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Neural effects of controllability as a key dimension of stress exposure

Published online by Cambridge University Press:  17 January 2022

Emily M. Cohodes Open the ORCID record for Emily M. Cohodes [Opens in a new window] ,
Paola Odriozola ,
Jeffrey D. Mandell ,
Camila Caballero ,
Sarah McCauley ,
Sadie J. Zacharek ,
H. R. Hodges ,
Jason T. Haberman ,
Mackenzye Smith  and
Janeen Thomas
...Show all authors
Emily M. Cohodes
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Paola Odriozola
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Jeffrey D. Mandell
Affiliation:
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
Camila Caballero
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Sarah McCauley
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Sadie J. Zacharek
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
H. R. Hodges
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Jason T. Haberman
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Mackenzye Smith
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Janeen Thomas
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Olivia C. Meisner
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Cameron T. Ellis
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Catherine A. Hartley
Affiliation:
Department of Psychology, New York University, New York, NY, USA
Dylan G. Gee*
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
*
Corresponding author: Dylan G. Gee, email: dylan.gee@yale.edu
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Abstract

Cross-species evidence suggests that the ability to exert control over a stressor is a key dimension of stress exposure that may sensitize frontostriatal-amygdala circuitry to promote more adaptive responses to subsequent stressors. The present study examined neural correlates of stressor controllability in young adults. Participants (N = 56; M age = 23.74, range = 18–30 years) completed either the controllable or uncontrollable stress condition of the first of two novel stressor controllability tasks during functional magnetic resonance imaging (fMRI) acquisition. Participants in the uncontrollable stress condition were yoked to age- and sex-matched participants in the controllable stress condition. All participants were subsequently exposed to uncontrollable stress in the second task, which is the focus of fMRI analyses reported here. A whole-brain searchlight classification analysis revealed that patterns of activity in the right dorsal anterior insula (dAI) during subsequent exposure to uncontrollable stress could be used to classify participants' initial exposure to either controllable or uncontrollable stress with a peak of 73% accuracy. Previous experience of exerting control over a stressor may change the computations performed within the right dAI during subsequent stress exposure, shedding further light on the neural underpinnings of stressor controllability.

Keywords

controlfrontolimbic circuitrystress reactivitystressstressor controllability
Type
Regular Article
Information
Development and Psychopathology , Volume 35 , Issue 1 , February 2023 , pp. 218 - 227
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Copyright
© The Author(s), 2022. Published by Cambridge University Press

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References

Alvarez, R. P., Kirlic, N., Misaki, M., Bodurka, J., Rhudy, J. L., Paulus, M. P.…Drevets, W. C. (2015). Increased anterior insula activity in anxious individuals is linked to diminished perceived control. Translational Psychiatry, 5(6), e591–e591. https://doi.org/10.1038/tp.2015.84 CrossRefGoogle ScholarPubMed
