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Mechanistic Models and Modeling Disorders

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Book cover Models and Inferences in Science

Part of the book series: Studies in Applied Philosophy, Epistemology and Rational Ethics ((SAPERE,volume 25))

Abstract

Recent debate has focused on how disorders should be modeled, and on how their onset, course and final outcome should be explained. I shall here address some issues arising from modeling neuropsychiatric disorders, which are in many cases still poorly understood, subject to a very high rate of individual variations, and tackled from different disciplinary standpoints. After recalling a few core features of current views on mechanistic models, and related views on psychiatric disorders, I shall discuss some models of Attention Deficit Hyperactivity Disorder. The main aspects of such models are analyzed in the light of the philosophical debate on the elaboration and use of mechanistic models, stressing the distance between the two. The paper highlights the many aspects entering the dynamics of modeling disorders and discusses a few problematic issues of explanatory models elaborated in an actual medical scenario that neo-mechanist accounts can only partly capture.

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Notes

  1. 1.

    For instance, “some computer models are purely how-possibly models” (Craver 2006, p. 366).

  2. 2.

    Kendler is thinking of a mechanistic approach like William Bechtel’s. Kendler also supports, with different motivations, the interventionist view, and suggests an “integrative pluralism” as the most adequate explanatory framework for psychiatry. See Kendler (2005, 2012), Campaner (2014, forthcoming).

  3. 3.

    We cannot dwell here on reductionist and antireductionist stances in psychiatry. See e.g. Schaffner (2013).

  4. 4.

    On mechanisms and psychiatric classification, see also Sirgiovanni (2009).

  5. 5.

    Two subtypes were identified: ADD/H, i.e. with hyperactivity, and ADD/WO, i.e. without hyperactivity.

  6. 6.

    “Pathogenetic models of ADHD have traditionally focused on molecules involved in neurotransmission and catecholamine synaptic dysfunction, including dopamine transporter DAT1 (SLC6A3), dopamine receptors DRD4, DRD5 and synaptosomal protein SNAP-25. More recently neural developmental genes including cadherin 13 (CDH13) and cGMP-dependent protein kinase I (PRKG1) have been associated with ADHD” (Cristino et al. 2014, p. 294; see also, Fowler et al. 2009; Sharp et al. 2009).

  7. 7.

    Medication and behavioural interventions are difficult to isolate completely in order to compare their efficacy. In contexts in which pharmacological treatments are adopted as a consequence of the disorder being diagnosed (e.g. school and home), some form of behavioral intervention—more or less systematic—is usually implemented at the same time.

  8. 8.

    See e.g. Barkeley (1997). All figures are from Sonuga-Barke (2005). Copyright © 2004 Society of Biological Psychiatry. Reprinted with permission of Elsevier.

  9. 9.

    Examples of such processes include “planning and implementing strategies for performance, initiation and discontinuation of actions, inhibiting habitual or prepotent responses or task irrelevant information, performance monitoring, vigilant attention and set switching. Researchers have struggled to understand whether the broad range of ‘executive’ functions are supported by a single unitary process or a diverse array of cognitive processes” (Castellanos et al. 2006, p. 118). Current models are supported by neuroimaging and studies on focal lesions and tend to conceive executive function as a collection of higher-order cognitive control processes.

  10. 10.

    “The fact that dopamine is a key neuro-modulator of both the executive and reward circuits therefore provides further support for the neurobiological plausibility for these cortico-basal ganglia models of AD/HD. At the same time, the fact that each circuit is influenced by inputs from different branches of the dopamine system confirms the differentiation of the pathways” (Sonuga-Barke 2003, p. 598).

  11. 11.

    The most confirmed genes x environmental factors interactions are those between dopaminergic genes and maternal smoking, alcohol abuse during pregnancy and psycho-social adversity (as severe deprivation experience in early childhood).

  12. 12.

    See Kaplan and Craver (2011).

  13. 13.

    On whether diseases are to be regarded as pathological mechanisms, conceived as separate and autonomous entities, or rather as malfunctions of physiological mechanisms, deemed as a conceptual prior over pathological mechanisms, see Nervi (2010), Moghaddam-Taaheri (2011).

  14. 14.

    Let us recall that recovery rates can vary too. Even if it is commonly considered a childhood disorder, ADHD actually endures into adulthood in more than a half of the cases. The relevant interactions between environmental factors and neurodevelopmental components differ over time, according to age, and so do the symptoms. On ADHD in adulthood, see Karama and Evans (2013), Shaw et al. (2013).

  15. 15.

    See Halperin and Healey (2011), Coghill (2014) and Sonuga-Barke and Coghill (2014).

  16. 16.

    On mechanistic modeling as an integrative and iterative process, see Boogerd et al. (2013).

  17. 17.

    See also Bechtel (2010).

  18. 18.

    McManus has convincingly argued that “too much emphasis has been given to the discreteness of parts, foreclosing the possibility that diffuse entities might be epistemically useful in the realm of mechanistic explanation” (McManus 2012, p. 532).

  19. 19.

    Their common final effect grounding individual vulnerability to psychosis is supposed to consist in a sensitization of an individual’s striatum, which is then expressed by modifications in dopamine release in the brain. Investigations are being carried on regarding both genetic and environmental etiologies of dopamine deficits and their effects on the dopamine system in early development.

  20. 20.

    See Oulis (2013a, b).

  21. 21.

    See Batterman (2009), Batterman and Rice (2014) and Rohwer and Rice (2013).

  22. 22.

    Some open issues along these lines are stressed in Campbell et al. (2014).

  23. 23.

    On the relation between mechanistic knowledge and control, see Craver and Darden (2013, Chap. 11).

  24. 24.

    On the co-construction of models and their target systems, see Knuuttila and Boon (2011), Green (2013).

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Authors and Affiliations

  1. Department of Philosophy and Communication, University of Bologna, Bologna, Italy

    Raffaella Campaner

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  1. Raffaella Campaner
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  1. Dipartimento di Filosofia, Sapienza University of Rome, Rome, Italy

    Emiliano Ippoliti

  2. Dipartimento di Filosofia, Sapienza University of Rome, Rome, Italy

    Fabio Sterpetti

  3. Department of Philosophy, University of Nevada, Reno, Nevada, USA

    Thomas Nickles

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Campaner, R. (2016). Mechanistic Models and Modeling Disorders. In: Ippoliti, E., Sterpetti, F., Nickles, T. (eds) Models and Inferences in Science. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-28163-6_7

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