represent fixation order. All fixations were on the target in (a),

whereas there was some fixation on cursor trajectory in (b). See alsoSupplemental Movies 1 and 2. (For interpretation of the references to

color in this figure legend, the reader is referred to the web version of this

article.)

T. Kaneko, M. Tomonaga/ Cognition 131 (2014) 355–366 357

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to the open circle. They also needed to keep their heads in a

particular area where the eye tracker could stably measure

their gaze at the same time. The validity of head location

was indicated by the color of the open circle (blue or

red). The main part of the trial was initiated when these

two criteria were satisfied. Following this start process, a

cursor (white closed circle, 7.4 mm [0.7] in diameter)

and a target (green closed rectangle, 10.6 10.6 mm;

1 1) were presented on the monitor. The distance be-

tween the target and the cursor was 150 mm (15). The rel-

ative directions from the cursor to the target varied across

trials. Once the cursor hit the target, that target disap-

peared and reappeared at a different location. The partici-

pants had to move the cursor to hit the target at three

different locations. The experiment consisted of test trials

(cursor action was distorted) and baseline trials (no pertur-

bation). In both trial types, the cursor action did not in-

volve any perturbation during the trial initiation process.

2.4. Conditions

The spatial mapping between trackball manipulation

and cursor action was distorted during the test trials. The

test-trial parameters consisted of two within-subject fac-

tors, i.e., distortion type (goal dissociation and goal congru-

ent) and distortion amplitude (6, 12, 24, and 46). Under the

goal-dissociation condition, cursor action was rotated in a

clockwise/counter-clockwise direction relative to trackball

manipulation. The amplitude of rotation was defined by

another experimental parameter, distortion amplitude. The

direction (clockwise/counter clockwise) of angular rotation

was pseudo-randomized across trials. Cursor location un-

der the goal-congruent condition was determined by the

following calculation. Suppose there was an invisible vir-

tual cursor, whose dependence on the trackball manipula-

tion was the same as that during the baseline trial (i.e., no

perturbation). The invisible cursor provided two values

(see also Fig. 1c). One was the distance between the virtual

cursor and its start position along the axis between the

start position and the target (D). The second value was

the offset distance from the axis between the start position

and the target (P ). The distorted visual feedback (location

of the visible cursor) was shown at the position where

the distance along the start-to-goal axis was D, and the off-

set distance relative to the start-to-goal axis was dP + P.

Distortion displacement dP was calculated using the fol-

lowing formula: dP = Amp sin(D/L p

), where L is the

distance from the start to the goal (150 mm). Amp was ad-

justed so that the mean of the momentary angular rotation

(angular error between the trackball manipulation and the

cursor movement) was the same as that under the goal dis-

association condition. Thus, the mean momentary angular

rotation under the goal congruent and dissociation condi-

tions was the same. By applying these processes, the cursor

typically showed a curving action, as shown in Fig. 1b.

2.5. Procedure

Distortion type and amplitude were within-subject fac-

tors. The order of trial type was pseudo-randomized. Thechimpanzees performed 32 trials under each condition,

and the humans performed five trials. The baseline trials,

where no perturbation occurred, were inserted in a pseu-

do-random order between the test trials. The ratio of the

test to the baseline was set to 1:2. Both humans and chim-

panzees performed more than 62 habituation trials before

the test sessions. The habituation trial was equivalent to

the baseline trial.

The chimpanzees were already experienced in moving a

cursor to hit a target using a trackball device (Kaneko &

Tomonaga, 2011; Kaneko & Tomonaga, 2012); thus, no

training specific to this study was required. Here, we

briefly describe the acquisition process of the trackball

use. The chimpanzees first performed the aiming action

where the target was huge and the initial location of the

cursor was close to the target. In this condition, random

manipulation of the trackball resulted in a coincident hit.

