Abstract

Introduction

For centuries, researchers have searched for the “self” (consciousness) in the brain, but no specific region seems to be dedicated to this (Legrand and Ruby, 2009). This is probably because the entire brain is involved in multiple functions and works as a network, forming what is called the default mode network (Northoff et al., 2006; Grimm et al., 2011; Qin and Northoff, 2011; Lipsman et al., 2014). The self can be regarded as surveilling the body, actions, and even the external environment (i.e., perception), which suggests that activity and functions corresponding to the self are distributed throughout the brain.

To better understand the self and its neural correlates, researchers have divided the self into essential and distinct functions. For example, Gallagher (2000) has postulated two components of the self: the minimal self and the narrative self. The minimal self is the online sensation of self and includes the sense of body (i.e., ownership) and action (i.e., agency). The narrative self is the offline storage for maintaining the sense of past and future self and includes autobiographical memory, personality and identity.

This categorization is still used in many studies because these concepts can be studied and, more importantly, tested using cognitive or neuroscientific methodologies. These functional selves have been examined theoretically through philosophy, clinical investigations and even computer models; subjectively through questionnaires and interviews; behaviorally through observations and experiments; electro-physiologically through electroencephalography (EEG) and skin conductance responses; and neurologically through functional and structural brain imaging. For example, the rubber hand illusion modulates our sense of ownership of our hand (Botvinick and Cohen, 1998). This has been examined using behavioral responses (Pavani et al., 2000), skin conductance responses (Armel and Ramachandran, 2003), skin temperature (Moseley et al., 2008), EEG (Kanayama et al., 2007, 2017; Press et al., 2008; Evans and Blanke, 2013), functional magnetic resonance imaging (fMRI; Ehrsson et al., 2004; Tsakiris et al., 2010; Brozzoli et al., 2012), and Bayesian causal modeling (Samad et al., 2015). The relationship between ownership and agency has also been experimentally investigated (Kalckert and Ehrsson, 2012, 2014). As a result, we now know that in healthy people, the subjectively reported minimal and narrative selves are expressed through behavior, physiological responses and brain activity.

However, previous studies have produced inconsistent results even when using the same measurements. This suggests the existence of individual differences in consciousness of the self. Traditional psychological studies have repeatedly shown the impact of individual differences using validated questionnaires (for schizophrenia, see Asai et al., 2011; Kanayama et al., 2009 for depersonalization; and Kanayama et al., 2008 for dissociative disorder). In cognitive neuroscience, some recent studies have shown that neural responses may be modulated by cortical structure (Suzuki et al., 2013), spontaneous cortical activation (Northoff et al., 2010; Nakao et al., 2013), and their interaction (Tavor et al., 2016), suggesting individual differences in neural responses as well. For a deeper understanding of the functional self, including the individual differences found in cognitive neuroscience studies, it is important to elucidate the relationship between individual differences measured using subjective reports and those measured neurologically. Some studies have shown that experience and learning induce structural changes in the human brain (Draganski and May, 2008; May, 2011). It may therefore be informative to compare anatomical brain structure with individual differences in the subjectively reported functional self. However, the relationship between anatomical brain structure and subjectivity of the functional self remains unclear. While some neuropsychological and psychiatric studies of patients with schizophrenia or brain lesions have investigated this, they did not measure subjectivity of the functional self in healthy subjects in daily life (rather than during a specific task) as an individual difference variable.

A previous study that applied exploratory factor analysis to a self-related questionnaire (Longo et al., 2008) showed that the factor structures of subjective response were related to the functional self, but the study was highly optimized for its own data. This data-driven approach failed to find a common factor structure for the functional self across studies. One difficulty was the lack of correspondence with studies that used different methodologies (e.g., fMRI). Therefore, a self-reported questionnaire for conceptions of the self was recently developed in a theory-driven manner. It is called the Embodied Sense of Self Scale (ESSS), and it measures three subfactors: “agency,” “ownership,” and “narrative” (Asai et al., 2016). The ESSS was developed by first listing 120 items related to the embodied sense of self, including items to assess schizotypal, depersonalizing and dissociative tendencies that relate to agency, ownership and narrative, respectively. Twenty-five items were ultimately selected for the short version, which is a reliable, valid and statistically usable scale. It significantly correlates with some related scales and clearly distinguishes healthy controls and patients with chronic schizophrenia (thought to be a disorder of the embodied sense of self).

