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Cognition, My Research, Neuroscience, Undergraduate

CVS Modulates Moral Judgments

Numerous experiments and high-tech functional imaging techniques have made clear that many of the brain’s abilities are anatomically lateralized; that is, they are the products of highly specialized processing modules localized in one or the other cerebral hemispheres. Recent evidence suggests that our moral judgments, too, are the product of lateralized, competing modules (Cope et al., 2010). Further, we have reason to believe that males and females employ subtly different processing strategies involving both the coordination and lateralization of contributing modules (Harenski, Antonenko, Shane, & Kiehl, 2008). This experiment sought to establish further evidence for the lateralization of moral circuitry using a safe, non-invasive, temporary stimulation of the vestibular nerve with ice water irrigation, which creates a convective current in the fluid of the proximal semicircular canals (Miller & Ngo, 2007; British Society of Audiology, 2010). This stimulation, herein referred to as caloric vestibular stimulation (CVS), has been shown to activate the insular cortex, temporo-parietal junction, superior temporal gyrus, and the anterior cingulate gyrus, among other areas (Miller & Ngo, 2007), all in the cerebral hemisphere contralateral to nerve stimulation. Studies using functional magnetic resonance imaging (fMRI) have shown many of these same regions to be involved in the processing of moral stimuli (Raine & Yang, 2006; Miller & Ngo, 2007; Mendez, 2009), making CVS a particularly promising tool for this study.

The existence of a “moral sense” has been deduced to explain normative, “universal” morality. This idea has recently received material support from fMRI studies, as well as theoretical development from the convergent approaches of evolutionary psychology, neurobiology, and social cognitive neuroscience. The emerging picture is one of morality as a pro-social, emotionally mediated “neuro-moral network” (Mendez, 2009). This network evolved in a demanding environment of ever-increasing social complexity in which the behavioral output of moral processing must have proved favorable for survival and reproduction (Funk & Gazzaniga, 2009). Morality, then, can be understood as a behavioral strategy for survival in complex social environments, with successful social evaluation, judgment, and adaptive action as its components. Moral behavior, the system’s output, appears to be generated by competitive processing between parallel judgment systems of two broad types (two-process theory): moral-emotional processing that produces the “feelings” associated with morality, and moral-cognitive processing that incorporates outcome probability with Theory of Mind. In fact, the subjective experience of a moral dilemma may be understood in terms of conflict between these parallel judgment systems (Funk & Gazzaniga, 2009).

But if moral behavior is determined by unconscious processing and propelled by emotions, what role is left for conscious interpretation and choice? Certainly, our subjective experiences suggest that explicit reasoning contributes to our moral judgments. Funk & Gazzaniga (2009) propose a different, counterintuitive conclusion: that the experience of moral reasoning is generated by a separate interpretive processor. This “interpreter”, they suggest, is concerned with generating coherent causal links between explicit social stimuli and our moral-emotional state, resulting in moral reasoning narratives constructed after automatic judgment processing has generated the behavior requiring explanation. Restated, moral judgment is automatic and unconscious; the generation of narrative that makes sense of that judgment is mostly unconscious as well; the narrative generated by the “interpreter” (by correlating contextual information and descriptive moral convention) is the only artifact from the complex process of moral judgment and interpretive processing available to our consciousness, which we are generally disposed to accept as accurately reflecting our moral reasoning.

The chief contributor to our faculty of moral judgment appears to be moral-emotional processing (J. Greene & Haidt, 2002), which generates the feelings of reciprocity, righteousness, consolation, guilt, shame, embarrassment, gratitude, compassion, pride, and outrage (Mendez, 2009). Moral conflicts have been found to elicit greater emotional distress than purely hedonistic conflicts, corroborating the status of emotion in driving moral behavior (Sommer et al., 2010). Antisocial, criminal, and psychopathic individuals share the inability to conform to societal norms largely because of a deficit in the “feeling” of what is moral, rather than a deficient understanding of moral norms (Raine & Yang, 2006), which again underlines the central role emotional processing plays in moral judgment. Particularly relevant to this study, Greene and colleagues identified a close relationship between personal moral judgments and emotional processing (J. D. S. Greene, 2001). Conversely, the same study found impersonal moral judgments (where the subject was only proposed to be an indirect, rather than direct, agent of consequential action) to be more strongly associated with cognitive processing centers.

