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On Consciousness and Neuroscience
I explained why understanding consciousness is important in my previous blog. In short, theories reason from assumptions not to them. Traditional cognitive theories assume consciousness and therefore can never explain it. This is a serious limitation. Not being able to explain consciousness means that psychologists cannot fully explain all that derives from consciousness which is essentially everything psychological.
I concluded my previous blog by saying that neural network models are computational neuropsychological methods that offer the exciting possibility of advancing our understanding of real brain models including how they compute qualia, including the subjective experience of conscious awareness. In this blog I focus on the brain models of attention that Michael S. A. Graziano (2013) claims cause consciousness in his book entitled Consciousness and the Social Brain.
Graziano reminded us that our conscious experience is a model of external reality, not an exact copy of it, by using white light as an example. White light appears to us as a single pure fully unified experience when in fact it is not. What we perceive as white light is actually composed of all of the wavelengths of the electromagnetic spectrum to which our eyes are sensitive. The neural networks that compose our visual system create, compute, a model of this visual event including the false color qualia of white light. Such qualia help guide our behavior. For example, the qualia of red and green help us find ripe fruit.
Graziano notes that attention and consciousness are closely related in that typically we are only conscious of what we attend to. Brain neural networks compute false colors to help us attend to relevant stimuli such as the example given above of picking ripe fruit. More importantly, humans survived because they lived in groups. It is important to attend to the behavior and motives of other people when living in groups. Graziano reported evidence that the Superior Temporal Sulcus (STS), Temporal Parietal Junction (TPJ) and Medial Prefrontal Cortex (MPFC) mediate social cognition by computing models concerning the motives and intentions of other people. He further claimed that these same structures enable us to attend to our own motives and behaviors by computing self-models that carry the qualia of consciousness. In support of this view, he cites evidence that damage to the STS, and TPJ, especially on the right side, impairs self-awareness in addition to social cognition. Graziano reported that disrupting the right TPJ using transcranial magnetic stimulation can relocate one’s locus of conscious awareness outside of their body.
Graziano uses Arrow A to represent the process by which the brain gives rise to the conscious mind and Arrow B to represent the process by which the conscious mind activates the relevant neural structures that enable us to report that we have a conscious mind for that is the only solid evidence we have that other people are as consciously aware as we are. Graziano observed that essentially all theories of consciousness focus on Arrow A but fail to provide mechanism information for how the mind emerges. For example, the argument that the mind emerges from a sufficiently complex neural network fails to explain how this occurs. Graziano prefers to focus on Arrow B, how conscious awareness enables us to talk about being consciously aware. Graziano concludes that Arrow A must produce conscious awareness in a form that enables it to activate our speech center and the muscles associated with speech. This requires a neural representation that Graziano refers to as a brain neural network model. But that is where Graziano’s explanation ends. He does not provide details regarding what constitutes a real brain model let alone a real brain model of attention that can activate speech.
How do you think that the brain constructs models? What do you think that these models look like? What components do you think are involved? I expect that most readers, including most psychologists, do not have clear answers to these questions because most people think about brain models in highly abstract terms if they think about them at all. Abstraction leaves out details and focuses on functional qualities.
I have consistently encouraged readers of my book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory and blogs to think about psychology and behavior in physical terms. This is not an endorsement of the medical model of psychopathology because while physicians conceptualize disease in physical terms, neuroscience understands both normal and abnormal behavior in physical terms. So how shall we think physically about the brain models that Graziano believes are responsible for computing the qualia of consciousness?
A good answer begins with the observation that the brain is a network of neural networks. This is the foundation that the following investigators built on. Hinton and Shallice (1991, p. 74) argued in favor of simulating connectionist neural networks on the following grounds:
One of the main arguments in favor of connectionist models is that the most effective ways of performing computations in these networks are likely to resemble the most effective ways of performing computations in the brain because the hardware is similar (bold font added for emphasis).
They claim a fundamental similarity, compatibility, between parallel distributed processing connectionist neural network (PDP-CNN) simulations and real brain networks. The entire idea behind these computational neuropsychology (CNP) models is to limit theorizing to the types of resources that the brain actually has. This includes at least the following six neuroscience features:
1. Some form of multilayered neural architecture is involved.
2. Each processing node, simulated neuron, is connected to many others.
3. Each of these connections, simulated synapses, is characterized by a connection weight. Positive values simulate degrees of excitation. Negative values simulate degrees of inhibition.
4. Each simulated neuron in other than the sensory input layer receives multiple inputs that simulate dendrites.
5. The sum of these inputs triggers an output from the receiving node, according to a transfer function, if inputs exceed a threshold.
6. Memory, learning, and other simulated characteristics depend heavily on changing synaptic properties; connection weights. This simulates the well documented neuroscience fact of experience-dependent plasticity.
It follows logically that the resulting parallel distributed processing connectionist neural network models that we have heretofore called “artificial” neural network models may be more real than previously imagined in the sense that real brains may implement the same principles that enable these PDP-CNN models to work. I chose the subtitle of my book to be Network Principles for a Unified Theory to emphasize this possibility. While the biological mechanisms involved in real brain networks differs from the software and hardware simulations of these mechanisms, the principles by which they work may well be the same. This is especially true when simulations are conducted on neuromorphic chips because the forces that drive electrons across transistors are the same as the forces that drive ions across cell membranes. Hence, the simulations that I have supported and illustrated in my book may in fact inform us regarding how the brain computes the social and self-models that I mentioned above.
In my next blog I focus on the general problem of integrating neuroscience facts into psychological theories. I find that psychological theories resist incorporating neuroscience facts because they are expressed in mental terms that are incompatible with physical neuroscience facts.
Warren’s book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is available for purchase on the Elsevier Store.
Use discount code “STC215” at checkout and save up to 30% on your very own copy.
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 firstname.lastname@example.org.
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