Book contents
- Levels of Analysis in Psychopathology
- Advance Praise for Levels of Analysis in Psychopathology
- Levels of Analysis in Psychopathology
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- General Introduction
- Part I Neuroscience, Mechanisms, and RDoC
- Part II Phenomenology, Biological Psychology, and the Mind–Body Problem
- Part III Taxonomy, Integration, and Multiple Levels of Explanation
- Index
- References
Part I - Neuroscience, Mechanisms, and RDoC
Published online by Cambridge University Press: 02 April 2020
Book contents
- Levels of Analysis in Psychopathology
- Advance Praise for Levels of Analysis in Psychopathology
- Levels of Analysis in Psychopathology
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- General Introduction
- Part I Neuroscience, Mechanisms, and RDoC
- Part II Phenomenology, Biological Psychology, and the Mind–Body Problem
- Part III Taxonomy, Integration, and Multiple Levels of Explanation
- Index
- References
Summary
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
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- Chapter
- Information
- Levels of Analysis in PsychopathologyCross-Disciplinary Perspectives, pp. 17 - 124Publisher: Cambridge University PressPrint publication year: 2020
References
References
Bechtel, W. (1988a) Philosophy of mind: An overview for cognitive science. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
Bechtel, W. (1988b) Philosophy of science: An overview for cognitive science. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
Bechtel, W. (2008) Mental mechanisms: Philosophical perspectives on cognitive neuroscience. New York: Routledge/Taylor & Francis Group.Google Scholar
Bechtel, W., & Abrahamsen, A. (2005) ‘Explanation: A mechanist alternative.’ Studies in History & Philosophy of Biological & Biomedical Sciences, 36(2), 421–441.CrossRefGoogle ScholarPubMed
Bechtel, W., & Richardson, R. C. (1993) Discovering complexity: Decomposition and localization as strategies in scientific research. Princeton, NJ: Princeton University Press.Google Scholar
Cronbach, L. J., & Meehl, P. E. (1955) ‘Construct validity in psychological tests.’ Psychological Bulletin, 52(4), 281–302.CrossRefGoogle ScholarPubMed
Hempel, C. G., & Oppenheim, P. (1948) ‘Studies in the logic of explanation.’ Philosophy of Science, 15, 135–175.CrossRefGoogle Scholar
Kendler, K. S. (2008) ‘Explanatory models for psychiatric illness.’ American Journal of Psychiatry, 165(6), 695–702.CrossRefGoogle ScholarPubMed
Thomas, J. G., & Sharp, P. B. (2019) ‘Mechanistic science: A new approach to comprehensive psychopathology research that relates psychological and biological phenomena.’ Clinical Psychological Science, 7(2), 196–215.CrossRefGoogle Scholar
References
Albert, P. R., & Benkelfat, C. (2013) “The neurobiology of depression: Revisiting the serotonin hypothesis. II. Genetic, epigenetic and clinical studies.” Philosophical Transactions of the Royal Society B: Biological Sciences, 368(1615), 20120535.CrossRefGoogle ScholarPubMed
Albert, P. R., Benkelfat, C., & Descarries, L. (2012) “The neurobiology of depression – Revisiting the serotonin hypothesis. I. Cellular and molecular mechanisms.” Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1601), 2378.CrossRefGoogle ScholarPubMed
Albrecht, U. (2017) “Molecular mechanisms in mood regulation involving the circadian clock.” Frontiers in Neurology, 8, 30.CrossRefGoogle ScholarPubMed
Bechtel, W. (2008) Mental mechanisms. Philosophical perspectives on cognitive neuroscience. London: Routledge.Google Scholar
Bechtel, W. (2015) “Circadian rhythms and mood disorders: Are the phenomena and mechanisms causally related?” Frontiers in Psychiatry, 6, 118.CrossRefGoogle ScholarPubMed
Bechtel, W. (2018) “The importance of constraints and control in biological mechanisms: Insights from cancer research.” Philosophy of Science, 85(4), 573–593.CrossRefGoogle Scholar
Bechtel, W. (in press) “Living machines: The extent and limits of the machine metaphor.” In Holm, S. & Serban, M. (Eds.), Philosophical perspectives on the engineering approach in biology: Living machines? New York: Routledge.Google Scholar
Bechtel, W., & Abrahamsen, A. (2005) “Explanation: A mechanist alternative.” Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441.CrossRefGoogle ScholarPubMed
Bechtel, W., & Richardson, R. C. (1993/2010) Discovering complexity: Decomposition and localization as strategies in scientific research. Cambridge, MA: MIT Press. 1993 edition published by Princeton University Press.Google Scholar
Boivin, D. B., Czeisler, C. A., Dijk, D. J., Duffy, J. F., Folkard, S., Minors, D. S., … Waterhouse, J. M. (1997) “Complex interaction of the sleep–wake cycle and circadian phase modulates mood in healthy subjects.” Archives of General Psychiatry, 54(2), 145–152.CrossRefGoogle ScholarPubMed
Buchwald, J. S., & Brown, K. A. (1973) “Subcortical mechanisms of behavioral plasticity.” In Maser, J. D. (Ed.), Efferent organization and the integration of behavior (pp. xii, 368 pp.). New York: Academic Press.Google Scholar