By moral-cognitive processing, I refer to moral judgments that include either the quantification of outcomes, the estimation of probability (Shenhav & Greene, 2010), or belief attribution and mental state reasoning (perceiving and accommodating the intentions of others), i.e., Theory of Mind (ToM) (Young, Camprodon, Hauser, Pascual-Leone, & Saxe, 2010). Significantly, in cases where the intentions of others differ from the outcomes of their actions, split-brain patients have been shown to rely entirely on outcome, perhaps because their verbal response, formulated in the left hemisphere, lacks access to belief attribution processing of the right temporo-parietal junction (RTPJ). Further evidence has confirmed split-brain patients to be severely limited in tasks requiring integration of cognitive and moral processing (Funk & Gazzaniga, 2009), with implications for the questions addressed in this study.

Lateralization and perception asymmetries (such as visual hemifield preference) are common among vertebrates (Vallortigara & Rogers, 2005). Language and motor control are widely recognized to be lateralized, but strong evidence for emotional lateralization has arrived only in the last few decades. Two theories have emerged from studies of emotional lateralization: the right hemisphere and valence hypotheses, though neither has been well supported in studies of moral-emotional processing based on Greene’s two-process theory. As mentioned previously, cognitive processing has been associated with right-hemisphere lateralization, particularly involving the RTPJ (Young et al., 2010), while other studies have found left lateralization for moral judgment processing of negative morally laden stimuli in both linguistic and pictorial domains (Cope et al., 2010). This observed lateralization may reflect moral judgment processing itself, or ancillary processing activated by moral processing elsewhere.

Many tools for the study of moral judgments have been developed [e.g., Defining Issues Test (Bailey, 2011; Rest, Narvaez, Thoma, & Bebeau, 1999), Moral Judgment Test (Lind, 2008), the Moral Sense Test (Hauser, n.d.)], but no current test seemed fully appropriate for this study. I therefore set out to build the Explicit Moral Judgment Test (EMJT) [Appendix D] bank around the variables of agency, valence, and processing that could be used to stimulate and measure moral judgments. By agency, I refer to the “who” responsible for some given action – either the subject to whom the stimulus is addressed, or someone else. By valence, I mean the preferential value of some given action – positive, negative, or neutral. By processing, I refer to two of the distinct modules that variably contribute to our moral judgments – moral-emotional processing and moral-cognitive processing. The EMJT bank of 108 statements was reviewed by 7 collaborators using the same rating scale used in the experiment. The statements were grouped and balanced across 3 EMJT sets, one to follow each of the CVS treatments, based on these ratings [Appendix C].

Because evidence for the lateralization of moral processing has been observed experimentally (Cope et al., 2010), asymmetric disruption of normal moral processing via cerebral activation contralateral to CVS was predicted to affect EMJT responses; subjects were expected to significantly alter their pattern of responses to EMJT statements (within-group, repeated measures) following each CVS treatment level. Further, I predicted left and right treatments to have different main effects.

Though agency was predicted to have no significant main effect, valence was expected to have a very large main effect, directionally consistent with variable level: that is, negative statements were predicted to be rated morally very bad or morally somewhat bad; neutral statements were expected to be rated morally neither bad nor good, and positive statements were predicted to be rated as either morally somewhat good or morally very good. Similarly, processing was predicted to have a large main effect, with moral-emotional statements being rated as more extreme (either morally very bad or morally very good), on average, than moral-cognitive statements, which were expected to elicit moderated judgments (trending toward neutral, i.e., neither bad nor good). Interaction effects, both two-way and three-way, were predicted to involve CVS and each of agency, valence, and processing, though the directionality of each effect was not predictable.

