Functional MRI Study to Examine Possible Emotional Connectedness in Identical Twins: A Case Study

Functional MRI Study to Examine Possible Emotional Connectedness in Identical Twins: A Case Study

Author’s Accepted Manuscript FUNCTIONAL MRI STUDY TO EXAMINE POSSIBLE EMOTIONAL CONNECTEDNESS IN IDENTICAL TWINS: A CASE ST UDY Efstratios Karavasilis...

823KB Sizes 0 Downloads 46 Views

Author’s Accepted Manuscript FUNCTIONAL MRI STUDY TO EXAMINE POSSIBLE EMOTIONAL CONNECTEDNESS IN IDENTICAL TWINS: A CASE ST UDY Efstratios Karavasilis, Foteini Christidi, Kalliopi Platoni, Panagiotis Ferentinos, Nikolaos L. Kelekis, Efstathios P. Efstathopoulos www.elsevier.com/locate/jsch

PII: DOI: Reference:

S1550-8307(17)30085-X http://dx.doi.org/10.1016/j.explore.2017.06.008 JSCH2242

To appear in: Explore: The Journal of Science and Healing Cite this article as: Efstratios Karavasilis, Foteini Christidi, Kalliopi Platoni, Panagiotis Ferentinos, Nikolaos L. Kelekis and Efstathios P. Efstathopoulos, FUNCTIONAL MRI STUDY TO EXAMINE POSSIBLE EMOTIONAL CONNECTEDNESS IN IDENTICAL TWINS: A CASE ST UDY, Explore: The Journal of Science and Healing, http://dx.doi.org/10.1016/j.explore.2017.06.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Functional MRI study to examine possible emotional connectedness in identical twins: a case study. Efstratios Karavasilis1, Foteini Christidi2, Kalliopi Platoni1, Panagiotis Ferentinos3, Nikolaos L. Kelekis1, Efstathios P. Efstathopoulos1

1. 2nd Department of Radiology, University General Hospital "Attikon", Medical School, National and Kapodistrian University of Athens 2. 1st Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens 3. 2nd Department of Psychiatry , University General Hospital "Attikon", Medical School, National and Kapodistrian University of Athens

Corresponding author:

Efstratios Karavasilis 19 Papadiamantopoulou street, Athens, 11528, Greece +302107289115 [email protected]

Keywords: emotional connectedness, fMRI, twins

Abstract In the present case study, we investigated possible emotional connectedness between monozygotic twins by means of functional magnetic resonance imaging (fMRI). During the experimental condition, twin 2 was randomly selected to participate in the neuroimaging protocol while twin 1 participated in the experimental condition outside the MRI scanner (none of them was aware of the experimental procedure). The experimental condition included two sessions with visual and acoustic stimuli, respectively. Between the two experimental conditions, there was a 2-min break with Twin 1 (i.e. the subject outside the scanner) relaxing with eyes closed. Data analysis revealed significant brain activation in three regions, namely left orbitofrontal gyrus (during visual condition) and left cingulum and precentral gyrus (during the acoustic condition). Our findings denote emotional connectedness between a pair of monozygotic twins using fMRI. Further studies in larger sample sizes are needed to investigate if this is a generalized and systematic phenomenon or an incidental finding.

Keywords: emotional connectedness, fMRI, twins

Introduction Emotional connectedness, shared empathy and physiological reaction in genetically-related pairs have been reported in the literature. This phenomenon has been tried to be explained by several hypotheses including genetic kinship, social bonding and quantum entanglement (Jensen and Parker, 2012; Roll et al., 2010; Walker, 2000). The latter considers the original physical entanglement of identical twins in one cell as a factor that might predispose these pairs towards such experiences. Similar brain activity between physically isolated genetically- or emotionally-related pairs with one of them facing a specific experience (e.g. processing of an external stimulus) has already been studied using electroencephalogram (EEG). Similar alpha activity in occipital lobes (Duane & Behrendt, 1965) and theta activity in frontal and occipital lobes (Persinger et al., 2003) has been found in genetically-related pairs using visual stimuli (i.e. Octopus paradigm) as stimulators for eliciting brain activity in the sender while the receiver was sitting in a different room. EEG voltage changes in the receivers’ brains when the senders’ brain were stimulated have also been reported in studies with emotionally-connected pairs (Kittenis et al., 2004; Radin, 2004; Standish et al., 2004; Wackermann et al., 2003). During the last two decades, further evidence has been provided by functional magnetic resonance imaging (fMRI) studies (i.e. Moulton and Kosslyn, 2008; Richards et al., 2005; Standish et al., 2003; Venkatasubramanian et al., 2008). The aim of our case study was to investigate possible emotional connectedness between monozygotic twins by means of functional brain activity.

