Mine and Me: Exploring the Neural Basis of

Mine and Me: Exploring the Neural Basis of
Object Ownership

David J. Turk, Kim van Bussel, Gordon D. Waiter, 和C. Neil Macrae

抽象的

■ Previous research has shown that encoding information in
the context of self-evaluation leads to memory enhancement,
supported by activation in ventromedial pFC. Recent evidence
suggests that similar self-memory advantages can be obtained
under nonevaluative encoding conditions, such as when object
ownership is used to evoke self-reference. Using fMRI, 当前的
study explored the neural correlates of object ownership. 期间
scanning, participants sorted everyday objects into self-owned or
other-owned categories. Replicating previous research, a signifi-
cant self-memory advantage for the objects was observed (IE。,
self-owned > other-owned). 此外, encoding self-owned

items was associated with unique activation in posterior dorso-
medial pFC (dMPFC), left insula, and bilateral supramarginal gyri
(SMG). Subsequent analysis showed that activation in a subset of
these regions (dMPFC and left SMG) correlated with the magni-
tude of the self-memory advantage. Analysis of the time-to-peak
data suggested a temporal model for processing ownership in
which initial activation of dMPFC spreads to SMG and insula.
These results indicate that a self-memory advantage can be elic-
ited by object ownership and that this effect is underpinned by
activity in a neural network that supports attentional, reward,
and motor processing.

介绍

Human identity is no longer defined by what one
做, but by what one owns (President Jimmy
Carter, Crisis of Confidence Speech, 15 七月 1979).

Ownership refers to the classification of a physical or
mental object as belonging to self and is a core facet of
human experience ( James, 1929). It pertains to our sense
of owning our bodies and movements and accumulated
material wealth. We can also claim ownership of ideas
and places, as well as other people (IE。, my wife). 的确,
the feeling of ownership extends to just about anything
for which the terms mine, 我的, or ours (for joint owner-
船) can be applied. It can be founded in the laws of
社会 (IE。, legal ownership) or manifest in the feelings
held toward an object that is owned by the individual
(IE。, psychological ownership) without any legal claim to
title (Pierce, Kostova, & Dirks, 2003). Noting this distinc-
的, Etzioni (1991) refers to the feeling of mineness that
is associated with psychological ownership, an experience
we explore in the current investigation. The question
motivating our inquiry is quite straightforward, what hap-
pens in the brain when people acquire arbitrary psycho-
logical ownership over a set of objects?

Ownership and the Self

In an influential article, 加拉格尔 (2000) has explored the
relationship between ownership and self. He states that

University of Aberdeen

this minimal sense of self is grounded in the moment-to-
moment mapping of intentions to act with the sensory
and proprioceptive feedback that accompanies the actions.
因此, we have a sense of body ownership and the ability to
author actions with that body ( Jeannerod, 2003). 虽然
these “minimal” components of self as agent and owner
of actions are generally indistinguishable in voluntary ac-
系统蒸发散, it is possible to experience action ownership without
the accompanying agentic control (Frith, 1992; 范伯格,
1978). Recent neuroimaging studies indicate a functional
role for parietal cortex in the experience of self as the
author of action (Farrer et al., 2008; Shimada, Hiraki, &
Oda, 2005). This bodily self-awareness, manifest in match-
ing intention and sensation, affords a mechanism to dis-
tinguish self from non-self-action. 重要的, agentic
movements may, on occasion, result in self-relevant out-
来了 (both good and bad). One such outcome may be
the acquisition of an object.

Although a minimal self may enable us to form a momen-
tary association with an object, it cannot easily recognize
the self-relevance of this item. For this to occur, Gallagherʼs
(2000) minimal self needs to be extended to include a
memorial component. The development of an extended
autobiographical or narrative self, with the ability to store
self-knowledge, allows us to form associations with self-
相关信息, 物体, 和人 (Damasio, 1999).
因此, object ownership represents the mental synthesis of
object and self in time. The relationships we form with a
childhood comforter, a wedding ring, or a birthday gift
from a child are all important aspects of this extended, 我-
morial self. 实际上, these self–object associations form the

© 2011 麻省理工学院

认知神经科学杂志 23:11, PP. 3657–3668

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basis for the concrete self-construct developed in early
童年 (Dyl & Wapner, 1996; Montemayor & Eisen,
1977). Loss of material possessions through theft or damage
or the need sell sentimental objects when moving into a
nursing home can be devastating and experienced as a loss
of self (Cram & Paton, 1993; Pierce et al., 2003). Given the
significance of material objects to the development and
maintenance of our sense of self, it is important to under-
stand how these associations are formed and the resultant
impact they exert on cognition and behavior.

As a result of their association with self, owned ob-
jects are believed to enjoy a special psychological status
(Beggan, 1992). 的确, owned objects are viewed as ex-
tensions of self, as Sartre states, “I am what I have…What
is mine is myself” (Sartre, 1943/1969, PP. 591–592; see also
James, 1890). This is further illustrated by the “mere owner-
ship” effect, a tendency for objects arbitrarily assigned
to self (IE。, owned but not chosen by self ) to be imbued
with more positive characteristics (Beggan, 1992; Belk,
1988, 1991) and to be perceived as more valuable (IE。, 这
endowment effect; Kahneman, Knetsch, & Thaler, 1991;
Knetsch & Sinden, 1984) and subsequently more memo-
rable than identical items not assigned to self ( Van den
Bos, 坎宁安, 康威, & Turk, 2010; 坎宁安,
Turk, & Macrae, 2008). This skewing of value and valence
reflects the operation of positivity biases that distort the
evaluation of material possessions that comprise an im-
portant element of self (Beggan, 1992; Belk, 1988, 1991;
Kahneman et al., 1991; Knetsch & Sinden, 1984).