As their manipulation skills improved, the target became

smaller, and the distance between the target and the cur-

sor became longer. Through trial and error, the chimpan-

zees gradually learned to use the trackball. The

chimpanzees were also familiar with fixing their head for

eye tracking before starting the trial. There was always a

trial initiation procedure before the main part of trial. Dur-

ing this phase, an open circle and cursor were presented,

and the participants were required to move the cursor to

the open circle. They also needed to keep their heads in a

particular area where the eye tracker could stably measure

their gaze at the same time. The appropriateness of head

location was indicated by the color of the open circle. Be-

cause a trial was not started until the head was stable

and at the proper location, the chimpanzees learned to

spontaneously move their heads to the predefined posi-

tion. The task was to hit the target with the cursor; thus,

we did not conduct further training specific to the current

experiment. Notably, our chimpanzees were naïve to the

spatial perturbation used in this study (only Chloe had

experienced a few spatial distortion trials (see Experiment

3 in Kaneko & Tomonaga, 2011).

The human participants were verbally instructed to

move the cursor to the target by manipulating the track-

ball. The human participants learned the contingencies of

trackball manipulation and cursor action during habitua-

tion trials. They were also instructed to move their heads

to the proper location to start a trial and were told that

accurate head position was indicated by the color of the

open circle during the trial initiation procedure. They

were also informed that their eye movements would be

tracked. After the habituation trial finished, they per-

formed test trials. They were instructed that ‘‘the main

part of experiment was basically the same as the habitu-

ation trials, except with minor changes regarding experi-

mental manipulation. Irrespective, please perform the

aiming task as efficiently as possible’’. The participants

were not informed of the presence or the property of per-

turbation. This procedure and instruction minimized pos-

sible differences between human and chimpanzee

participants in their knowledge about the task structure.

Ad lib questioning of the human participants after the

experiment confirmed that all participants were unaware

of the specific purpose and hypothesis of the presentstudy.


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2.6. Analysis

As a measurement of limb motor adjustment in re-

sponse to feedback errors, we defined the corrective move-

ment as shown in Fig. 4a. The vector input of the

participants’ manipulation was divided into vertical and

horizontal components relative to the axis between the

target and the initial cursor location. At the baseline trial,

in which no distortion was imposed, the vertical compo-

nent of the vector input was unnecessary but was induced

under the perturbation as a response to feedback error

during the test trial. Thus, we defined the total vertical

component as a corrective movement. Fixations were ex-

tracted from raw gaze-position data using a custom-made

fixation filter based on Stampe (1993). A fixation was

scored if the gaze remained stationary within a radius of

1 in visual angle for at least 50 ms. We calculated the

number of gaze shifts to the motor trajectory as an indica-

tor of times when the feedback error triggered partici-

pants’ overt attention to motor corrections. Gaze shift

was defined as fixation within a 1 visual angle from the

cursor location. We also recorded the movement time,

which was defined as time between the onset of stimulus

and hitting the target.

Statistical analyses were performed based on the func-

tions of the statistical toolbox (ttest for t -test and anovan

for analysis of variance [ANOVA]) in MATLAB (R2011a).

Post hoc comparisons were conducted with Bonferroni cor-

rection. Alpha was set at .05 for all analyses, and the Bon-

ferroni correction adjusted the alpha level as necessary.

Means of multiple trials for each subject were computed

for each behavioral measurement, and those values were

used as dependent variable in the statistical tests.

2.7. Expertise effect

We addressed possible artifactual effects of the differ-

ence in expertise between species. There were two types

of asymmetry between the two species in the degree of

expertise. The first was experience with our experimental

device. The chimpanzee participants had previously per-

formed several experiments using the current device, but

the humans had not. The second was the number of distor-

tion trials the participants experienced. The chimpanzee

participants performed 32 trials per condition, and the hu-

mans performed only five trials. Two controls were used

for these expertise asymmetries. First, we asked twohuman participants (one female and one male; age, 27–

28 years) to perform more than 1,200 aiming actions over

50 days (Fig. S1) until their movement performance be-

came very stable. Additionally, the same two participants

performed 32 trials per condition, like the chimpanzees.