Materials and Methods Subjects Two healthy male monozygotic twins of 15 years old (Twin 1; Twin 2) were recruited by word of mouth and agreed to participate in the study after written informed consent being provided by themselves and their parents. Participants who were raised together, claimed some kind of specific abilities including emotional connectedness. The study was approved by the Local Ethical Committee and conducted according to the Declaration of Helsinki and its later amendments.

Experimental Condition Twin 2 was randomly selected to participate in MRI protocol while Twin 1 participated in the experimental condition outside the MRI scanner. Twin 1 received the stimuli while Twin 2 was being recorded in a separate room 25 meters far away. None of them was aware of the experimental procedure and the specific aim of the study before the MRI scanning. They had been informed about participation in research project related to brain structure and functions in healthy population. The experimental condition included two sessions with visual and acoustic stimuli, respectively. For both conditions we used a personal computer

desktop equipped with a 25-inch monitor and earphones. Between the two experimental conditions, there was a 2-min break with Twin 1 (i.e. the subject outside the scanner) relaxing with eyes closed. Twin 1 was instructed to focus on the visually and acoustically presented stimuli while Twin 2 was instructed to stay calm with eyes closed during the MRI scanning. Experimental conditions outside the scanner for Twin 1 and MRI scanning inside the scanner for Twin 2 were synchronized by an in-house external trigger.

Visual condition. During the visual experimental condition (duration 260 sec), Twin 1 was sitting in a quiet control room 25 meters away from the scanner while Twin 2 was placed in the scanner. Twin 1 was physically and optically isolated from Twin 2; one of the investigators was also in the control room to verify the steps of the experimental condition. The 260-sec experimental condition included seven “resting” periods (with the subject watching a meaningless black-board) and six “active” periods (with the subject watching randomly presented pictures). Sixty pictures of 20-inch image size were selected as the visual stimuli for the “active” periods. These stimuli presented basic emotions of anger, disgust, fear, sadness, surprise and happiness, as well as subjects’ autobiographical memories from childhood. The autobiographical pictures were provided by twins’ parents. The emotional-related stimuli were selected from a pilot phase (20 healthy controls) with a pool of 100 pictures which were rated in a 5-point Likert scale (0 = no emotional reaction; 5 = intense emotional reaction). The final group of visual stimuli included pictures initially rated between 3-5 in the pilot phase. The number of visual stimuli per emotion/autobiographical memory was balanced across categories and across “active” conditions. All visual stimuli were presented in a randomized order in six trials (“active” condition) consisting of 10 stimuli presented at a rate of 2 sec/stimulus. Each “active” condition was 20 sec of duration and followed by a “rest” condition period of 20 sec. The start of the visual experimental condition, which was a “rest” condition, was synchronized to the start of the fMRI scan. Acoustic condition. A similar procedure was followed for acoustic experimental condition which was 260 sec of duration, as well. Using earphones, Twin 1 was listening to six different acoustic stimuli (“active” condition) consisting of sounds which cause fear. The acoustic stimuli were selected from a pilot phase (20 healthy controls) with a pool of 24 sounds which were rated in a 5-point Likert scale (0 = no emotional fear reaction; 5 = intense emotional fear reaction). The final group of acoustic stimuli included sounds initially rated between 3-5 in the pilot phase. Each “active” condition was 20 sec of duration, included one acoustic stimuli (i.e. sound) of 20 sec of duration and followed by a “rest” condition period of 20 sec. The acoustic stimuli were delivered in a random order. The start of the acoustic experimental condition, which was a “rest” condition, was synchronized to the start of the fMRI scan.

