Beyond the categorical museum: Why the DSM cannot name the neurodivergent mind
DOI:
https://doi.org/10.68178/egafya41Keywords:
Asperger’s syndrome, DSM-5, autism spectrum, phenomenological psychopathology, category mistake, Erlangen programme, nosologyAbstract
The removal of Asperger’s syndrome from the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders was defended as a refinement: the replacement of an unreliable subtype by a dimensional construct grounded in empirical continuity. This paper argues that the move was not a refinement but a category error in the precise sense developed by Ryle. The dimensional spectrum is a Cartesian instrument, a symptom space of discrete, additive criteria, bounded by thresholds, navigable by coordinates. The neurodivergent mind is not a Cartesian object. As a complex adaptive system operating in the vicinity of criticality, its identity is carried not by the values of isolated variables but by invariant dynamical structure: attractors, trajectories, phase-space signatures that persist under transformations which annihilate any pointwise description. To classify such an object by checklist is to apply a Euclidean ruler to a fractal coastline and report the measurement as fact. The result is not approximation; it is the wrong kind of answer to the question. An instrument’s adequacy to its object is the elementary methodological demand a nosology must satisfy, and the 2013 revision failed that demand for reasons that are structural rather than contingent. The paper proposes the recovery of the Asperger construct, not as a restored box with inclusion criteria, but as a recognizable emergent configuration of a cognitive system organized around a distinct attractor. It develops the argument by deriving, from two propositions already settled in mathematics, Klein’s, that geometric invariants are relative to a transformation group, and Mandelbrot’s, that a single object can carry two irreducible geometric descriptions both of which are true, the coexistence within one object of ontologically real geometric regimes irreducible to one another and accessible only by instruments adequate to each.
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References
1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: APA; 1994.
2. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Arlington, VA: APA; 2013. DOI: https://doi.org/10.1176/appi.books.9780890425596
3. Klin A, Pauls D, Schultz R, Volkmar FR. Three diagnostic approaches to Asperger syndrome: implications for research. J Autism Dev Disord. 2005;35(2):221–34. doi:10.1007/s10803-004-2001-y DOI: https://doi.org/10.1007/s10803-004-2001-y
4. Mahjouri S, Lord CE. What the DSM-5 portends for research, diagnosis, and treatment of autism spectrum disorders. Curr Psychiatry Rep. 2012;14(6):739–47. doi:10.1007/s11920-012-0327-2 DOI: https://doi.org/10.1007/s11920-012-0327-2
5. Volkmar FR, McPartland JC. From Kanner to DSM-5: autism as an evolving diagnostic concept. Annu Rev Clin Psychol. 2014;10:193–212. doi:10.1146/annurev-clinpsy-032813-153710 DOI: https://doi.org/10.1146/annurev-clinpsy-032813-153710
6. Lord C, Jones RM. Annual research review: re-thinking the classification of autism spectrum disorders. J Child Psychol Psychiatry. 2012;53(5):490–509. doi:10.1111/j.1469-7610.2012.02547.x DOI: https://doi.org/10.1111/j.1469-7610.2012.02547.x
7. Huerta M, Bishop SL, Duncan A, Hus V, Lord C. Application of DSM-5 criteria for autism spectrum disorder to three samples of children with DSM-IV diagnoses of pervasive developmental disorders. Am J Psychiatry. 2012;169(10):1056–64. doi:10.1176/appi.ajp.2012.12020276 DOI: https://doi.org/10.1176/appi.ajp.2012.12020276
8. Constantino JN, Todd RD. Autistic traits in the general population: a twin study. Arch Gen Psychiatry. 2003;60(5):524–30. doi:10.1001/archpsyc.60.5.524 DOI: https://doi.org/10.1001/archpsyc.60.5.524
9. Lundström S, Chang Z, Råstam M, Gillberg C, Larsson H, Anckarsäter H, et al. Autism spectrum disorders and autistic-like traits: similar etiology in the extreme end and the normal variation. Arch Gen Psychiatry. 2012;69(1):46–52. doi:10.1001/archgenpsychiatry.2011.144 DOI: https://doi.org/10.1001/archgenpsychiatry.2011.144
10. Hacking I. The looping effects of human kinds. In: Sperber D, Premack D, Premack AJ, editors. Causal Cognition: A Multidisciplinary Debate. Oxford: Clarendon Press; 1995. p. 351–94. DOI: https://doi.org/10.1093/acprof:oso/9780198524021.003.0012
