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A Neural Circuit for Spirituality and Religiosity Derived From Patients With Brain Lesions

  • Michael A. Ferguson
    Correspondence
    Address correspondence to Michael A. Ferguson, Ph.D.
    Affiliations
    Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts

    Harvard Medical School, Boston, Massachusetts
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  • Frederic L.W.V.J. Schaper
    Affiliations
    Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts

    Harvard Medical School, Boston, Massachusetts

    Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
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  • Alexander Cohen
    Affiliations
    Harvard Medical School, Boston, Massachusetts

    Department of Neurology, Boston Children’s Hospital, Boston, Massachusetts
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  • Shan Siddiqi
    Affiliations
    Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts

    Harvard Medical School, Boston, Massachusetts

    Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts

    Department of Psychiatry, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
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  • Sarah M. Merrill
    Affiliations
    Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
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  • Jared A. Nielsen
    Affiliations
    Department of Psychology, Brigham Young University, Provo, Utah
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  • Jordan Grafman
    Affiliations
    Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, Illinois

    Cognitive Neuroscience Laboratory, Think + Speak Lab, Shirley Ryan Ability Lab, Chicago, Illinois
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  • Cosimo Urgesi
    Affiliations
    Cognitive Neuroscience Laboratory, Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
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  • Franco Fabbro
    Affiliations
    Cognitive Neuroscience Laboratory, Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
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  • Michael D. Fox
    Affiliations
    Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts

    Harvard Medical School, Boston, Massachusetts

    Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts

    Athinoula A. Martinos Centre for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts

    Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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      Abstract

      Background

      Over 80% of the global population consider themselves religious, with even more identifying as spiritual, but the neural substrates of spirituality and religiosity remain unresolved.

      Methods

      In two independent brain lesion datasets (N1 = 88; N2 = 105), we applied lesion network mapping to test whether lesion locations associated with spiritual and religious belief map to a specific human brain circuit.

      Results

      We found that brain lesions associated with self-reported spirituality map to a brain circuit centered on the periaqueductal gray. Intersection of lesion locations with this same circuit aligned with self-reported religiosity in an independent dataset and previous reports of lesions associated with hyper-religiosity. Lesion locations causing delusions and alien limb syndrome also intersected this circuit.

      Conclusions

      These findings suggest that spirituality and religiosity map to a common brain circuit centered on the periaqueductal gray, a brainstem region previously implicated in fear conditioning, pain modulation, and altruistic behavior.

      Keywords

      Spiritual and religious behaviors have been present since early stages of human evolution (
      • Atran S.
      Gods We Trust: The Evolutionary Landscape of Religion.
      ) and played a significant role in shaping most human societies (
      • Atran S.
      Gods We Trust: The Evolutionary Landscape of Religion.
      ,
      • Dawkins R.
      • Ward L.
      The God Delusion.
      ,
      • Durkheim E.
      • Swain J.W.
      The Elementary Forms of the Religious Life.
      ,
      • Freud S.
      Civilization and Its Discontents.
      ,
      • Laine J.W.
      Meta-Religion: Religion and Power in World History.
      ). Today, over 80% of the global population identify as religious, and even more as spiritual (
      • Dawkins R.
      • Ward L.
      The God Delusion.
      ,
      • Hackett C.
      • Stonawski M.
      • McClendon D.
      The Changing Global Religious Landscape.
      ). Defining and measuring these behaviors scientifically is possible. Spirituality, or more precisely, spiritual acceptance, has been defined as “a stable shift in worldview towards belief in forces that cannot be rationally comprehended or objectively proven.” (
      • Cloninger C.R.
      • Svrakic D.M.
      • Przybeck T.R.
      A psychobiological model of temperament and character.
      ,
      • Garcia-Romeu A.
      Self-transcendence as a measurable transpersonal construct.
      ) It has been measured using the Temperament and Character Inventory, which includes questions about “being directed by a spiritual force,” “miracles,” “religious experiences,” and “purpose.” Religiosity has been defined as participation in a “unified system of beliefs and practices relative to sacred things.” (
      • Durkheim E.
      • Swain J.W.
      The Elementary Forms of the Religious Life.
      ) There is no accepted standard for measuring religiosity, but it can be assessed via simple self-report to the question “Do you consider yourself to be a religious person?” (
      • Cohen-Zimerman S.
      • Cristofori I.
      • Zhong W.
      • Bulbulia J.
      • Krueger F.
      • Gordon B.
      • Grafman J.
      Neural underpinning of a personal relationship with God and sense of control: A lesion-mapping study.
      ).
      The biological basis for spirituality and religiosity has been investigated using genetics, neurotransmitter levels, and functional neuroimaging (
      • Borg J.
      • Andrée B.
      • Soderstrom H.
      • Farde L.
      The serotonin system and spiritual experiences.
      ,
      • Comings D.E.
      • Gonzales N.
      • Saucier G.
      • Johnson J.P.
      • MacMurray J.P.
      The DRD4 gene and the spiritual transcendence scale of the character temperament index.
      ,
      • Lorenzi C.
      • Serretti A.
      • Mandelli L.
      • Tubazio V.
      • Ploia C.
      • Smeraldi E.
      5-HT1A polymorphism and self-transcendence in mood disorders.
      ,
      • Nilsson K.W.
      • Damberg M.
      • Ohrvik J.
      • Leppert J.
      • Lindström L.
      • Anckarsäter H.
      • Oreland L.
      Genes encoding for AP-2beta and the serotonin transporter are associated with the Personality Character Spiritual Acceptance.
      ,
      • Ferguson M.A.
      • Nielsen J.A.
      • King J.B.
      • Dai L.
      • Giangrasso D.M.
      • Holman R.
      • et al.
      Reward, salience, and attentional networks are activated by religious experience in devout Mormons.
      ,
      • Beauregard M.
      • Paquette V.
      Neural correlates of a mystical experience in Carmelite nuns.
      ,
      • Rim J.I.
      • Ojeda J.C.
      • Svob C.
      • Kayser J.
      • Drews E.
      • Kim Y.
      • et al.
      Current understanding of religion, spirituality, and their neurobiological correlates.
      ). Functional neuroimaging has identified many different brain regions whose activity is correlated with spirituality or religiosity, but whether these regions are causally involved in these behaviors is unknown.
      Patients with brain disorders can provide unique insight into the neural substrate of spirituality and religiosity that can complement data from functional neuroimaging (
      • Grafman J.
      • Cristofori I.
      • Zhong W.
      • Bulbulia J.
      The neural basis of religious cognition.
      ,
      • Waxman S.G.
      • Geschwind N.
      The interictal behavior syndrome of temporal lobe epilepsy.
      ,
      • Geschwind N.
      Behavioural changes in temporal lobe epilepsy1.
      ,
      • Ogata A.
      • Miyakawa T.
      Religious experiences in epileptic patients with a focus on ictus-related episodes.
      ,
      • Devinsky O.
      • Lai G.
      Spirituality and religion in epilepsy.
      ,
      • Urgesi C.
      • Aglioti S.M.
      • Skrap M.
      • Fabbro F.
      The spiritual brain: Selective cortical lesions modulate human self-transcendence.
      ,
      • Zhong W.
      • Cristofori I.
      • Bulbulia J.
      • Krueger F.
      • Grafman J.
      Biological and cognitive underpinnings of religious fundamentalism.
      ). Patients with temporal lobe epilepsy can present with hyper-religious symptoms (
      • Waxman S.G.
      • Geschwind N.
      The interictal behavior syndrome of temporal lobe epilepsy.
      ,
      • Geschwind N.
      Behavioural changes in temporal lobe epilepsy1.
      ,
      • Ogata A.
      • Miyakawa T.
      Religious experiences in epileptic patients with a focus on ictus-related episodes.
      ,
      • Devinsky O.
      • Lai G.
      Spirituality and religion in epilepsy.
      ), which has been linked to hippocampal as opposed to amygdala pathology (
      • Wuerfel J.
      • Krishnamoorthy E.S.
      • Brown R.J.
      • Lemieux L.
      • Koepp M.
      • Tebartz van Elst L.
      • Trimble M.R.
      Religiosity is associated with hippocampal but not amygdala volumes in patients with refractory epilepsy.
      ). Patients with parietal lobe damage can experience increased spirituality (
      • Urgesi C.
      • Aglioti S.M.
      • Skrap M.
      • Fabbro F.
      The spiritual brain: Selective cortical lesions modulate human self-transcendence.
      ), and patients with frontal lobe damage can show increased religious fundamentalism (
      • Zhong W.
      • Cristofori I.
      • Bulbulia J.
      • Krueger F.
      • Grafman J.
      Biological and cognitive underpinnings of religious fundamentalism.
      ,
      • Asp E.
      • Ramchandran K.
      • Tranel D.
      Authoritarianism, religious fundamentalism, and the human prefrontal cortex.
      ). Such patients can allow for causal inferences between neuroanatomy and spiritual or religious behaviors, but multiple different brain regions have been implicated.
      Recently, it has become possible to map complex behavior to human brain circuits based on locations of brain damage that modulate the behavior and a wiring diagram of the human brain termed the human connectome (
      • Fox M.D.
      Mapping symptoms to brain networks with the human connectome.
      ). This technique, termed lesion network mapping, is particularly helpful when lesions causing similar symptoms occur in multiple different brain locations. Lesion network mapping has identified human brain circuits associated with amnesia, delusions, hallucinations, and even disorders of free will (
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ,
      • Darby R.R.
      • Horn A.
      • Cushman F.
      • Fox M.D.
      Lesion network localization of criminal behavior.
      ,
      • Boes A.D.
      • Prasad S.
      • Liu H.
      • Liu Q.
      • Pascual-Leone A.
      • Caviness Jr., V.S.
      • Fox M.D.
      Network localization of neurological symptoms from focal brain lesions.
      ,
      • Darby R.R.
      • Joutsa J.
      • Burke M.J.
      • Fox M.D.
      Lesion network localization of free will.
      ). Here, we used this technique to test whether lesion locations associated with spiritual and religious belief map to a specific human brain circuit.