MRI protocol MR imaging were performed using a 3.0T Achieva TX, Philips manufactured scanner equipped with an eight channel head coil. The brain imaging protocol consisted of axial T2FLAIR, sagittal high resolution 3DT1-TFE and axial T2* EPI BOLD sequences. The used parameters in BOLD sequence were TR=2000 ms, TE=30 ms, flip angle=90o, field of view= 256x256, acquisition and reconstructed voxel size 3x3x3 mm and sensitivity encoding reduction factor of two. The acquisition protocol duration was approximately 18min. All data underwent visual quality control before further post-processing.

fMRI data acquisition and analysis FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version 6.00, part of FSL (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). Registration to high resolution structural and/or standard space images was carried out using FLIRT (Jenkinson, 2001; 2002). Then, registration from high resolution structural to standard space was further refined using FNIRT nonlinear registration (Andersson, 2007a; 2007b). The following prestatistics processing was applied; motion correction using MCFLIRT (Jenkinson, 2002); slicetiming correction using Fourier-space time-series phase-shifting; non-brain removal using BET (Smith, 2002); denoising using MELODIC; spatial smoothing using a Gaussian kernel of FWHM 5mm; grand-mean intensity normalisation of the entire 4D dataset by a single multiplicative factor; high-pass temporal filtering (Gaussian-weighted least-squares straight line fitting, with sigma=20.0s). Time-series statistical analysis was carried out using FILM with local autocorrelation correction (Woolrich, 2001). Z (Gaussianised T/F) statistic images were thresholded using clusters determined by Z>2.3 and a (corrected) cluster significance threshold of P=0.05 (Worsley, 2001). In order to avoid any bias on data post-processing, fMRI data analysis was conducted by an experimenter who was blinded to the aim of the study but fully aware of fMRI protocol details to generate the statistical model for first-level analysis on FSL.

Psychometric assessment After the experimental procedure and MRI protocol, both participants were administered the Temperament and Character Inventory-140 (TCI-140) which is a shortened version of the 240-item TCI-Revised (TCI-R) inventory, developed by Cloninger (1999). The TCI has good psychometric properties, has been translated and validated in many languages, including Greek, and has been used in the study of personality’s neurobiological foundations using methodological approaches such as molecular (Borg et al., 2003)) and structural (Yamasue et al., 2008) neuroimaging. The TCI-140 consists of 136 items related to temperament and character domains, as well as four response accuracy/validity items. The four temperament (i.e. novelty seeking; harm avoidance; reward dependence; persistence) and three character (i.e. self-directedness; cooperativeness; self-transcendence) dimensions of the TCI-140 reflect

Cloninger’s recent hypotheses regarding the higher-order dimensions of personality (Cloninger, 2003), with temperament reflecting “independently heritable” features (Cloninger et al., 1993) and genetic influences on personality and character being regarded as “shaped by environmental and cultural learning” (Farmer and Goldberg, 2008). For each of the TCI140 items, the response option format ranged from 1 = definitely false to 5 = definitely true. Each of the seven dimensions was computed as sum (total) of specific items corresponding to each dimension. In order to indirectly compare each participant’s TCI-140 profile, we further proceeded in normalization of each dimension by applying “feature scaling” that rescales all values into a range of [0,1] (Dodge, 2003). The following formula was used:

with X’ being the rescaled total value for each dimension, X being the initial raw total value for each dimension, Xmin being the minimum total value for each dimension (expressed as the number of items for each dimension multiplied by 1), and Xmax being the maximum total value for each dimension (expressed as the number of items for each dimension multiplied by 5). The resulted X’ was finally multiplied by 100 to express the rescaled value as percentage. A cut-off of 10% was used as the minimum accepted difference between participants’ rescaled values to further compare their TCI-140 profiles in temperament and character dimensions.