Gender differences in brain activation during moral evaluations have been observed (Harenski et al., 2008). Therefore, gender was predicted to have a significant main effect, with males having more moderate EMJT scores, overall, than females. Further, gender was predicted to contribute to significant 2-way interaction effects with CVS, and 3-way interaction effects with CVS and agency.

Method

To test these hypotheses, potential subjects were first screened; those cleared by a medical professional to participate were placed into one of two groups based on gender. After an introduction and orientation, consent was obtained and subjects were reclined to 30° above the horizontal. Each subject was given a CVS control treatment using body-temperature (37°C) water irrigation of the outer canal, followed immediately by the EMJT. Once the test was completed, a seven minute delay was observed to avoid any carryover effects (British Society of Audiology, 2010). The control treatment was balanced between ears, with half of subjects receiving the control treatment in the left ear, and half in the right, and the order of administration was counterbalanced, with half of subjects receiving the control treatment first, and half last. Each subject was given the ice water CVS treatment in both the left and right canal, with the order counterbalanced within groups. Immediately following each treatment, an equivalent EMJT was administered. Following a seven minute break, the ice water CVS treatment was applied to the other ear, with an EMJT again following. Once the protocol was completed, subjects were asked to remain seated until their balance had been fully restored. Full balance was confirmed with a modified “field sobriety” test.

Screening

Prospective subjects were recruited from across the college campus. Interested participants sent their hours of availability to the PI, who scheduled two appointments: one, a medical screening with Berea College Health Services, and a subsequent appointment for the experiment itself. Prospective participants were given a screening consent form [Appendix A] detailing the screening criteria. At the screening, a licensed physician performed an examination for those items enumerated on the form. At the conclusion of the screening, the physician noted the results and signed the consent form, which the subject, if cleared, returned to the PI at their scheduled experiment appointment. It should be noted that only those prospective subjects who cleared the screening examination returned the screening consent form; if one or more of the exclusion criteria were detected during examination, the prospective subject’s examination results were not reported to the PI – their results were kept confidential by the attending physician. Appointments and reminders were scheduled and updated using Microsoft Outlook’s calendar tools through the college’s Exchange network.

Procedure

Those prospective subjects that passed the clinical screening and chose to continue by returning the signed form from Health Services were scheduled for an experimental session, which lasted, on average, 1.2 hours. Upon arrival for the experiment, subjects were introduced to the purpose and methods. Each subject was oriented to the equipment used. An informed consent form [Appendix B] was required of each subject before proceeding with the experimental procedure.

Within each experimental group [group 1, female; group 2, male], repeated measures of EMJT sets following CVS treatments were taken to determine the existence and significance of gender differences in the lateralization of moral processing. CVS, a within-subjects treatment, had three levels: 1) a body-temperature treatment, and ice water treatments of 2) the left ear and 3) right ear. The body-temperature treatment was used as a control because it does not create a current in the proximal semicircular canal or stimulate the vestibular nerve. Subjects confirmed that they experienced no noticeable effects following the control treatment. The administration of body-temperature water was alternated, within each group, between the left and right ear such that ½ of each group’s subjects received the control treatment in the left ear, and ½ in the right ear. CVS administration followed the British Society of Audiology (2010) and Miller & Ngo (2007) protocols.

Judgment scores constituted the dependent variable. Between and within subjects, the EMJT responses were compared to identify and measure gender-based and hemisphere-based differences between personal (self) and impersonal (other) agency, among negative, positive, and neutral valence, and between moral-emotional and moral-cognitive processing. Subjects were given twelve types of statements (self-positive-emotional, self-negative-emotional, self-neutral-emotional, other-positive-emotional, other-negative-emotional, other-neutral-emotional, self-positive-cognitive, self-negative-cognitive, self-neutral-cognitive, other-positive-cognitive, other-negative-cognitive, other-neutral-cognitive) and asked to evaluate each on a five point scale (1. morally very bad, 2. morally somewhat bad, 3. morally neither bad nor good, 4. morally somewhat good, 5. morally very good). Each statement type was represented by a pool of 9 statements, for a total of 108 statements. Each EMJT consisted of 36 statements – 3 equivalent statements from each of the 12 level-combination types [the complete EMJT bank can be found in Appendix C]. Statements were read aloud by the PI, subjects’ evaluations were reported verbally, and the PI recorded the reported evaluations using SurveyMonkey.com, a web-based software-as-service survey platform.