This is the first study to examine how the subjectivity of self-related malfunctions correlates with brain structure in healthy people. For this, we searched for correlations between the ESSS subscales and measured gray matter (GM) volumes.

We focused on cortical regions that were related to the self-subscales in previous studies. We have a clear model of agency-related brain area networks because many experimental and schizophrenia patient studies have examined self-agency. These studies indicated that the cerebellum and left dorsolateral prefrontal area were involved in agency-related psychological functions. Cerebellar activation in particular was observed in subjects predicting the sensory consequences of self-action (Blakemore et al., 1999; Farrer and Frith, 2002) and those recognizing discrepancies between actual and predicted sensory consequences (Blakemore et al., 2001; Leube et al., 2003). Some studies have shown that the middle frontal gyrus detects visuomotor incongruencies (David et al., 2007; Farrer et al., 2008) and the agency of a self-propelled moving ball (Stosic et al., 2014). Schnell et al. (2007) also showed that a wide area of the middle frontal gyrus responded to the onset of visuomotor incongruence in a video game. This suggests that the dorsolateral prefrontal cortex (DLPFC) could be involved in switching the internal model of visuomotor contingency to predict body movement and sensory feedback (Imamizu et al., 2004; Imamizu and Kawato, 2008). The DLPFC is anatomically connected to the cerebellum (Kelly and Strick, 2003), which suggests that the DLPFC also has a role in switching the internal visuomotor model stored in the cerebellum in response to changing circumstances. However, structural abnormalities of the prefrontal cortex have been repeatedly reported in schizophrenic (Nickl-Jockschat et al., 2011; Schnack et al., 2014) and schizotypal individuals (Nenadic et al., 2015), while cerebellum atrophy has been less frequently reported (Zhang et al., 2015). We therefore focused on the DLPFC as an area of interest for the agency subscale.

We do not have as clear a model of the cortical networks and structural abnormalities relevant to the ownership subscale. The postcentral gyrus and insular cortex might be relevant because they are activated during the synchronous visuotactile stimulation of the rubber hand illusion (Ehrsson et al., 2004; Tsakiris et al., 2010). Additionally, the angular gyrus is a sensory association area commonly damaged in patients who frequently have out-of-body or autoscopic experiences (Blanke et al., 2004). Of these areas, the postcentral gyrus is an unlikely candidate because it is a primary somatosensory area with no reported abnormalities even in depersonalization disorder (Sierra et al., 2002), which is closely related to ownership dysfunction. The inferior parietal cortex, which contains the angular gyrus, is structurally abnormal in schizophrenic (Schnack et al., 2014) and schizotypal individuals (Nenadic et al., 2015), suggesting that it is not exclusively related to body ownership dysfunctions. However, the insular cortex is a good candidate because a body ownership-related task activates it (Tsakiris et al., 2007), but damage to this area has no impact on self-agency as measured by a task that requires distinguishing between self-generated and other-generated actions (Philippi et al., 2012). Additionally, a positron emission tomography study reported that the feeling of movement control in schizophrenia patients was related to regional cerebral blood flow in the right angular gyrus but not in the insular cortex (Farrer et al., 2004). We therefore examined the insular cortex as an area possibly correlated with the ownership subscale and irrelevant to the agency subscale.

It is difficult to identify any specific cortical region that is likely associated with the narrative self-ubscale. Araujo et al. (2015) tried to separate the core (minimal) self and autobiographical self using fMRI and showed that numerous cortical regions, including the temporal pole, precuneus and lateral occipital cortex, were involved in autobiographical self-recognition as measured with personality trait questionnaires. Legrand and Ruby (2009) showed that a task requiring self-relatedness evaluation, which is closely related to personality as an important concept of narrative self, activated cortical areas distributed over a wide cerebral network, including the medial prefrontal cortex, precuneus, temporoparietal junction and temporal poles. They suggested that this cortical network could be explained by two cognitive processes: inferential processing and memory recall. If the narrative self is a temporal expansion of the minimal self (Gallagher, 2000), it must include a process to retrieve autobiographical memory (memory recall) and a process to use these retrieved memories to generate behavioral patterns (e.g., personality) for optimizing future behavior (inferential processing). We therefore examined the network areas from Legrand and Ruby (2009) for possible correlations with the ESSS narrative self-subscale.