Chao, M. Y., Komatsu, H., Fukuto, H. S., Dionne, H. M., & Hart, A. C. (2004) “Feeding status and serotonin rapidly and reversibly modulate a Caenorhabditis elegans chemosensory circuit.” Proceedings of the National Academy of Sciences of the United States of America, 101(43), 15512.Google Scholar
Chen, L., Eaton, W. W., Gallo, J. J., & Nestadt, G. (2000) “Understanding the heterogeneity of depression through the triad of symptoms, course and risk factors: A longitudinal, population-based study.” Journal of Affective Disorders, 59(1), 1–11.CrossRefGoogle ScholarPubMed
Cowen, P. J., & Browning, M. (2015) “What has serotonin to do with depression?” World Psychiatry, 14(2), 158–160.CrossRefGoogle Scholar
Craver, C. F. (2007) Explaining the brain: Mechanisms and the mosaic unity of neuroscience. New York: Oxford University Press.Google Scholar
Craver, C. F., & Darden, L. (2013) In search of mechanisms: Discoveries across the life sciences. Chicago: University of Chicago Press.Google Scholar
Culverhouse, R. C., Saccone, N. L., Horton, A. C., Ma, Y., Anstey, K. J., Banaschewski, T., … Bierut, L. J. (2018) “Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression.” Molecular Psychiatry, 23(1), 133–142.CrossRefGoogle Scholar
Dahlstroem, A., & Fuxe, K. (1964) “Evidence for the existence of monoamine-containing neurons in the central nervous system. I. Demonstration of monoamines in the cell bodies of brain stem neurons.” Acta Physiologica Scandinavica. Supplementum, 232, 231–255.Google Scholar
Erdös, P., & Rényi, A. (1960) “On the evolution of random graphs.” Proceedings of the Mathematical Institute of the Hungarian Academy of Sciences, 5, 17–61.Google Scholar
Ermentrout, G. B., & Kopell, N. (1984) “Frequency plateaus in a chain of weakly coupled oscillators. 1.” Siam Journal on Mathematical Analysis, 15(2), 215–237.Google Scholar
Fried, E. I. (2017) “The 52 symptoms of major depression: Lack of content overlap among seven common depression scales.” Journal of Affective Disorders, 208, 191–197.CrossRefGoogle ScholarPubMed
Gaspar, P., & Lillesaar, C. (2012) “Probing the diversity of serotonin neurons.” Philosophical Transactions: Biological Sciences, 367(1601), 2382–2394.Google Scholar
Goldberg, D. (2011) “The heterogeneity of ‘major depression.’” World Psychiatry, 10(3), 226–228.CrossRefGoogle ScholarPubMed
Hale, M. W., & Lowry, C. A. (2011) “Functional topography of midbrain and pontine serotonergic systems: Implications for synaptic regulation of serotonergic circuits.” Psychopharmacology (Berlin), 213(2–3), 243–264.CrossRefGoogle ScholarPubMed
Hampp, G., Ripperger, J. A., Houben, T., Schmutz, I., Blex, C., Perreau-Lenz, S., … Albrecht, U. (2008) “Regulation of monoamine oxidase A by circadian-clock components implies clock influence on mood.” Current Biology, 18(9), 678–683.CrossRefGoogle ScholarPubMed
Hardin, P. E., Hall, J. C., & Rosbash, M. (1990) “Feedback of the Drosophila period gene product on circadian cycling of its messenger RNA levels.” Nature, 343(6258), 536–540.CrossRefGoogle ScholarPubMed
Hensler, J. G. (2010) “Serotonin in mood and emotion.” In Christian, P. M. & Barry, L. J. (Eds.), Handbook of behavioral neuroscience (Vol. 21, pp. 367–378). London: Elsevier.Google Scholar
Hinton, J. M. (1963) “Patterns of insomnia in depressive states.” Journal of Neurological and Neurosurgical Psychiatry, 26, 184–189.Google Scholar
Hooker, C. A. (2013) “On the import of constraints in complex dynamical systems.” Foundations of Science, 18(4), 757–780.Google Scholar
Jackson, J. H. (1868–1869/1931) “Notes on the physiology and pathology of the nervous system.” In Taylor, J. (Ed.), Selected writings of John Hughlings Jackson (Vol. II, pp. 215–237). New York: Basic Books.Google Scholar
Keijzer, F., van Duijn, M., & Lyon, P. (2013) “What nervous systems do: Early evolution, input–output, and the skin brain thesis.” Adaptive Behavior, 21(2), 67–85.Google Scholar
Konopka, R. J., & Benzer, S. (1971) “Clock mutants of Drosophila melanogaster.” Proceedings of the National Academy of Sciences of the United States of America, 89(9), 2112–2116.CrossRefGoogle Scholar
Kripke, D. F., Mullaney, D. J., Atkinson, M., & Wolf, S. (1978) “Circadian rhythm disorders in manic-depressives.” Biological Psychiatry, 13(3), 335–351.Google ScholarPubMed
Kristan, W. B., & Nusbaum, M. P. (1982) “The dual role of serotonin in leech swimming.” Journal of Physiology (Paris), 78(8), 743–747.Google ScholarPubMed
Lacasse, J. R., & Leo, J. (2005) “Serotonin and depression: A disconnect between the advertisements and the scientific literature.” PLoS Medicine, 2(12), 1211–1216.Google Scholar
Landgraf, D., Long, J. E., Proulx, C. D., Barandas, R., Malinow, R., & Welsh, D. K. (2016) “Genetic disruption of circadian rhythms in the Suprachiasmatic Nucleus causes helplessness, behavioral despair, and anxiety-like behavior in mice.” Biological Psychiatry. 80(11), 827–835.Google Scholar
Landgraf, D., McCarthy, M. J., & Welsh, D. K. (2014) “The role of the circadian clock in animal models of mood disorders.” Behavioral Neuroscience, 128(3), 344–359.CrossRefGoogle ScholarPubMed