Notwithstanding the observation that we are what we
own, recent neuroimaging investigations have focused on
the effect of explicit, evaluative self-referential encoding
on memory. In the most widely used paradigm (Turk,
坎宁安, & Macrae, 2008; Heatherton et al., 2006;
Macrae, Moran, Heatherton, Banfield, & Kelley, 2004; Kelley
等人。, 2002; 罗杰斯, Kuiper, & Kirker, 1977; see Symons &
约翰逊, 1997, for a review), participants are required
to evaluate personality traits on the degree to which they
describe either self or a familiar other person (例如, 乔治
瓦. 衬套, Angelina Jolie). When memory for the trait words
is subsequently assessed, those encoded in relation to self
are better remembered than those processed in the con-
text of a familiar other. This so-called self-reference effect
is a reliable phenomenon that has been reported in a range
of experimental settings (see Symons & 约翰逊, 1997).

Psychological ownership, 所以, offers an alternative
route to study self through its association with objects.
Cunningham et al. (2008) tested subjects in pairs and told
them to imagine that they each owned one of two colored
shopping baskets that were placed in front of them. 帕-
ticipants were asked to place pictures of items found
in any supermarket (例如, apple, socks, pencil ) 进入
baskets on the basis of a color-sorting task, at the end of
which they each “owned” the items in one of the baskets.
The task was operationalized, such that action (IE。, mov-
ing the item) was equally shared between self-owned and
other-owned items. At the end of this sorting task, a recog-

nition memory task revealed a significant memorial ad-
vantage for items owned by self, regardless of who acted
upon the object.

What Cunningham et al.ʼs (2008) findings reveal is that
self-item associations forged through psychological owner-
ship yield a similar mnemonic advantage to that generated
through the explicit, evaluative encoding of trait adjectives
(Turk et al., 2008; Symons & 约翰逊, 1997). This then
raises an interesting question: To what extent are owner-
ship effects supported by activation of the neural systems
associated with self-referential processing?

The Neural Basis of Self-referential Encoding

A recent meta-analysis of functional neuroimaging studies
suggests that self-referential processing is supported by
activity in a network of cortical midline structures (CMS), 在
addition to task-related lateral brain areas (Northoff et al.,
2006). The CMS areas engaged in core aspects of self-
referential cognition include ventromedial pFC (vMPFC),
dorsomedial pFC (dMPFC), posterior cingulate, and parietal
cortices (Amodio & Frith, 2006; Heatherton et al., 2006;
Macrae et al., 2004; Kelley et al., 2002). Northoff et al.
(2006) argue that these commonly activated regions have
specific functional roles in the instantiation of a core men-
tal self. 具体来说, the vMPFC functions as a polymodal
convergence zone between exteroceptive sensory areas
(例如, amygdala, BG including the striatum and nucleus
accumbens) and interoceptive areas in the midbrain and
brainstem. 此外, the dorsal part of the medial pFC
(including the anterior cingulate) is densely connected to
lateral pFC (including the insula). These regions are be-
lieved to play an important role in affective processing and
the reappraisal and evaluation of stimuli with regard to self
(and “mind reading” ;Frith & Frith, 2003). 最后, the pos-
terior regions (composed of cingulate, retrosplenial, 和
parietal cortices) are densely connected to the hippocampus
and may, 所以, reflect activity associated with autobio-
graphical aspects of the self.

In the case of the trait–adjective paradigm (Kelley et al.,
2002), the coactivation of ventromedial and posterior CMS
areas reflects a need to evaluate external cues against inter-
nal representations of self in memory (例如, “am I happy?”).
But what of object ownership, how may it be supported
in the brain? In addition to the aforementioned regions, 它
may be expected that ownership would also activate areas
associated with affective processing, as acquiring an object
is a potentially rewarding experience. 在人类中, the neural
basis of reward has been studied in the context of taking
addictive substances (David et al., 2005; Stein et al., 1998;
Breiter et al., 1997), monetary gains and losses (Chiu,
Holmes, & Pizzagalli, 2008; 刘等人。, 2007; Elliott, 弗里斯顿,
& Dolan, 2000; Koepp et al., 1998; Thut et al., 1997), 风险-
taking behavior (Dreher, 2007; Bechara, Damasio, Damasio,
& 安德森, 1994; Damasio, 1994), listening to music
(Menon & Levitin, 2005), and sexual intercourse (Ortigue,
Grafton, & Bianchi-Demicheli, 2007). Brain areas associated

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认知神经科学杂志

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with reward and hedonic experience include the striatum,
midbrain, thalamus, orbito-frontal cortices, limbic areas (在-
cluding the amygdala and insula), and medial pFC (刘等人。,
2007; 克林格尔巴赫 & Rolls, 2004; Damasio, 1996). We could,
所以, expect that in addition to CMS activation as-
sociated with self, psychological ownership may recruit a
subset these affective brain regions reflecting the hedonic
importance of self–object associations.