Subjects were given a brief exit survey and debriefed after the experiment (during the final seven minute recovery period) when all pertinent information regarding the theories being tested was presented. Additionally, each subject was instructed to contact Health Services immediately if they experienced any symptoms of depression, prolonged dizziness, nausea, or disorientation. Following completion of all treatments and tests, and upon completion of the exit survey and debriefing, subjects were given time in a safe space to fully recuperate from treatment effects. Once the subject reported full normalcy, a field sobriety test was administered, after which, subjects were thanked for their participation and the experiment ended.

Results

The dependent variable, Subjects’ EMJT evaluations, which ranged between 1 (morally very bad) and 5 (morally very good), constituted the primary data set analyzed using a 2 x 3 x 2 x 3 x 2 mixed-design ANOVA. Tables 1 – 3 (descriptive) and 4 (inferential) show many of the relevant statistics. CVS treatments had a significant but small main effect [F (2,18) = 2.687, p = 0.046; partial η2 = 0.291] on subjects’ EMJT scores, with experimental treatments (left and right ear cold water) having different effects [left ear cold water: m = 2.887, sd = 0.050; right ear cold water: m = 2.785, sd = 0.051; p = 0.013] – our first evidence of lateralization. Overall, subjects’ ratings were lower in experimental conditions than in control conditions, though this difference was small. Meanwhile, gender [female: m = 2.792, sd = 0.069; male: m = 2.904, sd = 0.063], the only between-subjects variable, did not have a significant main effect [F (1, 9) = 1.458, p = 0.258, partial η2 = 0.139], though the small sample size may be obscuring a mild but real effect.

Valence and processing – two of the three EMJT variables – were important checks of experimental validity. It was critical that the EMJT statements be accurate and reliable such that, in control conditions and on average, subjects evaluate valently negative statements as being somewhat to very bad [m = 1.402, sd = 0.098], valently neutral statements as neither bad nor good [m = 3.069, sd = 0.036], and valently positive statements as somewhat to very good [m = 4.073, sd = 0.119]. If consistency had not be obtained on this level, the data would have been unusable and the EMJT judged unsound. Reassuringly, valence had the very large, significant effect expected [F (2,18) = 194.829, p < .001; partial η2 = .956], confirming that this variable worked as intended. Similarly, it was important that processing levels have predictable effects: cognitive processing, such as with cost-benefit analysis, was expected to moderate, or temper, subjects’ evaluations. Put another way, because the variable level “emotional-processing” was intended to stimulate brain regions involved in emotional processing, and the variable level “cognitive-processing” was designed to engage modules associated with quantitative, probabilistic, and TOM processing, emotional-processing [m = 2.964, sd = 0.040] was expected to result in less moderate evaluations, such as “very bad” or “very good”, than cognitive-processing [m = 2.732, sd = 0.074], and in fact, this outcome was observed [F (1,9) = 9.968, p = .012; partial η2  = .526]. Meanwhile, agency [self: m = 2.831, sd = 0.039; other: m = 2.865, sd = 0.056], as expected, did not have a significant main effect [F (1,9) = 1.631, p = .234], meaning that, overall, subjects did no evaluate statements in which the main action was attributed to others differently than those in which they – the participants evaluating the statement – were the proposed agents of action.

However, agency and CVS interacted to produce a medium, significant effect [F (2,18) = 6.46, p = .008; partial η2 = .417] such that during left hemisphere activation [m = 2.704, sd = 0.042], subjects evaluated statements involving self-agency as more negative, on average, than during either control conditions [m = 2.866, sd = 0.052] or right hemisphere activation [m = 2.921, sd = 0.060]. Conversely, right hemisphere activation resulted in self-agency statements being evaluated as more positive than during either control or left hemisphere activation [Figure 1]. These results suggest that self-agency processing may be somewhat lateralized.