Lapin, I. P., & Oxenkrug, G. F. (1969) ‘Intensification of the central serotoninergic processes as a possible determinatnt of the thymoleptic effect.’ The Lancet, 293(7586), 132–136.CrossRefGoogle Scholar
Lazzerini Ospri, L., Prusky, G., & Hattar, S. (2017) ‘Mood, the circadian system, and melanopsin retinal ganglion cells.’ Annual Review of Neuroscience, 40, 539–556.CrossRefGoogle ScholarPubMed
Lesch, K.-P., & Waider, J. (2012) ‘Serotonin in the modulation of neural plasticity and networks: Implications for neurodevelopmental disorders.’ Neuron, 76(1), 175–191.CrossRefGoogle ScholarPubMed
Lewy, A. J., Kern, H. A., Rosenthal, N. E., & Wehr, T. A. (1982) ‘Bright artificial light treatment of a manic-depressive patient with a seasonal mood cycle.’ American Journal of Psychiatry, 139(11), 1496–1498.Google ScholarPubMed
Lewy, A. J., Sack, R. L., Singer, C. M., & White, D. M. (1987) ‘The phase shift hypothesis for bright light’s therapeutic mechanism of action: Theoretical considerations and experimental evidence.’ Psychopharmacology Bulletin, 23(3), 349–353.Google ScholarPubMed
Li, J. Z., Bunney, B. G., Meng, F., Hagenauer, M. H., Walsh, D. M., Vawter, M. P., … Bunney, W. E. (2013) ‘Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.’ Proceedings of the National Academy of Sciences of the United States of America, 110(24), 9950–9955.Google Scholar
Logan, R. W., Edgar, N., Gillman, A. G., Hoffman, D., Zhu, X., & McClung, C. A. (2015) ‘Chronic stress induces brain region-specific alterations of molecular rhythms that correlate with depression-like behavior in mice.’ Biological Psychiatry, 78(4), 249–258.Google Scholar
Lux, V., & Kendler, K. S. (2010) ‘Deconstructing major depression: A validation study of the DSM-IV symptomatic criteria.’ Psychological Medicine, 40(10), 1679–1690.Google Scholar
Machamer, P., Darden, L., & Craver, C. F. (2000) ‘Thinking about mechanisms.’ Philosophy of Science, 67(1), 1–25.Google Scholar
Marr, D. C. (1982) Vision: A computation investigation into the human representational system and processing of visual information. San Francisco: Freeman.Google Scholar
Martin, K. C., Casadio, A., Zhu, H., E, Y., Rose, J. C., Chen, M., … Kandel, E. R. (1997) ‘Synapse-specific, long-term facilitation of Aplysia sensory to motor synapses: A function for local protein synthesis in memory storage.’ Cell, 91(7), 927–938.Google Scholar
McClung, C. A. (2007) ‘Circadian genes, rhythms and the biology of mood disorders.’ Pharmacology & Therapeutics, 114(2), 222–232.Google Scholar
Moreno, A., & Mossio, M. (2014) Biological autonomy: A philosophical and theoretical inquiry. Dordrecht: Springer.Google Scholar
Parkinson, J. S., Hazelbauer, G. L., & Falke, J. J. (2015) ‘Signaling and sensory adaptation in Escherichia coli chemoreceptors: 2015 update.’ Trends in Microbiology, 23(5), 257–266.CrossRefGoogle Scholar
Pattee, H. H. (1972/2012) ‘Laws and constraints, symbols and languages.’ In Laws, language and life (Vol. 7, pp. 81–89). Netherlands: Springer.Google Scholar
Pattee, H. H. (1973/2012) ‘The physical basis and origin of hierarchical control.’ In Laws, language and life (Vol. 7, pp. 91–110). Netherlands: Springer.Google Scholar
Ralph, M. R., Foster, R. G., Davis, F. C., & Menaker, M. (1990) ‘Transplanted suprachiasmatic nucleus determines circadian period.’ Science, 247(4945), 975–978.CrossRefGoogle ScholarPubMed
Rosen, R. (1991) Life itself: A comprehensive inquiry into the nature, origin, and fabrication of life. Columbia: New York.Google Scholar
Rosenthal, N. E., Sack, D. A., Gillin, J. C., Lewy, A. J., Goodwin, F. K., Davenport, Y., … Wehr, T. A. (1984) ‘Seasonal affective disorder. A description of the syndrome and preliminary findings with light therapy.’ Archive of General Psychiatry, 41(1), 72–80.CrossRefGoogle ScholarPubMed
Souetre, E., Salvati, E., Belugou, J. L., Pringuey, D., Candito, M., Krebs, B., … Darcourt, G. (1989) ‘Circadian rhythms in depression and recovery: Evidence for blunted amplitude as the main chronobiological abnormality.’ Psychiatry Research, 28(3), 263–278.CrossRefGoogle ScholarPubMed
Traffanstedt, M. K., Mehta, S., & LoBello, S. G. (2016) ‘Major depression with seasonal variation: Is it a valid construct?’ Clinical Psychological Science, 4(5), 825–834.CrossRefGoogle Scholar
Vadnie, C. A., & McClung, C. A. (2017) ‘Circadian rhythm disturbances in mood disorders: Insights into the role of the suprachiasmatic nucleus.’ Neural Plasticity, 2017, 1504507.Google Scholar
Watts, D., & Strogratz, S. (1998) ‘Collective dynamics of small worlds.’ Nature, 393, 440–442.Google Scholar
Welsh, D. K., Takahashi, J. S., & Kay, S. A. (2010) ‘Suprachiasmatic nucleus: Cell autonomy and network properties.’ Annual Review of Physiology, 72(1), 551–577.Google Scholar
Winning, J., & Bechtel, W. (2018) ‘Rethinking causality in neural mechanisms: Constraints and control.’ Minds and Machines, 28(2), 287–310.CrossRefGoogle Scholar
References
Bechtel, W. (2007) Mental Mechanisms: Philosophical Perspectives on Cognitive Neuroscience. First ed. New York: Lawrence Erlbaum.CrossRefGoogle Scholar