We hypothesized that in healthy participants regularly experiencing self anomalies in daily life, ESSS-measured subjectively reported self-related malfunctions would predict GM volume in the target cortical areas mentioned above.

Materials and Methods

Results

Averages and SDs of ESSS total and subscale scores are listed in Table ​Table1,1, and total brain volumes are listed in Table ​Table22.

ROI Analysis

Correlation analysis revealed a significant negative correlation between ownership subscale scores and GM volumes in the left posterior insular cortex (peak coordinates: x = −47, y = 2, z = −2; number of voxels = 42; t = 3.91, p < 0.05 after FWE correction at peak level; Figure ​Figure1).1). There were no other significant correlations between regional GM volumes and ESSS subscale scores.

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Figure 1

Significant correlations between GM volumes and ESSS ownership subscale scores by ROI analysis. Abbreviations: GM, gray matter; ESSS, Embodied Sense of Self Scale; ROI, region of interest.

Whole-Brain Analysis

Permutation testing of the original data calculated 615 as the minimum significant cluster size. Random sampling tests that paired open source cortical structure data with either the original questionnaire scores or randomly generated questionnaire scores calculated significance thresholds of 797 or 682, respectively.

With an uncorrected p < 0.001 threshold and a 20-voxel extent, all significant correlations between GM volumes and questionnaire scores are listed in Table ​Table3.3. As listed in Table ​Table3,3, no cortical area had a cluster size greater than the lowest statistical threshold (615 voxles). The greatest cluster size which was found in analysis with our original data was 224 for the positive correlation between the narrative subscale scores and GM volumes in the left inferior temporal gyrus. There were therefore no significant correlations in whole-brain analysis using corrected cluster size criteria.

Table 3

Brain regions in which local GM volume was significantly correlated with ESSS subscale scores.

Location name	x	y	z	k	t
Negative correlations between GM volumes and ownership scores
L insula (BA 13)	−47	2	−2	134	3.91
L angular gyrus (BA 39)	−53	−56	30	31	3.48
R postcentral gyrus (BA 2)	59	−21	47	32	3.37
Positive correlations between GM volumes and narrative scores
L lingual gyrus (BA 18)	−35	−92	−20	96	3.89
L inferior temporal gyrus	−47	−57	−11	224	3.85
R cuneus (BA 18)	9	−101	15	60	3.80
L superior temporal pole (BA 22)	−50	9	−2	107	3.80
L precuneus (BA 5)	−11	−39	56	46	3.37
Positive correlation between GM volumes and agency scores
R cerebellum crus 1	44	−59	−36	90	3.46
Negative correlations between GM volumes and agency scores
L medial orbitofrontal cortex (BA 11)	−15	38	−24	68	3.72
L middle frontal cortex (BA 9)	−30	35	26	60	3.69

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Regions significantly correlated with each ESSS subscale are listed. The codes in parentheses indicate Brodmann areas (e.g., BA13 = Brodmann area 13). In the first row, x, y and z refer to Montreal Neurological Institute coordinates, k refers to the number of voxels in each significant area and t refers to the t-score in each brain region (local maxima). Abbreviations: GM, gray matter; ESSS, Embodied Sense of Self Scale; L, left; R, right.

The significant correlations between ESSS subscales and GM volumes in whole-brain analysis with an uncorrected p < 0.001 threshold and a 20-voxel extent were described below.

Correlation between Agency Subscale Scores and GM Volumes

Agency subscale scores were positively correlated with GM volumes in the right cerebellum (peak coordinates: x = 44, y = −59, z = −36; number of voxels = 90; t = 3.46; Figure ​Figure2A).2A). Agency scores were negatively correlated with GM volumes in two cortical areas: the left medial orbitofrontal cortex (peak coordinates: x = −15, y = 38, z = −24; number of voxels = 68; t = 3.72; Figure ​Figure2B)2B) and the left medial frontal cortex (peak coordinates: x = −30, y = 35, z = 26; number of voxels = 60; t = 3.69).