3. Results

The descriptive results of the participants’ overall

behavior are shown in Fig. 3. The results show that both

the chimpanzee and the human participants mainly fixated

on the goal of the action and occasionally looked at cursortrajectory during aiming. This trend was consistent across

species and from the baseline trial to the test trials involv-

ing distortion. The fixation probability maps (color maps in

the first row of Fig. 3) showed that there were roughly

three different color regions, i.e., gray, yellow, and green

areas, suggesting that the participants predominantly

looked at the target location (corresponding to the green

areas), irrespective of distortion type, and that they occa-

sionally looked at the trajectory of the cursor (correspond-

ing to the yellow areas). This trend is also evident in the

second row of Fig. 3, which shows the fixation probability

as a function of the target and the start location axis. Target

location was the most frequent target of fixation for both

humans and chimpanzees. The characteristics of the cor-

rective movements were also similar between the species

(bottom row in Fig. 3). Corrective movements appeared

gradually as the cursor moved under both the goal-dissoci-

ation and goal-congruent conditions. Under the goal-disso-

ciation condition, such corrective movements further

accumulated at the latter part of the trajectory. The polar-

ity of corrective movement was reversed at the mid-point

of the trajectory during the goal-congruent condition. This

is because corrective movement was not required at all un-

der this condition, and the corrective movements per-

formed until the mid-part of the trajectory must be

compensated by movement in the opposite direction.

These patterns in the corrective movements appeared

comparable between species. In the latter analysis, we fur-

ther analyzed the details of the corrective movement and

how the needs for these motor corrections induced gaze

direction toward the motor trajectory.

Both species effectively corrected their limb move-

ments when distortion was applied (Fig. 5). The results

show that both species increased their corrective move-

ments as distortion increased, irrespective of distortion

type. We performed a two-way ANOVA with distortion

type and distortion amplitude as fixed factors and partici-

pant as a random factor for each species. The overall statis-

tical results for corrective movement were comparable

between species. The ANOVAs showed significant interac-

tions of distortion type distortion amplitude

(F (3,12) = 58.7, p < .001, g p2 = .94 for chimpanzees;

F (3,18) = 33.2, p < .001, g p2 = .85 for humans). Post hoc

comparisons of distortion type for each distortion ampli-

tude with Bonferroni correction revealed that the correc-

tive movements were the same between the distortion

types when the distortion amplitude was small

(t (4) = 1.8, p = .15, r = .67, for chimpanzees at 6;

t (6) = 1.6, p = .17, r = .54, t (6) = 1.6, p = .16, r = .55 for hu-

mans at 6 and 12, respectively) but were larger under

the goal-dissociation condition than the goal-congruent

condition when the distortion amplitudes were large

(t (4) = 3.1, p = .04, r = .84, t (4) = 6.1, p = .004, r = .95,

t (4) = 8.1, p = .001, r = .97 for chimpanzees at 12, 28, and

46, respectively; t (6) = 8.4, p = .0002, r = .96; t (6) = 7.2,

p = .0004, r = .95 for humans at 28 and 46, respectively).

The main effects of distortion type (F (1,12) = 57.8,

p = .002, g p2 = .83 for chimpanzees; F (1,18) = 68.4,

p < .001, g p2 = .79 for humans) and distortion amplitude

(F (3,12) = 510.7, p < .001, g p2 = .99 for chimpanzees;

F (3,18) = 130.6,

p < .001, g

p2

= .96 for humans) were alsosignificant. These results show that both species increased


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their corrective movements as distortion increased, and

the amount of the corrective movement was higher under

the goal-dissociation than under the goal-congruent condi-

tion, particularly when the distortion amplitude was high.

This is reasonable, because the corrective movements were

necessary to reach the target during goal dissociation but

were completely unnecessary during the goal-congruent

condition. The overall results of motor corrections suggest

that the two species have similar sensitivity to feedback er-

ror in terms of limb motor adjustment.

