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Top-Down, Bottom-Up Processing
This blog presents the final corollary principle that I discuss in my book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory beginning on page 249. I refer to it as Top-down vs. Bottom-up processing to emphasize the bidirectional network flow that occurs among our network of neural networks. Introductory psychology textbooks tend to emphasize network flow from the sense organs to higher brain centers. I refer to this as Bottom-up processing. However, expectations govern what we perceive. This involves network flow from higher brain centers “down” to lower brain centers and to sensory organs. The remainder of this blog concerns this Top-down processing.
Before I begin, I want to defend my use of the term “Top-down” against Gazzaniga’s (2011, p. 70) claim that this term is just another word for a homunculus, a central processor that controls what we do and provides us with our sense of being unified as a person and in control. Neuroscientists have worked long and hard to remove the ghost from the machine; to discredit the idea that some central processing center, a homunculus, makes all of our decisions and this “little man” is what psychology should study. Gazzaniga also disparages the term “executive functions” for the same reasons. I make no such central decision claims when I use the term Top-down processing. Gazzaniga and I agree that the brain is democratic; it is composed of many neurons and neural networks. Each neuron “votes” by turning on or off. Neural networks “vote” in direct proportion to their level of activation. The decisions that we feel that we make are the result of these votes which occur between a third of a second and ten seconds before the results enter our consciousness. I elaborate on this point on page 116 of my book as follows:
The massive empirical evidence reviewed in Chapter 3 concerning unconscious processing, and especially the evidence that brain changes precede conscious decision, seriously undercuts both free will and final causes. It seems that we are the editor/monitor of our thoughts rather than their author/originator. The temporal delay between brain activation and conscious decision is short but decisively sufficient to settle this matter.
Clearly the brain has “higher” and “lower” brain centers and they interact with each other. I use the terms Top-down and Bottom-up to refer to the direction that activations take from one network to another. I concur with Gazzaniga that the speech center located in the left hemisphere, what he calls the “interpreter module” (p. 73) is responsible for the illusion that we are the authors of our lives.
Nature conserves neural networks. For example, the neural network that we use for vision (Kosslyn & Thompson, 2000) also mediates our imagination (Farah, 2000). When we visualize an object, when we place it in our imagination, the neural networks that mediate vision become active. A supporting study was recently reported by Laeng and Sulutvedt (2014). They demonstrated that imaginary light activates the same neural networks that control pupil size as does real light. The authors cited (without source identification) that 130 years ago Sir Francis Galton (1883/1907) asked “Is the brightness of a mental image comparable to that of the actual scene?” They noted that pupil size reacts unconsciously and uncontrollably to brightness of light therefore precluding the possibility of faking a correct response. The authors measured pupil diameter under actual perception and active imagery conditions regarding dark and bright images. They reported that pupil diameter changed in the same ways when light was imagined as when light was actually present. Imaginary light produced smaller changes than real light did. Pupils constricted when participants imagined the bright image and dilated when they imagined the dark image just as is the case when viewing the bright and dark images. This is hard evidence that imagination activates at least some the same neural networks that control pupil diameter, but to a lesser degree, than real light does.
One of the functions that our higher brain centers perform is to generate Internal Working Models. On page 249 of my book I noted that:
Eagleman (2011, pp. 48–51) described top-down processing as what Internal working modelsdo. These models are built up from years of experience. They generate expectations. These expectations are combined with sensory data that are processed from the bottom up. The result is sensory experience modulated by expectations generated by these internal working models. Eagleman (2011, p. 45) used the term anchored perceptions to refer to this phenomenon. One way to experimentally demonstrate the validity of this claim is to unanchor perception. Placing persons in pitch-dark solitary confinement is one way to do this. Another way is to put participants into a sensory deprivation chamber. While short-term sensory deprivation can be described as relaxing and conducive to meditation, long term sessions can produce hallucinations.
In sum, the brain is a network of neural networks. What I refer to as Bottom-up activations proceed from the sensory organs to central brain areas. What I refer to as Top-down activations proceed from “higher” brain centers, such as those located in the frontal lobes, to other areas of the brain and perhaps even to sensory organs. I discuss prospection, placebos, and nocebos in my next blog.
About the Author

Warren W. Tryon received his undergraduate degree from Ohio Northern University in 1966. He was enrolled in the APA approved Doctoral Program in Clinical Psychology at Kent State University from 1966 – 1970. Upon graduation from Kent State, Dr. Tryon joined the Psychology Department faculty at Fordham University in 1970 as an Assistant Professor. He was promoted to Associate Professor in 1977 and to Full Professor in 1983. Licensed as a psychologist in New York State in 1973, he joined the National Register of Health Service Providers in Psychology in 1976, became a Diplomate in Clinical Psychology from the American Board of Professional Psychology (ABPP) in 1984, was promoted to Fellow of Division 12 (Clinical) of the American Psychological Association in 1994 and a fellow of the American Association of Applied and Preventive Psychology in 1996. Also in 1996 he became a Founder of the Assembly of Behavior Analysis and Therapy. In 2003 he joined The Academy of Clinical Psychology. He was Director of Clinical Psychology Training from 1997 to 2003, and presently is in the third and final year of phased retirement. He will become Emeritus Professor of Psychology in May 2015 after 45 years of service to Fordham University. Dr. Tryon has published 179 titles, including 3 books, 22 chapters, and 140 articles in peer reviewed journals covering statistics, neuropsychology, and clinical psychology. He has reviewed manuscripts for 45 journals and book publishers and has authored 145 papers/posters that were presented at major scientific meetings. Dr. Tryon has mentored 87 doctoral dissertations to completion. This is a record number of completed dissertations at the Fordham University Graduate School of Arts and Sciences and likely elsewhere.
His academic lineage is as follows. His mentor was V. Edwin Bixenstein who studied with O. Hobart Mowrer at the University of Illinois who studied with Knight Dunlap at Johns Hopkins University who studied with Hugo Munsterberg at Harvard University who studied with Wilhelm Wundt at the University of Leipzig.
Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is Dr. Tryon’s capstone publication. It is the product of more than a quarter of a century of scholarship. Additional material added after this book was printed is available at www.fordham.edu/psychology/tryon. This includes chapter supplements, a color version of Figure 5.6, and a thirteenth “Final Evaluation” chapter. He is on LinkedIn and Facebook. His email address is wtryon@fordham.edu.
This blog and all others by Dr. Warren Tryon can be found on his Fordham faculty webpage located at www.fordham.edu/psychology/tryon.
References
Eagleman, D. (2011). Incognito: The secret lives of the brain. New York: Vintage Books.
Farah, M. J. (2000). The neural bases of mental imagery. In M. S. Gazzaniga (Ed.). The new cognitive neurosciences (2nd ed, pp. 965-974). Cambridge, MA: The MIT Press.Gazzaniga, M. S. (2011). Who’s in charge? Free will and the science of the brain. New York: HarperCollins.
Kosslyn, S. M., & Thompson, W. L. (2000). Shared mechanisms in visual imagery and visual perception: Insights from cognitive neuroscience. In M. S. Gazzaniga (Ed.). The new cognitive neurosciences (2nd ed, pp. 975-985). Cambridge, MA: The MIT Press.
Laeng, B., & Sulutvedt, U. (2014). The eye pupil adjusts to imaginary light. Psychological Science, 25 (1), 188-197. doi 10.1177/0956797613503556
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