Amat, J., Aleksejev, R. M., Paul, E., Watkins, L. R., & Maier, S. F. (2010). Behavioral control over shock blocks behavioral and neurochemical effects of later social defeat. Neuroscience, 165(4), 1031–1038. https://doi.org/10.1016/j.neuroscience.2009.11.005 CrossRefGoogle ScholarPubMed
Amat, J., Matus-Amat, P., Watkins, L. R., & Maier, S. F. (1998). Escapable and inescapable stress differentially alter extracellular levels of 5-HT in the basolateral amygdala of the rat. Brain Research, 812(1), 113–120. https://doi.org/10.1016/S0006-8993(98)00960-3 CrossRefGoogle ScholarPubMed
Amat, J., Paul, E., Watkins, L. R., & Maier, S. F. (2008). Activation of the ventral medial prefrontal cortex during an uncontrollable stressor reproduces both the immediate and long-term protective effects of behavioral control. Neuroscience, 154(4), 1178–1186. https://doi.org/10.1016/j.neuroscience.2008.04.005 CrossRefGoogle ScholarPubMed
Amat, J., Paul, E., Zarza, C., Watkins, L. R., & Maier, S. F. (2006). Previous experience with behavioral control over stress blocks the behavioral and dorsal raphe nucleus activating effects of later uncontrollable stress: Role of the ventral medial prefrontal cortex. Journal of Neuroscience, 26(51), 13264–13272. https://doi.org/10.1523/JNEUROSCI.3630-06.2006 CrossRefGoogle ScholarPubMed
Baratta, M. V., & Maier, S. F. (2017). New tools for understanding coping and resilience. Neuroscience Letters, 693, 54–57. https://doi.org/10.1016/j.neulet.2017.09.049 CrossRefGoogle ScholarPubMed
Baratta, M. V., Zarza, C. M., Gomez, D. M., Campeau, S., Watkins, L. R., & Maier, S. F. (2009). Selective activation of dorsal raphe nucleus-projecting neurons in the ventral medial prefrontal cortex by controllable stress. European Journal of Neuroscience, 30(6), 1111–1116. https://doi.org/10.1111/j.1460-9568.2009.06867.x CrossRefGoogle ScholarPubMed
Bhanji, J. P., & Delgado, M. R. (2014). Perceived control influences neural responses to setbacks and promotes persistence. Neuron, 83(6), 1369–1375. https://doi.org/10.1016/j.neuron.2014.08.012 CrossRefGoogle ScholarPubMed
Blakemore, S.-J., & Mills, K. L. (2014). Is adolescence a sensitive period for sociocultural processing? Annual Review of Psychology, 65(1), 187–207. https://doi.org/10.1146/annurev-psych-010213-115202 CrossRefGoogle ScholarPubMed
Boeke, E. A., Moscarello, J. M., LeDoux, J. E., Phelps, E. A., & Hartley, C. A. (2017). Active avoidance: Neural mechanisms and attenuation of Pavlovian conditioned responding. The Journal of Neuroscience, 37(18), 4808–4818. https://doi.org/10.1523/JNEUROSCI.3261-16.2017 CrossRefGoogle ScholarPubMed
Boyce, W. T. (2007). A biology of misfortune: Stress reactivity, social context, and the ontogeny of psychopathology in early life. In A. S. Masten (Ed.), Multilevel dynamics in developmental psychopathology: Pathways to the future (pp. 45–82). Taylor & Francis Group/Lawrence Erlbaum Associates.Google Scholar
Bravo-Rivera, C., Roman-Ortiz, C., Montesinos-Cartagena, M., & Quirk, G. J. (2015). Persistent active avoidance correlates with activity in prelimbic cortex and ventral striatum. Frontiers in Behavioral Neuroscience, 9, 184. https://doi.org/10.3389/fnbeh.2015.00184 CrossRefGoogle ScholarPubMed
Brown, T. A., & Barlow, D. H. (2014). Anxiety and related disorders interview schedule for DSM-5 (ADIS-5L). Oxford University Press.Google Scholar
