Taming the shrewdness of neural function: Methodological challenges in computational psychiatry

Current Opinion in Behavioral Sciences

Volumn 5, Issue , 2015, Pages 128-132

  Dayan, Peter ^a   Dolan, Raymond J ^b,c   Friston, Karl J ^b   Montague, P Read ^b,d  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b WELLCOME TRUST CENTRE FOR NEUROIMAGING   (United Kingdom)

^c MAX PLANCK UCL CENTRE FOR COMPUTATIONAL PSYCHIATRY AND AGEING RESEARCH   (United Kingdom)

^d VIRGINIA TECH CARILION SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL FUNCTION; DATA ANALYSIS; DECISION MAKING; ELECTRON MICROSCOPY; GENETICS; HUMAN; INFORMATION PROCESSING; METHODOLOGY; NERVE CELL; NERVE POTENTIAL; NERVOUS SYSTEM; NEUROSCIENCE; PSYCHIATRY; REACTION TIME; REVIEW; SCHIZOPHRENIA; STATISTICAL ANALYSIS; TASK PERFORMANCE;

EID: 84945314461     PISSN: None     EISSN: 23521546     Source Type: Journal    
DOI: 10.1016/j.cobeha.2015.09.009     Document Type: Review

References (67)

1. Schwartz E.L. Computational Neuroscience 1993, MIT Press.
2. Sejnowski T.J., Koch C., Churchland P.S. Computational neuroscience. Science 1988, 241:1299-1306.
3. Kass R.E., Eden U.T., Brown E.N. Analysis of Neural Data 2014, Springer.
4. Sejnowski T.J., Churchland P.S., Movshon J.A. Putting big data to good use in neuroscience. Nat Neurosci 2014, 17:1440-1441.
5. Ermentrout G.B., Terman D.H. Mathematical Foundations of Neuroscience 2010, vol 35. Springer Science & Business Media.
6. Cohen J.D., Servan-Schreiber D. Context, cortex, and dopamine: a connectionist approach to behavior and biology in schizophrenia. Psychol Rev 1992, 99:45-77.
7. Hoffman R.E. Computer simulations of neural information processing and the schizophrenia-mania dichotomy. Arch Gen Psychiatry 1987, 44:178-188.
8. Braver T.S., Barch D.M., Cohen J.D. Cognition and control in schizophrenia: a computational model of dopamine and prefrontal function. Biol Psychiatry 1999, 46:312-328.
9. Flint J., Goodwin G. Psychiatric genetics: a genetic basis for health?. Curr Biol 1999, 9:R326-R328.
10. Eichler S.A., Meier J.C. E-I balance and human diseases-from molecules to networking. Front Mol Neurosci 2008, 1:2.
11. Huys Q., Guitart-Masip M., Dolan R., Dayan P. Decision-theoretic psychiatry. Clin Psychol Sci 2015, 10.1177/2167702614562040.
12. Tretter F., Gebicke-Haerter P.J. Systems biology in psychiatric research: from complex data sets over wiring diagrams to computer simulations. Methods Mol Biol 2012, 829:567-592.
13. Maia T.V., Frank M.J. From reinforcement learning models to psychiatric and neurological disorders. Nat Neurosci 2011, 14:154-162.
14. Montague P.R., Dolan R.J., Friston K.J., Dayan P. Computational psychiatry. Trends Cogn Sci 2012, 16:72-80.
15. Huys Q.J.M., Moutoussis M., Williams J. Are computational models of any use to psychiatry?. Neural Netw 2011, 24:544-551.
16. Wang X.J., Krystal J.H. Computational psychiatry. Neuron 2014, 84:638-654.
17. Stephan K.E., Mathys C. Computational approaches to psychiatry. Curr Opin Neurobiol 2014, 25:85-92.
18. Di Martino A., Fair D.A., Kelly C., Satterthwaite T.D., Castellanos F.X., Thomason M.E., Craddock R.C., Luna B., Leventhal B.L., Zuo X.N., Milham M.P. Unraveling the miswired connectome: a developmental perspective. Neuron 2014, 83:1335-1353.