      Methods and Materials

      Lesion Dataset for Spiritual Acceptance

      We analyzed a previously published dataset (
      • Urgesi C.
      • Aglioti S.M.
      • Skrap M.
      • Fabbro F.
      The spiritual brain: Selective cortical lesions modulate human self-transcendence.
      ) in which neurosurgical patients were recruited for the purpose of studying temperament and character changes after brain tumor resection (N = 88) (Figure 1) (Supplemental Methods). For the current study, we focused on the spiritual acceptance subscale of the self-transcendence domain because it has previously been validated as a metric of spirituality and religiosity (
      • Garcia-Romeu A.
      Self-transcendence as a measurable transpersonal construct.
      ,
      • Borg J.
      • Andrée B.
      • Soderstrom H.
      • Farde L.
      The serotonin system and spiritual experiences.
      ,
      • Nilsson K.W.
      • Damberg M.
      • Ohrvik J.
      • Leppert J.
      • Lindström L.
      • Anckarsäter H.
      • Oreland L.
      Genes encoding for AP-2beta and the serotonin transporter are associated with the Personality Character Spiritual Acceptance.
      ). Note that this differs from a previous report on this dataset (
      • Urgesi C.
      • Aglioti S.M.
      • Skrap M.
      • Fabbro F.
      The spiritual brain: Selective cortical lesions modulate human self-transcendence.
      ), which focused on the broader self-transcendence category.
      Figure thumbnail gr1
      Figure 1Lesion locations associated with changes in spirituality occur in many different brain locations. (A) Spirituality (or, more precisely spiritual acceptance) is measured by the Temperament and Character Inventory using a series of true or false self-report items. Spirituality is calculated as a single-value score based on participant responses across the items. Spirituality scores were obtained before and after neurosurgical resection of brain tumors, and changes in spirituality calculated from these longitudinal time points. (B) Lesion locations from the 4 patients with the greatest decrease in spiritual acceptance after neurosurgery. (C) Lesion locations from the 4 patients with the greatest increase in spiritual acceptance. L, left; R, right.

      Lesion Network Mapping of Spiritual Acceptance

      We used lesion network mapping and previously validated methods to derive a brain network for spiritual acceptance in a data-driven fashion (
      • Fox M.D.
      Mapping symptoms to brain networks with the human connectome.
      ,
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ) (Figure 2). First, resting-state functional connectivity between each lesion location and the rest of the brain was computed using a publicly available normative connectome dataset from 1000 healthy right-handed subjects (42.7% male subjects, ages 18–35 years, mean age 21.3 years) (
      • Yeo B.T.T.
      • Krienen F.M.
      • Sepulcre J.
      • Sabuncu M.R.
      • Lashkari D.
      • Hollinshead M.
      • et al.
      The organization of the human cerebral cortex estimated by intrinsic functional connectivity.
      ,
      • Holmes A.J.
      • Hollinshead M.O.
      • O’Keefe T.M.
      • Petrov V.I.
      • Fariello G.R.
      • Wald L.L.
      • et al.
      Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures.
      ). This connectome dataset was processed in accordance with the strategy of Fox et al. (
      • Fox M.D.
      • Snyder A.Z.
      • Vincent J.L.
      • Corbetta M.
      • Van Essen D.C.
      • Raichle M.E.
      The human brain is intrinsically organized into dynamic, anticorrelated functional networks.
      ), which results in a map of brain regions functionally connected to each lesion location referred to as a lesion network (
      • Fox M.D.
      Mapping symptoms to brain networks with the human connectome.
      ,
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ). Second, we identified the peak connection most associated with changes in spiritual acceptance using voxelwise permutation analysis of linear models (PALM) with changes in spiritual acceptance as a behavioral covariable (Figure 2). The peak voxelwise association was identified and the coordinates recorded in Montreal Neurological Institute (MNI) space. By definition, functional connectivity with this peak coordinate (using the same normative connectome described above) defines a brain network that best aligns with lesion locations decreasing or increasing spirituality. We previously used this same approach to define brain networks for memory (
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ) and depression (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.A.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ). Because we were searching for the peak voxelwise association to define a spirituality network, this analysis was not corrected for multiple comparisons across all brain voxels. This peak should therefore be considered descriptive until validated in an independent dataset.
      Figure thumbnail gr2
      Figure 2Data-driven method for identifying a lesion network for spiritual acceptance. (A) The network of brain regions functionally connected to each lesion location was computed using resting-state functional connectivity data from a large database of healthy volunteers (N = 1000). Lesion locations and lesion networks are shown for 3 of the 88 neurosurgical cases. Positively connected voxels are shown in warm colors, while negatively connected voxels are shown in cool colors. The peak voxelwise association between lesion connectivity and changes in spiritual acceptance was identified (image shown at uncorrected p < .001). (B) Functional connectivity with this peak was computed using the same resting-state functional connectivity database from healthy volunteers (N = 1000) to derive a brain circuit for spirituality (image shown after voxelwise correction for multiple comparisons, familywise error [FWE]-corrected p < .05). (C, D) Circular demonstration that our brain circuit for spirituality aligns with lesion locations associated with decreased spirituality (C) or increased spirituality (D). Lesions locations associated with increased spirituality intersect negatively connected regions (cool colors), while legions associated with decreased spirituality intersect positively connected regions (warm colors).
      To test for robustness, we repeated this PALM analysis including lesion size as a covariate. To test for specificity to spiritual acceptance, we repeated this PALM analysis using all seven Temperament and Character Inventory measures available in this dataset as covariates while also controlling for lesion size.