Processing and CVS, too, interacted to produce a medium, significant effect [F (2,18) = 5.511, p = .014; partial η2= .380]. During left hemisphere activation [m = 2.607, sd = 0.089], subjects evaluated statements targeting cognitive processing as more negative, on average, than during control conditions [m = 2.744, sd = 0.088] or during right hemisphere activation [m = 2.844, sd = 0.075], when subjects evaluated cognitive-level statements as more positive than during control conditions and left hemisphere activation. These results are consistent with lateralization of cognitive processing, but without further information, the direction (whether left or right) of lateralization is unclear. To establish clearer evidence for directionality, we need significant 3-way interactions.

CVS, processing, and valence produced a medium, significant, 3-way interaction effect [F (4,36) = 6.156, p = .001; partial η2 = .406; Figure 3] such that, during both left and right hemisphere activation and in the context of negative-valence, subjects evaluated statements involving cognitive-processing as more negative than during control conditions [left treatment: m = 1.513, sd = 0.131; control: m = 1.836, sd = 0.170; right treatment: m = 1.388, sd = 0.125; figure 3]. This makes sense; we expect cognitive processing to moderate emotional processing, causing scores to trend toward the morally neutral “3 – neither bad nor good” and away from the extremes of “1 – very bad” or “5 – very good” common with emotional processing alone, and we see just this pattern in control conditions. When the valent content of the statement being evaluated was negative, hemisphere activation interrupted cognitive processing’s moderating effect, causing scores to move toward “1 – very bad”. This is evidence of CVS effect, but not of lateralization, as effects were similar during activation of both hemispheres. But during right hemisphere activation and in the context of positive-valence, subjects evaluated statements involving cognitive-processing as being more positive [m = 3.895, sd = 0.212], on average, than when in control conditions [m = 3.412, sd = 0.141] or during left hemisphere activation [m = 3.404, sd = 0.196]. That is, the moderating cognitive effect was interrupted during right hemisphere activation, but not during left hemisphere activation [figure 3], which I interpret as evidence for the left hemisphere lateralization of what I have tentatively called positive-subtraction processing, that is, the circuitry responsible for calculating the negative cost to be subtracted from a complex, valently positive stimulus.

CVS, agency, and valence also produced a medium, significant, 3-way interaction effect [F (4,36) = 3.959, p = .009; partial η2 = .305]. During both left and right activation and in the context of valently positive stimuli, self-agency statements were evaluated differently than in control conditions. However, right hemisphere activation caused self-positive stimuli to be evaluated more positively [m = 4.277, sd = 0.157] than during control conditions [m = 4.093, sd = 0.133] – the opposite effect of left hemisphere activation, which caused self-positive stimuli to be evaluated more negatively [m = 3.863, sd = 0.143] than when in control conditions [figure 4]. This evidence suggests that self-positive processing may be right-lateralized.

Discussion

Few things feel more intuitive than our sense of right and wrong. Yet, with only cold water, I was able to influence subjects’ evaluations of moral stimuli. The pattern in this alteration of moral judgments was highly consistent with my hypothesis of moral processing lateralization. Agency, valence, and processing were shown to be intricately involved in this processing, and all three aided, via 2- and 3-way interactions with CVS treatment levels, in the identification and localization of two distinct, lateralized processing types: self-positive processing, which appears to be right-lateralized, and left-lateralized positive-subtraction processing.

Despite the small number of participants, this study’s design allowed for diverse theoretical testing, not just of lateralization, but of the utility of both caloric vestibular stimulation and the Explicit Moral Judgment Test in moral-cognition research. Both CVS and the EMJT proved to be appropriate, effective tools deserving of further utilization and development in this and other related cognitive fields. With more specific hypotheses, more subjects, and refined procedures, the line of research herein reported would likely produce even more valuable and conclusive results in the future.

Acknowledgments

I would like to thank Drs. Miriam David and Nancy Ryan and the staff at Berea College Health Services for their generous facilitation of subject screenings; Catelyn Williams, Florence Anyabuonwu, Jennifer Mante, and Erica Brown, who offered valuable feedback during each stage of the project, and David Porter, whose counsel was vital to this project from design to analysis. And I am especially grateful to the Berea College students who participated in this study – they braved health screenings and ice water irrigations when few of their peers would.

