Every couple of years, I seem to go back and look at “decision making” books that have arrived in my local library. I clearly take a broad view of decision making. This time I came up with Farsighted, Elastic, and the Mind is Flat. The first two books were definitely written to be popular books with the third less so. They share quite a bit. They all rely quite a bit on illustrations or questionnaires that show the peculiarities and shortcomings of our minds. They all rely on literature to explain their cases on how our minds work. Farsighted uses George Eliot and Middlemarch. Elastic uses Jonathan Franzen and mentions his book Corrections. The Mind is Flat uses Leo Tolstoy and Anna Karenina.
This post is based on the paper: “Priors in perception: Top-down modulation, Bayesian
perceptual learning rate, and prediction error
minimization,” authored by Jakob Hohwy (see post Explaining Away) that appeared (or is scheduled to appear) in Consciousness and Cognition, 2017. Hohwy writes in an understandable manner and is so open that he posts papers even before they are complete of which this is an example. Hohwy pursues the idea of cognitive penetration – the notion that beliefs can determine perception.
Can ‘high level’ or ‘cognitive’ beliefs modulate perception? Hohwy methodically examines this question by trying to create the conditions under which it might work and not be trivial. For under standard Bayesian inference, the learning rate declines gradually as evidence is accumulated, and the prior updated to be ever more accurate. The more you already know the less you will learn from the world. In a changing world this is not optimal since when things in the environment change we should vary the learning rate. Hohwy provides this example. As the ambient light conditions improve, the learning rate for detecting a visible target should increase (since the samples and therefore the prediction error has better precision in better light). This means Bayesian perceptual inference needs a tool for regulating the learning rate. The inferential system should build expectations for the variability in lighting conditions throughout the day, so that the learning rate in visual detection tasks can be regulated up and down accordingly.
The human brain is thus hypothesized to build up a vast hierarchy of expectations that overall help regulate the learning rate and thereby optimize perceptual inference for a world that delivers changeable sensory input. Hohwy suggests that this makes the brain a hierarchical filter that takes the non-linear time series of sensory input and seeks to filter out regularities at different time scales. Considering the distributions in question to be normal or Gaussian, the brain is considered a hierarchical Gaussian filter or HGF .
This post examines the paper: “Are There Levels of Consciousness?” written by
Tim Bayne, Jakob Hohwy, and Adrian M. Owen, that appeared in Trends in Cognitive Sciences, June 2016, Vol. 20, No. 6. The paper is described as opinion and for me bridges ideas of predictive processing with some of the ideas of Stanislas Dehaene. Jakob Hohwy is an important describer of predictive processing. The paper argues that the levels-based or continuum based framework for conceptualizing global states of consciousness is untenable and develops in its place a multidimensional account of global states.
Consciousness is typically taken to have two aspects: local states and global states. Local states of consciousness include perceptual experiences of various kinds, imagery experiences, bodily sensations, affective experiences, and occurrent thoughts. In the science of consciousness local states are usually referred to as ‘conscious contents. By contrast, global states of consciousness are not typically distinguished from each other on the basis of the objects or features that are represented in experience. Instead, they are typically distinguished from each other on cognitive, behavioral, and physiological grounds. For example, the global state associated with alert wakefulness is distinguished from the global states that are associated with post-comatose conditions.
The authors suggest that to describe global states as levels of consciousness is to imply that consciousness comes in degrees, and that changes in a creature’s global state of consciousness can be represented as changes along a single dimension of analysis. Bayne, Hohwy, and Owen see two problems with this. One person can be conscious of more objects and properties than another person, but to be conscious of more is not to be more conscious. A sighted person might be conscious of more than someone who is blind, but they are not more conscious than the blind person is. The second problem that they see with the level-based analysis of global states is that there is good reason to doubt whether all global states can be assigned a determinate ordering relative to each other. The authors provide the example of the relationship between the global conscious state associated with rapid eye movement (REM) sleep and that which is associated with light levels of sedation. They do not believe that one of these states must be absolutely ‘higher’ than the other. Perhaps states can be compared with each other only relative to certain dimensions of analysis: the global state associated with REM sleep might be higher than that associated with sedation on some dimensions of analysis, whereas the opposite might be the case on other dimensions of analysis (Figure 1A).