19. Bargary G., Mitchell K.J. Synaesthesia and cortical connectivity. Trends Neurosci 2008, 31:335-342.
20. Gargus J.J. Ion channel functional candidate genes in multigenic neuropsychiatric disease. Biol Psychiatry 2006, 60:177-185.
21. Meyer-Lindenberg A., Tost H. Neuroimaging and plasticity in schizophrenia. Restor Neurol Neurosci 2014, 32:119-127.
22. Wondolowski J., Dickman D. Emerging links between homeostatic synaptic plasticity and neurological disease. Front Cell Neurosci 2013, 7:223.
23. Newman M., Barabasi A.L., Watts D.J. The Structure and Dynamics of Networks 2006, Princeton University Press.
24. Bullmore E., Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 2009, 10:186-198.
25. Sporns O. Networks of the Brain 2011, MIT Press.
26. Jain V., Seung H.S., Turaga S.C. Machines that learn to segment images: a crucial technology for connectomics. Curr Opin Neurobiol 2010, 20:653-666.
27. Shenoy K.V., Sahani M., Churchland M.M. Cortical control of arm movements: a dynamical systems perspective. Annu Rev Neurosci 2013, 36:337-359.
28. Tsuda I. Toward an interpretation of dynamic neural activity in terms of chaotic dynamical systems. Behav Brain Sci 2001, 24:93-810.
29. Kay L.M. A challenge to chaotic itinerancy from brain dynamics. Chaos 2003, 13:1057-1066.
30. Globus G.G., Arpaia J.P. Psychiatry and the new dynamics. Biol Psychiatry 1994, 35:352-364.
31. Mackey M.C., Milton J.G. Dynamical diseases. Ann N Y Acad Sci 1987, 504:16-32.
32. Tretter F., Gebicke-Haerter P.J., an der Heiden U., Rujescu D., Mewes H.W., Turck C.W. Affective disorders as complex dynamic diseases-a perspective from systems biology. Pharmacopsychiatry 2011, 44(Suppl 1):S2-S8.
33. Brodersen K.H., Deserno L., Schlagenhauf F., Lin Z., Penny W.D., Buhmann J.M., Stephan K.E. Dissecting psychiatric spectrum disorders by generative embedding. Neuroimage Clin 2014, 4:98-111.
34. Strogatz S.H. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering 2014, Westview press.
35. Woolrich M.W., Stephan K.E. Biophysical network models and the human connectome. Neuroimage 2013, 80:330-338.
36. Tretter F., Pogarell O., Rujescu D., Meisenzahl E., Mewes H.W. Systems biology of oscillatory processes in sleep and mental disorders. Pharmacopsychiatry 2013, 46(Suppl 1):S1.
37. Heise D.R. Separating reliability and stability in test-retest correlation. Am Sociol Rev 1969, 93-101.
38. Widiger T.A., Samuel D.B. Diagnostic categories or dimensions? A question for the diagnostic and statistical manual of mental disorders-fifth edition. J Abnorm Psychol 2005, 114:494-504.
39. Markon K.E., Krueger R.F. Information-theoretic latent distribution modeling: distinguishing discrete and continuous latent variable models. Psychol Methods 2006, 11:228-243.
40. Goldberg D. Plato versus Aristotle: categorical and dimensional models for common mental disorders. Compr Psychiatry 2000, 41:8-13.
41. Steyer R., Ferring D., Schmitt M.J. States and traits in psychological assessment. Eur J Psychol Assess 1992, 79-98.
42. Collins L.M. Analysis of longitudinal data: the integration of theoretical model, temporal design, and statistical model. Annu Rev Psychol 2006, 57:505-528.
43. McArdle J.J. Latent variable modeling of differences and changes with longitudinal data. Annu Rev Psychol 2009, 60:577-605.