The Current Study

To determine the neural correlates of psychological owner-
船, we used fMRI to measure brain activity while par-
ticipants performed a simple sorting task similar to that
employed by Cunningham et al. (2008). Participants were
required to allocate shopping items to one of two baskets
(one of which was owned by self ) by means of a button
press. Following this sorting phase, participants undertook
a surprise recognition test to assess the impact of owner-
ship on memory. Because object possession reflects a
combination of self-referential and affective processing
(Pierce et al., 2003; Beggan, 1992; Belk, 1991), we expected
cortical midline areas as well as regions associated with
positive reward to underpin psychological ownership.

方法

参加者

Nineteen participants (12 女性) recruited from the
University of Aberdeen undergraduate community took
part in the study. All participants were right-handed, 本国的
English speakers with no history of neurological problems.
All gave informed consent according to the procedures
approved by the Grampian Region Ethics Committee.

Design and Stimulus Materials

The experiment included an encoding (IE。, sorting) phase
and a recognition test phase. Both were carried out while
participants were lying in the magnet bore, but only brain
activity at encoding was recorded. Before scanning com-
menced, participants were informed that the experiment
was designed to measure the neural activity associated with
sorting shopping items according to a color cue. 期间
the encoding phase, images were presented in two func-
tional runs. Each run contained 72 trials of interest and
38 rest trials. During the encoding phase images of two
colored shopping baskets were presented in the top left
(blue basket) and top right quadrants (red basket) 的
visual field. Participants were informed that one basket
belonged to them, whereas the other belonged to the ex-
perimenter in the control room. The color of the basket
associated with self or experimenter was counterbalanced
across participants. The task was to place items into the
correct basket by matching a color patch presented di-
rectly above the item with the color of the basket.

The stimulus set comprised 216 full color photographic
images of items available for purchase in a large super-
市场 (例如, 食物, 衣服, electrical items) sized to 400 ×
400 pixels at a resolution of 72 dpi. They were divided
into three equal sets (matched for item type, word length
and number of syllables, and broadly on purchase price).
One of the sets was paired with a red color patch, 一
was paired with a blue color patch, and the third was used
as foils in a surprise recognition memory test that followed
the encoding phase. In this phase, 全部 216 items were pre-
sented individually, and participants made an old/new rec-
ognition judgment.

During the encoding phase, a single item was presented
为了 2 秒. Following a 500-msec delay interval, a circular
color patch (50 pixels in diameter) was presented to de-
note the location into which the item should be placed.
Participants were then required to make a response with
either the left or right index finger to place the item into
the appropriate colored basket. There was then a 500-msec
intertrial interval in which only the two colored baskets
remained on the screen. In addition to the 144 encoding
试验, data from a further 76 randomly interleaved “jittered”
rest trials were also collected. On these rest trials, only the
basket image remained on the screen for the full 2.5-sec
TR period. During the test phase, 全部 216 stimuli were used.
Each was centrally presented and remained on the screen
while participants made an old/new recognition memory
判断.

Image Acquisition

Image acquisition was undertaken on a 1.5-T whole body
scanner (GE Healthcare) with a standard head coil. Cush-
ions were used to minimize head movement. Anatomical
images were acquired using a high-resolution 3-D spoiled
gradient recalled echo sequence (124 sagittal slices, =
3.2 毫秒, TR = 8 毫秒, flip angle = 15°, voxel size = 1 ×
1 × 1.6 毫米). Functional images were collected in runs,
each comprising 110 volumes using a gradient spin-echo,
echo-planar sequence sensitive to BOLD contrast (TR =
2500 毫秒, = 40 毫秒, flip angle = 90°, 3.75 × 3.75 在-
plane resolution). For each volume, 30 axial slices, 5-毫米
slice thickness and 0-mm skip between slices, were ac-
quired allowing complete brain coverage.

结果

Image Analysis

Preprocessing and analysis of the imaging data were per-
formed using SPM2 (Wellcome Department of Cognitive
Neurology, 伦敦, 英国). 第一的, functional data were time-
corrected for differences in acquisition time between slices
for each whole-brain volume and realigned to the first vol-
ume to minimize the effects of head movements on data
分析. Functional data were then transformed into a stan-
dard anatomical space (2-mm 各向同性体素) 基于

Turk et al.

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the ICBM 152 brain template (MNI). Normalized data were
then spatially smoothed (6 mm FWHM) using a Gaussian
kernel. Statistical analyses were performed using the gen-
eral linear model. An event-related design was modeled
using a canonical hemodynamic response function and
its temporal derivative. The model also included regressors
for additional covariates of no interest (例如, linear trends
for each functional run). This analysis was performed indi-
vidually for each participant, and resulting contrast im-
ages were subsequently entered in a second-level analysis,
treating participants as a random effect. To minimize false-
positive results, we ran a Monte Carlo simulation (看
Slotnick, Moo, Segal, & 哈特, 2003) to determine the mini-
mum cluster size necessary to enforce an a priori threshold
of p < .05 (corrected for multiple comparisons). This simu- lation effects were considered statistically significant using a criterion of 27 or more contiguous resampled voxels at a voxelwise threshold of p < .0001. For each functional run, data were preprocessed to re- move sources of noise and artifact. Functional data were corrected for differences in acquisition time between slices for each whole-brain volume, realigned within and across runs to correct for head movement, and coregistered with each participantʼs anatomical data. Functional data were then transformed into a standard anatomical space (3 mm isotropic voxels) based on the ICBM 152 brain template (MNI), which approximates Talairach and Tournouxʼs atlas space. Normalized data were then spatially smoothed using a Gaussian kernel (6 mm FWHM). For each participant, a general linear model specifying task effects (modeled with a function for the hemodynamic response) and runs (mod- eled as constants) was used to compute parameter esti- mates (β) and t contrast images for each comparison at each voxel. These individual contrast images were then submitted to a second-level, random-effects analysis to ob- tain mean t images. A direct contrast between the two con- ditions of interest (thresholded at p < .0001, uncorrected; K > 27; see Slotnick et al., 2003) revealed a network of
brain areas more active for owned than not-owned objects.
These regions are reported in Talairach atlas space.

