Complexity measures in molecular psychiatry

Molecular Psychiatry

Volumn 1, Issue 5, 1996, Pages 408-416

  Rapp, P E ^a   Schmah, T ^b  

^a DREXEL UNIVERSITY COLLEGE OF MEDICINE   (United States)

^b BRYN MAWR COLLEGE   (United States)

Author keywords

Algorithmic complexity; Choice task paradigm; Electroencephalograms; Electromyograms; Interspike intervals; Metric entropy; Protocol analysis; Stochastic model complexity; Symbolic dynamics; Topological entropy

Indexed keywords

ALGORITHM; ANIMAL; ANIMAL BEHAVIOR; BIOLOGICAL MODEL; ELECTROENCEPHALOGRAPHY; ELECTROMYOGRAPHY; ENTROPY; HUMAN; MOLECULAR BIOLOGY; PHYSIOLOGY; PSYCHIATRY; REVIEW;

ALGORITHMS; ANIMALS; BEHAVIOR, ANIMAL; ELECTROENCEPHALOGRAPHY; ELECTROMYOGRAPHY; ENTROPY; HUMANS; MODELS, BIOLOGICAL; MOLECULAR BIOLOGY; PSYCHIATRY;

EID: 0030275488     PISSN: 13594184     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (83)

1. Simansky KJ, Vaidya AH. Behavioral mechanisms for the anorectic action of the serotonin (5-HT) uptake inhibitor sertraline in rates: comparison with directly acting 5-HT agonists. Brain Res Bull 1990; 50: 953-960.
2. Crutchfield JP, Packard NH. Noise scaling of symbolic dynamics entropies. In: Haken H (ed). Evolution of Order and Chaos. Springer-Verlag: Berlin, 1983, pp 215-227.
3. Huberman BA, Hogg T. Complexity and adaptation. Physica 1986; 22D: 376-384.
4. Rapp PE, Jiménez-Montaño MA, Langs RJ, Thomson L. Quantitative characterization of patient-therapist communication. Math Biosci 1991; 105: 207-227.
5. Xu J. The measure of sequence complexity for EEG studies. Chaos, Solitons and Fractals 1994; 4: 2111-2119.
6. D'Alessandro G, Politi A. Hierarchical approach to complexity with applications to dynamic systems. Phys Rev Letts 1990; 64: 1609-1612.
7. Wolfram S. Computation theory of cellular automata. Commun Math Physics 1984; 96: 15-57.
8. Grassberger P. Toward a quantitative theory of self-generated complexity. Int J Theoret Phys 1986; 25: 907-938.
9. Kolmogorov AN. Three approaches to the definition of the concept of quantity of information. IEEE Trans Inform Theory 1965; IT14: 662-669.
10. Chaitin GJ. Information theoretical computational complexity. IEEE Trans Inform Theory 1974; IT20: 10-15.
11. Zvonkin AK, Levin LA. The complexity of finite-objects and the development of the concepts of information and randomness by means of the theory of algorithms. Russ Math Survey 1970; 25: 83-124.
12. Watanabe O (ed). Kolmogorov Complexity and Computational Complexity. Springer-Verlag: Berlin, 1992.
13. Li M, Vitányi P. An Introduction to Kolmogorov Complexity and Its Applications. Springer-Verlag: New York, 1993.
14. Ebling W, Jiménez-Montaño MA. On grammars, complexity and information measures of biological macromolecules. Math Biosci 1980; 52: 53-71.
15. Jiménez-Montanó MA. On the syntactic structure of protein sequences and the concept of complexity. Bull Math Biol 1984; 46: 641-659.
16. Crutchfield JP, Young K. Inferring statistical complexity. Phys Rev Lett 1989; 63: 105-108.
17. Rissanen JA. Universal data compression system. IEEE Trans Inform Theory 1983; IT29: 656-664.
18. Rissanen J. Stochastic complexity and modeling. Ann Stats 1986; 14: 1080-1100.
19. Rissanen J. Universal coding, information, prediction, and estimation. IEEE Trans Inform Theory 1984; IT30: 629-636.
20. Schwartz G. Estimating the dimension of a model. Ann Stat 1978; 6: 461-464.
21. Auerbach D, Procaccia I. Grammatical complexity of strange sets. Phys Rev 1990; 41A: 6602-6614.
22. Hao BL. Symbolic dynamics and characterization of complexity. Physica 1991; 51D: 161-176.
23. Kaspar F, Schuster HG. Easily calculable measure for the complexity of spatiotemporal patterns. Phys Rev 1987; 36A: 842-848.
24. Rissanen J. Estimation of structure by minimum description length. Circuit Systems Signal Processing 1982; 1: 395-396.
25. Rissanen Y. Stochastic Complexity in Statistical Inquiry. World Scientific: Singapore, 1992.
26. Schuster HG. Information content of chaotic signals. Physica Scripta 1989; 40: 367-372.
27. Wallace CS, Boulton DM. An information measure for classification. Computer J 1968; 11: 185-195.
28. Wolfram S. Cellular automata as models of complexity. Nature 1984; 311: 419-424.
29. Storella RJ, Shi Y, Wood HW, Jiménez-Montaño MA, Albano AM, Rapp PE. The variance and the algorithmic complexity of heart rate variability display different responses to anesthesia. Intn J Bifurcation and Chaos 1996; (in press).