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M.…Garavan, H. (2018). The adolescent brain cognitive development (ABCD) study: Imaging acquisition across 21 sites. Developmental Cognitive Neuroscience, 32, 43–54. https://doi.org/10.1016/j.dcn.2018.03.001 CrossRefGoogle ScholarPubMed
Casey, B. J., Heller, A. S., Gee, D. G., & Cohen, A. O. (2019). Development of the emotional brain. Neuroscience Letters, 693, 29–34. https://doi.org/10.1016/j.neulet.2017.11.055 CrossRefGoogle ScholarPubMed
Cohodes, E. M., Kitt, E. R., Baskin-Sommers, A., & Gee, D. G. (2020). Influences of early-life stress on frontolimbic circuitry: Harnessing a dimensional approach to elucidate the effects of heterogeneity in stress exposure. Developmental Psychobiology, 63(2), 153–172. https://doi.org/10.1002/dev.21969 CrossRefGoogle ScholarPubMed
Collins, K. A., Mendelsohn, A., Cain, C. K., & Schiller, D. (2014). Taking action in the face of threat: Neural synchronization predicts adaptive coping. Journal of Neuroscience, 34(44), 14733–14738. https://doi.org/10.1523/JNEUROSCI.2152-14.2014 CrossRefGoogle ScholarPubMed
Craig, A. D. (2009). How do you feel — now? The anterior insula and human awareness. Nature Reviews Neuroscience, 10(1), 59–70. https://doi.org/10.1038/nrn2555 CrossRefGoogle Scholar
Ellis, B. J., Figueredo, A. J., Brumbach, B. H., & Schlomer, G. L. (2009). Fundamental dimensions of environmental risk. Human Nature, 20(2), 204–268. https://doi.org/10.1007/s12110-009-9063-7 CrossRefGoogle ScholarPubMed
Fox, S. E., Levitt, P., & Nelson III, C. A. (2010). How the timing and quality of early experiences influence the development of brain architecture. Child Development, 81(1), 28–40. https://doi.org/10.1111/j.1467-8624.2009.01380.x CrossRefGoogle ScholarPubMed
Frankenhuis, W. E., Gergely, G., & Watson, J. S. (2013). Infants may use contingency analysis to estimate environmental states: An evolutionary, life-history perspective. Child Development Perspectives, 7(2), 115–120. https://doi.org/10.1111/cdep.12024 CrossRefGoogle Scholar
Gabbay, V., Oatis, M. D., Silva, R. R., & Hirsch, G. (2004). Epidemiological aspects of PTSD in children and adolescents. In R. R. Silva (Ed.), Posttraumatic stress disorder in children and adolescents: Handbook (pp. 1–17, 1st ed.). WW Norton.Google Scholar
Gardumi, A., Ivanov, D., Hausfeld, L., Valente, G., Formisano, E., & Uludağ, K. (2016). The effect of spatial resolution on decoding accuracy in fMRI multivariate pattern analysis. NeuroImage, 132, 32–42. https://doi.org/10.1016/j.neuroimage.2016.02.033 CrossRefGoogle ScholarPubMed
Gee, D. G., & Casey, B. J. (2015). The impact of developmental timing for stress and recovery. Neurobiology of Stress, 1, 184–194. https://doi.org/10.1016/j.ynstr.2015.02.001 CrossRefGoogle ScholarPubMed
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L.…Polimeni, J. R. (2013). The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage, 80, 105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127 CrossRefGoogle ScholarPubMed
Gorgolewski, K. J., Auer, T., Calhoun, V. D., Craddock, R. C., Das, S., Duff, E. P.…Halchenko, Y. O. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Scientific Data, 3, 160044. https://doi.org/10.1038/sdata.2016.44 CrossRefGoogle ScholarPubMed
Grupe, D. W., & Nitschke, J. B. (2013). Uncertainty and anticipation in anxiety: An integrated neurobiological and psychological perspective. Nature Reviews Neuroscience, 14(7), 488–501. https://doi.org/10.1038/nrn3524 CrossRefGoogle ScholarPubMed
Gunnar, M. R. (1980). Control, warning signals, and distress in infancy. Developmental Psychology, 16(4), 281. https://doi.org/10.1037/0012-1649.16.4.281 CrossRefGoogle Scholar