      Validation in an Independent Dataset

      To validate these data-driven findings, we analyzed a second independent dataset from patients with lesions caused by penetrating head trauma from combat during the Vietnam War (N = 105). Religiosity was assessed via questionnaire (“Do you consider yourself to be a religious person?”; yes or no) administered several decades after brain injury, during phase 4 of the Vietnam Head Injury Study (
      • Raymont V.
      • Salazar A.M.
      • Krueger F.
      • Grafman J.
      “Studying injured minds” - The Vietnam head injury study and 40 years of brain injury research.
      ). Lesion locations were outlined on computed tomography scans and transformed to MNI space as described previously (
      • Raymont V.
      • Salazar A.M.
      • Krueger F.
      • Grafman J.
      “Studying injured minds” - The Vietnam head injury study and 40 years of brain injury research.
      ).
      We calculated functional connectivity between each head trauma lesion location (n = 105) with the peak coordinate identified from our neurosurgical dataset. In other words, the data-driven result from our neurosurgical dataset (discovery) was used as an a priori region of interest in the analysis of our independent head trauma dataset (validation). Using our normative connectome and previously reported methods (
      • Snider S.B.
      • Hsu J.
      • Darby R.R.
      • Cooke D.
      • Fischer D.
      • Cohen A.L.
      • et al.
      Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem.
      ), we computed the Pearson correlation between functional magnetic resonance imaging time-series extracted from each lesion location with the time-series extracted from our a priori region of interest. The resulting r values were converted to a normal distribution using Fischer’s r-to-z transform, then averaged across the 1000 subjects, resulting in a single value that reflects the functional connectivity between each lesion location and our a priori region of interest (spirituality peak). We then used a two-sample two-tailed t test to compare connectivity values between nonreligiously self-identified individuals (n = 25) versus religiously self-identified individuals (n = 80).
      In a related analysis, we tested whether intersection of lesion locations from our head trauma dataset (N = 105) with the spirituality circuit derived from our neurosurgical dataset was associated with religiosity. A circuit damage score was computed by overlapping each head trauma lesion (N = 105) with the circuit map defined by functional connectivity to the peak coordinate from the neurosurgical dataset (N = 88). We then calculated the sum of functional connectivity values for all voxels within the lesion trace (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.A.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ,
      • Cotovio G.
      • Talmasov D.
      • Barahona-Corrêa J.B.
      • Hsu J.
      • Senova S.
      • Ribeiro R.
      • et al.
      Mapping mania symptoms based on focal brain damage.
      ). We again used a two-sample two-tailed t test to compare circuit damage score values between nonreligiously self-identified (n = 25) versus religiously self-identified (n = 80) individuals. For visualization purposes, we overlaid lesion locations from nonreligious versus religious individuals on the brain circuit derived from our spirituality dataset (Figure 3).
      Figure thumbnail gr3
      Figure 3Cross-validation of lesion network mapping results across two independent datasets. (A) Discovery: lesion network mapping of spiritual acceptance in a neurosurgical dataset (N = 88) identified a peak association in the periaqueductal gray (PAG) (uncorrected [unc] p < .001; z = −10). (B) Cross-validation: functional connectivity between this PAG location and lesion locations from an independent dataset of head trauma lesions (N = 105) was associated with religiosity (white outlines showing 8 of 105 lesions). Positive functional connectivity with the PAG is shown in warm colors (intersecting lesion locations associated with nonreligiosity), while negative functional connectivity with the PAG is shown in cool colors (intersecting lesion locations associated with religiosity). (C) Discovery: lesion network mapping of religiosity in a head trauma dataset (N = 105) also identified a peak association in the PAG (unc p < .002; z = −11). (D) Cross-validation: functional connectivity between this PAG location and lesion locations from an independent dataset of neurosurgical lesions (N = 88) was associated with changes in spirituality (white outlines showing 8 of 105 lesions). Positive functional connectivity with the PAG is shown in warm colors (intersecting lesion locations associated with decreased spirituality), while negative functional connectivity with the PAG is shown in cool colors (intersecting lesion locations associated with increased spirituality). R, right.

      Swapping Discovery and Validation Datasets

      To ensure that results were not dependent on which dataset we used for discovery versus validation, we repeated analyses using the head trauma dataset to define a data-driven network for religiosity (discovery) and the independent neurosurgical dataset to test whether this network was related to lesion-induced changes in spirituality (validation). For a more detailed description, see Supplemental Methods.

      Voxel-Based Lesion Symptom Mapping

      To test whether or results depended on connectivity or could be obtained based on lesion location alone, we repeated all analyses using voxel-based lesion symptom mapping (VLSM) (see Supplemental Methods).

      Robustness to Methodological Changes

      To ensure that our lesion network mapping results were not dependent on methods used for processing resting-state functional connectivity, we repeated our analyses using a human connectome processed without global signal regression (Supplemental Methods) (
      • Snider S.B.
      • Hsu J.
      • Darby R.R.
      • Cooke D.
      • Fischer D.
      • Cohen A.L.
      • et al.
      Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem.
      ). We repeated lesion network mapping analysis for spirituality (in the neurosurgical dataset) and religiosity (in the head trauma dataset) using this alternative connectome.
      To ensure that our lesion network mapping results were not dependent on the peak voxel, we repeated our lesion network analyses using the top 1% and 5% of voxels rather than only the peak voxel. This analysis was performed separately on our spirituality dataset and our religiosity dataset, each processed using two different connectome processing strategies described above. This resulted in 8 total maps (4 maps with the 1% cutoff and 4 maps at the 5% cutoff). Of these four maps for each voxel cutoff, two maps were voxelwise associations with spirituality (with and without global signal regression) and two maps were voxelwise associations with religiosity (with and without global signal regression). We performed a conjunction analysis by binarizing each map and overlapping them, showing results that are independent of dataset and these methodological changes (Figure 4).
      Figure thumbnail gr4
      Figure 4Conjunction of lesion network mapping results using different analysis approaches shows consistent localization to the periaqueductal gray: the top 5% of voxels (red) and top 1% of voxels (yellow) identified across our two independent datasets analyzed using two different connectome processing strategies (i.e., connectomes processed either with or without global signal regression).

      Characterization of the Spirituality Network

      We identified local maxima in our spirituality network using a clustering analysis (FSL, version 6.0, 2018 release). No a priori threshold was applied for clustering or local maxima searching. The top ten positive and negative peaks were identified and recorded.

      Literature-Based Case Reports of Hyper-religiosity

      Case reports of patients with lesion-induced hyper-religiosity were identified using a systematic literature search (see Supplement). Lesion location was traced by hand from the published image onto the MNI template brain using 3D Slicer (available at https://www.slicer.org) (Figure 5). Although previous work has shown high test-retest reproducibility of these tracings (
      • Cotovio G.
      • Talmasov D.
      • Barahona-Corrêa J.B.
      • Hsu J.
      • Senova S.
      • Ribeiro R.
      • et al.
      Mapping mania symptoms based on focal brain damage.
      ), the tracings were repeated by a second person blinded to the lesion network mapping results of this study (Figure S3). Intersections of each lesion location with our spirituality circuit were quantified by summing the t values of each voxel in our spirituality circuit that fell within each lesion trace (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.A.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ).
      Figure thumbnail gr5
      Figure 5Our brain circuit for spiritual acceptance aligns with previous literature on hyper-religiosity. (A–D) Case reports of lesion locations associated with hyper-religiosity (white outlines) intersect negative nodes of our spirituality circuit. (E) Brain regions previously associated with seizure-induced hyper-religiosity (hippocampus [H]) intersects positive nodes of our spirituality circuit, but not adjacent brain regions not associated with hyper-religiosity (amygdala [A]). Positive periaqueductal gray connectivity is shown in warm colors, while negative periaqueductal gray connectivity is shown in cool colors. L, left; R, right.

      Relationship to Hyper-religiosity in Temporal Lobe Epilepsy

      To explore whether spirituality circuit topography aligns with previously published descriptions of hyper-religiosity in the context of mesial temporal lobe epilepsy (
      • Wuerfel J.
      • Krishnamoorthy E.S.
      • Brown R.J.
      • Lemieux L.
      • Koepp M.
      • Tebartz van Elst L.
      • Trimble M.R.
      Religiosity is associated with hippocampal but not amygdala volumes in patients with refractory epilepsy.
      ), we leveraged a previous study linking hyper-religiosity to neuroanatomy (
      • Wuerfel J.
      • Krishnamoorthy E.S.
      • Brown R.J.
      • Lemieux L.
      • Koepp M.
      • Tebartz van Elst L.
      • Trimble M.R.
      Religiosity is associated with hippocampal but not amygdala volumes in patients with refractory epilepsy.
      ). Specifically, hyper-religiosity was associated with hippocampal but not amygdala atrophy. We therefore computed the intersection of our circuit with anatomical masks of the hippocampus and the amygdala from the Harvard-Oxford neuroanatomical atlas. Intersection was quantified by summing the t values of each voxel in our spirituality circuit that fell within the hippocampus and amygdala masks (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.A.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ).