We also measured the gaze-shifting responses from the

goal to the action kinematics during motor correction

(Fig. 6). Gaze-shifting responses increased in both species

as distortion increased; however, these trends differed

between chimpanzees and humans. We performed an AN-

OVA for each species with distortion type and distortion

amplitude as fixed factors and participant as a random fac-

tor for each species. The ANOVAs showed a significant

interaction of distortion type and distortion amplitude in

chimpanzees (F (3,12) = 15.2, p < .001, g p2 = .79) but not

in humans (F (3,18) = 0.17, p = .91, g p2 = .028). Post hoc

analyses of the simple main effects were conducted for

each distortion type for the chimpanzee results. The

chimpanzees increased their gaze-shifting response as

distortion increased under the goal-dissociation condition

(F (3,12) = 10.96, p = .0009, g p2 = .73) but not under the

goal-congruent condition (F (3,12) = 2.26, p = .13,

g p2 = .36). The main effect of distortion amplitude was

(a) Chimpanzees

(b) Humans

F i x a t i on

pr o p er t i on

F i x a t i on

pr o p er t i on

Fig. 3. Cursor action, hand manipulation, and gaze behavior. The three columns represent the baseline, goal-congruent, and goal-dissociation conditions,

respectively. The first row shows cursor trajectory and fixation probability. The solid line represents cursor trajectory, the left terminus is the start position,

and the right terminus is the target position. The yellow–green color represents fixation probability. The second and third rows represent fixation

probability and corrective movements, respectively, as a function of the horizontal distance from the start position on the axis and the target. The dotted

vertical lines represent the start positions (left, 0 mm) and target locations (right, 150 mm). Data are given as the mean across participants. Shaded areas

represent 95% confidence intervals. Results for the goal-congruent and goal-dissociation conditions were derived from the maximum degree of distortion,

which shows the most salient distortion effect on the participant’s behavior. Note that the direction of distortion and the directions from the start position

to the target varied across trials; thus, the results were realigned so that relative geometry was constant across trials. (For interpretation of the references to

color in this figure legend, the reader is referred to the web version of this article.)


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significant for both chimpanzees (F (3,12) = 7.98, p = .003,

g p2 = .67) and humans (F (3,18) = 16.6, p < .001, g p2 = .73),

whereas distortion type was not significant in either chim-

panzees (F (1,12) = 5.64, p = .076, g p2 = .32) or humans

(F (1,18) = 0.09, p = .77, g p2 = .0058). These results showthat humans increased their gaze-shift responses as distor-

tion increased, regardless of whether the distortion af-

fected only the momentary spatiotemporal parameters or

actually interfered with achieving the final goal of the ac-

tion. In contrast, in chimpanzees, overt attention shifted

to motor kinematics only when the distortion actually

interfered with the chimpanzee reaching the action goal.

Additionally, we analyzed the movement time for the

aiming action. If the pattern of overall movement times

were the same as the pattern of gaze shifts, this could cre-

ate difficulty when interpreting species differences in gaze

pattern. However, the results showed that overall patterns

of time spent to hit the target were comparable between

species (Fig. 6), and differed from that of gaze shifts. Both

species increased movement time as distortion amplitude

increased (F (3,12) = 112.8, p < .001, g p2 = .97 for chimpan-

zees; F (3,18) = 72.8, p < .001, g p2 = .92 for humans). The

degree of incentive was larger under the goal-dissociationthan under the goal-congruent condition, which is evident

in the significant interaction between distortion type and

distortion amplitude (F (3,12) = 66.2, p < .001, g p2 = .94 for

chimpanzees; F (3,18) = 7.10, p = .002, g p2 = .54 for hu-

mans). A post hoc analysis showed that movement time

was not different between distortion types (t (4) = 1.07,

p = .34, r = .48, t (4) = 1.29, p = .27, r = .54 , t (4) = 3.38,

p = .028, r = .86 for chimpanzees; t (6) = 1.55, p = .17,

r = .53 , t (6) = .29, p = .78, r = .12 , t (6) = .85, p = .43, r = .33

for humans at 6, 12, and 28 respectively), except that

for the largest distortion amplitude. Under the largest dis-

tortion, the movement time was longer under the goal-dis-

sociation than under the goal-congruent condition

Vector input

Horizontal component

Vertical component

=Corrective movement

Goal congruentGoal dissociation

6 12 28 46-100

0

100

200

300

400

500

600

C o r r e c t i v e

m o v e m e n t ( m m )

Distortion (degree)

Chimpanzees

6 12 28 46-100

0

100

200

300

400

500

600

C o r r e c t i v e

m o v e m e n t ( m m )

Distortion (degree)

Humans(a) (b)

Fig. 4. Motor adjustment in response to feedback error. (a) Schematic illustration of the definition of corrective movements. (b) Mean corrective

movements across participants as a function of distortion amplitude. The figure shows values for each test condition subtracted from values for the baseline

condition. Error bars indicate standard errors. Dotted red lines represent the minimal corrective movements required for the goal-dissociation condition.