Hartley, C. A., Gorun, A., Reddan, M. C., Ramirez, F., & Phelps, E. A. (2014). Stressor controllability modulates fear extinction in humans. Neurobiology of Learning and Memory, 113, 149–156. https://doi.org/10.1016/j.nlm.2013.12.003 CrossRefGoogle ScholarPubMed
Hayasaka, S., & Nichols, T. E. (2003). Validating cluster size inference: Random field and permutation methods. Neuroimage, 20(4), 2343–2356. https://doi.org/10.1016/j.neuroimage.2003.08.003 CrossRefGoogle ScholarPubMed
Heller, S. C. Comparison of accuracy and movement for phonological grain size matching during fMRI scanning versus outside the scanner, 2017, (Doctoral dissertation, University of Colorado at Boulder).Google Scholar
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17(2), 825–841. https://doi.org/10.1016/s1053-8119(02)91132-8 CrossRefGoogle ScholarPubMed
Kahana, Y., Kots, A., Mican, S., Chambers, J., & Bullock, D.. Optoacoustical ear defenders with active noise reduction in an MRI communication system . Paper presented at the: INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 2004, 1009–1024,Google Scholar
Kriegeskorte, N., Goebel, R., & Bandettini, P. (2006). Information-based functional brain mapping. Proceedings of the National Academy of Sciences of the United States of America, 103(10), 3863–3868. https://doi.org/10.1073/pnas.0600244103 CrossRefGoogle ScholarPubMed
Kubala, K. H., Christianson, J. P., Kaufman, R. D., Watkins, L. R., & Maier, S. F. (2012). Short-and long-term consequences of stressor controllability in adolescent rats. Behavioural Brain Research, 234(2), 278–284. https://doi.org/10.1016/j.bbr.2012.06.027 CrossRefGoogle ScholarPubMed
Kubierschky, M.. ‘Snow Angel-1.1 2009, http://snowangel.knirz.de/snowangel-1.1.py Google Scholar
Kumar, M., Anderson, M., Antony, J., Baldassano, C., Brooks, P. P., Cai, M. B.…et al. (2020). BrainIAK: The brain imaging analysis kit. OSF Preprints, https://doi.org/10.31219/osf.io/db2ev,Google Scholar
Ligneul, R., Mainen, Z., Ly, V., & Cools, R. (2020). Stress-sensitive brain computations of task controllability, https://doi.org/10.1101/2020.11.19.390393 Google Scholar
Limbachia, C., Morrow, K., Khibovska, A., Meyer, C., Padmala, S., & Pessoa, L. (2021). Controllability over stressor decreases responses in key threat-related brain areas. Communications Biology, 4(1), 1–11. https://doi.org/10.1038/s42003-020-01537-5 CrossRefGoogle ScholarPubMed
Liu, X., Tang, X., & Sanford, L. (2009). Stressor controllability and Fos expression in stress regulatory regions in mice. Physiology & Behavior, 97(3-4), 321–326. https://doi.org/10.1016/j.physbeh.2009.02.038 CrossRefGoogle ScholarPubMed
Luthar, S. S. (1999). Poverty and children’s adjustment. Sage. https://doi.org/10.4135/9781452233758 CrossRefGoogle Scholar
Maier, S. F., Grahn, R. E., Kalman, B. A., Sutton, L. C., Wiertelak, E. P., & Watkins, L. R. (1993). The role of the amygdala and dorsal raphe nucleus in mediating the behavioral consequences of inescapable shock. Behavioral Neuroscience, 107(2), 377–388. https://doi.org/10.1037/0735-7044.107.2.377 CrossRefGoogle ScholarPubMed
Maier, S. F., & Seligman, M. E. (1976). Learned helplessness: Theory and evidence. Journal of Experimental Psychology: General, 105(1), 3. https://doi.org/10.1037/0096-3445.105.1.3 CrossRefGoogle Scholar
Maier, S. F., & Watkins, L. R. (2005). Stressor controllability and learned helplessness: The roles of the dorsal raphe nucleus, serotonin, and corticotropin-releasing factor. Neuroscience & Biobehavioral Reviews, 29(4-5), 829–841. https://doi.org/10.1016/j.neubiorev.2005.03.021 CrossRefGoogle ScholarPubMed