      Relationship to Lesions Associated With Other Neurologic or Psychiatric Symptoms

      Spirituality circuit damage scores were calculated as described above for 356 symptom-causing lesions spanning 12 unique symptoms (Figure 6) (
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.A.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ,
      • Cotovio G.
      • Talmasov D.
      • Barahona-Corrêa J.B.
      • Hsu J.
      • Senova S.
      • Ribeiro R.
      • et al.
      Mapping mania symptoms based on focal brain damage.
      ). These 12 symptoms represent all lesion network mapping studies previously published by our laboratory at the time of this manuscript preparation. In other words, these symptoms were not selected on the basis of any a priori hypothesis for which symptoms should align with our spirituality and religiosity circuit. These 12 queried symptoms included akinetic mutism (n = 28) (
      • Darby R.R.
      • Joutsa J.
      • Burke M.J.
      • Fox M.D.
      Lesion network localization of free will.
      ), alien limb (n = 50) (
      • Darby R.R.
      • Joutsa J.
      • Burke M.J.
      • Fox M.D.
      Lesion network localization of free will.
      ), amnesia (n = 53) (
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ), asterixis (n = 30) (
      • Bell V.
      • Raihani N.
      • Wilkinson S.
      Derationalizing delusions.
      ), criminality (n = 17) (
      • Geschwind N.
      Behavioural changes in temporal lobe epilepsy1.
      ), delusions (n = 15) (
      • Bronstein M.V.
      • Pennycook G.
      • Joormann J.
      • Corlett P.R.
      • Cannon T.D.
      Dual-process theory, conflict processing, and delusional belief.
      ), expressive aphasia (n = 12) (
      • Boes A.D.
      • Prasad S.
      • Liu H.
      • Liu Q.
      • Pascual-Leone A.
      • Caviness Jr., V.S.
      • Fox M.D.
      Network localization of neurological symptoms from focal brain lesions.
      ), freezing of gait (n = 14) (
      • Fasano A.
      • Laganiere S.E.
      • Lam S.
      • Fox M.D.
      Lesions causing freezing of gait localize to a cerebellar functional network.
      ), hallucinations (n = 15) (
      • Kim N.Y.
      • Hsu J.
      • Talmasov D.
      • Joutsa J.
      • Soussand L.
      • Wu O.
      • et al.
      Lesions causing hallucinations localize to one common brain network.
      ), hemichorea (n = 29) (
      • Fasano A.
      • Laganiere S.E.
      • Lam S.
      • Fox M.D.
      Lesions causing freezing of gait localize to a cerebellar functional network.
      ), pain (n = 24) (
      • Boes A.D.
      • Prasad S.
      • Liu H.
      • Liu Q.
      • Pascual-Leone A.
      • Caviness Jr., V.S.
      • Fox M.D.
      Network localization of neurological symptoms from focal brain lesions.
      ), and parkinsonism (n = 29) (
      • Joutsa J.
      • Horn A.
      • Hsu J.
      • Fox M.D.
      Localizing parkinsonism based on focal brain lesions.
      ). A one-way analysis of variance was performed across symptom categories to test for preferential relationships between specific categories of symptom-causing lesions and the spirituality circuit. Post hoc one-sample t tests were performed on spirituality circuit damage for each individual symptom to quantitatively characterize the relationships between symptom-causing lesions and the spirituality circuit.
      Figure thumbnail gr6
      Figure 6Lesion locations associated with other neurologic and psychiatric symptoms intersect our spirituality circuit. Lesion locations (white outlines) associated with parkinsonism (showing 4 of 29 cases) (A) intersected positive nodes of our spirituality circuit, similar to lesions associated with nonreligiosity. Lesion locations associated with alien limb syndrome (showing 4 of 50 cases) (B) and delusions (showing 4 of 15 cases) (C) showed the strongest intersection with negative nodes of our spirituality circuit, similar to lesion locations associated with religiosity. The sum of voxel intensities within lesion locations associated with 12 different neurologic and psychiatric symptoms (n = 356) are shown in a bar graph (D). Error bars reflect standard error across different lesion locations within each lesion syndrome. dPAG, dorsal periaqueductal gray.

      Results

      Lesion Network Mapping of Spiritual Acceptance

      Of the 88 neurosurgical patients, 30 patients showed a decrease, 29 showed an increase, and 29 showed no change in self-reported spiritual belief before and after neurosurgical brain tumor resection (Tables S1 and S2) (
      • Cloninger C.R.
      • Svrakic D.M.
      • Przybeck T.R.
      A psychobiological model of temperament and character.
      ,
      • Urgesi C.
      • Aglioti S.M.
      • Skrap M.
      • Fabbro F.
      The spiritual brain: Selective cortical lesions modulate human self-transcendence.
      ). Lesion locations were heterogeneously distributed throughout the brain (Figure 1B, C).
      Using lesion network mapping (Figure 2), the peak association with changes in spiritual acceptance was connectivity between lesion locations and the periaqueductal gray (PAG) (MNI: x = −2, y = −36, z = −10, uncorrected p < .001) (Figure 2A). Functional connectivity with this PAG location thus defines a brain circuit that best aligns with lesion locations that modulate spirituality (Figure 2B), such that lesion locations associated with decreased spirituality intersect positive nodes in this map, while lesion locations associated with increased spirituality intersect negative nodes (Figure 2C, D).
      Connectivity between lesion locations and the PAG was still associated with changes in spirituality after controlling for lesion size (p = .002). Lesion connectivity to PAG was also specific for spiritual acceptance when controlling for all seven Temperament and Character Inventory measures of temperament and character (p = .02).

      Validation in an Independent Dataset

      Of the 105 patients who completed a questionnaire about religiosity after penetrating head trauma (Tables S1 and S2), 24% identified as nonreligious and 76% self-identified as religious. Functional connectivity between lesion locations in this independent dataset (N = 105) and the PAG hub of our spirituality circuit (defined using our neurosurgical dataset) was significantly associated with whether subjects self-identified as nonreligious or religious (p < .01). Circuit damage scores for damage caused by lesions in this independent dataset (N = 105) to the spirituality circuit (defined using our neurosurgical dataset) were also significantly associated with self-identification as nonreligious or religious (p < .03). To illustrate this cross-dataset convergence, we show lesion locations from the head trauma dataset overlaid on the spirituality circuit derived from our neurosurgical dataset (Figure 3B).

      Swapping Discovery and Validation Datasets

      Using our head trauma lesion dataset (N = 105) to derive a data-driven lesion network for religiosity, we again found a peak association in the PAG (MNI: x = 3, y = −35, z = −11, uncorrected p < .002) (Figure 3B). The peak association for religiosity in this independent dataset was within 4 mm of the peak association for spirituality (Figure 3A, C). As before, this relationship persisted after controlling for lesion size (p = .003) and was specific to religiosity when controlling for other behavioral measures (p = .003). Functional connectivity between neurosurgical lesion locations (N = 88) and the PAG hub of our religiosity circuit (defined in the independent head trauma dataset) was significantly associated with changes in spiritual acceptance (p < .02). Circuit damage scores for neurosurgical lesion damage to the religiosity circuit was also significantly associated with changes in spiritual acceptance (p < .05) (Figure 3D).

      Voxel-Based Lesion Symptom Mapping

      Using VLSM, no voxels were associated with changes in spiritual acceptance at the uncorrected threshold of p < .001 (matching the peak voxelwise association discovered from lesion network mapping) and no voxels were associated with self-identified religiosity at the uncorrected threshold of p < .002 (matching the peak voxelwise association discovered from lesion network mapping). Using the unthresholded VLSM maps and testing for cross-dataset validation, there was no association between our VLSM map for spirituality and lesion locations associated with religiosity (p = .98) and no association between our VLSM map for religiosity and lesion locations associated with changes in spiritual acceptance (p = .76).

      Robustness to Methodological Changes

      To ensure that our data-driven localization to the PAG was independent of our specific methods, we repeated our lesion network mapping analysis using a connectome processed without global signal regression, in each case looking at the top 1% and 5% of voxels rather than just the peak association. Results were robust to these processing changes, again identifying a brain circuit for spirituality and religiosity centered on the PAG (Figure 4).

      Characterization of PAG Functional Connectivity Network

      Our spirituality circuit (defined by functional connectivity to the PAG) includes positive connectivity to subcortical and limbic regions and negative connectivity to frontoparietal networks and cortical regions previously implicated in reasoning (for peak coordinates, see Table S3; for overlap images, see Figure S1).

      Alignment With Previous Literature on Hyper-religiosity

      Our systematic literature search identified four case reports of lesions associated with hyper-religiosity (Figure S2 and Table S4). Each lesion location intersected negative nodes of our brain circuit, similar to lesions from our initial datasets associated with increased spirituality or religiosity (Figure 5A–D). Exploratory analyses of brain regions linked to seizure-induced hyper-religiosity also align well with our circuit (Figure 5E).

      Relationship to Lesions Associated With Other Neurologic or Psychiatric Symptoms

      Finally, in our examination of 356 lesion locations associated with a range of other neurologic and psychiatric symptoms, we found that lesion locations associated with certain symptoms intersected our spirituality circuit more so than others (one-way analysis of variance, F11 = 6.1, p = 10−8) (Figure 6). Specifically, lesions causing parkinsonism (t28 = 2.7, p = .01, 95% CI, 243 to 1668) intersected positive areas of our circuit, similar to lesions associated with decreased spirituality (Figure 6). Lesions causing delusions (t14 = −4.4, p = .001, 95% CI, −3667 to −1253) and alien limb syndrome (t49 = −3.5, p = .001, 95% CI, −1320 to −352) intersected negative regions on our map, similar to lesion locations associated with increased spirituality and religiosity (Figure 6).