Event-related fMRI Latency

To determine the latency or time to peak for each condition
(IE。, self-owned vs. other-owned), functional activity was
modeled using one regressor for each condition. 那里-
gressors were obtained by convolving the vector of onsets
of each condition with a canonical hemodynamic response
function, as described by SPM2. This resulted in two pre-
dictors of brain activity for each experimental run. 这
model was fitted to the fMRI time course data on a voxel-
by-voxel basis. The fitted hemodynamic response for each
condition and each participant in a number of ROIs (的-
termined from the self-owned > other-owned contrast)
was extracted. The individual fitted hemodynamic re-
sponse curves were then averaged to produce a grand
average hemodynamic response curve. The latency of each

condition in each ROI was therefore the time to peak of
this grand average response curve (IE。, the time after stim-
ulus onset where the maximum fitted signal amplitude
occurred). This calculation affords a mechanism to de-
termine the time at which each brain region reached its
peak level of activation (Sun, 磨坊主, & DʼEsposito, 2005).
This analysis can therefore be used to explore the temporal
relationship in activity across regions of the ownership
网络.

Behavioral Data

Overall recognition rates were reasonable for this type of
任务 (Hits Self = .55, Hits Other = .42, False Alarms =
.21). Each participantʼs recognition score was corrected
for baseline false alarm rate by subtracting the propor-
tion of old responses to foils from the proportion of old
responses to previously presented items. Participantsʼ cor-
rected scores were submitted to a single factor (所有权:
self-owned or other-owned) paired t test. The analysis re-
vealed a significant effect of ownership [t(18) = 3.944, p < .001, two-tailed], such that more self-owned than other- owned items were correctly recognized (mean = 0.34 (SD = 0.14) and mean = 0.21 (SD = 0.11), respectively). fMRI Analysis To explore differences in brain activation to owned and not-owned objects, two specific contrasts were conducted. First, we explored brain regions, in which BOLD signal was greater for owned than not-owned objects. This contrast revealed a network of areas including a large cluster of voxels on the medial surface of the superior frontal gyrus (SFG; BA 6) extending dorsally to a caudal region of the ACC (cACC; BA 24/32). In addition, activation was also ob- served in left insula (including frontal operculum), bilateral regions of the anterior inferior parietal lobe (BA 2, 40), and right superior temporal cortex (BA 22) (see Figure 1A and B). Significant BOLD increases were also observed in the cerebellum and in subcortical structures (e.g., bilateral thal- amus, left putamen, left globus pallidus; see Table 1, top). The second contrast examined brain regions showing greater BOLD signal for other-owned relative to self-owned items. This analysis revealed a number of brain regions more active during the encoding of other–object relations (see Table 1, bottom). Of particular interest, regions lo- cated along the cortical midline (see Figure 2C), previously shown to be important in self-referential processing, were more active during other than self-trials. Kelley et al. (2002) reported task-related decreases in posterior cingu- late (BA 23/31) and vMPFC (BA 10) during explicit, eval- uative encoding. The contrast BOLD difference in these regions was characterized by significantly greater deactiva- tion on trials in which other-referential processing occurred relative to self-related activity. Task-related deactivation relative to rest in anterior and posterior cortical midline 3660 Journal of Cognitive Neuroscience Volume 23, Number 11 D o w n l o a d e d l l / / / / j f / t t i t . : / / f r o m D o h w t t n p o : a / d / e m d i f r t o p m r c h . s p i l d v i r e e r c t c . m h a i e r d . u c o o m c n / j a o r t c i c n e / - a p r d t i 2 c 3 l 1 e 1 - 3 p 6 d 5 f 7 / 1 2 9 3 4 / 1 1 8 1 7 / 5 3 6 o 5 c 7 n _ / a 1 _ 7 0 7 0 6 0 8 4 4 2 1 p / d j o b c y n g _ u a e _ s 0 t 0 o 0 n 4 0 2 8 . S p d e f p e b m y b e g r u 2 e 0 s 2 t 3 / j t . / f o n 1 8 M a y 2 0 2 1 D o w n l o a d e d l l / / / / j t t f / i t . : / / f r o m D o h w t t n p o : a / d / e m d i f r t o p m r c h . s p i l d v i r e e r c t c . m h a i e r d . u c o o m c n / j a o r t c i c n e / - a p r d t i 2 c 3 l 1 e 1 - 3 p 6 d 5 f 7 / 1 2 9 3 4 / 1 1 8 1 7 / 5 3 6 o 5 c 7 n _ / a 1 _ 7 0 7 0 6 0 8 4 4 2 1 p / d j o b c y n g _ u a e _ s 0 t 0 o 0 n 4 0 2 8 . S p d e f p e b m y b e g r u 2 e 0 s 2 t 3 / j f / . t Figure 1. (A and B) Brain regions more active for self-owned than other-owned trials and their corresponding parameter estimates (calculated as the average for all voxels in the ROI). Error bars indicate SEM. (C) Areas that show a significant correlation between ROI parameter estimate and self-memory bias (self-other memory). Table 1. Group Activations Associated with Ownership Coordinates Brain Region Self Owned > Other Owned