Results [Please insert Table 1 approximately here] Table 1. Cluster results with increased activation in Twin 2 when Twin 1 was involved in visual and acoustic experimental conditions Cluster

Voxels

P

-log10(P)

Max Z

Index

COG-x COG-y COG-z

Mean

(vox)

(vox)

(vox)

COPE

Visual condition 1

91

0.00848

2.07

4.88

53.8

54.3

7.44

40.7

Acoustic condition 2

141

0.000904 3.04

3.49

-8.66

-19

35

83.6

3

131

0.00158

4.22

-40.2

-2.26

40.9

46.3

2.8

Note. Log10(P): logarithmic transformation of the p-value; Max Z: maximum z-score within the cluster; COG-z: center of gravity of the cluster in Talaraich space x direction; COG-y: center of gravity of the cluster in Talaraich space y direction; COG-z: center of gravity of the cluster in Talaraich space z direction; Mean COPE: contrast of parameter estimates (the parameter estimated is associated with the change in brain signal intensity comparing the on/“active” and off/”resting” conditions of fMRI). Voxels correspond to the number of positive activated voxels within the cluster thresholded at z-score > 2.3 (with corrected cluster significant threshold p < 0.05).

Table 1 shows clusters of increased activation in Twin 2, when Twin 1 was participating in active experimental condition. We found increased activation in left orbitofrontal gyrus (visual condition) and left cingulum and left precentral gyrus (acoustic condition). [Please insert Figure 1 approximately here]

Figure 1. Significant activation in left orbitofrontal gyrus (a), left cingulum (b) and left precentral gyrus (c) in Twin 2 when Twin 1 was involved in visual (a) an acoustic (b, c) experimental conditions.

The signal of these regions (Figure 1) followed the theoretical experimental time series (Figure 2), at the 95% confidence level. [Please insert Figure 2 approximately here]

Figure 2: Time series plot of activated clusters during (a) visual and (b) acoustic active experimental conditions.

As can be observed in Table 2, Twin 2 and Twin 1 showed a similar profile in all TCI-140 temperament dimensions (% difference in each scale, novelty seeking 8.8%; harm avoidance:

5.0%; reward dependence: 8.8%; persistence: 6.3%) and all but one character dimensions (% difference in each scale, self-directedness: 6.2%, cooperativeness: 2.5%; self-transcendence: 17.2). [Please insert Table 2 approximately here] Table 2. Twins’ scores in TCI-140 temperament and character dimensions TCI-140 dimensions

Twin 2

Twin 1

Difference (%) in

Total value

Total value

normalized total

Initial raw

After normalization

Initial raw

After

values

normalization

Temperament Novelty seeking

71

63.8

78

72.5

8.8

Harm avoidance

52

40.0

56

45.0

5.0

Reward dependence

74

67.5

67

58.8

8.8

Persistence

59

48.8

64

55.0

6.3

Self-directedness

61

51.3

56

45.0

6.2

Cooperativeness

53

41.3

51

38.8

2.5

Self-transcendence

47

48.4

58

65.6

17.2

Character

Note. TCI-140 = Temperament and Character Inventory-140. Bold values represent >10% of difference between Twin 1 and Twin 2 scores in each TCI-140 dimension.

Discussion We detected a clear correlation between the emotional stimuli to which the one of the twins was exposed and the fMRI BOLD response of the second twin. The psychometric assessment by the TCI-140 questionnaire has verified a similar temperament and character profile in our participants. Data analysis revealed significant brain activation in three regions, namely left orbitofrontal gyrus (during visual condition) and left cingulum (middle part) and precentral gyrus (during the acoustic condition). We replicate brain regions that have been activated in other studies that examined emotional connectedness between physically and sensory isolated subjects who do or do not share the same genetical background (Krippner and Friedman, 2010). Orbitofrontal cortex is involved in the cognitive processing and is thought to be associated with emotional and reward aspects in decision making (Miller and Cummings, 2007). Fear, sadness and happiness activity in middle cingulum gyrus has been found to be related to emotion (Vogt et al., 2003).