Frith, C. (1996) ‘Neuropsychology of schizophrenia: What are the implications of intellectual and experimental abnormalities for the neurobiology of schizophrenia?’ British Medical Bulletin, 52:618–626.Google Scholar
Frith, C.D., Blakemore, S., Wolpert, D.M. (2000) ‘Explaining the symptoms of schizophrenia: Abnormalities in the awareness of action.’ Brain Research and Brain Research Review, 31:357–363.Google Scholar
Kendler, K.S. (2008) ‘Explanatory models for psychiatric illness.’ American Journal of Psychiatry, 165:695–702.Google Scholar
Klein, D.F. (1993) ‘False suffocation alarms, spontaneous panics, and related conditions. An integrative hypothesis.’ Archives of General Psychiatry, 50:306–317.CrossRefGoogle ScholarPubMed
Sekar, A., Bialas, A.R., de Rivera, H. et al. (2016) ‘Schizophrenia risk from complex variation of complement component 4.’ Nature, 530:177–183.Google Scholar
References
Bilder, R. M., Howe, A. G., & Sabb, F. W. (2013) ‘Multilevel models from biology to psychology: Mission impossible?’ Journal of Abnormal Psychology, 122(3), 917–927.Google Scholar
Bilder, R. M., Lenartowicz, A., Rissman, J., Loo, S., Pochon, J. B., Truong, H., … Sugar, C. (2018) RDoC working memory constructs spanning levels from disability to structural MRI. Paper presented at the American College of Neuropsychopharmacology, Hollywood, FL.Google Scholar
Bilder, R. M., & Reise, S. P. (2019) ‘Neuropsychological tests of the future: How do we get there from here?’ The Clinical Neuropsychologist, 33(2), 220–245.CrossRefGoogle Scholar
Bilder, R. M., Volavka, J., Lachman, H., & Grace, A. (2004) ‘The catechol-O-methyltransferase polymorphism: Relations to the tonic-phasic dopamine hypothesis and neuropsychiatric phenotypes.’ Neuropsychopharmacology, 29(11), 1943–1961.CrossRefGoogle Scholar
Borsboom, D., & Cramer, A. O. (2013) ‘Network analysis: An integrative approach to the structure of psychopathology.’ Annual Review of Clinical Psychology, 9, 91–121.CrossRefGoogle Scholar
Collins, A. G., & Frank, M. J. (2018) ‘Within-and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.’ Proceedings of the National Academy of Sciences, 115(10), 2502–2507.Google Scholar
Cronbach, L. J. (1951) ‘Coefficient alpha and the internal structure of tests.’ Psychometrika, 16(3), 297–334.CrossRefGoogle Scholar
Cronbach, L. J., & Meehl, P. E. (1955) ‘Construct validity in psychological tests.’ Psychological Bulletin, 52(4), 281–302.Google Scholar
Decker, H. S. (2007) ‘How Kraepelinian was Kraepelin? How Kraepelinian are the neo-Kraepelinians? – From Emil Kraepelin to DSM-III.’ History of Psychiatry, 18(71 Pt 3), 337–360.Google Scholar
Durstewitz, D., Seamans, J. K., & Sejnowski, T. J. (2000a) ‘Dopamine-mediated stabilization of delay-period activity in a network model of prefrontal cortex.’ Journal of Neurophysiology, 83(3), 1733–1750.Google Scholar
Durstewitz, D., Seamans, J. K., & Sejnowski, T. J. (2000b) ‘Neurocomputational models of working memory.’ Nature Neuroscience, 3(Suppl.), 1184–1191.Google Scholar
Embretson, S. E., & Reise, S. P. (2002) Item response theory for psychologists. Mahwah, NJ: Erlbaum.Google Scholar
Flint, J., & Munafo, M. R. (2007) ‘The endophenotype concept in psychiatric genetics.’ Psychological Medicine, 37(2), 163–180.CrossRefGoogle ScholarPubMed
Freud, S. (1966) Project for a scientific psychology (1950 [1895]). London: Hogarth Press.Google Scholar
Friston, K. J., Li, B., Daunizeau, J., & Stephan, K. E. (2011) ‘Network discovery with DCM.’ NeuroImage, 56(3), 1202–1221.CrossRefGoogle ScholarPubMed
Geschwind, N., & Galaburda, A. M. (1985a) ‘Cerebral lateralization: Biological mechanisms, associations, and pathology: II. A hypothesis and a program for research.’ Archives of Neurology, 42, 521–552.CrossRefGoogle Scholar
Geschwind, N., & Galaburda, A. M. (1985b) ‘Cerebral lateralization: Biological mechanisms, associations, and pathology: III. A hypothesis and program for research.’ Archives of Neurology, 42, 634–654.Google Scholar
Geschwind, N., & Galaburda, A. M. (1985c) ‘Cerebral lateralization. Biological mechanisms, associations, and pathology: I. A hypothesis and a program for research.’ Archives of Neurology, 42, 428–459.Google Scholar
Geschwind, N., & Galaburda, A. M. (1987) Cerebral lateralization. Biological mechanisms, associations, and pathology. Cambridge, MA: MIT Press.Google Scholar
McManus, I. C., & Bryden, M. P. (1992) ‘Geschwind’s theory of cerebral laterization: Developing a formal causal model.’ Psychological Bulletin, 110, 237–253.Google Scholar
Nunnally, J. C., & Bernstein, I. (1994) Psychometric theory (McGraw-Hill Series in Psychology) (Vol. 3). New York: McGraw-Hill.Google Scholar
O’Reilly, R. C., Wyatte, D. R., & Rohrlich, J. J. (2017) Deep Predictive Learning: A Comprehensive Model of Three Visual Streams. Available at https://arxiv.org/abs/1709.04654.Google Scholar
Olesen, P. J., Macoveanu, J., Tegnér, J., & Klingberg, T. (2006) ‘Brain activity related to working memory and distraction in children and adults.’ Cerebral Cortex, 17(5), 1047–1054.CrossRefGoogle ScholarPubMed
Pearl, J., & Mackenzie, D. (2018) The book of why: The new science of cause and effect. New York: Basic Books.Google Scholar