      Discussion

      Brain lesions associated with changes in spiritual acceptance map to a functionally connected brain circuit centered on the PAG. Intersection of lesion locations with this spirituality circuit was associated with self-reported religiosity in an independent dataset, intersected previous case reports of hyper-religiosity, and intersected lesion locations associated with delusions and alien limb syndrome.
      Our finding that spirituality and religiosity map better to a functionally connected brain circuit than an individual brain region is consistent with recent results across a range of complex human behaviors (
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ,
      • Darby R.R.
      • Horn A.
      • Cushman F.
      • Fox M.D.
      Lesion network localization of criminal behavior.
      ,
      • Boes A.D.
      • Prasad S.
      • Liu H.
      • Liu Q.
      • Pascual-Leone A.
      • Caviness Jr., V.S.
      • Fox M.D.
      Network localization of neurological symptoms from focal brain lesions.
      ,
      • Darby R.R.
      • Joutsa J.
      • Burke M.J.
      • Fox M.D.
      Lesion network localization of free will.
      ) and may help explain why previous studies have implicated multiple different brain regions (
      • Hackett C.
      • Stonawski M.
      • McClendon D.
      The Changing Global Religious Landscape.
      ,
      • Ferguson M.A.
      • Nielsen J.A.
      • King J.B.
      • Dai L.
      • Giangrasso D.M.
      • Holman R.
      • et al.
      Reward, salience, and attentional networks are activated by religious experience in devout Mormons.
      ,
      • Beauregard M.
      • Paquette V.
      Neural correlates of a mystical experience in Carmelite nuns.
      ,
      • Grafman J.
      • Cristofori I.
      • Zhong W.
      • Bulbulia J.
      The neural basis of religious cognition.
      ,
      • Kapogiannis D.
      • Barbey A.K.
      • Su M.
      • Zamboni G.
      • Krueger F.
      • Grafman J.
      Cognitive and neural foundations of religious belief.
      ). Our spirituality circuit is defined by connectivity to one focal brain region (the PAG), similar to previous work identifying a memory circuit defined by connectivity to the subiculum or a depression circuit defined by connectivity to the left dorsal lateral prefrontal cortex (
      • Ferguson M.A.
      • Lim C.
      • Cooke D.
      • Darby R.R.
      • Wu O.
      • Rost N.S.
      • et al.
      A human memory circuit derived from brain lesions causing amnesia.
      ,
      • Padmanabhan J.L.
      • Cooke D.
      • Joutsa J.
      • Siddiqi S.H.
      • Ferguson M.A.
      • Darby R.R.
      • et al.
      A human depression circuit derived from focal brain lesions.
      ). In each case, lesion locations disrupting the behavior map to a brain circuit, but the circuit is defined by connectivity to one specific brain region that may play a critical role in mediating the behavior.
      The PAG has been implicated in numerous functions including fear conditioning (
      • Kim J.J.
      • Rison R.A.
      • Fanselow M.S.
      Effects of amygdala, hippocampus, and periaqueductal gray lesions on short- and long-term contextual fear.
      ), pain modulation (
      • Hosobuchi Y.
      Dorsal periaqueductal gray-matter stimulation in humans.
      ), altruistic behaviors (
      • Linnman C.
      • Moulton E.A.
      • Barmettler G.
      • Becerra L.
      • Borsook D.
      Neuroimaging of the periaqueductal gray: State of the field.
      ), and unconditional love (
      • Beauregard M.
      • Courtemanche J.
      • Paquette V.
      • St-Pierre E.L.
      The neural basis of unconditional love.
      ). It is anatomically connected to both the limbic system and prefrontal cortex (
      • Linnman C.
      • Moulton E.A.
      • Barmettler G.
      • Becerra L.
      • Borsook D.
      Neuroimaging of the periaqueductal gray: State of the field.
      ) and enriched in receptors implicated in pain regulation (e.g., mu-opioid) and pair bonding (e.g., oxytocin) (
      • Linnman C.
      • Moulton E.A.
      • Barmettler G.
      • Becerra L.
      • Borsook D.
      Neuroimaging of the periaqueductal gray: State of the field.
      ,
      • Jenkins J.S.
      • Ang V.T.
      • Hawthorn J.
      • Rossor M.N.
      • Iversen L.L.
      Vasopressin, oxytocin and neurophysins in the human brain and spinal cord.
      ,
      • Back F.P.
      • Carobrez A.P.
      Periaqueductal gray glutamatergic, cannabinoid and vanilloid receptor interplay in defensive behavior and aversive memory formation.
      ). Although speculative, these classic PAG functions may align with aspects of spirituality and religiosity. For example, religiosity increases under threat or after natural disasters (
      • Koenig H.G.
      In the Wake of Disaster: Religious Responses to Terrorism and Catastrophe.
      ), consistent with the role of the PAG in fear conditioning (
      • Kim J.J.
      • Rison R.A.
      • Fanselow M.S.
      Effects of amygdala, hippocampus, and periaqueductal gray lesions on short- and long-term contextual fear.
      ). Spirituality can alleviate pain and augment placebo (
      • Kohls N.
      • Sauer S.
      • Offenbächer M.
      • Giordano J.
      Spirituality: An overlooked predictor of placebo effects?.
      ), consistent with the role of the PAG in opiate and nonopiate analgesia (
      • Hosobuchi Y.
      Dorsal periaqueductal gray-matter stimulation in humans.
      ,
      • Silva C.
      • McNaughton N.
      Are periaqueductal gray and dorsal raphe the foundation of appetitive and aversive control? A comprehensive review.
      ). Finally, spirituality and religiosity have been linked to, if not equated with, unconditional love (
      • Goleman D.
      Healing Emotions: Conversations With the Dalai Lama on Mindfulness, Emotions, and Health.
      ,
      • Pope Benedict X.V.I.
      God Is Love--Deus Caritas Est: Encyclical Letter.
      ), consistent with the role of the PAG in maternal and pair bonding (
      • Beauregard M.
      • Courtemanche J.
      • Paquette V.
      • St-Pierre E.L.
      The neural basis of unconditional love.
      ,
      • Acevedo B.P.
      • Aron A.
      • Fisher H.E.
      • Brown L.L.
      Neural correlates of long-term intense romantic love.
      ,
      • Bartels A.
      • Zeki S.
      The neural basis of romantic love.
      ,
      • Bartels A.
      • Zeki S.
      The neural correlates of maternal and romantic love.
      ,
      • Cacioppo S.
      • Bianchi-Demicheli F.
      • Frum C.
      • Pfaus J.G.
      • Lewis J.W.
      The common neural bases between sexual desire and love: A multilevel kernel density fMRI analysis.
      ,
      • Diamond L.M.
      • Dickenson J.A.
      The neuroimaging of love and desire: Review and future directions.
      ,
      • Stoléru S.
      • Fonteille V.
      • Cornélis C.
      • Joyal C.
      • Moulier V.
      Functional neuroimaging studies of sexual arousal and orgasm in healthy men and women: A review and meta-analysis.
      ), unconditional love (
      • Beauregard M.
      • Courtemanche J.
      • Paquette V.
      • St-Pierre E.L.
      The neural basis of unconditional love.
      ), maternal love (
      • Noriuchi M.
      • Kikuchi Y.
      • Senoo A.
      The functional neuroanatomy of maternal love: Mother’s response to infant’s attachment behaviors.
      ), nonsexual love (
      • Diamond L.M.
      • Dickenson J.A.
      The neuroimaging of love and desire: Review and future directions.
      ), compassion (
      • Kim J.J.
      • Cunnington R.
      • Kirby J.N.
      The neurophysiological basis of compassion: An fMRI meta-analysis of compassion and its related neural processes.
      ), and the duration of long-term relationships (
      • Acevedo B.P.
      • Aron A.
      • Fisher H.E.
      • Brown L.L.
      Neural correlates of long-term intense romantic love.
      ). These findings of shared brain circuitry for spiritual acceptance and altruism are also convergent with the hypothesis that spiritual beliefs facilitated the expansion of prosociality over the course of human evolution (
      • Purzycki B.G.
      • Apicella C.
      • Atkinson Q.D.
      • Cohen E.
      • McNamara R.A.
      • Willard A.K.
      • et al.
      Moralistic gods, supernatural punishment and the expansion of human sociality.
      ). Therefore, although the PAG was not an a priori region of interest before our study, it has been implicated in many functions that could be relevant for spirituality and religiosity.
      Notably, the negative functional topography in our PAG-defined circuit for spirituality and religiosity aligns with the frontoparietal control network (
      • Yeo B.T.T.
      • Krienen F.M.
      • Sepulcre J.
      • Sabuncu M.R.
      • Lashkari D.
      • Hollinshead M.
      • et al.
      The organization of the human cerebral cortex estimated by intrinsic functional connectivity.