Middle cingulate cortex has strong anatomical and

functional connections with frontal regions, including the ones found in our study (Beckmann et al., 2009) and has been functionally engaged in the prediction and monitor of decision outcome during social interactions (Apps et al., 2013). The previous

brain areas and precentral gyrus seems to modulate brain activity during the preparation for and active regulation of emotional states, either negative or positive (Seo et al., 2014). The mechanism of this phenomenon is still under investigation (Grinberg-Zylberbaum et al., 1994). Even though no comprehensive theoretical models have been developed, it appears that advanced neuroimaging techniques, including fMRI, together with neurophysiological approaches that capture behavioral responses to external and internal stimuli can be used and further validated as candidate methodological approaches to study this phenomenon. We

acknowledge that fMRI is a relative measure and might not be the optimal method for individual analysis especially when studying higher mental functions, including emotional connectedness. Even though other functional techniques (e.g.

positron

emission

tomography)

allow

for

absolute

measures

of

metabolic/functional activity and might be more accurate for case studies, fMRI remains one of the most applicable non-invasive and non-ionizing method for the in vivo study of brain function. Conclusion In conclusion, our findings denote emotional connectedness between a pair of monozygotic twins using fMRI. We acknowledge that our findings cannot be directly generalized due to the inclusion of a single pair of twins, the relative small number of repetitions (Button et al, 2009) and the absence of more sophisticated analysis methods including bootstrap resampling (Darki& Oghabian, 2013). Thus, further studies are needed to investigate if this is a generalized and systematic phenomenon or an accidental finding.

Acknowledgments We would like to thank the participants of the present study for their willingness to contribute to the study.

Competing interests The authors declare that they have no competing interests.

References

Andersson JLR, Jenkinson M, Smith S. Non-linear optimisation. FMRIB technical report TR07JA1 from www.fmrib.ox.ac.uk/analysis/techrep 2007a.

Andersson JLR, Jenkinson M, Smith S. Non-linear registration, aka Spatial normalisation FMRIB technical report TR07JA2 from www.fmrib.ox.ac.uk/analysis/techrep 2007b.

Apps MA, Lockwood PL, Balsters JH. The role of the midcingulate cortex in monitoring others' decisions. Frontiers in Neuroscience. 2013; 7: 251.

Beckmann M, Johansen-Berg H, Rushworth MF. Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization. The Journal of Neuroscience. 2009; 29: 1175-90. Borg J, Andrée B, Soderstrom H, Farde L. The Serotonin System and Spiritual Experiences. American Journal of Psychiatry 2003; 160(11): 1965–1969. Button KS, Ioannidis JPA, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, Munafò MR. Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience 2013; 14: 365-376. Cloninger CR, Svrakic DM, Przybeck TR. A psychobiological model of temperament and character. Archives of General Psychiatry 1993; 50: 975–990. Cloninger CR. Completing the psychobiological architecture of human personality development: Temperament, character, and coherence. In: Staudinger U, Lindenberger U, editors. Understanding human development: Dialogues with lifespan psychology. Boston, MA: Kluwer; 2003. Cloninger CR. The Temperament and Character Inventory—Revised. St. Louis, MO: Center for Psychobiology of Personality, Washington University; 1999. Darki F, Oghabian MA. False positive control of activated voxels in single fMRI analysis using bootstrap resampling in comparison to spatial smoothing. Magnetic Resonance Imaging 2013;31(8):1331-1337. Dodge Y. The Oxford Dictionary of Statistical Terms, OUP 2003; ISBN 0-19-920613-9 Duane TD, Behrendt T. Extrasensory electroencephalographic induction between identical twins. Science 1965; 150(3694): 367. Farmer

RF,

Goldberg

LR.

the revised Temperament and Character Inventory (TCI-R)

A psychometric evaluation of and

the TCI-140.