The minimal correction movement for the goal-congruent condition was zero regardless of distortion amplitude. (For interpretation of the references to

color in this figure legend, the reader is referred to the web version of this article.)

Default action

Gaze shift

Altered action


6 12 28 46-0.5

0

0.5

1

1.5

2

2.5

N u m b e r o f g a z e s h i f t s ( n )

Distortion (degree)

Chimpanzees

6 12 28 46-0.5

0

0.5

1

1.5

2

2.5

N u m b e r o f g a z e s h i f t s ( n )

Distortion (degree)

Humans

(a) (b)

Fig. 5. Overt attention to motor kinematics induced by feedback error. (a) Gaze shift was defined as fixation within a 1 visual angle from the cursor

location. (b) Mean gaze shift across participants as a function of distortion amplitude. The figure shows the values for each test condition subtracted from

the values for the baseline condition. Error bars indicate standard errors.


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(t (4) = 8.96, p < .001, r = .98 for chimpanzees; t (6) = 2.55,

p = .044, r = .72 for humans), although this effect was notstatistically significant after the Bonferroni correction in

humans. Close inspection of the data revealed that there

was one exceptional participant who showed longer move-

ment time for the goal-congruent condition than that for

the goal-dissociation condition, and removing this partici-

pant made the result significant even after the Bonferroni

correction (t (5) = 4.04, p = .099, r = .88). Notably, this sub-

ject was similar to the other human participants in gaze-

shift pattern. The main effect of distortion type was signif-

icant in chimpanzees (F (1,12) = 93.7, p < .001, g p2 = .89)

but not in humans (F (1,18) = 3.25, p = .12, g p2 = .15). How-

ever, it is problematic to interpret the absence or presence

of a main effect in ANOVA when there is a significant inter-action (Tabachnick & Fidell, 2001). The important point

here is the presence of a significant main interaction in

both species. An increasing trend was observed as distor-

tion amplitude increased in both species, and its effect

was higher under the goal-dissociation than under the

goal-congruent condition at the largest distortion ampli-

tude. This overall movement time was not the same as

the gaze shift pattern and could not account for the species

differences in gaze pattern.

3.1. Expertise effect

We controlled for the asymmetry of task expertise be-

tween species. The results for the human participants

who were experts at trackball manipulation and performed

the same number of test trials as chimpanzees were com-

parable to those for novice participants (Fig. S2). We con-

ducted a two-way ANOVA on distortion type and

distortion amplitude for each participant, combining the

128 consecutive trials into a single block and treating the

mean value for each block as a dependent variable. The

ANOVAs showed a significant main effect of distortion

amplitude (F (3,15) = 34.1, p < .0001, g p2 = .87 for partici-

pant T; F (3,) = 11.3, p = .0004, g p2 = .69 for participant F).

Importantly, no significant two-way interaction wasobserved between distortion type and amplitude

(F (3,15) = 2.0, p = .16, g p2 = .28 for participant T;

F (3,15) = 2.1, p = .14, g p2

= .29 for participant F). The maineffect of distortion type was also non-significant

(F (1,15) = 0.7, p = .40, g p2 = .05 for participant T;

F (1,15) = 2.0, p = .18, g p2 = .12 for participant F). These sta-

tistical results were qualitatively the same as those for the

human participants who did not have extensive experience

with this experiment. Thus, expertise with the trackball

device or with the perturbation did not explain the species

difference in the allocation of attention during online mo-

tor adjustment.

4. Discussion

We examined the difference between chimpanzees and

humans in their reliance on automatic motor control and

investigated when and to what extent they shifted their

attention from the goal to their own motor kinematics.

