
20. James, W. (1890). Principles of Psychology.
21. Kahneman, D., & Tversky, A. (1991). Theory of loss aversion.
22. Kasperson, R.E., et al. (1988). Social Amplificaon of Risk Framework.
23. Krimsky, S. (2007). Internet risks and uncertaines.
24. Larrañaga, M. (2009). Epistemic representaon in scienfic models.
25. Lindzen, R.S. (2007). Climate change controversies.
26. Llinás, R. (2001a). The role of belief in percepon formaon.
27. López-Cerezo, J.A., & Luján, J.L. (2000). Subjecve elements in risk percepon.
28. Marnez-Conde, S., et al. (2005). Neural efficiency in visual processing.
29. Mangan, B. (2003). Fringe consciousness as a semi-permeable membrane.
30. Morrison, M. (2009). Disncon between digital and analog simulaons.
31. Penrose, R. (Citado en [page: 107]). Complex brain distribuon in percepon.
32. Pidgeon, N., et al. (1992). Situaonal factors in risk communicaon.
33. Popper, K. (1962). Measurement process in quantum mechanics.
34. Ropeik, D., & Slovic, P. (2003). Awareness and risk concern relaonship.
35. Russell, B. (1910). Knowledge by acquaintance and descripon.
36. Sarewitz, D. (2004). Complexity of science in decision-making.
37. Searle, J. (2007). Inhibitors of percepon at consciousness threshold.
38. Shrader-Frechee, K. (1988, 1995, 2005). Responsibility and ethics in scienfic decisions.
39. Slovic, P., et al. (1981). Psychometric paradigm of risk percepon.
40. Slovic, P., & Weber, E.U. (2002). Fear and knowledge factors in risk percepon.
41. Smith, J. (2003). Corporate influence on scienfic publicaons.
42. Tarbox, J. (1994). Contrast between philosophical thinkers on percepon.
43. Txapartegi, I. (2004). Connecon between signs and physical properes.
44. Winsberg, E. (2009). Computer simulaons in scienfic research.
Esta revisión bibliográfica demuestra la riqueza y complejidad del estudio de la percepción,
destacando la necesidad de enfoques interdisciplinarios para avanzar en su comprensión completa.