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Figure 2

Significant correlations between GM volumes and ESSS subscale scores by whole-brain analysis. (A) Positive correlations between GM volumes and ESSS agency subscale scores. The right cerebellum is highlighted in the sagittal, coronal and transverse views [44, −59 −36]. (B) Negative correlations between GM volumes and ESSS agency subscale scores. The left medial orbitofrontal cortex is focused in the sagittal, transverse view. The left medial orbitofrontal and left medial frontal cortices are highlighted in the coronal view [−14, 34 −27]. (C) Negative correlations between GM volumes and ESSS ownership subscale scores. The left insular cortex is focused in the sagittal, coronal and transverse views [−47, 2, −2]. (D) Positive correlations between GM volumes and ESSS narrative subscale scores. The left superior temporal pole and left inferior temporal gyrus are highlighted in the sagittal view. The left lingual gyrus and right cuneus are highlighted in the coronal view. The left precuneus is highlighted in the transverse view [−47, −96, 56]. Abbreviations: GM, gray matter; ESSS, Embodied Sense of Self Scale.

Correlation between Ownership Subscale Scores and GM Volumes

Ownership subscale scores were negatively correlated with GM volumes in three brain areas: the left insular cortex (peak coordinates: x = −47, y = 2, z = −2; number of voxels = 134; t = 3.91; Figure ​Figure2C),2C), left angular gyrus (peak coordinates: x = −53, y = −56, z = 30; number of voxels = 31; t = 3.48), and right postcentral gyrus (peak coordinates: x = 59, y = −21, z = 47; number of voxels = 32; t = 3.37). Ownership scores were not significantly positively correlated with GM volumes in any examined area.

Correlation between Narrative Subscale Scores and GM Volumes

Narrative subscale scores were positively correlated with GM volumes in five cortical areas: the left lingual gyrus (peak coordinates: x = −35, y = −92, z = −20; number of voxels = 96; t = 3.89), left inferior temporal gyrus (peak coordinates: x = −47, y = −57, z = −11; number of voxels = 224; t = 3.85; Figure ​Figure2D),2D), right cuneus (peak coordinates: x = 9, y = −101, z = 15; number of voxels = 60; t = 3.80), left superior temporal pole (peak coordinates: x = −50, y = 9, z = −2; number of voxels = 107; t = 3.80), and left precuneus (peak coordinates: x = −11, y = −39, z = 56; number of voxels = 46; t = 3.37). Narrative scores were not significantly negatively correlated with GM volumes in any examined area.

Discussion

We aimed to determine the relationship between subjectively reported self-related malfunction and GM volume. Self-related malfunctions were subjectively measured using our recently developed ESSS questionnaire (Asai et al., 2016). The ESSS measures daily experiences rather than illusory feelings induced by specific experimental tasks (e.g., the rubber hand illusion). ROI analysis showed that ownership subscale scores were negatively correlated with left posterior insula GM volumes. This association suggests that daily experiences of self-related malfunctions could induce cortical structure changes. We also conducted whole-brain analysis, but this showed no significant correlations between cortical areas and ESSS subscale scores.

Conclusion

Collectively, ESSS-measured, ownership-related self malfunctions in daily life were confirmed to be associated with the insular cortex. This is consistent with previous findings about the cortical areas related to self ownership. It also shows that the ESSS can be a quick assessment tool to predict individual differences in cortical volume related to ownership malfunction.

Author Contributions

NK and TA designed the study. NK, TA, KM, RK, TU, TY, and HK performed the experiment. NK and TN analyzed the data. NK, TA, and TN wrote the manuscript. SY supervised the project. All authors approved the final version of the manuscript.

Funding

This study was supported by Research Fellowships for Young Scientists, grant numbers 26780418 and 16H05958 (Japan Society for the Promotion of Science). The Japan Science and Technology Agency’s Center of Innovation Program partially supported this research.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Glossary

Footnotes

References