      ), previously implicated in executive control, as well as brain regions previously implicated in neuroimaging studies of reasoning (Figure S1). This result is consistent with previous work suggesting that spiritual acceptance is the opposite of rational materialism (
      • Cloninger C.R.
      • Svrakic D.M.
      • Przybeck T.R.
      A psychobiological model of temperament and character.
      ,
      • Garcia-Romeu A.
      Self-transcendence as a measurable transpersonal construct.
      ) and previous work suggesting that negatively correlated brain networks represent opposing functions (
      • Fox M.D.
      • Snyder A.Z.
      • Vincent J.L.
      • Corbetta M.
      • Van Essen D.C.
      • Raichle M.E.
      The human brain is intrinsically organized into dynamic, anticorrelated functional networks.
      ).
      Medically, hyper-religiosity has been noted after focal brain lesions and in patients with mesial temporal lobe epilepsy for many decades (
      • Waxman S.G.
      • Geschwind N.
      The interictal behavior syndrome of temporal lobe epilepsy.
      ,
      • Geschwind N.
      Behavioural changes in temporal lobe epilepsy1.
      ,
      • Ogata A.
      • Miyakawa T.
      Religious experiences in epileptic patients with a focus on ictus-related episodes.
      ,
      • Devinsky O.
      • Lai G.
      Spirituality and religion in epilepsy.
      ). Lesion locations in these case reports align well with our spirituality circuit. It remains unclear whether seizure onset zones associated with hyper-religiosity align with our circuit and whether hyper-religiosity is driven by regional hyperactivity during seizures or hypoactivity between seizures (
      • Devinsky O.
      • Lai G.
      Spirituality and religion in epilepsy.
      ). Our exploratory results support the former, as atrophy locations associated with hyper-religiosity intersect positive nodes of our spirituality circuit, while lesions associated with hyper-religiosity intersect negative nodes (
      • Wuerfel J.
      • Krishnamoorthy E.S.
      • Brown R.J.
      • Lemieux L.
      • Koepp M.
      • Tebartz van Elst L.
      • Trimble M.R.
      Religiosity is associated with hippocampal but not amygdala volumes in patients with refractory epilepsy.
      ) (Figure 5). The fact that hyper-religiosity can resolve after resection of the medial temporal lobe further supports this finding (
      • Devinsky O.
      • Lai G.
      Spirituality and religion in epilepsy.
      ). Whether seizure propagation to the PAG is related to hyper-religiosity is a testable hypothesis for future work but is potentially consistent with brainstem propagation of mesial temporal seizures (
      • Blumenfeld H.
      • McNally K.A.
      • Vanderhill S.D.
      • Paige A.L.
      • Chung R.
      • Davis K.
      • et al.
      Positive and negative network correlations in temporal lobe epilepsy.
      ,
      • Blumenfeld H.
      • Varghese G.I.
      • Purcaro M.J.
      • Motelow J.E.
      • Enev M.
      • McNally K.A.
      • et al.
      Cortical and subcortical networks in human secondarily generalized tonic-clonic seizures.
      ) and atrophy of the PAG in patients with mesial temporal lobe epilepsy (
      • Mueller S.G.
      • Bateman L.M.
      • Laxer K.D.
      Evidence for brainstem network disruption in temporal lobe epilepsy and sudden unexplained death in epilepsy.
      ).
      We also examined our database of lesions associated with neurologic and psychiatric symptoms to see which, if any, of these symptoms share neuroanatomy with spirituality. Similarities between lesions associated with delusions and increased spirituality suggest a shared neural substrate, potentially consistent with shared features such as strongly held fixed beliefs or the occurrence of religious content in patients with delusions (
      • Bell V.
      • Raihani N.
      • Wilkinson S.
      Derationalizing delusions.
      ,
      • Bronstein M.V.
      • Pennycook G.
      • Joormann J.
      • Corlett P.R.
      • Cannon T.D.
      Dual-process theory, conflict processing, and delusional belief.
      ,
      • Kraepelin E.
      Dementia Praecox and Paraphrenia.
      ,
      • Kraepelin E.
      Manic depressive insanity and paranoia.
      ). Our data also suggest a shared neural substrate between spirituality and alien limb phenomenon, both of which can be associated with feelings of control by an external agent (
      • Darby R.R.
      • Joutsa J.
      • Burke M.J.
      • Fox M.D.
      Lesion network localization of free will.
      ,
      • Taves A.
      Revelatory Events: Three Case Studies of the Emergence of New Spiritual Paths.
      ). This relationship may have clinical value, such as surrendering to a higher power in the context of addiction treatment (
      • Cole B.
      • Pargament K.
      Spiritual surrender: A paradoxical path to control.
      ,
      • Miller W.R.
      • Thoresen C.E.
      Spirituality, religion, and health. An emerging research field.
      ). Finally, our results suggest an inverse association between spirituality and lesions associated with parkinsonism, potentially consistent with decreased religiosity in patients with Parkinson’s disease (
      • McNamara P.
      • Durso R.
      • Brown A.
      Religiosity in patients with Parkinson’s disease.
      ,
      • Butler P.M.
      • McNamara P.
      • Durso R.
      Deficits in the automatic activation of religious concepts in patients with Parkinson’s disease.
      ).
      It is important to note that a shared neural substrate between two phenomena may be helpful for understanding shared features and associations, but these results should not be overinterpreted. For example, our results do not imply that religion is a delusion, that historical religious figures suffered from alien limb syndrome, or that Parkinson’s disease arises due to a lack of religious faith. Similarly, our results have no bearing on the truth of any particular religious or spiritual belief.
      There are several limitations in the current study. First, participants in both our spirituality and religiosity datasets came from predominantly Christian cultures, which may limit generalizability to other cultures and religious traditions, and our assessment of religiosity in our head trauma dataset was limited to a single yes/no question, which does not capture the wide variety of religious beliefs, behaviors, or contributing factors such as exposure to religiosity during their youth. Second, our religiosity dataset was mostly Caucasian, older males, which may not generalize to other races, ages, or genders. Third, we investigated spirituality and religiosity as single behaviors, but different aspects of spirituality and religiosity may map to different brain circuits, an important topic for future work (
      • Grafman J.
      • Cristofori I.
      • Zhong W.
      • Bulbulia J.
      The neural basis of religious cognition.
      ,
      • Kapogiannis D.
      • Barbey A.K.
      • Su M.
      • Zamboni G.
      • Krueger F.
      • Grafman J.
      Cognitive and neural foundations of religious belief.
      ). Fourth, our localization of spirituality and religiosity to a brain circuit centered on the PAG was a post hoc discovery in the neurosurgical dataset (N = 88), which did not survive correction for multiple comparisons across all brain voxels; however, this limitation is largely mitigated by validation and replication of this finding in a second independent dataset (head trauma dataset, N = 105), in which the PAG circuit from the neurosurgical dataset was used as an a priori hypothesis. Relatedly, the lesions that we studied do not directly intersect with the PAG, and PAG involvement is inferred from connectivity to lesion rather than from direct lesion location. Additionally, our lesion networks explain only a small amount of behavioral variance, and there are undoubtedly many other factors contributing to these complex behaviors. Finally, the function of the PAG is based largely on animal studies, and any relationship between these functions and features of religiosity and spirituality should be considered speculative.
      Our data provide several testable hypotheses for future work. First, we hypothesize that intersection of neurosurgical lesions with our PAG circuit will explain variance in spirituality or religiosity measured before and after intervention (as in the neurosurgical dataset). Second, we hypothesize that intersection of stroke lesions with our PAG circuit will be associated with measures of spirituality and religiosity assessed after the lesion (as in the head trauma dataset). Finally, we hypothesize that intersection of seizure onset zones with our PAG circuit will be associated with the presence or absence of seizure-induced hyper-religiosity.
      In conclusion, our study demonstrates that lesions associated with spirituality and religiosity map to a human brain circuit defined by connectivity to the PAG. This brain circuit aligns with lesion locations from previous case reports of hyper-religiosity and with lesion locations previously associated with strongly held fixed beliefs and feelings of control by an external agent.