References
Bai, Y, Nakao, T, Xu, J, Qin, P, Chaves, P, Heinzel, A, Duncan, N, Lane, T, Yen, NS, Tsai, SY, Northoff, G. (2016) ‘Resting state glutamate predicts elevated pre-stimulus alpha during self-relatedness: A combined EEG-MRS study on “rest-self overlap”.’ Society for Neuroscience. 11(3):249–63.Google Scholar
Bilder, RM, Sabb, FW, Parker, DS, Kalar, D, Chu, WW, Fox, J, Freimer, NB, Poldrack, RA. (2009) ‘Cognitive ontologies for neuropsychiatric phenomics research.’ Cognitive Neuropsychiatry. 14(4–5):419–50.CrossRefGoogle ScholarPubMed
Bilder, RM, Howe, AG, Sabb, FW. (2013) ‘Multilevel models from biology to psychology: Mission impossible?’ Journal of Abnormal Psychology. 122(3):917–27.Google Scholar
Cole, MW, Bassett, DS, Power, JD, Braver, TS, Petersen, SE. (2014) ‘Intrinsic and task-evoked network architectures of the human brain.’ Neuron. 83(1):238–51.Google Scholar
Cole, MW, Ito, T, Bassett, DS, Schultz, DH. (2016) ‘Activity flow over resting-state networks shapes cognitive task activations.’ Nature Neuroscience. 19(12):1718–26.CrossRefGoogle ScholarPubMed
D’Argembeau, A, Collette, F, Van der Linden, M, Laureys, S, Del Fiore, G, Degueldre, C, Luxen, A, Salmon, E. (2005) ‘Self-referential reflective activity and its relationship with rest: A PET study.’ NeuroImage. 25(2):616–24.Google Scholar
Davey, CG, Pujol, J, Harrison, BJ. (2016) ‘Mapping the self in the brain’s default mode network.’ NeuroImage. 132:390–97.CrossRefGoogle ScholarPubMed
Ferri, F, Nikolova, YS, Perrucci, MG, Costantini, M, Ferretti, A, Gatta, V, Huang, Z, Edden, RAE, Yue, Q, D’Aurora, M, Sibille, E, Stuppia, L, Romani, GL, Northoff, G. (2017) ‘A neural “tuning curve” for multisensory experience and cognitive-perceptual schizotypy.’ Schizophrenia Bulletin. 43(4):801–13.CrossRefGoogle ScholarPubMed
Halligan, PW, David, AS. (2001) ‘Cognitive neuropsychiatry: Towards a scientific psychopathology.’ Nature Reviews Neuroscience. 2(3):209–15.Google Scholar
Hastings, J, Frishkoff, GA, Smith, B, Jensen, M, Poldrack, RA, Lomax, J, Bandrowski, A, Imam, F, Turner, JA, Martone, ME.(2014) ‘Interdisciplinary perspectives on the development, integration, and application of cognitive ontologies.’ Frontiers in Neuroinformatics. 8:62.CrossRefGoogle ScholarPubMed
He, BJ. (2014) ‘Scale-free brain activity: Past, present, and future.’ Trends in Cognitive Sciences. 18(9):480–87.Google Scholar
He, BJ, Zempel, JM, Snyder, AZ, Raichle, ME. (2010) ‘The temporal structures and functional significance of scale-free brain activity.’ Neuron. 66(3):353–69.Google Scholar
Huang, Z, Zhang, J, Wu, J, Qin, P, Wu, X, Wang, Z, Dai, R, Li, Y, Liang, W, Mao, Y, Yang, Z, Zhang, J, Wolff, A, Northoff, G. (2016) ‘Decoupled temporal variability and signal synchronization of spontaneous brain activity in loss of consciousness: An fMRI study in anesthesia.’ NeuroImage. 124(Pt A):693–703.Google Scholar
Huang, Z, Zhang, J, Wu, J, Liu, X, Xu, J, Zhang, J, Qin, P, Dai, R, Yang, Z, Mao, Y, Hudetz, AG, Northoff, G. (2018) ‘Disrupted neural variability during propofol-induced sedation and unconsciousness.’ Human Brain Mapping. 39(11):4533–44.Google Scholar
Insel, TR, Cuthbert, BN. (2015) ‘Medicine. Brain disorders? Precisely.’ Science. 348(6234):499–500.CrossRefGoogle ScholarPubMed
Liu, X, de Zwart, JA, Schölvinck, ML, Chang, C, Ye, FQ, Leopold, DA, Duyn, JH. (2018) ‘Subcortical evidence for a contribution of arousal to fMRI studies of brain activity.’ Nature Communications. 9(1):395.CrossRefGoogle ScholarPubMed
Logothetis, NK, Murayama, Y, Augath, M, Steffen, T, Werner, J, Oeltermann, A. (2009) ‘How not to study spontaneous activity.’ NeuroImage. 45(4):1080–89.Google Scholar
Morcom, AM, Fletcher, PC. (2007) ‘Does the brain have a baseline? Why we should be resisting a rest.’NeuroImage. 37(4):1073–82.Google Scholar
Northoff, G. (2012) ‘Immanuel Kant’s mind and the brain’s resting state.’ Trends in Cognitive Sciences. 16(7):356–9.Google Scholar
Northoff, G. (2014a) Unlocking the Brain. Volume I: Coding. New York: Oxford University Press.Google Scholar
Northoff, G. (2014b) Unlocking the Brain. Volume II: Consciousness. Oxford: Oxford University.Google Scholar
Northoff, G. (2018) ‘The brain’s spontaneous activity and its psychopathological symptoms; “Spatiotemporal binding and integration”.’ Progress in Neuro-Psychopharmacology & Biological Psychiatry. 80(Pt B):81–90.Google Scholar
Northoff, G, Huang, Z. (2017) ‘How do the brain’s time and space mediate consciousness and its different dimensions? Temporo-spatial theory of consciousness (TTC).’Neuroscience and Biobehavioral Reviews. 80:630–45.Google Scholar
Northoff, G, Sibille, E. (2014) ‘Why are cortical GABA neurons relevant to internal focus in depression? A cross-level model linking cellular, biochemical and neural network findings.’ Molecular Psychiatry. 19(9):966–77.Google ScholarPubMed
Poldrack, RA, Kittur, A, Kalar, D, Miller, E, Seppa, C, Gil, Y, Parker, DS, Sabb, FW, Bilder, RM. (2011) ‘The cognitive atlas: Toward a knowledge foundation for cognitive neuroscience.’ Frontiers in Neuroinformatics. 5:17.Google Scholar