Frontal cortex

Medial surface of SFG

Extending to cACC

Left insula/frontal operculum

Parietal cortex

Right precentral gyrus

Right precentral gyrus

Right supramarginal/postcentral gyrus

Left SMG

Extending to postcentral gyrus

Left postcentral gyrus

Right postcentral gyrus

X

4
−2
−42

36

42

51
−46
−50
−65

60

y

−3

8
−3

−9
−13
−26
−35
−27
−20
−20

z

50

38

9

59

56

53

46

46

19

18

t

BA

13.39

9.39

9.26

10.83

8.42

10.24

9.84

8.80

7.95

6.26


n

1
8

中号
A
y

2
0
2
1

6

24/32

4/6

4

2/40

40

2/40

2

42/2

Turk et al.

3661

桌子 1. (continued )

Brain Region

Temporal cortex

Right superior temporal gyrus

小脑

小脑

小脑

小脑

小脑

小脑

Subcortical

Left putamen

Left medial globus pallidus

Right thalamus

Other Owned > Self Owned

Frontal cortex

Left middle frontal gyrus

Left middle frontal gyrus

Right middle frontal gyrus

Anterior cingulate

Cingulate/calloso SMG

Medial/SFG

dMPFC

vMPFC

vMPFC

Parietal cortex

Right angular gyrus

Left posterior cingulate

Left precuneus extending to PCC

Right postcentral gyrus

Temporal cortex

Right middle temporal gyrus

Left superior occipital gyrus

Extending to

Left superior occipital gyrus

Left superior temporal gyrus

Coordinates

y

6

10

−69
−68
−67
−63
−52

2

0
−19

8

29

29

33

25

31

46

49

54

54

57

−70
−55
−44
−63
−11

−69
−51

−65
−59

X

48

55

0

4
−28

24

42

−28
−10

2

−44
−24

28

24

36

6

10

18

10
−6
−4

50
−12
−4
−2

42

53
−44

−42
−57

z

0
−4

−22
−10
−22
−22
−21

0

4

10

49

41

32

44

39

6
−7

10

27
−6

5

29

21

43

14

23

11

25

25

23

t

6.15

5.84

6.85

6.14

11.47

5.54

8.22

8.11

6.94

6.36

8.17

9.10

6.22

6.01

5.73

4.94

5.7

8.06

7.26

6.25

6.68

6.63

8.43

9.04

8.08

5.77

6.46

8.01

7.65

6.81

BA

22

21

6

8

9

8/9

8

24

32/10

10

9

10

10

39

31/23

31/7

31

43/41

39

19

19

39

3662

认知神经科学杂志

体积 23, 数字 11

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桌子 1. (continued )