      Acknowledgments and Disclosures

      This work was supported by was supported by an National Institutes of Health Ruth L. Kirschstein National Research Service Award Institutional Research Training Grant (Grant No. T32MH112510 [to AC]) and the Shields Research Grant from the Child Neurology Foundation (to AC); the Sidney R. Baer, Jr. Foundation, the Nancy Lurie Marks Foundation, the Mather’s Foundation, the Kaye Family Research Endowment , and the National Institutes of Health (Grant Nos. R01 MH113929 , R01 MH115949 , and R01 AG060987 [to MDF]). None of the funding agencies had a role in the design and conduct of the study, in the collection, management, analysis and interpretation of the data, in the preparation, review or approval of the manuscript, nor in the decision to submit the manuscript for publication.
      MAF and MDF conceptualized and designed the work. MAF, AC, SS, and MDF designed and developed methods. MAF, AC, and SS contributed to programming, software development, and implementation of computer code. MAF performed validation and formal analysis. JG, CU, and FF conducted data collection. MAF, FLWVJS, and SMM contributed to data curation. MAF prepared the original draft. MAF, FLWVJS, AC, SS, SMM, JAN, JG, CU, FF, and MDF reviewed and edited. MAF visualized data and prepared data presentation. MDF supervised research planning and execution. MAF and MDF coordinated project administration. AC and MDF acquired financial support for the project leading to this publication.
      Data, code, and materials used in the analysis are available upon reasonable request.
      The authors report no biomedical financial interests or potential conflicts of interest.