References

Bailey, C. D. (2011). Does the Defining Issues Test Measure Ethical Judgment Ability or Political Position? The Journal of Social Psychology, 151, 314-330. doi:10.1080/00224545.2010.481690

British Society of Audiology. (2010). Recommended Procedure: The Caloric Test. British Society of Audiology. Retrieved from http://www.thebsa.org.uk/docs/RecPro/CTP.pdf

Cope, L. M., Borg, J. S., Harenski, C. L., Sinnott-Armstrong, W., Lieberman, D., Nyalakanti, P. K., Calhoun, V. D., et al. (2010). Hemispheric Asymmetries during Processing of Immoral Stimuli, 2. doi:10.3389/fnevo.2010.00110

Funk, C. M., & Gazzaniga, M. S. (2009). The functional brain architecture of human morality. Current Opinion in Neurobiology, 19(6), 678-681. doi:doi: 10.1016/j.conb.2009.09.011

Greene, J. D. S. (2001). An fMRI Investigation of Emotional Engagement in Moral Judgment. Science, 293(5537), 2105.

Greene, J., & Haidt, J. (2002). How (and where) does moral judgment work? Trends in Cognitive Sciences, 6(12), 517-523. doi:10.1016/S1364-6613(02)02011-9

Harenski, C. L., Antonenko, O., Shane, M. S., & Kiehl, K. A. (2008). Gender differences in neural mechanisms underlying moral sensitivity. Social Cognitive and Affective Neuroscience, 3(4), 313 -321. doi:10.1093/scan/nsn026

Hauser, M. (n.d.). Learn About the MST. The Moral Sense Test. educational, . Retrieved December 4, 2011, from http://wjh1.wjh.harvard.edu/~moral/learn.html

Lind, G. (2008). THE MEANING AND MEASUREMENT OF MORAL JUDGMENT COMPETENCE. Contemporary philosophical and psychological perspectives on moral development and education, 185.

Mendez, M. F. (2009). The Neurobiology of Moral Behavior: Review and Neuropsychiatric Implications, 14(11), 608-620.

Miller, S. M., & Ngo, T. T. (2007). Studies of caloric vestibular stimulation: implications for the cognitive neurosciences, the clinical neurosciences and neurophilosophy. Acta Neuropsychiatrica, 19, 183-203. doi:10.1111/j.1601-5215.2007.00208.x

Raine, A., & Yang, Y. (2006). Neural foundations to moral reasoning and antisocial behavior. Social Cognitive and Affective Neuroscience, 1(3), 203 -213. doi:10.1093/scan/nsl033

Rest, J. R., Narvaez, D., Thoma, S. J., & Bebeau, M. J. (1999). DIT2: Devising and testing a revised instrument of moral judgment. Journal of Educational Psychology, 91(4), 644-659. doi:10.1037/0022-0663.91.4.644

Shenhav, A., & Greene, J. D. (2010). Moral Judgments Recruit Domain-General Valuation Mechanisms to Integrate Representations of Probability and Magnitude. Neuron, 67(4), 667-677. doi:doi: 10.1016/j.neuron.2010.07.020

Sommer, M., Rothmayr, C., Döhnel, K., Meinhardt, J., Schwerdtner, J., Sodian, B., & Hajak, G. (2010). How should I decide? The neural correlates of everyday moral reasoning. Neuropsychologia, 48(7), 2018-2026. doi:doi: 10.1016/j.neuropsychologia.2010.03.023

Vallortigara, G., & Rogers, L. J. (2005). Survival with an asymmetrical brain: advantages and disadvantages of cerebral lateralization. The Behavioral and Brain Sciences, 28(4), 575-589; discussion 589-633. doi:10.1017/S0140525X05000105