11. Hacking I. The Social Construction of What? Cambridge, MA: Harvard University Press; 1999.
12. Ryle G. The Concept of Mind. London: Hutchinson; 1949.
13. Wittgenstein L. Philosophical Investigations. Anscombe GEM, translator. Oxford: Blackwell; 1953.
14. Klein F. Vergleichende Betrachtungen über neuere geometrische Forschungen [Erlangen Programme]. Erlangen: Deichert; 1872.
15. Rowe DE. The early geometrical works of Sophus Lie and Felix Klein. In: Rowe DE, McCleary J, editors. The History of Modern Mathematics, Vol. I. Boston: Academic Press; 1989. p. 209–73. DOI: https://doi.org/10.1016/B978-0-12-599661-7.50014-8
16. Mandelbrot BB. How long is the coast of Britain? Statistical self-similarity and fractional dimension. Science. 1967;156(3775):636–8. doi:10.1126/science.156.3775.636 DOI: https://doi.org/10.1126/science.156.3775.636
17. Mandelbrot BB. The Fractal Geometry of Nature. New York: W. H. Freeman; 1982.
18. Beggs JM, Plenz D. Neuronal avalanches in neocortical circuits. J Neurosci. 2003;23(35):11167–77. doi:10.1523/JNEUROSCI.23-35-11167.2003 DOI: https://doi.org/10.1523/JNEUROSCI.23-35-11167.2003
19. Beggs JM, Plenz D. Neuronal avalanches are diverse and precise activity patterns that are stable for many hours in cortical slice cultures. J Neurosci. 2004;24(22):5216–29. doi:10.1523/JNEUROSCI.0540-04.2004 DOI: https://doi.org/10.1523/JNEUROSCI.0540-04.2004
20. Petermann T, Thiagarajan TC, Lebedev MA, Nicolelis MAL, Chialvo DR, Plenz D. Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc Natl Acad Sci USA. 2009;106(37):15921–6. doi:10.1073/pnas.0904089106 DOI: https://doi.org/10.1073/pnas.0904089106
21. Shriki O, Alstott J, Carver F, Holroyd T, Henson RNA, Smith ML, et al. Neuronal avalanches in the resting MEG of the human brain. J Neurosci. 2013;33(16):7079–90. doi:10.1523/JNEUROSCI.4286-12.2013 DOI: https://doi.org/10.1523/JNEUROSCI.4286-12.2013
22. Tagliazucchi E, Balenzuela P, Fraiman D, Chialvo DR. Criticality in large-scale brain fMRI dynamics unveiled by a novel point process analysis. Front Physiol. 2012;3:15. doi:10.3389/fphys.2012.00015 DOI: https://doi.org/10.3389/fphys.2012.00015
23. Poil SS, Hardstone R, Mansvelder HD, Linkenkaer-Hansen K. Critical-state dynamics of avalanches and oscillations jointly emerge from balanced excitation/inhibition in neuronal networks. J Neurosci. 2012;32(29):9817–23. doi:10.1523/JNEUROSCI.5990-11.2012 DOI: https://doi.org/10.1523/JNEUROSCI.5990-11.2012
24. Friedman N, Ito S, Brinkman BAW, Shimono M, DeVille REL, Dahmen KA, et al. Universal critical dynamics in high resolution neuronal avalanche data. Phys Rev Lett. 2012;108(20):208102. doi:10.1103/PhysRevLett.108.208102 DOI: https://doi.org/10.1103/PhysRevLett.108.208102
25. Ma Z, Turrigiano GG, Wessel R, Hengen KB. Cortical circuit dynamics are homeostatically tuned to criticality in vivo. Neuron. 2019;104(4):655–664.e4. doi:10.1016/j.neuron.2019.08.031 DOI: https://doi.org/10.1016/j.neuron.2019.08.031
26. Chialvo DR. Emergent complex neural dynamics. Nat Phys. 2010;6(10):744–50. doi:10.1038/nphys1803 DOI: https://doi.org/10.1038/nphys1803
27. Shew WL, Plenz D. The functional benefits of criticality in the cortex. Neuroscientist. 2013;19(1):88–100. doi:10.1177/1073858412445487 DOI: https://doi.org/10.1177/1073858412445487
28. Cocchi L, Gollo LL, Zalesky A, Breakspear M. Criticality in the brain: a synthesis of neurobiology, models and cognition. Prog Neurobiol. 2017;158:132–52. doi:10.1016/j.pneurobio.2017.07.002 DOI: https://doi.org/10.1016/j.pneurobio.2017.07.002