30. Paulus MP, Geyer MA, Gold LH, Mandell AJ. Application of entropy measures derived from the ergodic theory of dynamical systems to rat locomotor behavior. Proc Natn Acad Sci 1990; 87: 723-727.
31. Paulus MP, Geyer MA. The effects of MDMA and other methylenedioxy-substituted phenylalkylamines on the structure of rat locomotor activity. Neuropsychopharmacology 1992; 7: 15-31.
32. Paulus MP, Callaway CW, Geyer MA. Quantitative assessment of the microstructure of rat behavior: II Distinctive effects of dopamine releasers and uptake inhibitors. Psychopharmacology 1993; 113: 187-198.
33. Paulus MP, Geyer MA. Quantitative assessment of the microstructure of rat behavior: I f(d), the extension of the scaling hypothesis. Psychopharmacology 1993; 113: 177-186.
34. Paulus MP, Geyer MA. Three independent factors characterize spontaneous rat motor activity. Behav Brain Res 1993; 53: 11-20.
35. Paulus MP, Kadtke JB, Menkello FV. Statistical mechanics of biological and other complex experimental time series: assessing geometrical and dynamical properties. Int J Bifurcation and Chaos 1993; 3: 717-727.
36. Selz KA, Mandell AJ, Anderson CM, Smotherman WP, Teicher TH. Distributions of local Mandelbrot-Hurst exponents: motor activity in cocaine treated fetal rats and manic-depressive patients. Fractals 1995; 3: 893-904.
37. Smotherman WP, Selz KA, Mandell AJ. Dynamical entropy is conserved during cocaine-induced changes in fetal rat motoric patterns. Psychoneuroendocrinology 1995; 20: 31-46.
38. Sherry CJ, Klemm WR. Failure of large doses of ethanol to eliminate Markovian serial dependencies in neuronal spike train intervals. Int J Neurosci 1982; 17: 109-117.
39. Sherry CJ, Klemm WR. Divergence from statistical independence in specified clusters of adjacent neuronal spike train intervals before and after ethanol state changes. Int J Neurosci 1982; 17: 119-128.
40. Sherry CJ, Klemm WR. What is the meaningful measure of neuronal spike train activity? J Neurosci Meth 1984; 10: 205-213.
41. Klemm WR, Sherry CJ. Do neurons process information by relative intervals in spike trains? Neurosci Biobehav Rev 1982; 6: 429-437.
42. Dayhoff JE. Distinguished words in data sequences: analysis and applications to neural coding and other fields. Bull Math Biol 1984; 46: 529-543.
43. Dayhoff JE, Gerstein GL. Favored patterns in spike trains. I. Detection. J Neurophysiol 1983; 49: 1334-1346.
44. Dayhoff JE, Gerstein GL. Favored patterns in spike trains. II. Application. J Neurophysiol 1983; 49: 1347-1363.
45. Mandell AJ, Selz KA. Brain stem neuronal noise and neocortical resonance. J Stat Phys 1993; 70: 355-373.
46. Mandell AJ, Selz KA. Resonance, synchronization and lexical redundancy in the expanding dynamics of brains stem neurons. Int Soc Opt Engng. SPIE Proc 1994; 2036: 86-99.
47. Selz KA, Mandell AJ. Bernoulli partition-equivalence of intermittent neuronal discharge patterns. Int J Bifurcation and Chaos 1991; 1: 717-722.
48. Rapp PE, Zimmerman ID, Vining EP, Cohen N, Albano AM, Jiménez-Montaño MA. The algorithmic complexity of neural spike trains increases during focal seizures. J Neurosci 1994; 14: 4731-4739.
49. Rapp PE, Albano AM, Zimmerman ID, Jiménez-Montanó MA. Phase-randomized surrogates can produce spurious identifications of non-random structure. Phys Lett 1994; 192A: 27-33.
50. Theiler J, Eubank S, Longtin A, Galdrikian B, Farmer JD. Testing for nonlinearity in time series: the method of surrogate data. Physica 1992; 58D: 77-94.
51. Rapp PE, Goldberg G, Albano AM, Janicki MB, Murphy D, Niemeyer E, Jiménez-Montanó MA. Using coarse-grained measures to characterize electromyographic signals. Int J Bifurcation and Chaos 1993; 3: 525-542.
52. Teicher MH, Lawrence JM, Barber NI, Finkelstein SP, Lieberman H, Baldessarini RJ. Altered locomotor activity in neuropsychiatric patients. Prog Neuropsychopharm Biol Psych 1981; 10: 755-761.
53. Wu X-B, Xu J. Complexity and brain function. In: Li ZP (ed). Retrospect and Prospect of Protein Research. World Scientific: Singapore, 1991, pp 247-253.
54. Xu J-H, Wu X-B. The information transmission on cerebral cortex based on the complexity measures of EEG signals. In: Eisenfeld J, Levine DS, Witten M (eds). Biomedical Modeling and Simulation. Elsevier: Amsterdam, 1992, pp 375-381.
55. Xu J-H, Wu X-B. Using complexity measure to characterize information transmission in the human cortex. Science in China (Series B) 1994; 37: 1455-1462.