Young, L., Camprodon, J. A., Hauser, M., Pascual-Leone, A., & Saxe, R. (2010). Disruption of the right temporoparietal junction with transcranial magnetic stimulation reduces the role of beliefs in moral judgments. Proceedings of the National Academy of Sciences, 107(15), 6753 -6758. doi:10.1073/pnas.0914826107

Bailey, C. D. (2011). Does the Defining Issues Test Measure Ethical Judgment Ability or Political Position? The Journal of Social Psychology, 151, 314-330. doi:10.1080/00224545.2010.481690

British Society of Audiology. (2010). Recommended Procedure: The Caloric Test. British Society of Audiology. Retrieved from http://www.thebsa.org.uk/docs/RecPro/CTP.pdf

Cope, L. M., Borg, J. S., Harenski, C. L., Sinnott-Armstrong, W., Lieberman, D., Nyalakanti, P. K., Calhoun, V. D., et al. (2010). Hemispheric Asymmetries during Processing of Immoral Stimuli, 2. doi:10.3389/fnevo.2010.00110

Funk, C. M., & Gazzaniga, M. S. (2009). The functional brain architecture of human morality. Current Opinion in Neurobiology, 19(6), 678-681. doi:doi: 10.1016/j.conb.2009.09.011

Greene, J. D. S. (2001). An fMRI Investigation of Emotional Engagement in Moral Judgment. Science, 293(5537), 2105.

Greene, J., & Haidt, J. (2002). How (and where) does moral judgment work? Trends in Cognitive Sciences, 6(12), 517-523. doi:10.1016/S1364-6613(02)02011-9

Harenski, C. L., Antonenko, O., Shane, M. S., & Kiehl, K. A. (2008). Gender differences in neural mechanisms underlying moral sensitivity. Social Cognitive and Affective Neuroscience, 3(4), 313 -321. doi:10.1093/scan/nsn026

Hauser, M. (n.d.). Learn About the MST. The Moral Sense Test. educational, . Retrieved December 4, 2011, from http://wjh1.wjh.harvard.edu/~moral/learn.html

Lind, G. (2008). THE MEANING AND MEASUREMENT OF MORAL JUDGMENT COMPETENCE. Contemporary philosophical and psychological perspectives on moral development and education, 185.

Mendez, M. F. (2009). The Neurobiology of Moral Behavior: Review and Neuropsychiatric Implications, 14(11), 608-620.

Miller, S. M., & Ngo, T. T. (2007). Studies of caloric vestibular stimulation: implications for the cognitive neurosciences, the clinical neurosciences and neurophilosophy. Acta Neuropsychiatrica, 19, 183-203. doi:10.1111/j.1601-5215.2007.00208.x

Raine, A., & Yang, Y. (2006). Neural foundations to moral reasoning and antisocial behavior. Social Cognitive and Affective Neuroscience, 1(3), 203 -213. doi:10.1093/scan/nsl033

Rest, J. R., Narvaez, D., Thoma, S. J., & Bebeau, M. J. (1999). DIT2: Devising and testing a revised instrument of moral judgment. Journal of Educational Psychology, 91(4), 644-659. doi:10.1037/0022-0663.91.4.644

Shenhav, A., & Greene, J. D. (2010). Moral Judgments Recruit Domain-General Valuation Mechanisms to Integrate Representations of Probability and Magnitude. Neuron, 67(4), 667-677. doi:doi: 10.1016/j.neuron.2010.07.020

Sommer, M., Rothmayr, C., Döhnel, K., Meinhardt, J., Schwerdtner, J., Sodian, B., & Hajak, G. (2010). How should I decide? The neural correlates of everyday moral reasoning. Neuropsychologia, 48(7), 2018-2026. doi:doi: 10.1016/j.neuropsychologia.2010.03.023

Vallortigara, G., & Rogers, L. J. (2005). Survival with an asymmetrical brain: advantages and disadvantages of cerebral lateralization. The Behavioral and Brain Sciences, 28(4), 575-589; discussion 589-633. doi:10.1017/S0140525X05000105