29. Strogatz SH. Nonlinear Dynamics and Chaos. 2nd ed. Boulder, CO: Westview Press; 2015.
30. Bruining H, Hardstone R, Juarez-Martinez EL, Sprengers J, Avramiea AE, Simpraga S, et al. Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics. Sci Rep. 2020;10:9195. doi:10.1038/s41598-020-65500-4 DOI: https://doi.org/10.1038/s41598-020-65500-4
31. Tinker J, Velazquez JLP. Power law scaling in synchronization of brain signals depends on cognitive load. Front Syst Neurosci. 2014;8:73. doi:10.3389/fnsys.2014.00073 DOI: https://doi.org/10.3389/fnsys.2014.00073
32. Rubenstein JLR, Merzenich MM. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav. 2003;2(5):255–67. doi:10.1034/j.1601-183X.2003.00037.x DOI: https://doi.org/10.1034/j.1601-183X.2003.00037.x
33. Yizhar O, Fenno LE, Prigge M, Schneider F, Davidson TJ, O'Shea DJ, et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature. 2011;477(7363):171–8. doi:10.1038/nature10360 DOI: https://doi.org/10.1038/nature10360
34. Sohal VS, Rubenstein JLR. Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders. Mol Psychiatry. 2019;24(9):1248–57. doi:10.1038/s41380-019-0426-0 DOI: https://doi.org/10.1038/s41380-019-0426-0
35. Asperger H. Die 'Autistischen Psychopathen' im Kindesalter. Arch Psychiatr Nervenkr. 1944;117:76–136. DOI: https://doi.org/10.1007/BF01837709
36. Frith U, editor and translator. Autism and Asperger Syndrome. Cambridge: Cambridge University Press; 1991. DOI: https://doi.org/10.1017/CBO9780511526770
37. Wing L. Asperger's syndrome: a clinical account. Psychol Med. 1981;11(1):115–29. doi:10.1017/S0033291700053332 DOI: https://doi.org/10.1017/S0033291700053332
38. Baron-Cohen S, Leslie AM, Frith U. Does the autistic child have a 'theory of mind'? Cognition. 1985;21(1):37–46. doi:10.1016/0010-0277(85)90022-8 DOI: https://doi.org/10.1016/0010-0277(85)90022-8
39. Baron-Cohen S. The extreme male brain theory of autism. Trends Cogn Sci. 2002;6(6):248–54. doi:10.1016/S1364-6613(02)01904-6 DOI: https://doi.org/10.1016/S1364-6613(02)01904-6
40. Mottron L, Dawson M, Soulières I, Hubert B, Burack J. Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception. J Autism Dev Disord. 2006;36(1):27–43. doi:10.1007/s10803-005-0040-7 DOI: https://doi.org/10.1007/s10803-005-0040-7
41. Robertson CE, Baron-Cohen S. Sensory perception in autism. Nat Rev Neurosci. 2017;18(11):671–84. doi:10.1038/nrn.2017.112 DOI: https://doi.org/10.1038/nrn.2017.112
42. Jaspers K. General Psychopathology. Hoenig J, Hamilton MW, translators. 2 vols. Baltimore: Johns Hopkins University Press; 1997. (Original work published 1913.)