56. Xu J, Liu Z-R, Liu R, Yang Q-F. The information transmission of human brain cortex. J Computational Neurosci 1996; (in press).
57. Theiler J, Rapp PE. Re-examination of evidence for low-dimensional nonlinear structure in the human electroen-cephalogram. Electroenceph Clin Neurophysiol 1996; 98: 213-222.
58. Rapp PE. Chaos in the neurosciences: cautionary tales from the frontier. The Biologist (Institute of Biology, London) 1993; 40: 89-94.
59. Matarazzo JD, Wiens AN. The Interview: Research on Its Anatomy and Structure. Aldine-Atherton: Chicago, 1972.
60. Harper RB, Wiens AN, Matarazzo JD. Nonverbal Communication: The State of the Art. Wiley: New York, 1978.
61. Matarazzo JD, Wiens AN, Jackson RH, Manaugh TS. Interviewee speech behavior under conditions of endogenously-present and exogenously-induced motivational states. J Clin Psychol 1970; 26: 141-148.
62. Matarazzo JD, Wiens AN, Jackson RH, Manaugh TS. Interviewee speech behavior under different conditions. J Appl Psychol 1970; 54: 15-26.
63. Winefield HR, Basset DL, Chandler MA, Proske I. Process in psychotherapy as decreasing asymmetry betwen patient and therapist: evidence from verbal interaction. Am J Psychother 1987; 41: 117-126.
64. Berelson B. Content Analysis in Communication Research. Hafner/Free Press: New York, 1971.
65. Holsti OR. Content Analysis for Social Sciences and Humanities. Addison-Wesley: Reading, MA, 1969.
66. Lolas F, Mergenthaler E, von Rad M. Content analysis of verbal behavior in psychotherapy research: a comparison between two methods. Br J Med Psychol 1982; 55: 327-333.
67. Gottschalk LA, Gleser GC. The Measurement of Psychological States Through the Content of Verbal Behavior. University of California Press: Berkeley, CA, 1969.
68. Rapp PE, Jiménez-Montanó MA, Langs RJ, Thomson L. Quantitative characterization of patient-therapist communication. Math Biosci 1991; 105: 207-222.
69. Langs R, Rapp PE, Pinto A, Cramer G, Badalamenti A. Three quantitative studies of gender and identity in psychotherapy consultations. Am J Psychotherapy 1992; 46: 183-206.
70. Rachlin H, Logue AW, Gibbon J, Frankel M. Cognition and behavior in studies of choice. Psychol Rev 1986; 93: 33-45.
71. Gray JA, Feldon J, Rawlins JNP, Hemsley DR, Smith AD. The neuropsychology of schizophrenia. Behav Brain Sci 1991; 14: 1-19.
72. Frith CD, Done DJ. Stereotyped responding by schizophrenic patients on a two-choice guessing task. Psych Med 1983; 13: 779-786.
73. Lyon M, Lyon N, Magnusson MS. The importance of temporal structure in analyzing schizophrenic behavior: some theoretical and diagnostic implications. Schizophrenia Res 1994; 13: 45-56.
74. Lyon N, Gerlach J. Perseverative structuring of responses by schizophrenic and affective disorder patients. J Psychiatry Res 1985; 22: 261-277.
75. Lyon N, Gerlach J. Perseverative structuring of responses of schizophrenic and affective patients. J Psychiatric Res 1988; 22: 261-277.
76. Wise RA. The role of reward pathways in development of drug dependence. Pharmacol Ther 1987; 35: 227-263.
77. Paulus MP, Geyer MA, Braff DL. The assessment of sequence response organization in schizophrenic and control subjects. Prog Neuro-Psychopharmacol & Biol Psychiatry 1994; 18: 1169-1185.
78. Selz KA. Mixing Properties in Human Behavioral Style and Time Dependencies in Behavior Identification: The Modeling and Application of a Universal Dynamical Law. Doctoral Dissertation, Florida Atlantic University (University Microfilms International), 1992.
79. Selz KA, Mandell AJ. Style as mechanism: from man to a map of the interval and back. SPIE 1993; 2036: 174-182.
80. Selz KA, Mandell AJ. A family of autocorrelation graph equivalence classes on symbolic dynamics as models of individual differences in human behavioral style. In: Vallacher RR, Nowak AJ (eds). Dynamical Systems in Social Psychology. Academic Press: NY, 1994, pp 169-197.
81. Selz KA, Mandell AJ. Recovering a deterministic equation with a parametric relation to age from apparently random human behavior. Preprint: Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 1996.
82. Owen MJ, Craddock N. Modern molecular genetic approaches to complex traits: implications for psychiatric disorders. Mol Psychiatry 1996; 1: 21-26.
83. Plomin R, Owen MJ, McGuffin P. The genetic basis of complex human behaviors. Science 1994; 264: 1733-1739.