We found that the two species were similar with respect

to online motor correction in response to feedback error,

whereas the attentional allocation for that motor adjust-

ment differed. Humans were sensitive to both goal and tra-

jectory information about gaze shift, whereas chimpanzees

were mainly sensitive to goal information. Our results sug-

gest that chimpanzees have a more parsimonious cognitive

system in that they relied on an automatic process for on-

line motor adjustment as long as they were able to reach

the planned action goal. The motor system recruited their

deliberate attention only when they could not reach the

goal. In contrast, humans appeared to have more complex

criteria for shifting to deliberate control of their action and

exerted excess attentional monitoring over their own mo-

tor kinematics.

One may argue that because the chimpanzees were

interested only in the food reward and thus lacked motiva-

tion to move the cursor precisely to hit the target, they did

not pay attention to the detailed motor kinematics re-

quired to reach the target. However, this is unlikely, be-

cause the chimpanzees showed a certain amount of

corrective movement under the goal-congruent condition.No corrective movement was necessary to obtain a reward

6 12 28 46-500

250

1000

1750

2500

M o v e m e n t t i m e ( m s )

Distortion (degree)

Chimpanzees

6 12 28 46-500

250

1000

1750

2500

M o v e m e n

t t i m e ( m s )

Distortion (degree)

Humans


Fig. 6. Movement time under perturbation. Mean movement time across participants as a function of distortion amplitude. The figure shows the values for

each test condition subtracted from the values for the baseline condition. Error bars indicate standard errors.


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under this condition, and yet the chimpanzees modified

their limb motor movement. If they were interested only

in getting rewards, the chimpanzees would not have

shown corrective movements under this condition. Thus,

a lack of motivation to control the cursor precisely is unli-

kely to explain the species difference in the allocation of

attention. Furthermore, we confirmed that the time re-

quired to hit the target could not explain the species differ-

ences. We also ruled out the possibility of expertise effects.

The overall results of expert human participants were the

same as those for human participants who did not undergo

extensive training. These results eliminate the possibility

that the difference in gaze pattern derived from expertise.

In our previous study, we investigated the relative con-

tributions of kinematic information and goal representa-

tions to self-monitoring in chimpanzees and humans

(Kaneko & Tomonaga, 2012). Both species performed aim-

ing actions whereby participants moved a cursor to hit tar-

gets. Additionally, a distractor cursor was presented

simultaneously, and participants discriminated a cursor

under their control from a cursor not under their control.

The results showed that chimpanzees found it difficult to

determine whether they were controlling the distractor

when it moved toward the same target as the one the par-

ticipant intended to hit, even though the distractor’s kine-

matics and the participant’s actions were dissociated.

These results suggest that goal representation, rather than

motor kinematics, is the primary source of information for

self-monitoring in chimpanzees. However, the monitoring

process for the outcome of one’s own action occurs hierar-

chically; that is, sensorimotor processing occurs at a lower

level, and conceptual representation of action goals occurs

at a higher level. It is hard to believe that chimpanzees are

insensitive to their own motor kinematics with respect to

sensorimotor control. In our previous study, we hypothe-

sized that the species difference we observed reflected a

difference in the extent to which implicit motor informa-

tion can reach explicit recognition. However, we were un-

able to determine to what extent automatic/implicit and

more explicit aspects of monitoring were involved in that

task. The present study directly supports our hypothesis.

We found that both species showed similar sensitivity to

altered visual feedback in terms of limb motor adjustment.

However, we observed a clear difference in how the two

species allocated their overt attention to these motor

adjustments. In chimpanzees, unlike in humans, the feed-

back error that occurred at the motor kinematics level

was insufficient to trigger overt attention to it. Overall,

our results support the view that chimpanzees and hu-

mans differ in the extent to which implicit kinematic mo-

tor information reaches explicit recognition (Kaneko &

Tomonaga, 2012).

Our results indicate that the species difference in copy-

ing actions is due not only to the difference in the recogni-

tion/encoding of others’ actions but also to the difference

in the execution of one’s own actions. Many studies have

revealed that great apes tend to copy the goal, but not

the kinematic aspects, of others’ actions, whereas human

show a bias toward copying the kinematics of actions (Call,

2001; Call et al., 2005; Myowa-Yamakoshi & Matsuzawa,1999; Myowa-Yamakoshi & Matsuzawa, 2000; Nagell

et al., 1993; Tennie et al., 2006; Tomasello et al., 1987 ).