Power, JD, Schlaggar, BL, Petersen, SE. (2015) ‘Recent progress and outstanding issues in motion correction in resting state fMRI.’ NeuroImage. 105:536–51.CrossRefGoogle ScholarPubMed
Power, JD, Plitt, M, Laumann, TO, Martin, A. (2017) ‘Sources and implications of whole-brain fMRI signals in humans.’ NeuroImage. 146:609–25.Google Scholar
Power, JD, Plitt, M, Gotts, SJ, Kundu, P, Voon, V, Bandettini, PA, Martin, A. (2018) ‘Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.’ Proceedings of the National Academy of Sciences of the United States of America. 115(9):E2105–14.Google ScholarPubMed
Qin, P, Northoff, G. (2011) ‘How is our self related to midline regions and the default-mode network?’ NeuroImage. 57(3):1221–33.CrossRefGoogle Scholar
Raichle, ME. (2009) ‘A brief history of human brain mapping.’ Trends in Neuro-science. 32(2):118–26.Google Scholar
Raichle, ME. (2015) ‘The brain’s default mode network.’ Annual Review of Neuroscience. 38:433–47.Google Scholar
Schölvinck, ML, Maier, A, Ye, FQ, Duyn, JH, Leopold, DA. (2010) ‘Neural basis of global resting-state fMRI activity.’ Proceedings of the National Academy of Sciences of the United States of America. 107(22):10238–43.Google Scholar
Tagliazucchi, E Wegner, F, Morzelewski, A, Brodbeck, V, Jahnke, K, Laufs, H. (2013) ‘Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep.’ Proceedings of the National Academy of Sciences of the United States of America. 110(38):15419–24.Google Scholar
Tagliazucchi, E, Chialvo, DR, Siniatchkin, M, Amico, E, Brichant, JF, Bonhomme, V, Noirhomme, Q, Laufs, H, Laureys, S. (2016) ‘Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics.’ Journal of the Royal Society Interface. 13(114):20151027.CrossRefGoogle ScholarPubMed
Tsuchiya, N, Wilke, M, Frässle, S, Lamme, VAF. (2015) ‘No-report paradigms: Extracting the true neural correlates of consciousness.’ Trends in Cognitive Science. 19(12):757–70.Google Scholar
Whitfield-Gabrieli, S, Moran, JM, Nieto-Castanon, A, Triantafyllou, C, Saxe, R, Gabrieli, JD. (2011) ‘Associations and dissociations between default and self-reference networks in the human brain.’ NeuroImage. 55(1):225–32.CrossRefGoogle ScholarPubMed
Wolff, A, Di Giovanni, DA, Gómez-Pilar, J, Nakao, T, Huang, Z, Longtin, A, Northoff, G. (2019) ‘The temporal signature of self: Temporal measures of resting-state EEG predict self-consciousness.’ Human Brain Mapping. 40(3):789–803.Google Scholar
Zhang, J, Magioncalda, P, Huang, Z, Tan, Z, Hu, X, Hu, Z, Conio, B, Amore, M, Inglese, M, Martino, M, Northoff, G.(2018) ‘Altered global signal topography and its different regional localization in motor cortex and hippocampus in mania and depression.’ Schizophrenia Bulletin. 45(4):902–10.Google Scholar
References
Badura-Brack, A. S., Naim, R., Ryan, T. J., Levy, O., Abend, R., Khanna, M. M., … Bar-Haim, Y. (2015) ‘Effect of attention training on attention bias variability and PTSD symptoms: Randomized controlled trials in Israeli and U.S. combat veterans.’ American Journal of Psychiatry, 172(12), 1233–1241.Google Scholar
Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., & van Ijzendoorn, M. H. (2007) ‘Threat-related attentional bias in anxious and nonanxious individuals: A meta-analytic study.’ Psychological Bulletin, 133(1), 1–24.Google Scholar
Barberini, C. L., Morrison, S. E., Saez, A., Lau, B., & Salzman, C. D. (2012) ‘Complexity and competition in appetitive and aversive neural circuits.’ Frontiers in Neuroscience, 6, 170.Google Scholar
Beesdo, K., Knappe, S., & Pine, D. S. (2009) ‘Anxiety and anxiety disorders in children and adolescents: Developmental issues and implications for DSM-V.’ Psychiatric Clinics of North America, 32(3), 483–524.Google Scholar
Briggs-Gowan, M. J., Grasso, D., Bar-Haim, Y., Voss, J., McCarthy, K. J., Pine, D. S., & Wakschlag, L. S. (2016) ‘Attention bias in the developmental unfolding of post-traumatic stress symptoms in young children at risk.’ Journal of Child Psychology and Psychiatry, 57(9), 1083–1091.Google Scholar
Britton, J. C., Suway, J. G., Clementi, M. A., Fox, N. A., Pine, D. S., & Bar-Haim, Y. (2015) ‘Neural changes with attention bias modification for anxiety: A randomized trial.’ Social Cognitive and Affective Neuroscience, 10(7), 913–920.Google Scholar
Corbetta, M., Patel, G., & Shulman, G. L. (2008) ‘The reorienting system of the human brain: From environment to theory of mind.’ Neuron, 58(3), 306–324.Google Scholar
Cristea, I. A., Kok, R. N., & Cuijpers, P. (2015) ‘Efficacy of cognitive bias modification interventions in anxiety and depression: Meta-analysis.’ British Journal of Psychiatry, 206(1), 7–16.Google Scholar
Cuthbert, B. N., & Insel, T. R. (2013) ‘Toward the future of psychiatric diagnosis: The seven pillars of RDoC.’ BMC Medicine, 11, 126.Google Scholar
Davis-Kean, P. E., Huesmann, L. R., Jager, J., Collins, W. A., Bates, J. E., & Lansford, J. E. (2008) ‘Changes in the relation of self-efficacy beliefs and behaviors across development.’ Child Development, 79(5), 1257–1269.Google Scholar