      Supplementary Material

      References

        • Atran S.
        Gods We Trust: The Evolutionary Landscape of Religion.
        Oxford University Press, Oxford2002
        • Dawkins R.
        • Ward L.
        The God Delusion.
        Houghton Mifflin Company, Boston2006
        • Durkheim E.
        • Swain J.W.
        The Elementary Forms of the Religious Life.
        Dover Publications, Mineola2008
        • Freud S.
        Civilization and Its Discontents.
        Broadview Press, Peterborough2015
        • Laine J.W.
        Meta-Religion: Religion and Power in World History.
        University of California Press, Oakland2014
        • Hackett C.
        • Stonawski M.
        • McClendon D.
        The Changing Global Religious Landscape.
        Pew Research Centre, Washington, D.C.2017
        • Cloninger C.R.
        • Svrakic D.M.
        • Przybeck T.R.
        A psychobiological model of temperament and character.
        Arch Gen Psychiatry. 1993; 50: 975-990
        • Garcia-Romeu A.
        Self-transcendence as a measurable transpersonal construct.
        J Transpers Psychol. 2010; 42: 26
        • Cohen-Zimerman S.
        • Cristofori I.
        • Zhong W.
        • Bulbulia J.
        • Krueger F.
        • Gordon B.
        • Grafman J.
        Neural underpinning of a personal relationship with God and sense of control: A lesion-mapping study.
        Cogn Affect Behav Neurosci. 2020; 20: 575-587
        • Borg J.
        • Andrée B.
        • Soderstrom H.
        • Farde L.
        The serotonin system and spiritual experiences.
        Am J Psychiatry. 2003; 160: 1965-1969
        • Comings D.E.
        • Gonzales N.
        • Saucier G.
        • Johnson J.P.
        • MacMurray J.P.
        The DRD4 gene and the spiritual transcendence scale of the character temperament index.
        Psychiatr Genet. 2000; 10: 185-189
        • Lorenzi C.
        • Serretti A.
        • Mandelli L.
        • Tubazio V.
        • Ploia C.
        • Smeraldi E.
        5-HT1A polymorphism and self-transcendence in mood disorders.
        Am J Med Genet B Neuropsychiatr Genet. 2005; 137B: 33-35
        • Nilsson K.W.
        • Damberg M.
        • Ohrvik J.
        • Leppert J.
        • Lindström L.
        • Anckarsäter H.
        • Oreland L.
        Genes encoding for AP-2beta and the serotonin transporter are associated with the Personality Character Spiritual Acceptance.
        Neurosci Lett. 2007; 411: 233-237
        • Ferguson M.A.
        • Nielsen J.A.
        • King J.B.
        • Dai L.
        • Giangrasso D.M.
        • Holman R.
        • et al.
        Reward, salience, and attentional networks are activated by religious experience in devout Mormons.
        Soc Neurosci. 2018; 13: 104-116
        • Beauregard M.
        • Paquette V.
        Neural correlates of a mystical experience in Carmelite nuns.
        Neurosci Lett. 2006; 405: 186-190
        • Rim J.I.
        • Ojeda J.C.
        • Svob C.
        • Kayser J.
        • Drews E.
        • Kim Y.
        • et al.
        Current understanding of religion, spirituality, and their neurobiological correlates.
        Harv Rev Psychiatry. 2019; 27: 303-316
        • Grafman J.
        • Cristofori I.
        • Zhong W.
        • Bulbulia J.
        The neural basis of religious cognition.
        Curr Dir Psychol Sci. 2020; 29: 126-133
        • Waxman S.G.
        • Geschwind N.
        The interictal behavior syndrome of temporal lobe epilepsy.
        Arch Gen Psychiatry. 1975; 32: 1580-1586
        • Geschwind N.
        Behavioural changes in temporal lobe epilepsy1.
        Psychol Med. 1979; 9: 217-219
        • Ogata A.
        • Miyakawa T.
        Religious experiences in epileptic patients with a focus on ictus-related episodes.
        Psychiatry Clin Neurosci. 1998; 52: 321-325
        • Devinsky O.
        • Lai G.
        Spirituality and religion in epilepsy.
        Epilepsy Behav. 2008; 12: 636-643
        • Urgesi C.
        • Aglioti S.M.
        • Skrap M.
        • Fabbro F.
        The spiritual brain: Selective cortical lesions modulate human self-transcendence.
        Neuron. 2010; 65: 309-319
        • Zhong W.
        • Cristofori I.
        • Bulbulia J.
        • Krueger F.
        • Grafman J.
        Biological and cognitive underpinnings of religious fundamentalism.
        Neuropsychologia. 2017; 100: 18-25
        • Wuerfel J.
        • Krishnamoorthy E.S.
        • Brown R.J.
        • Lemieux L.
        • Koepp M.
        • Tebartz van Elst L.
        • Trimble M.R.
        Religiosity is associated with hippocampal but not amygdala volumes in patients with refractory epilepsy.
        J Neurol Neurosurg Psychiatry. 2004; 75: 640-642
        • Asp E.
        • Ramchandran K.
        • Tranel D.
        Authoritarianism, religious fundamentalism, and the human prefrontal cortex.
        Neuropsychology. 2012; 26: 414-421
        • Fox M.D.
        Mapping symptoms to brain networks with the human connectome.
        N Engl J Med. 2018; 379: 2237-2245
        • Ferguson M.A.
        • Lim C.
        • Cooke D.
        • Darby R.R.
        • Wu O.
        • Rost N.S.
        • et al.
        A human memory circuit derived from brain lesions causing amnesia.
        Nat Commun. 2019; 10: 3497
        • Darby R.R.
        • Horn A.
        • Cushman F.
        • Fox M.D.
        Lesion network localization of criminal behavior.
        Proc Natl Acad Sci U S A. 2018; 115: 601-606
        • Boes A.D.
        • Prasad S.
        • Liu H.
        • Liu Q.
        • Pascual-Leone A.
        • Caviness Jr., V.S.
        • Fox M.D.
        Network localization of neurological symptoms from focal brain lesions.
        Brain. 2015; 138: 3061-3075
        • Darby R.R.
        • Joutsa J.
        • Burke M.J.
        • Fox M.D.
        Lesion network localization of free will.
        Proc Natl Acad Sci U S A. 2018; 115: 10792-10797
        • Yeo B.T.T.
        • Krienen F.M.
        • Sepulcre J.
        • Sabuncu M.R.
        • Lashkari D.
        • Hollinshead M.
        • et al.
        The organization of the human cerebral cortex estimated by intrinsic functional connectivity.
        J Neurophysiol. 2011; 106: 1125-1165
        • Holmes A.J.
        • Hollinshead M.O.
        • O’Keefe T.M.
        • Petrov V.I.
        • Fariello G.R.
        • Wald L.L.
        • et al.
        Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures.
        Sci Data. 2015; 2: 150031
        • Fox M.D.
        • Snyder A.Z.
        • Vincent J.L.
        • Corbetta M.
        • Van Essen D.C.
        • Raichle M.E.
        The human brain is intrinsically organized into dynamic, anticorrelated functional networks.
        Proc Natl Acad Sci U S A. 2005; 102: 9673-9678
        • Padmanabhan J.L.
        • Cooke D.
        • Joutsa J.
        • Siddiqi S.H.
        • Ferguson M.A.
        • Darby R.R.
        • et al.
        A human depression circuit derived from focal brain lesions.
        Biol Psychiatry. 2019; 86: 749-758
        • Raymont V.
        • Salazar A.M.
        • Krueger F.
        • Grafman J.
        “Studying injured minds” - The Vietnam head injury study and 40 years of brain injury research.
        Front Neurol. 2011; 2: 15
        • Snider S.B.
        • Hsu J.
        • Darby R.R.
        • Cooke D.
        • Fischer D.
        • Cohen A.L.
        • et al.
        Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem.
        Hum Brain Mapp. 2020; 41: 1520-1531
        • Cotovio G.
        • Talmasov D.
        • Barahona-Corrêa J.B.
        • Hsu J.
        • Senova S.
        • Ribeiro R.
        • et al.
        Mapping mania symptoms based on focal brain damage.
        J Clin Invest. 2020; 130: 5209-5222
        • Bell V.
        • Raihani N.
        • Wilkinson S.
        Derationalizing delusions.
        Clin Psychol Sci. 2021; 9: 24-37
        • Bronstein M.V.
        • Pennycook G.
        • Joormann J.
        • Corlett P.R.
        • Cannon T.D.
        Dual-process theory, conflict processing, and delusional belief.
        Clin Psychol Rev. 2019; 72: 101748
        • Fasano A.
        • Laganiere S.E.
        • Lam S.
        • Fox M.D.
        Lesions causing freezing of gait localize to a cerebellar functional network.
        Ann Neurol. 2017; 81: 129-141
        • Kim N.Y.
        • Hsu J.
        • Talmasov D.
        • Joutsa J.
        • Soussand L.
        • Wu O.
        • et al.
        Lesions causing hallucinations localize to one common brain network.
        Mol Psychiatry. 2021; 26: 1299-1309
        • Joutsa J.
        • Horn A.
        • Hsu J.
        • Fox M.D.
        Localizing parkinsonism based on focal brain lesions.
        Brain. 2018; 141: 2445-2456
        • Kapogiannis D.
        • Barbey A.K.
        • Su M.
        • Zamboni G.
        • Krueger F.
        • Grafman J.
        Cognitive and neural foundations of religious belief.
        Proc Natl Acad Sci U S A. 2009; 106: 4876-4881
        • Kim J.J.
        • Rison R.A.
        • Fanselow M.S.
        Effects of amygdala, hippocampus, and periaqueductal gray lesions on short- and long-term contextual fear.
        Behav Neurosci. 1993; 107: 1093-1098
        • Hosobuchi Y.
        Dorsal periaqueductal gray-matter stimulation in humans.
        Pacing Clin Electrophysiol. 1987; 10: 213-216
        • Linnman C.
        • Moulton E.A.
        • Barmettler G.
        • Becerra L.
        • Borsook D.
        Neuroimaging of the periaqueductal gray: State of the field.
        Neuroimage. 2012; 60: 505-522
        • Beauregard M.
        • Courtemanche J.
        • Paquette V.
        • St-Pierre E.L.
        The neural basis of unconditional love.
        Psychiatry Res. 2009; 172: 93-98
        • Jenkins J.S.
        • Ang V.T.
        • Hawthorn J.
        • Rossor M.N.
        • Iversen L.L.
        Vasopressin, oxytocin and neurophysins in the human brain and spinal cord.
        Brain Res. 1984; 291: 111-117
        • Back F.P.
        • Carobrez A.P.
        Periaqueductal gray glutamatergic, cannabinoid and vanilloid receptor interplay in defensive behavior and aversive memory formation.
        Neuropharmacology. 2018; 135: 399-411
        • Koenig H.G.
        In the Wake of Disaster: Religious Responses to Terrorism and Catastrophe.
        Templeton Foundation Press, West Conshohocken2006
        • Kohls N.
        • Sauer S.
        • Offenbächer M.
        • Giordano J.
        Spirituality: An overlooked predictor of placebo effects?.
        Philos Trans R Soc Lond B Biol Sci. 2011; 366: 1838-1848
        • Silva C.
        • McNaughton N.
        Are periaqueductal gray and dorsal raphe the foundation of appetitive and aversive control? A comprehensive review.
        Prog Neurobiol. 2019; 177: 33-72
        • Goleman D.
        Healing Emotions: Conversations With the Dalai Lama on Mindfulness, Emotions, and Health.
        Shambhala Publications, Boston2003
        • Pope Benedict X.V.I.
        God Is Love--Deus Caritas Est: Encyclical Letter.
        USCCB Publishing, Washington, D.C.2006
        • Acevedo B.P.
        • Aron A.
        • Fisher H.E.
        • Brown L.L.
        Neural correlates of long-term intense romantic love.
        Soc Cogn Affect Neurosci. 2012; 7: 145-159
        • Bartels A.
        • Zeki S.
        The neural basis of romantic love.
        Neuroreport. 2000; 11: 3829-3834
        • Bartels A.
        • Zeki S.
        The neural correlates of maternal and romantic love.
        NeuroImage. 2004; 21: 1155-1166
        • Cacioppo S.
        • Bianchi-Demicheli F.
        • Frum C.
        • Pfaus J.G.
        • Lewis J.W.
        The common neural bases between sexual desire and love: A multilevel kernel density fMRI analysis.
        J Sex Med. 2012; 9: 1048-1054
        • Diamond L.M.
        • Dickenson J.A.
        The neuroimaging of love and desire: Review and future directions.
        Clin Neuropsychiatry. 2012; 9: 39-46
        • Stoléru S.
        • Fonteille V.
        • Cornélis C.
        • Joyal C.
        • Moulier V.
        Functional neuroimaging studies of sexual arousal and orgasm in healthy men and women: A review and meta-analysis.
        Neurosci Biobehav Rev. 2012; 36: 1481-1509
        • Noriuchi M.
        • Kikuchi Y.
        • Senoo A.
        The functional neuroanatomy of maternal love: Mother’s response to infant’s attachment behaviors.
        Biol Psychiatry. 2008; 63: 415-423
        • Kim J.J.
        • Cunnington R.
        • Kirby J.N.
        The neurophysiological basis of compassion: An fMRI meta-analysis of compassion and its related neural processes.
        Neurosci Biobehav Rev. 2020; 108: 112-123
        • Purzycki B.G.
        • Apicella C.
        • Atkinson Q.D.
        • Cohen E.
        • McNamara R.A.
        • Willard A.K.
        • et al.
        Moralistic gods, supernatural punishment and the expansion of human sociality.
        Nature. 2016; 530: 327-330
        • Blumenfeld H.
        • McNally K.A.
        • Vanderhill S.D.
        • Paige A.L.
        • Chung R.
        • Davis K.
        • et al.
        Positive and negative network correlations in temporal lobe epilepsy.
        Cereb Cortex. 2004; 14: 892-902
        • Blumenfeld H.
        • Varghese G.I.
        • Purcaro M.J.
        • Motelow J.E.
        • Enev M.
        • McNally K.A.
        • et al.
        Cortical and subcortical networks in human secondarily generalized tonic-clonic seizures.
        Brain. 2009; 132: 999-1012
        • Mueller S.G.
        • Bateman L.M.
        • Laxer K.D.
        Evidence for brainstem network disruption in temporal lobe epilepsy and sudden unexplained death in epilepsy.
        Neuroimage Clin. 2014; 5: 208-216
        • Kraepelin E.
        Dementia Praecox and Paraphrenia.
        Livingstone, London1919
        • Kraepelin E.
        Manic depressive insanity and paranoia.
        J Nerv Ment Dis. 1921; 53: 350
        • Taves A.
        Revelatory Events: Three Case Studies of the Emergence of New Spiritual Paths.
        Princeton University Press, Princeton2016
        • Cole B.
        • Pargament K.
        Spiritual surrender: A paradoxical path to control.
        in: Miller W.R. Integrating Spirituality Into Treatment: Resources for Practitioners. American Psychological Association, Washington, D.C.1999: 179-198
        • Miller W.R.
        • Thoresen C.E.
        Spirituality, religion, and health. An emerging research field.
        Am Psychol. 2003; 58: 24-35
        • McNamara P.
        • Durso R.
        • Brown A.
        Religiosity in patients with Parkinson’s disease.
        Neuropsychiatr Dis Treat. 2006; 2: 341-348
        • Butler P.M.
        • McNamara P.
        • Durso R.
        Deficits in the automatic activation of religious concepts in patients with Parkinson’s disease.
        J Int Neuropsychol Soc. 2010; 16: 252-261