Our results suggest that chimpanzees’ control of motor

kinematics is highly dependent on the automatic aspects

of motor control, making it difficult for chimpanzees to

imitate a motor action in the absence of an explicit action

goal. Thus, the extent to which species differ in the encod-

ing/recognition of others’ actions remains unclear because

most studies have not differentiated between the observa-

tional and executional aspects of copying actions and have

focused exclusively on the recognition aspect. On the one

hand, there is growing evidence in support of the direct-

matching hypothesis, which holds that the same neural

circuits are involved in perceiving and understanding oth-

ers’ actions and in executing one’s own actions (Rizzolatti

& Craighero, 2004; Rizzolatti, Fogassi, & Gallese, 2001).

For example, Kanakogi and Itakura (2011) showed a devel-

opmental correspondence between the ability to recognize

the action of others and the ability to execute the same ac-

tion in early infancy. Following this theory, it can be argued

that the ability to deliberately control one’s own motor

kinematics and the ability to both explicitly and implicitly

encode the detailed motor kinematics of others’ actions

may be related, from an evolutionary perspective.

A growing number of studies in recent years have iden-

tified neural differences between humans and other prima-

tes, including chimpanzees, which seems consistent with

our view. Hecht et al. (2012) discussed connectivity differ-

ences in the mirror system among chimpanzees, maca-

ques, and humans. They found that only humans possess

a dense connection between the superior parietal cortex

and temporal cortex on diffusion tensor imaging, which

may support spatial attention to the kinematics of motor

action. Additionally, functional imaging studies suggest

that the human brain may process actions at a higher level

of kinematic/motion detail. Non-human primates have

more frontal activation than do humans during the obser-

vation/execution of grasping movements (Hecht et al.,

2013; Nelissen, Luppino, Vanduffel, Rizzolatti, & Orban,

2005), suggesting that non-human primates represent

incoming visual information using higher-order cognitive

operations (Denys et al., 2004) involving coding the ab-

stract goal rather than the detailed motor kinematics. Fur-

thermore, humans show parietal cortex responses to

observed actions that are lacking in macaques, suggesting

that humans process observed actions at a higher level of

movement detail (Peeters et al., 2009; Vanduffel et al.,

2002).

Our present findings raise the question of why humans

evolved the ability to monitor redundant motor kinematics

with deliberate attention to detail. The execution and

adjustment of motor kinematics entails implicit processing

and is generally beyond one’s deliberate intentional con-

trol (Mechsner et al., 2001; Norman & Shallice, 1986;

Pisella et al., 2000). Automatic control of a motor action

enables us to perform motor movement smoothly and

quickly and also allows us to save cognitive resources such

as attention (Liu, Chua, & Enns, 2008). Furthermore,

excessive attention to one’s own motor kinematics inter-

feres with performance of the motor repertoire of familiar

routines (Beilock, Carr, MacMahon, & Starkes, 2002; Gray,2004). Primate species evolved distinct neural architecture


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for planning abstract action goals and converting them into

actual motor actions (Hoshi & Tanji, 2007; Tanji & Hoshi,

2008) and for online motor control of the actual motor exe-

cution (Desmurget & Grafton, 2000). Thus, it is an optimal

and adaptive strategy not to pay attention to the execution

and control of motor kinematics, as the usual motor rou-

tines are sufficient to achieve the goal of an ongoing action.

Therefore, it is rather peculiar that human participants fo-

cused overt attention on motor kinematics when feedback

errors occurred in the spatiotemporal parameters of ac-

tions that could have been managed automatically.

The advantage of extensive attention to motor kinemat-

ics may be that humans can thereby develop a novel motor

repertoire, particularly via imitation. If the imitator readily

appreciates the goal of others’ actions, then emulation is a

sufficient strategy to reproduce others’ motor actions.