Maier, S. F., & Watkins, L. R. (2010). Role of the medial prefrontal cortex in coping and resilience. Brain Research, 1355, 52–60. https://doi.org/10.1016/j.brainres.2010.08.039 CrossRefGoogle ScholarPubMed
Manly, J. T., Kim, J. E., Rogosch, F. A., & Cicchetti, D. (2001). Dimensions of child maltreatment and children’s adjustment: Contributions of developmental timing and subtype. Development and Psychopathology, 13(4), 759–782. https://doi.org/10.1017/S0954579401004023 CrossRefGoogle ScholarPubMed
McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2010). Childhood adversities and adult psychopathology in the National Comorbidity Survey Replication (NCS-R) III: Associations with functional impairment related to DSM-IV disorders. Psychological Medicine, 40(5), 847–859. https://doi.org/10.1017/S0033291709991115 CrossRefGoogle ScholarPubMed
McLaughlin, K. A., & Sheridan, M. A. (2016). Beyond cumulative risk: A dimensional approach to childhood adversity. Current Directions in Psychological Science, 25(4), 239–245. https://doi.org/10.1177/0963721416655883 CrossRefGoogle Scholar
McLaughlin, K. A., Sheridan, M. A., Tibu, F., Fox, N. A., Zeanah, C. H., & Nelson, C. A. (2015). Causal effects of the early caregiving environment on development of stress response systems in children. Proceedings of the National Academy of Sciences of the United States of America, 112(18), 5637–5642. https://doi.org/10.1073/pnas.1423363112 CrossRefGoogle ScholarPubMed
McLoyd, V. C. (1998). Socioeconomic disadvantage and child development. American Psychologist, 53(2), 185. https://doi.org/10.1037//0003-066x.53.2.185 CrossRefGoogle ScholarPubMed
Meyer, H. C., Odriozola, P., Cohodes, E. M., Mandell, J. D., Li, A., Yang, R.…Liston, C. (2019). Ventral hippocampus interacts with prelimbic cortex during inhibition of threat response via learned safety in both mice and humans. Proceedings of the National Academy of Sciences of the United States of America, 116(52), 26970–26979. https://doi.org/10.1073/pnas.1910481116 CrossRefGoogle ScholarPubMed
Mobbs, D., & Kim, J. J. (2015). Neuroethological studies of fear, anxiety, and risky decision-making in rodents and humans. Current Opinion in Behavioral Sciences, 5, 8–15. https://doi.org/10.1016/j.cobeha.2015.06.005 CrossRefGoogle ScholarPubMed
Moscarello, J. M., & Hartley, C. A. (2017). Agency and the calibration of motivated behavior. Trends in Cognitive Sciences, 21(10), 725–735. https://doi.org/10.1016/j.tics.2017.06.008 CrossRefGoogle ScholarPubMed
Moscarello, J. M., & LeDoux, J. E. (2013). Active avoidance learning requires prefrontal suppression of amygdala-mediated defensive reactions. Journal of Neuroscience, 33(9), 3815–3823. https://doi.org/10.1523/JNEUROSCI.2596-12.2013 CrossRefGoogle ScholarPubMed
Odriozola, P., Uddin, L. Q., Lynch, C. J., Kochalka, J., Chen, T., & Menon, V. (2016). Insula response and connectivity during social and non-social attention in children with autism. Social Cognitive and Affective Neuroscience, 11(3), 433–444. https://doi.org/10.1093/scan/nsv126 CrossRefGoogle ScholarPubMed
Paulus, M. P., & Stein, M. B. (2006). An insular view of anxiety. Biological Psychiatry, 60(4), 383–387. https://doi.org/10.1016/j.biopsych.2006.03.042 CrossRefGoogle ScholarPubMed
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O.…Duchesnay, É. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12(85), 2825–2830.Google Scholar
Peirce, J. W. (2007). PsychoPy—Psychophysics software in Python. Journal of Neuroscience Methods, 162(1-2), 8–13. https://doi.org/10.1016/j.jneumeth.2006.11.017 CrossRefGoogle ScholarPubMed