44. Proust-Lima C., Amieva H., Jacqmin-Gadda H. Analysis of multivariate mixed longitudinal data: a flexible latent process approach. Br J Math Stat Psychol 2013, 66:470-487.
45. Fitzmaurice G., Davidian M., Verbeke G., Molenberghs G. Longitudinal Data Analysis 2008, CRC Press.
46. Bollen K.A., Curran P.J. Latent curve models: A structural equation perspective 2006, vol 467. John Wiley & Sons.
47. Verbeke G., Fieuws S., Molenberghs G., Davidian M. The analysis of multivariate longitudinal data: a review. Stat Methods Med Res 2014, 23:42-59.
48. Floyd F.J., Widaman K.F. Factor analysis in the development and refinement of clinical assessment instruments. Psychol Assess 1995, 7:286.
49. Fabrigar L.R., Wegener D.T., MacCallum R.C., Strahan E.J. Evaluating the use of exploratory factor analysis in psychological research. Psychol Methods 1999, 4:272.
50. McLachlan G., Peel D. Finite Mixture Models 2004, John Wiley & Sons.
51. Gibbons R.D., Dorus E., Ostrow D.G., Pandey G.N., Davis J.M., Levy D.L. Mixture distributions in psychiatric research. Biol Psychiatry 1984, 19:935-961.
52. Lubke G.H., Muthén B. Investigating population heterogeneity with factor mixture models. Psychol Methods 2005, 10:21.
53. Skrondal A., Rabe-Hesketh S. Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models 2004, CRC Press.
54. Kohavi R., et al. A study of cross-validation and bootstrap for accuracy estimation and model selection. IJCAI, vol 14 1995, 1137-1145.
55. Penny W. Comparing dynamic causal models using AIC, BIC and free energy. Neuroimage 2012, 59:319-330.
56. Kruschke J.K. Bayesian data analysis. Wiley Interdiscip Rev Cogn Sci 2010, 1:658-676.
57. Lee M.D., Wagenmakers E.J. Bayesian Cognitive Modeling: A Practical Course 2014, Cambridge University Press.
58. Daw N.D. Trial-by-trial data analysis using computational models. Decision Making, Affect, and Learning: Attention and Performance XXIII 2011, vol 23:3-38. Oxford University Press.
59. Stan Development Team Stan Modeling Language User's Guide and Reference Manual 2014.
60. Moutoussis M., Bentall R.P., El-Deredy W., Dayan P. Bayesian modelling of jumping-to-conclusions bias in delusional patients. Cogn Neuropsychiatry 2011, 16:422-447.
61. Mour ao-Miranda J., Hardoon D.R., Hahn T., Marquand A.F., Williams S.C.R., Shawe-Taylor J., Brammer M. Patient classification as an outlier detection problem: an application of the one-class support vector machine. Neuroimage 2011, 58:793-804.
62. Huber P.J. Robust Statistics 2011, Springer.
63. Hertzog C., Nesselroade J.R. Assessing psychological change in adulthood: an overview of methodological issues. Psychol Aging 2003, 18:639.
64. McArdle J.J., Grimm K.J., Hamagami F., Bowles R.P., Meredith W. Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement. Psychol Methods 2009, 14:126-149.
65. Nesselroade J.R. The warp and the woof of the developmental fabric. Visions of Aesthetics, The Environment, and Development: The Legacy of Joachim F. Wohlwill 1991, 213-240. Erlbaum Hillsdale, NJ. R.M. Downs, L.S. Liben, D.S. Palermo (Eds.).
66. Lövdén M., Bäckman L., Lindenberger U., Schaefer S., Schmiedek F. A theoretical framework for the study of adult cognitive plasticity. Psychol Bull 2010, 136:659.
67. Song C., Kuo L., Derby C.A., Lipton R.B., Hall C.B. Multi-stage transitional models with random effects and their application to the Einstein aging study. Biom J 2011, 53:938-955.