However, if the goal of others’ actions is obscure, then

the imitator needs to pay attention to the spatiotemporal

characteristics of others’ actions. As the direct-matching

hypothesis states (Kanakogi & Itakura, 2011; Rizzolatti &

Craighero, 2004; Rizzolatti et al., 2001), the recognition of

others’ action goals seems to partially depend on the neu-

ral mechanism for the execution of one’s own actions,

which, in turn, means that to understand the goals under-

lying others’ actions, one should already have acquired the

skill to perform the same goal-directed action. Therefore,

imitation of detailed motor kinematics, rather than simple

reproduction of others’ goal actions, may be necessary to

truly expand the novel repertoire of goal-directed behav-

iors. In fact, human infants copy others’ actions even when

they have an alternative, more efficient behavioral strategy

to achieve the same goal (Gergely, Bekkering, & Kiraly,

2002; Jones, 2009; Nielsen, 2006). Human infants have a

stronger bias for imitation than for mere reproduction of

a goal. This tendency has been proposed to be an adaptive

strategy for cultural transmission of complex action reper-

toires. Furthermore, the advantage of extensive attention

to motor kinematics is not limited to imitation but in a

more general context. Theoretical and experimental stud-

ies have indicated that humans pay more attention to ac-

tion kinematics when they are learning novel motor

actions (Curran & Keele, 1993; Nissen & Bullemer, 1987;

Norman & Shallice, 1986; Sailer et al., 2005; Taylor &

Thoroughman, 2007; Willingham, 1998). Thus, extensive

attentional monitoring of one’s own kinematics could be

advantageous to the acquisition of a variety of motor

repertoires during the course of ontogenic development.

Our results showed chimpanzees were insensitive to

motor kinematics at the explicit level. However, our results

do not necessarily mean that they never monitor kinemat-

ics explicitly. It may be better to consider the species dif-

ference as a matter of extent. Horner and Whiten (2005)

showed that chimpanzees have the ability to copy motor

kinematics during social learning in a particular situation

when goal emulation is not available and when copying a

motor action is the only way to solve the problem. How-

ever, chimpanzees immediately switch to copying only

goals once the situation allows. These authors suggested

that chimpanzees share the ability to attend to and copy

action-specific methods with humans to some extent, but

that chimpanzees have a bias toward goal-copying,

whereas humans have a bias toward method-copying

(which has been called ‘over-imitation’). Thus, it seems

possible that chimpanzees may be capable of deliberately

monitoring their own kinematics but that they may exer-

cise this ability only under very limited circumstances,

whereas humans may have a relatively stronger bias to-

ward kinematic monitoring. The opposite is also true,

namely that not all kinematic errors reach explicit recogni-

tion in humans. Metcalfe and Greene (2007) asked human

participants to perform an aiming action where a hidden

force helped participants achieve their goal (compensating

for their errors). Participants felt better control when task

performance was experimentally manipulated so that it

appeared they achieved the task goal more efficiently than

was actually the case. This result suggests that the detec-

tion of errors at the kinematic level may be masked by

the monitoring process at a more abstract level. It requires

further research to understand how error detection at an

implicit level reaches explicit recognition and to under-

stand how the two levels of processing interact.

As a final note, we found that the species differed in

their reliance on automatic motor control and the atten-

tional monitoring of their own motor kinematics. It is

widely accepted that sophisticated motor repertoires have

evolved in humans (Courtine et al., 2007; Heffner &

Masterton, 1975; Heffner & Masterton, 1983; Nakajima,

Maier, Kirkwood, & Lemon, 2000). Our results suggest that

the deliberate attention to one’s own motor kinematics

may have also evolved in the human lineage in response

to the demand for expanding the variety of one’s novel

motor repertoires during the course of ontogenic

development.

Acknowledgments

We thank Drs. Tomoko Imura and Christoph D. Dahl for

useful discussion. We also acknowledge the continuous

support of Dr. Tetsuro Matsuzawa. This project was finan-

cially supported by JSPS-MEXT Grants-in-Aid for Scientific

Research (212668, 16002001, 19300091, 20002001 and

23220006) and the Global COE Program (A06, D07).

Appendix A. Supplementary data

Supplementary data associated with this article can be

found, in the online version, at http://dx.doi.org/10.1016/ j.cognition.2014.02.002.

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