Brain Fields, Complexity, and Consciousness
Complexity science provides more accurate consciousness meters.
Posted Nov 12, 2017
Earlier posts focused on the “easy problem” of consciousness—finding relationships between mental activity and the dynamic patterns measured with various brain imaging methods. This new post advances additional supporting ideas from neuroscience and physics, facilitating our exploration of the “hard problem,” the origin of consciousness itself. Here we stick with classical physics (everything known before 1905). Later posts will employ additional ideas from modern physics, including the controversial idea of possible connections between consciousness and quantum mechanics.
Physicists often label dynamic patterns as fields, and similar ideas are employed in brain science. Scientists speak of temperature fields, electromagnetic fields, gravitational fields, information fields, quantum fields, and more. For example, a temperature field indicates that temperature depends on both location and time. In analogous cases, brain fields might represent patterns of action potentials in individual neurons, synaptic activity, oxygen levels, and so forth in brain tissue masses of various sizes. One simple way to represent brain fields is to employ a “Christmas tree model” as shown in the first figure. Suppose one performs some mental task. Certain parts of the brain may be found to “light up” analogous to Christmas tree lights. In other words, some measure of brain activity, typically electroencephalography (EEG) or functional magnetic resonance imaging (fMRI), will respond when the particular mental task is carried out. While this approach reveals important information, the metaphorical Christmas tree provides only an impoverished brain model. For one thing, a naïve view is that more high level mental activity should correspond to more lights burning or lights burning brighter. But, are such “hot” brains really thinking great thoughts? The answer is no; the fully lighted Christmas tree metaphor corresponds to an epileptic seizure, a decidedly unconscious brain state.
Another issue concerns the “dynamic” aspects of dynamic patterns or brain fields. Consciousness apparently requires certain kinds of brain patterns that persist for at least a half second or so. Furthermore, consciousness is closely associated with special kinds of brain rhythms, recorded as electric field (EEG) oscillations. Apparently, brains must be appropriately “tuned” to be conscious. Finally, there is the issue of the multiscale nature of brain fields. If we magnify small regions of brain tissue we find complicated structure and associated patterns as indicated by the neurons shown in the second figure. Thus, brain fields consist of dynamic sub-sub patterns within sub patterns within patterns measured at different organizational levels (scales). In summary, consciousness evidently requires special types and levels of complexity in brain fields.
Two competing interpretations of brain fields measured at different scales are evident. First, maybe consciousness is encoded in dynamic patterns at some special consciousness scale (the C-scale). In this view, the conscious signatures observed at other scales are mere byproducts of the “mind-creating” C-scale field behavior. Maybe, for example, consciousness is encoded in patterns at the single neuron level, a view embraced by some scientists. Neuroscience, in this view, takes on a reductionist flavor—the single neuron C-scale is then the level where consciousness “resides” or is “encoded.” One implication of this view is that an artificial brain consisting of some hundred billion or so artificial neurons, if appropriately interconnected, might achieve genuine consciousness.
An alternate interpretation is that no special C-scale actually exists; that is, consciousness is fundamentally a multiscale phenomenon. We call this the multi-scale conjecture. In this view, consciousness is encoded by the dynamic patterns occurring at multiple scales. Consciousness is then intimately associated with cross scale interactions—both bottom-up and top-down. The multiscale conjecture argues against philosophical positions that trivialize the complexity of consciousness. In essence, consciousness seems to require systems that are at least as complex as nonconscious life, which consists of interacting multiscale structures—molecules, cells, organ systems, and so forth. Thus, two distinct intellectual domains are proposed in which the multiscale conjecture may operate. First, the multiscale conjecture is to be taken seriously as a stand-alone idea, independent of questions about materialism, dualism, and the hard problem. Second, the multiscale conjecture may provide a tentative bridge connecting brain fields to minimally materialistic or perhaps even nonmaterialistic concepts underlying the hard problem.
For many years most brain scientists avoided the science of complexity, but such omission has lessened over the past 20 years or so (see example references). Complexity science investigates how relationships between the small parts of some entity give rise to the collective behavior of large-scale systems and how these emergent global systems interact and form relationships with lower levels of organization and with the surrounding environment. Entirely new properties emerge at each level of complexity—psychology is not just applied biology; biology is not just applied chemistry; nor is chemistry just applied physics. One notable application of complexity science is the development of more accurate consciousness meters, discussed in a recent article by neuroscientist Christof Koch concerning patients in coma or semiconscious states. This new complexity measure is based on transcranial magnetic stimulation—the patient’s brain is zapped with a strong magnetic field pulse. The stimulated EEG is recorded, and a complexity index is computed from this particular brain field, thereby providing one important measure of the patient’s consciousness or lack thereof. We can expect to see many more applications of complexity science to brain science in the near future.
Christof Koch, How to make a consciousness meter, Scientific American 28–33, Nov. 2017.
Paul L Nunez, The New Science of Consciousness: Exploring the Complexity of Brain, Mind, and Self, Amherst, New York: Prometheus Books, 2016.
Paul L Nunez, Brain, Mind, and the Structure of Reality, New York: Oxford University Press, 2010.
Gerald M Edelman and Giulio Tononi, A Universe of Consciousness, New York: Basic Books, 2000.
Lester Ingber and Paul L Nunez, Statistical mechanics of neocortical interactions: High resolution path-integral calculation of short-term memory, Physical Review E 51: 5074-5083, 1995.
Karl J Friston, Giulio Tononi, Olaf Sporns, and Gerald M Edelman, Characterizing the complexity of neuronal interactions, Human Brain Mapping 3: 302–314, 1995.
Paul L Nunez, Neocortical Dynamics and Human EEG Rhythms, Oxford University Press, 1995.
Lester Ingber, Statistical mechanics of neocortical interactions. i. basic formulation, Physica D 5: 83–107, 1982.