Brain Region

Right superior temporal gyrus

Left middle temporal gyrus

Right hippocampal gyrus

Left middle temporal gyrus

Left lingual gyrus

Left middle temporal gyrus

Right superior temporal gyrus

Right superior temporal gyrus

Left superior temporal gyrus

Subcortical

Left anterior commissure/hippocampus

Coordinates

y

−59
−49
−49
−46
−45
−27
−14
−6

5

−9

z

23

1

1

4
−4
−2
−11

10
−14

−16

X

55
−53

30
−61
−22
−61

51

57
−40

−34

BA

37

21

19

21

19

21

41/42

42

38

t

7.43

6.96

6.25

7.35

6.77

5.99

6.39

5.54

8.39

6.3

Activations determined to be significant are listed along with the best estimate of their location. BA = approximate Brodmannʼs area. Coordinates are
from the Talairach and Tournoux (1988) atlas. Locations of the activations are determined based on the functional responses superimposed on averaged
anatomical MRI images and are referenced to the Talairach and Tournoux atlas. Minimum cluster size = 27 voxels ( p < .0001, uncorrected). D o w n l o a d e d l l / / / / j f / t t i t . : / / f r o m D o h w t t n p o : a / d / e m d i f r t o p m r c h . s p i l d v i r e e r c t c . m h a i e r d . u c o o m c n / j a o r t c i c n e / - a p r d t i 2 c 3 l 1 e 1 - 3 p 6 d 5 f 7 / 1 2 9 3 4 / 1 1 8 1 7 / 5 3 6 o 5 c 7 n _ / a 1 _ 7 0 7 0 6 0 8 4 4 2 1 p / d j o b c y n g _ u a e _ s 0 t 0 o 0 n 4 0 2 8 . S p d e f p e b m y b e g r u 2 e 0 s 2 t 3 / j t f . / o n 1 8 M a y 2 0 2 1 Figure 2. (A) Time-to-peak analysis of signal change across SFG/cACC (SFG), supramarginal cortex (SMG), and left insula (LI). (B) Temporal neural model of ownership. Activation in regions highlighted in yellow also predicted self-memory bias. (C) Specific regions of cortical midline (CMS) previously shown to be functionally important in explicit, evaluative self-referential encoding and memory (posterior cingulate and vMPFC). These regions show decreased activation on trials in which objects were owned by self. Turk et al. 3663 sites has been also observed in previous studies exploring default brain state (Raichle & Snyder, 2007; Gusnard & Raichle, 2001; Raichle et al., 2001). What makes the current pattern of cortical midline activity particularly interesting is that in the deactivation observed was significantly greater for self-owned events. This finding is therefore in direct opposition to the pattern of CMS activation observed in previous studies investigating the neural correlates of self- referential processing (e.g., Kelley et al., 2002). Self-memory Bias and the Ownership Network To investigate the relationship between memory perfor- mance and the brain activity that accompanied self-owned trials, we examined the correlation between the BOLD response in the ownership network and self-memory bias (i.e., the difference in memory for self-owned vs. other- owned objects). This revealed a positive relationship be- tween self-memory bias and brain activation in the SFG/ cACC [r(19) = .473, p < .05] and left supramarginal cortex [r(19) = .503, p < .05] (see Figure 1C). However, there was no significant correlation between BOLD response and memory bias in right supramarginal cortex [r(19) = .357, p = .13] or in left insula [r(19) = .312, p = .19]. A Temporal Pattern of Activation in the Ownership Network In addition to exploring the spatial extent of the ownership network, we also performed an analysis of the temporal aspects of the BOLD signal when processing self-owned objects. This analysis examined the time-to-peak latency in medial pFC (including SFG and cACC), averaged across bilateral parietal cortex (supramarginal and postcentral gyri) and left insular cortex (including frontal operculum). In this analysis, differences in the latency of the peak hemodynamic response function were used to build a tem- poral model of activation during self–object association. The fitted hemodynamic response functions are presented in Figure 2A, along with a simplified temporal model of maximal neural activation in each region (see Figure 2B). For analysis of the time-to-peak data, we explored temporal differences in peak activation across dorsomedial frontal, parietal and fronto-temporal clusters. We submitted the time-to-peak data to a single factor (region: SFG/cACC, bilateral supramarginal gyri [SMG], left insula) repeated- measures ANOVA. This revealed a significant main effect of Region F(1.29, 39.6) = 16.362, p < .001. Post hoc pair- wise t tests exploring the temporal relationship between these three brain regions demonstrated that time-to-peak was significantly faster in medial prefrontal than SMG re- gions [t(18) = -3.191, p < .005] and left insular cortex [t(18) = −4.303, p < .001]. The difference in time-to-peak between parietal cortex and insula also approached sta- tistical significance [t(18) = −1.96, p = .066 ns]. These data suggest a temporal model in which initial activation in dorsal midline areas promulgates secondary activity in lateral posterior and frontal brain regions. DISCUSSION Whereas previous research exploring the self-reference effect in memory and its neural basis has tended to utilize a directed approach to the formation of self-item associa- tions (Macrae et al., 2004; Kelley et al., 2002; Rogers et al., 1977; see Symons & Johnson, 1997, for a full review), the current study supports the notion that self-memory biases can be generated under less evaluative encoding conditions such as object ownership (Van den Bos et al., 2010; Cunningham et al., 2008), unconstrained choice (Cloutier & Macrae, 2008), or the incidental presentation of the perceiverʼs own name or face with the task-relevant information (Turk et al., 2008). The present investigation explored the neural correlates of self–object associations formed through temporary ownership. A Network of Brain Regions for Ownership Brain regions exhibiting increased BOLD response to objects owned by self included posterior dMPFC extend- ing ventrally to cACC (BA 6/24/32), bilateral areas in ante- rior inferior parietal cortex, including the supramarginal and postcentral gyri (BA 40/2), left insula (including the frontal operculum), and right superior temporal gyrus. In addition, BOLD signal increases were also observed bilaterally in the thalamus and in the left medial globus pallidus and putamen. In comparison with rest, activity in these ownership brain areas is characterized by increased BOLD signal, whereas for other-owned objects there ap- pears to be no difference in evoked neural response. This suggests that activation in this network is specific to self– object associations. In addition, this ownership network was characterized by a distinct pattern of temporal onsets