Davis, M., Walker, D. L., Miles, L., & Grillon, C. (2010) ‘Phasic vs sustained fear in rats and humans: Role of the extended amygdala in fear vs anxiety.’ Neuropsychopharmacology, 35(1), 105–135.Google Scholar
Duits, P., Cath, D. C., Lissek, S., Hox, J. J., Hamm, A. O., Engelhard, I. M., … Baas, J. M. (2015) ‘Updated meta-analysis of classical fear conditioning in the anxiety disorders.’ Depression and Anxiety, 32(4), 239–253.Google Scholar
Gold, A. L., Shechner, T., Farber, M. J., Spiro, C. N., Leibenluft, E., Pine, D. S., & Britton, J. C. (2016) ‘Amygdala–cortical connectivity: Associations with anxiety, development, and threat.’ Depression and Anxiety, 33(10), 917–926.Google Scholar
Goodkind, M., Eickhoff, S. B., Oathes, D. J., Jiang, Y., Chang, A., Jones-Hagata, L. B., … Etkin, A. (2015) ‘Identification of a common neurobiological substrate for mental illness.’ JAMA Psychiatry, 72(4), 305–315.Google Scholar
Harter, S. (1992) ‘Visions of self: Beyond the me in the mirror.’ Nebraska Symposium on Motivation, 40, 99–144.Google Scholar
Harter, S., Bresnick, S., Bouchey, H. A., & Whitesell, N. R. (1997) ‘The development of multiple role-related selves during adolescence.’ Development and Psychopathology, 9(4), 835–853.Google Scholar
Insel, T. R. (2014) ‘The NIMH Research Domain Criteria (RDoC) project: Precision medicine for psychiatry.’ American Journal of Psychiatry, 171(4), 395–397.Google Scholar
Lau, J. Y., Britton, J. C., Nelson, E. E., Angold, A., Ernst, M., Goldwin, M., … Pine, D. S. (2011) ‘Distinct neural signatures of threat learning in adolescents and adults.’ Proceedings of the National Academy of the Sciences U S A, 108(11), 4500–4505.Google Scholar
Lazarov, A., Marom, S., Yahalom, N., Pine, D. S., Hermesh, H., & Bar-Haim, Y. (2018) ‘Attention bias modification augments cognitive-behavioral group therapy for social anxiety disorder: A randomized controlled trial.’ Psychological Medicine, 48(13), 2177–2185.Google Scholar
Lazarov, A., Pine, D. S., & Bar-Haim, Y. (2017) ‘Gaze-contingent music reward therapy for social anxiety disorder: A randomized controlled trial.’ American Journal of Psychiatry, 174(7), 649–656.Google Scholar
LeDoux, J. E. (2014) ‘Coming to terms with fear.’ Proceedings of the National Academy of the Sciences U S A, 111(8), 2871–2878.Google Scholar
LeDoux, J. E., & Brown, R. (2017) ‘A higher-order theory of emotional consciousness.’ Proceedings of the National Academy of the Sciences U S A, 114(10), E2016–E2025.Google Scholar
LeDoux, J. E., & Pine, D. S. (2016) ‘Using neuroscience to help understand fear and anxiety: A two-system framework.’ American Journal of Psychiatry, 173(11), 1083–1093.Google Scholar
McTeague, L. M., Huemer, J., Carreon, D. M., Jiang, Y., Eickhoff, S. B., & Etkin, A. (2017) ‘Identification of common neural circuit disruptions in cognitive control across psychiatric disorders.’ American Journal of Psychiatry, 174(7), 676–685.CrossRefGoogle ScholarPubMed
Miyake, A., & Friedman, N. P. (2012) ‘The nature and organization of individual differences in executive functions: Four general conclusions.’ Current Directions in Psychological Science, 21(1), 8–14.Google Scholar
Monk, C. S., Telzer, E. H., Mogg, K., Bradley, B. P., Mai, X., Louro, H. M., … Pine, D. S. (2008) ‘Amygdala and ventrolateral prefrontal cortex activation to masked angry faces in children and adolescents with generalized anxiety disorder.’ Archives of General Psychiatry, 65(5), 568–576.Google Scholar
Moore, T., & Zirnsak, M. (2017) ‘Neural mechanisms of selective visual attention.’ Annual Review of Psychology, 68, 47–72.Google Scholar
Pine, D. S. (2013) ‘A 60-year climb on the mountain of nosology.’ Journal of the American Academy of Child and Adolescent Psychiatry, 52(12), 1251–1254.Google Scholar
Pine, D. S., & Fox, N. A. (2015) ‘Childhood antecedents and risk for adult mental disorders.’ Annual Review of Psychology, 66, 459–485.Google Scholar
Pine, D. S., & Leibenluft, E. (2015) ‘Biomarkers with a mechanistic focus.’ JAMA Psychiatry, 72(7), 633–634.CrossRefGoogle ScholarPubMed
Price, R. B., Wallace, M., Kuckertz, J. M., Amir, N., Graur, S., Cummings, L., … Bar-Haim, Y. (2016) ‘Pooled patient-level meta-analysis of children and adults completing a computer-based anxiety intervention targeting attentional bias.’ Clinical Psychology Review, 50, 37–49.Google Scholar
Rappaport, B. I., Pagliaccio, D., Pine, D. S., Klein, D. N., & Jarcho, J. M. (2017) ‘Discriminant validity, diagnostic utility, and parent-child agreement on the Screen for Child Anxiety Related Emotional Disorders (SCARED) in treatment- and non-treatment-seeking youth.’ Journal of Anxiety Disorders, 51, 22–31.Google Scholar
Shaffer, D., Fisher, P., Dulcan, M. K., Davies, M., Piacentini, J., Schwab-Stone, M. E., … Regier, D. A. (1996) ‘The NIMH Diagnostic Interview Schedule for Children Version 2.3 (DISC-2.3): Description, acceptability, prevalence rates, and performance in the MECA study. Methods for the epidemiology of child and adolescent mental disorders study.’ Journal of the American Academy of Child and Adolescent Psychiatry, 35(7), 865–877.Google Scholar