Psychological Assessment 2008; 20(3): 281-291. Grinberg-Zylberbaum J, Delaflor M, Attie L, Goswami L. The Einstein-Podolsky-Rosen paradox in the brain: The transferred potential. Physics Essays 1994; 7: 422–428. Jenkinson M, Bannister PR, Brady JM, Smith SM. Improved optimisation for the robust and accurate linear registration and motion correction of brain images. NeuroImage 2002; 17(2): 825-841. Jenkinson M, Smith SM. A global optimisation method for robust affine registration of brain images. Medical Image Analysis 2001; 5(2): 143-156. Jensen C, Parker A. Entangled in the Womb? A pilot study on the possible physiological connectedness between identical twins with different embryonic backgrounds. EXPLORE:The journal of Science and Healing 2012; 8(6): 339-347.

Kittenis MD, Caryl PGC, Stevens P. Distant psychophysiological interaction effects between related and unrelated participants. 47th Annual Convention of the Parapsychological Association. 2004;Vienna, Austria. Krippner S, Friedman HL. Mysterious minds: the neurobiology of physics, mediums, and other extraordinary people. Greenwood Publishing Group; 2010. Miller BL, Cummings JL. The human frontal lobes: functions and disorders. NY: The Guilford Press; 2007. Moulton ST, Kosslyn SM. Using neuroimaging to resolve the psi debate. Journal of Cognitive Neuroscience 2008; 20: 182-192. Persinger MA, Koren SA, Tsang EW. Enhanced power within a specific band of theta activity in one person while another receives circumcerebral pulsed magnetic fields: a mechanism for cognitive influence at a distance? Perception and Motor Skill 2003; 97(3): 877-894. Radin DI. Event-related electroencephalographic correlations between isolated human subjects. Journal of Alternative and Complementary Medicine 2004; 10: 315-323. Richards TL, Kozak L, Johnson C, Standish LJ. Replicable functional magnetic resonance imaging evidence of correlated brain signals between physically and sensory isolated subjects. Journal of Alternative and Complementary Medicine 2005; 11: 955-963. Roll WG, Williams BJ. Quantum theory, neurobiology, and parapsychology. In: Krippner S, Friedman H (eds). Mysterious Minds: the Neurobiology of Psychics, Mediums and Other Extraordinary People. Santa Barbara: Praeger; 2010. Seo D, Olman CA, Haut KM, Sinha R, MacDonald AW, III, Patrick CJ. Neural correlates of preparatory and regulatory control over positive and negative emotion. Social Cognition and Affective Neuroscience 2014; 9(4): 494-504. Smith SM. Fast robust automated brain extraction. Human Brain Mapping 2002; 17(3):143155. Standish L, Kozak L, Johnson L, Richards T. Electroencephalographic evidence of correlated event-related signals between the brains of spatially and sensorially isolated human subjects. Journal of Alternative and Complementary Medicine 2004; 10: 307-314. Standish LJ, Johnson LC, Kozak L, Richards T. Evidence of correlated functional MRI signals between distant human brains. Alternative Therapies in Health and Medicine 2003; 9:122-128. Venkatasubramanian G, Jayakumar PN, Nagendra HR, Nagaraja D, Deeptha R, Gangadhar BN. Investigating paranormal phenomena: Functional brain imaging of telepathy. International Journal of Yoga 2008; 1(2): 66-71. Vogt BA, Berger GR, Derbyshire SW. Structural and functional dichotomy of human midcingulate cortex. European Journal of Neuroscince 2003; 18: 3134-3144. Wackermann J, Seiter C, Keibel H, Walach H. Correlations between brain electrical activities of two spatially separated human subjects. Neuroscience Letters 2003; 336: 60-64. Walker EH. The Physics of Consciousness. New York: Basic Books; 2000.

Woolrich MW, Ripley BD, Brady JM, Smith SM. Temporal Autocorrelation in Univariate Linear Modelling of FMRI Data. NeuroImage 2001; 14(6): 1370-1386. Worsley KJ. Statistical analysis of activation images. In P Jezzard, PM Matthews, SM Smith, Functional MRI: An Introduction to Methods, eds. OUP; 2001. Yamasue H, Abe O, Suga M, Yamada H, Inoue H, Tochigi M, Rogers M, Aoki S, Kato N. Gender-common and -specific neuroanatomical basis of human anxiety-related personality traits. Cerebral Cortex 2008; 18 (1): 46–42.