where early medial prefrontal activity was followed by ac- tivation in both posterior parietal cortex and insula. This suggests that multiple processes across a range of brain areas support temporary object ownership. Dorsomedial SFG and cACC Initially, self-ownership is characterized by increased activ- ity in cACC and medial SFG. This region has been defined as functionally important in modulating attention to salient stimuli (Chiu et al., 2008; Carretié, Hinojosa, Martin- Loeches, Mercado, & Tapia, 2004), as well as in the sig- naling of positive reward (Liu et al., 2007). Activation of the cACC region has also been observed in studies involv- ing simple cued responses ( Winterer, Adams, Jones, & Knutson, 2002) attributable to motivational, volitional, and effortful task requirements (Winterer et al., 2000) and subsequent information processing and memory. In the current study, signal change in this region correlated with the ownership bias in memory. These dual processes of 3664 Journal of Cognitive Neuroscience Volume 23, Number 11 D o w n l o a d e d l l / / / / j t t f / i t . : / / f r o m D o h w t t n p o : a / d / e m d i f r t o p m r c h . s p i l d v i r e e r c t c . m h a i e r d . u c o o m c n / j a o r t c i c n e / - a p r d t i 2 c 3 l 1 e 1 - 3 p 6 d 5 f 7 / 1 2 9 3 4 / 1 1 8 1 7 / 5 3 6 o 5 c 7 n _ / a 1 _ 7 0 7 0 6 0 8 4 4 2 1 p / d j o b c y n g _ u a e _ s 0 t 0 o 0 n 4 0 2 8 . S p d e f p e b m y b e g r u 2 e 0 s 2 t 3 / j t . f / o n 1 8 M a y 2 0 2 1 attentional modulation and the experiencing of positive reward can be observed in temporal patterns of activity within the ownership network in which activation from this region occurs before activity in anterior inferior pa- rietal cortex and insular cortex that have also been impli- cated in attentional and affective processing, respectively. nal change in this region predicted the magnitude of the observed memorial advantage. Because our sample group was composed of right-handed participants, this finding suggests a possible link between activation of motor afford- ances associated with object use (by the dominant right hand) and self-memory effects. Anterior Inferior Parietal Cortex—Supramarginal and Postcentral Gyri Activation in parietal cortex is generally associated with attentional processes (Milner & Goodale, 1995). Although posterior regions of the inferior and superior parietal lobe have been identified in spatial aspects of attentional orien- tation (Hopfinger, Buonocore, & Mangun, 2000; Corbetta, Miezin, Shulman, & Petersen, 1993; see also Corbetta & Shulman, 2002, for a review), the current study identified anterior aspects of the inferior parietal lobe as functionally important in self–object associations. Specifically, bilateral regions of the SMG (BA 40) and postgentral gyrus (BA 2) showed increased BOLD signal toward self-owned com- pared with other-owned objects. Several studies have also recorded activity in anterior inferior parietal cortex in perceiver-object associations. For example, Handy, Grafton, Shroff, Ketay, and Gazzaniga (2003) suggest that when the potential for acting upon objects is recognized (without specific instruction to do so) this signals increased activation in inferior parietal cortex, predominantly on the left. When compared with viewing or naming houses, faces, animals, or abstract shapes, viewing tools lead to increased activity in identical regions of supramarginal cortex (Chao & Martin, 2000). It has, therefore, been sug- gested that, in contrast to nonmanipulable objects, the per- ception of graspable items is accompanied by activation of the motor affordances associated with those objects (Martin, Wiggs, Ungerleider, & Haxby, 1996; Martin, Haxby, Lalonde, Wiggs, & Ungerleider, 1995) or in the simulation of actions associated with object use (Ruby & Decety, 2001) in anterior inferior parietal lobe. In the current study, participants responded to objects found in any major supermarket (e.g., apple, iPod, beer). Although these items might not be considered as tools, they are all manipulable objects and as such have actions associated with them. It is these motor affordances that are represented in anterior inferior parietal cortex. Of note in the current study is that both self- and other-owned objects have similar action affordances (e.g., apple vs. pear) and yet, compared with rest, BOLD increases in action- related perceptual areas was uniquely associated with self-owned items. This may be because self-ownership signals the motor affordance of objects, whereas objects that belong to others should generally not be touched or used by self without prior approval. In this case, the po- tential for action upon graspable objects owned by others is not activated, and thus, concomitant perceptuo-motor action representations may be suppressed. Subsequent analysis of activity in SMG showed that left lateralized sig- Insula/ Frontal Operculum Previous research has suggested that the insula is involved in a diverse set of functions. When directly stimulated, some regions of the insula give rise to visceral, somes- thetic, and gustatory responses (Penfield & Faulk, 1955). The insula appears to be important for emotional sensa- tion, and projections to limbic regions suggest it plays an important function in the integration of emotion and behavior (Dupont, Bouilleret, Hasboun, Semah, & Baulac, 2003) and the signaling of reward (Liu et al., 2007; see also Phan, Wager, Taylor, & Liberzon, 2002, for a review). Acti- vation in a similar region of the insula was reported by Liu et al. (2007) to reflect the processing of positive reward resulting from gain in a gambling task. Although BOLD sig- nal in left insula does differentiate self-owned from other- owned items, it does not predict subsequent memory bias. According to Ferraro, Escalas, and Bettman (2011), the monetary value of possessions may influence the per- ceived importance of those items but does not affect the strength of self-possession associations likely to support memory performance. CMS and Ownership We hypothesized that a network of cortical midline brain areas previously associated with self-referential encod- ing (see Northoff et al., 2006) as well as regions that have been shown to support hedonic aspects of item owner- ship might play an important role in forming associations between self and owned objects. Although dorsomedial aspects of the cortical midline did show increased BOLD signal for self–object associations, other previously identi- fied brain areas associated with self-referential processing did not. Specifically, regions in vMPFC (Heatherton et al., 2006; Macrae et al., 