Shaffer, D., Fisher, P., Lucas, C. P., Dulcan, M. K., & Schwab-Stone, M. E. (2000) ‘NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): Description, differences from previous versions, and reliability of some common diagnoses.’ Journal of the American Academy of Child and Adolescent Psychiatry, 39(1), 28–38.Google Scholar
van Vugt, B., Dagnino, B., Vartak, D., Safaai, H., Panzeri, S., Dehaene, S., & Roelfsema, P. R. (2018) ‘The threshold for conscious report: Signal loss and response bias in visual and frontal cortex.’ Science, 360(6388), 537–542.Google Scholar
Wald, I., Degnan, K. A., Gorodetsky, E., Charney, D. S., Fox, N. A., Fruchter, E., … Bar-Haim, Y. (2013) ‘Attention to threats and combat-related posttraumatic stress symptoms: Prospective associations and moderation by the serotonin transporter gene.’ JAMA Psychiatry, 70(4), 401–408.Google Scholar
Wald, I., Lubin, G., Holoshitz, Y., Muller, D., Fruchter, E., Pine, D. S., … Bar-Haim, Y. (2011) ‘Battlefield-like stress following simulated combat and suppression of attention bias to threat.’ Psychological Medicine, 41(4), 699–707.Google Scholar
White, L. K., Degnan, K. A., Henderson, H. A., Perez-Edgar, K., Walker, O. L., Shechner, T., … Fox, N. A. (2017) ‘Developmental relations among behavioral inhibition, anxiety, and attention biases to threat and positive information.’ Child Development, 88(1), 141–155.Google Scholar
White, L. K., Sequeira, S., Britton, J. C., Brotman, M. A., Gold, A. L., Berman, E., … Pine, D. S. (2017) ‘Complementary features of attention bias modification therapy and cognitive-behavioral therapy in pediatric anxiety disorders.’ American Journal of Psychiatry, 174(8), 775–784.Google Scholar
References
Dehaene, S. and Changeux, J. P. (2011) ‘Experimental and theoretical approaches to conscious processing.’ Neuron 70(2): 200–227.Google Scholar
Dehaene, S., Charles, L., King, J. R. and Marti, S. (2014) ‘Toward a computational theory of conscious processing.’ Current Opinion in Neurobiology 25: 76–84.Google Scholar
Dehaene, S., Lau, H. and Kouider, S. (2017) ‘What is consciousness, and could machines have it?’ Science 358(6362): 486–492.Google Scholar
Fanselow, M. S. and Pennington, Z. T. (2018) ‘A return to the psychiatric dark ages with a two-system framework for fear.’ Behaviour Research and Therapy 100: 24–29.Google Scholar
Fanselow, M. S. and Pennington, Z. T. (2017) ‘The danger of LeDoux and Pine’s two-system framework for fear.’ American Journal of Psychiatry 174(11): 1120–1121.CrossRefGoogle ScholarPubMed
Gordon, J. A. (2016) ‘On being a circuit psychiatrist.’ Nature Neuroscience 19(11): 1385–1386.Google Scholar
Katsuki, F. and Constantinidis, C. (2014) ‘Bottom-up and top-down attention: Different processes and overlapping neural systems.’ Neuroscientist 20(5): 509–521.Google Scholar
LeDoux, J. E. and Brown, R. (2017) ‘A higher-order theory of emotional consciousness.’ Proceedings of the National Academy of Sciences of the United States of America 114(10): E2016–E2025.Google Scholar
LeDoux, J. E. and Pine, D. S. (2016) ‘Using neuroscience to help understand fear and anxiety: A two-system framework.’ American Journal of Psychiatry 173(11): 1083–1093.Google Scholar
Parnas, J. (2011) ‘A disappearing heritage: The clinical core of schizophrenia.’ Schizophrenia Bulletin 37(6): 1121–1130.Google Scholar
Parnas, J., Moller, P., Kircher, T., Thalbitzer, J., Jansson, L., Handest, P. and Zahavi, D. (2005) ‘EASE: Examination of anomalous self-experience.’ Psychopathology 38(5): 236–258.Google Scholar
Pine, D. S. (2020) ‘Tackling hard problems: Neuroscience, treatment, and anxiety.’ In Levels of Analysis in Psychopathology: Cross-Disciplinary Perspectives, Kendler, K. S., Parnas, J. and Zachar, P. (eds.). New York: Cambridge University Press.Google Scholar
Pine, D. S. and LeDoux, J. E. (2017) ‘Elevating the role of subjective experience in the clinic: Response to Fanselow and Pennington.’ American Journal of Psychiatry 174(11): 1121–1122.Google Scholar
Prinz, J. (2012). The conscious brain: How attention engenders experience. New York: Oxford University Press.Google Scholar
Schaffner, K. F. (2020) ‘Approaches to multi-level models of fear: The what, where, why, how, and how much?’ In Levels of Analysis in Psychopathology: Cross-Disciplinary Perspectives, Kendler, K. S., Parnas, J. and Zachar, P. (eds.). New York: Cambridge University Press.Google Scholar
van der Staay, F. J., Arndt, S. S. and Nordquist, R. E. (2009) ‘Evaluation of animal models of neurobehavioral disorders.’ Behavioral and Brain Functions 5: 11.Google Scholar
White, L. K., Sequeira, S., Britton, J. C., Brotman, M. A., Gold, A. L., Berman, E., Towbin, K., Abend, R., Fox, N. A., Bar-Haim, Y., Leibenluft, E. and Pine, D. S. (2017) ‘Complementary features of attention bias modification therapy and cognitive-behavioral therapy in pediatric anxiety disorders.’ American Journal of Psychiatry 174(8): 775–784.Google Scholar
Zahavi, D. (2014) Self and Other: Exploring Subjectivity, Empathy, and Shame. New York: Oxford University Press.Google Scholar
Zahavi, D. (2018) The Oxford Handbook of the History of Phenomenology. New York: Oxford University Press.Google Scholar