Young, L., Camprodon, J. A., Hauser, M., Pascual-Leone, A., & Saxe, R. (2010). Disruption of the right temporoparietal junction with transcranial magnetic stimulation reduces the role of beliefs in moral judgments. Proceedings of the National Academy of Sciences, 107(15), 6753 -6758. doi:10.1073/pnas.0914826107

Tables and Graphs

Table 1. Descriptive statistics for independent variables

Independent Variable

Type

Level

N

Mean

Std. Error

Gender Between Subjects Male 6 2.904 0.069
Female 5 2.792 0.063
CVS Within Subjects Left Ear Cold Water 36 2.887 0.050
Control 36 2.872 0.055
Right Ear Cold Water 36 2.785 0.051
Agency Within Subjects Self 54 2.831 0.039
Other 54 2.865 0.056
Valence Within Subjects Negative 36 1.402 0.098
Neutral 36 3.069 0.036
Positive 36 4.073 0.119
Processing Within Subjects Emotional 54 2.964 0.040
Cognitive 54 2.732 0.074

Table 2. Statistics Descriptive of CVS Effects on EMJT Scores by Agency, Valence, and Processing

CVS

ID 2

Level

N

Mean

Std. Error

Left Ear Cold Water Agency Self 18 2.921 0.060
Other 18 2.852 0.047
Valence Negative 12 1.344 0.102
Neutral 12 3.115 0.049
Positive 12 4.202 0.143
Processing Emotional 18 2.930 0.041
Cognitive 18 2.844 0.075
Control Agency Self 18 2.866 0.052
Other 18 2.877 0.071
Valence Negative 12 1.546 0.122
Neutral 12 3.063 0.055
Positive 12 4.006 0.122
Processing Emotional 18 2.999 0.053
Cognitive 18 2.744 0.088
Right Ear Cold Water Agency Self 18 2.704 0.042
Other 18 2.865 0.064
Valence Negative 12 1.315 0.089
Neutral 12 3.029 0.032
Positive 12 4.010 0.127
Processing Emotional 18 2.962 0.042
Cognitive 18 2.607 0.089

Table 3. Descriptive Statistics of Select 3-Way Environments

CVS

Valence

IV 3 Level

N

Mean

Std. Error

Left Ear Cold Water Negative Self-Agency 6 1.367 0.122
Cognitive-Processing 6 1.513 0.131
Neutral Self-Agency 6 3.121 0.050
Cognitive-Processing 6 3.123 0.052
Positive Self-Agency 6 4.277 0.157
Cognitive-Processing 6 3.895 0.212
Control Negative Self-Agency 6 1.428 0.130
Cognitive-Processing 6 1.836 0.170
Neutral Self-Agency 6 3.078 0.060
Cognitive-Processing 6 2.985 0.014
Positive Self-Agency 6 4.093 0.133
Cognitive-Processing 6 3.412 0.141
Right Ear Cold Water Negative Self-Agency 6 1.249 0.092
Cognitive-Processing 6 1.388 0.125
Neutral Self-Agency 6 3.000 0.000
Cognitive-Processing 6 3.029 0.032
Positive Self-Agency 6 3.863 0.143
Cognitive-Processing 6 3.404 0.196

Table 4. Significant Inferential Statistics

Independent Variable(s)

Mean Square

df

F

Sign. (p)

Partial η2

CVS 0.399 2 3.687 0.046 0.291
Valence 238.229 2 194.829 < 0.001 0.956
Processing 5.286 1 9.968 0.012 0.526
CVS + Agency 0.445 2 6.446 0.008 0.417
CVS + Valence 0.462 4 3.932 0.010 0.304
CVS + Agency + Valence 0.277 4 3.959 0.009 0.305
CVS + Processing 0.601 2 5.511 0.014 0.380
Valence + Processing 15.953 2 44.022 < 0.001 0.830
CVS + Valence + Processing 0.629 4 6.156 0.001 0.406

Figure 1. Interaction Between CVS and Agency

Figure 2. Interaction Between CVS and Processing

Figure 3. CVS Effects on Cognitive Processing Across Valence Levels

Figure 4. CVS Effects on Self-Agency Processing Across Valences

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