43. Sass LA, Parnas J. Schizophrenia, consciousness, and the self. Schizophr Bull. 2003;29(3):427–44. doi:10.1093/oxfordjournals.schbul.a007017 DOI: https://doi.org/10.1093/oxfordjournals.schbul.a007017
44. Stanghellini G. Disembodied Spirits and Deanimated Bodies: The Psychopathology of Common Sense. Oxford: Oxford University Press; 2004. doi:10.1093/med/9780198520894.001.0001 DOI: https://doi.org/10.1093/med/9780198520894.001.0001
45. Cooper R. Diagnosing the Diagnostic and Statistical Manual of Mental Disorders. London: Karnac; 2014.
46. Pellicano E. The development of executive function in autism. Autism Res Treat. 2012;2012:146132. doi:10.1155/2012/146132 DOI: https://doi.org/10.1155/2012/146132
47. Insel TR. The NIMH Research Domain Criteria (RDoC) Project: precision medicine for psychiatry. Am J Psychiatry. 2014;171(4):395–7. doi:10.1176/appi.ajp.2014.14020138 DOI: https://doi.org/10.1176/appi.ajp.2014.14020138
48. Linkenkaer-Hansen K, Nikouline VV, Palva JM, Ilmoniemi RJ. Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci. 2001;21(4):1370–7. doi:10.1523/JNEUROSCI.21-04-01370.2001 DOI: https://doi.org/10.1523/JNEUROSCI.21-04-01370.2001
49. Hellyer PJ, Scott G, Shanahan M, Sharp DJ, Leech R. Cognitive flexibility through metastable neural dynamics is disrupted by damage to the structural connectome. J Neurosci. 2015;35(24):9050–63. doi:10.1523/JNEUROSCI.4648-14.2015 DOI: https://doi.org/10.1523/JNEUROSCI.4648-14.2015
50. Loth E, Charman T, Mason L, Tillmann J, Jones EJH, Wooldridge C, et al. The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders. Mol Autism. 2017;8:24. doi:10.1186/s13229-017-0146-8 DOI: https://doi.org/10.1186/s13229-017-0146-8
51. Charman T, Loth E, Tillmann J, Crawley D, Wooldridge C, Goyard D, et al. The EU-AIMS Longitudinal European Autism Project (LEAP): clinical characterisation. Mol Autism. 2017;8:27. doi:10.1186/s13229-017-0145-9 DOI: https://doi.org/10.1186/s13229-017-0145-9
52. Beggs JM, Timme N. Being critical of criticality in the brain. Front Physiol. 2012;3:163. doi:10.3389/fphys.2012.00163 DOI: https://doi.org/10.3389/fphys.2012.00163
53. Wilting J, Priesemann V. 25 years of criticality in neuroscience — established results, open controversies, novel concepts. Curr Opin Neurobiol. 2019;58:105–11. doi:10.1016/j.conb.2019.08.002 DOI: https://doi.org/10.1016/j.conb.2019.08.002
54. Bak P. How Nature Works: The Science of Self-Organized Criticality. New York: Copernicus; 1996. DOI: https://doi.org/10.1007/978-1-4757-5426-1
55. Kanner L. Autistic disturbances of affective contact. Nerv Child. 1943;2:217–50.
56. Kauffman SA. The Origins of Order: Self-Organization and Selection in Evolution. New York: Oxford University Press; 1993. DOI: https://doi.org/10.1093/oso/9780195079517.001.0001
57. McPartland JC, Reichow B, Volkmar FR. Sensitivity and specificity of proposed DSM-5 diagnostic criteria for autism spectrum disorder. J Am Acad Child Adolesc Psychiatry. 2012;51(4):368–83. doi:10.1016/j.jaac.2012.01.007 DOI: https://doi.org/10.1016/j.jaac.2012.01.007
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