2004; Johnson et al., 2002; Kelley et al., 2002; see also Northoff et al., 2006, for a review) and posterior cingulate that have been shown to predict self-referential encoding and memory (Macrae et al., 2004) showed greater neural responses to other-owned objects, characterized by smaller decreases from baseline. Specifically, vMPFC and posterior cingulate regions re- ported by Kelley et al. (2002) during self-referential encod- ing appear to be associated with other–object encoding in the present study. So why in this case do these putative self areas respond more to objects associated with others? Sustained activity in cortical midline regions in posterior and anterior frontal cortex has been observed during per- iods of sustained rest (Shulman et al., 1997). Gusnard and Raichle (2001) suggest that this default state represents Turk et al. 3665 D o w n l o a d e d l l / / / / j f / t t i t . : / / f r o m D o h w t t n p o : a / d / e m d i f r t o p m r c h . s p i l d v i r e e r c t c . m h a i e r d . u c o o m c n / j a o r t c i c n e / - a p r d t i 2 c 3 l 1 e 1 - 3 p 6 d 5 f 7 / 1 2 9 3 4 / 1 1 8 1 7 / 5 3 6 o 5 c 7 n _ / a 1 _ 7 0 7 0 6 0 8 4 4 2 1 p / d j o b c y n g _ u a e _ s 0 t 0 o 0 n 4 0 2 8 . S p d e f p e b m y b e g r u 2 e 0 s 2 t 3 / j / t . f o n 1 8 M a y 2 0 2 1 “a stable, unified perspective of the organism relative to its environment (a self )” (p. 692). Activity is tonically high during rest, as this area may be ready to interpret, respond to, and perhaps predict future environmental events (Raichle & Snyder, 2007). Only when individuals are re- quired to engage in specified cognitive tasks does meta- bolic activity decrease. These regions (in addition to lateral parietal areas) are also characterized by their associative functions. In line with this preparatory or predictive function, Bar, Aminoff, Mason, and Fenske (2007) noted that tasks that manipu- late the degree of association between stimuli also activate the default network. That is, highly associated items showed higher BOLD signal relatively to weakly associated items. They argue that this is because of unconstrained or stimulus-independent thoughts (SITs) that propagate such associations. These SITs are also referred to as mind wandering (Mason et al., 2007). The greater the associa- tion, the more mind wandering, the higher the metabolic rate recorded in posterior and anterior cortical midline. Mason et al. (2007) explored the impact of SITs on default activity by giving participants novel and practiced tasks to undertake. In addition, they probed participants during task performance to see if they were currently on task or mind wandering (i.e., having SITs). Because a practiced task requires less effort, it affords a greater opportunity for unconstrained thought and incidents of SITs. This level of mind wandering positively correlated with the magni- tude of the BOLD response in areas of the default network. Conversely, stimulus-driven cognitive processes reduce BOLD signal in these networks (Burgess, Dumontheil, & Gilbert, 2007). Thus, it may be the nature of the thought process (i.e., unconstrained and spontaneous vs. con- strained and task related) that governs activation in the default network rather than the referent to whom they are directed. In the current study, there was a greater decrease in BOLD signal in posterior and anterior midline areas for self-owned relative to other-owned trials. This can be in- terpreted in the context of increased SITs during other– object associations than to self–object associations. As we have previously indicated, self-owned events appear to increase arousal, affective state and attentional processes. As a result, one might infer that such states are accompa- nied by increased stimulus-driven processes (e.g., “I own the iPod. I could listen to music on the way to work.”). Other–object associations do not result in changes in at- tentional processes nor do they offer a change in reward state. As such, it is possible that these events therefore lead to increased SITs and, therefore, sustained BOLD signal in default areas. Conclusion The current investigation explored the neural basis of nonevaluative self-referential encoding through the use of a novel temporary ownership paradigm. This revealed a network of brain regions that appear to respond specifi- cally to owned objects in a distinct temporal sequence. Given the functional specificity of these brain areas and the temporal order in which they appear to reach maximal activation, it is tempting to speculate upon a functional temporal model of object ownership, with the initial de- tection of object salience in caudal medial pFC followed by activation of motor affordances in parietal cortex and processing of reward in insula. Future research might prof- itably seek to expand upon this speculative model by de- termining the extent to which factors pertaining to the objects (e.g., value/valence or usability) or to self (e.g., whether or not self was the agent or mere recipient during the acquisition of the item or the degree to which self has prior association with the items) might modulate the ac- tivity in this ownership network. That these effects were obtained from temporary ownership of ordinary, low-value, common objects speaks to the potential usefulness of such a methodology in elucidating the mechanisms that under- pin the nature of self reflected in material possessions. Acknowledgments D. J. T. was supported by grants from the BBSRC (RGA1149) and the European Research Council (202893). C. N. M. was supported by a Royal Society Wolfson Fellowship. Reprint requests should be sent to David J. 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Frontal dysfunction in schizophrenia: A new electrophysiological classifier for research and clinical applications. European Archives of Psychiatry & Clinical Neuroscience, 250, 207–214. D o w n l o a d e d l l / / / / j f / t t i t . : / / f r o m D o h w t t n p o : a / d / e m d i f r t o p m r c h . s p i l d v i r e e r c t c . m h a i e r d . u c o o m c n / j a o r t c i c n e / - a p r d t i 2 c 3 l 1 e 1 - 3 p 6 d 5 f 7 / 1 2 9 3 4 / 1 1 8 1 7 / 5 3 6 o 5 c 7 n _ / a 1 _ 7 0 7 0 6 0 8 4 4 2 1 p / d j o b c y n g _ u a e _ s 0 t 0 o 0 n 4 0 2 8 . S p d e f p e b m y b e g r u 2 e 0 s 2 t 3 / j t f / . o n 1 8 M a y 2 0 2 1 3668 Journal of Cognitive Neuroscience Volume 23, Number 11Mine and Me: Exploring the Neural Basis of image
Mine and Me: Exploring the Neural Basis of image
Mine and Me: Exploring the Neural Basis of image
Mine and Me: Exploring the Neural Basis of image

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