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59(3), 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018 CrossRefGoogle ScholarPubMed
Ramirez, F., Moscarello, J. M., LeDoux, J. E., & Sears, R. M. (2015). Active avoidance requires a serial basal amygdala to nucleus accumbens shell circuit. Journal of Neuroscience, 35(8), 3470–3477. https://doi.org/10.1523/JNEUROSCI.1331-14.2015 CrossRefGoogle ScholarPubMed
Seligman, M. E., & Maier, S. F. (1967). Failure to escape traumatic shock. Journal of Experimental Psychology, 74(1), 1–9. https://doi.org/10.1037/h0024514 CrossRefGoogle ScholarPubMed
Sheridan, M. A., & McLaughlin, K. A. (2014). Dimensions of early experience and neural development: Deprivation and threat. Trends in Cognitive Sciences, 18(11), 580–585. https://doi.org/10.1016/j.tics.2014.09.001 CrossRefGoogle ScholarPubMed
Shonkoff, J. P., Boyce, W. T., & McEwen, B. S. (2009). Neuroscience, molecular biology, and the childhood roots of health disparities: Building a new framework for health promotion and disease prevention. Journal of the American Medical Association, 301(21), 2252–2259. https://doi.org/10.1001/jama.2009.754 CrossRefGoogle ScholarPubMed
Shonkoff, J. P., The Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood Adoption, and Dependent Care, and Section on Developmental and Behavioral Pediatrics, Siegel, B. S., Dobbins, M. I., Earls, M. F., Garner, A. S.…Wood, D. L. (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246, https://doi.org/10.1542/peds.2011-2663 CrossRefGoogle ScholarPubMed
Sinha, R., Lacadie, C. M., Constable, R. T., & Seo, D. (2016). Dynamic neural activity during stress signals resilient coping. Proceedings of the National Academy of Sciences of the United States of America, 113(31), 8837–8842. https://doi.org/10.1073/pnas.1600965113 CrossRefGoogle ScholarPubMed
Smith, S. M., & Brady, J. M. (1997). SUSAN—A new approach to low level image processing. International Journal of Computer Vision, 23(1), 45–78. https://doi.org/10.1023/A:1007963824710 CrossRefGoogle Scholar
Tottenham, N., & Sheridan, M. A. (2010). A review of adversity, the amygdala and the hippocampus: A consideration of developmental timing. Frontiers in Human Neuroscience, 3, 68. https://doi.org/10.3389/neuro.09.068.2009 Google ScholarPubMed
Tukey, J. W. (1977). Exploratory data analysis. Addison-Wesley.Google Scholar
Uddin, L. Q. (2015). Salience processing and insular cortical function and dysfunction. Nature Reviews Neuroscience, 16(1), 55–61. https://doi.org/10.1038/nrn3857 CrossRefGoogle ScholarPubMed
Vanderwal, T., Kelly, C., Eilbott, J., Mayes, L. C., & Castellanos, F. X. (2015). Inscapes: A movie paradigm to improve compliance in functional magnetic resonance imaging. Neuroimage, 122, 222–232. https://doi.org/10.1016/j.neuroimage.2015.07.069 CrossRefGoogle ScholarPubMed
Wechsler, D. (2011). Wechsler abbreviated scale of intelligence, Second edition (WASI-II). NCS Pearson.Google Scholar
Woolrich, M. W., Behrens, T. E., Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2004). Multilevel linear modelling for FMRI group analysis using Bayesian inference. Neuroimage, 21(4), 1732–1747. https://doi.org/10.1016/j.neuroimage.2003.12.023 CrossRefGoogle ScholarPubMed
Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001). Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage, 14(6), 1370–1386. https://doi.org/10.1006/nimg.2001.0931 CrossRefGoogle ScholarPubMed
Zald, D. H., & Pardo, J. V. (2002). The neural correlates of aversive auditory stimulation. NeuroImage, 16(3, Part A), 746–753. https://doi.org/10.1006/nimg.2002.1115 CrossRefGoogle ScholarPubMed