The authors recognize two clear dimensions, but suggest there are likely several more. The first is gating. In some global states the contents of consciousness appear to be gated in various ways, with the result that individuals are able to experience only a restricted range of contents. MCS patients, patients undergoing absence seizures, and mildly sedated individuals can consciously represent the low-level features of objects, but they are typically unable to represent the categories to which perceptual objects belong. Thus, the gating of conscious contents is likely to provide one dimension along which certain global states can be hierarchically organized. The second dimension of consciousness is often captured by saying that the contents of consciousness are globally available for the control of thought and action. However, there is good reason to think that it is compromised in a number of pathologies of consciousness. For example, patients undergoing absence seizures can engage in perceptual-driven motor responses even though their capacities for reasoning, executive processing, and memory consolidation are typically limited. With respect to this dimension, the global state of consciousness associated with the EMCS is ‘higher’ than that which is associated with the MCS, for EMCS patients have access to a wider range of cognitive and behavioral consuming systems than MCS patients do.
Beyond the dimensions of gating of contents and the availability associated with consciousness, the authors suggest there might there be a role for attention in structuring global states. There is also the question of the possibility of interaction between some of the dimensions that structure consciousness. Although some dimensions may be completely independent of each other, others are likely to modulate each other. For example, there might be interactions between the gating of contents and functionality such that consciousness cannot be high on the gating dimension but low on certain dimensions of functionality (Figure 1C).
This idea that global states of consciousness are best understood as regions in a multidimensional space seems to me a natural progression as we learn more about consciousness and its underpinnings. An example is the time when you are completely immersed in some task and you don’t notice time passing or who walked by. Your attention is completely focused and gated so that you are missing other things. It is not a higher level of consciousness, but a different level of consciousness. The spotlight is focused on a smaller area. The light itself is not any brighter. At the same time, the argument that Bayne, Hohwy and Owen are making seems to be focused at very limited consciousness. Most of us just see a sleeping person as unconscious without an active global neuronal workspace. We do not see a person as conscious until some threshold or phase change occurs so that the light is brighter so that the availability is greater. There must be some level of error coming back from our predictions. Several previous posts including Consciousness. Confessions of a Romantic Reductionist, The Global Neuronal Workspace, and Dehaene: Consciousness and Decision Making, have looked at consciousness. This paper did not address the consciousness of other animals. It also did not address Intuition which is often considered unconscious in some ways since it is typically effortless as we perceive it. Global availability seems important to the idea. Of course, as you develop expertise, global availability is not so necessary for certain subjects. Auto-pilot can handle normal situations once you have expertise so maybe we all have different conscious realms since we have different expertise.
Frankly, I doubt that many would argue that consciousness has only a single dimension. Dehaene may ignore multiple dimensions, but I would suggest that he does this to make the idea more understandable to laymen.
This post joins several others in being only tangentially related to JDM. It is based on the paper: “The felt presence of other minds: predictive processing, counterfactual predictions, and mentalizing in autism,” that appears in 2015 Consciousness and Cognition. The authors are Colin J. Palmer, Anil K. Seth and Jakob Hohwy. (Post Prediction error minimization)
A central ingredient of social experience is that we represent the mental states of other people. This sense of others’ mental states is a part of our understanding and anticipation of their behavior, and molds our own behavior correspondingly. If our friend shows up to the restaurant with a grim face, we have a sense of her mood and adjust our greeting accordingly. If she glances at our empty glass while pouring herself some wine, we have a sense of her intentions and might move our glass closer. This is the concept of mentalizing.
Fun facts about neurons that impact decisions
Since neurons encode changes in stimulation (rather than absolute levels), absolute judgments on any dimension are much more difficult than relative judgments. This lies at the root of Ernst Weber’s 1834 observation that detectable increases in visual or auditory signal intensity are proportional to the starting value, i.e., need to be larger for larger starting values. (from post First Half of 2009 JDM Research Summary)
There is a hierarchy of neurons and there are a lot of them. So it is quite likely that I have a neuron dedicated to Salma Hayek, etc.
Neural responses are noisy. As an example, a radiologist may have tumor detecting neurons. These hypothetical tumor detectors will give noisy and variable responses. After one glance at a scan of a healthy lung, our hypothetical tumor detectors might fire 10 spikes per second. After a different glance at the same scan and under the same conditions, these neurons might fire 40 spikes per second. (from post Signal Detection Theory)
In Reading in the Brain, Dehaene introduces the idea of “neuronal recycling” whereby portions of our ventral visual system are turned over to reading and writing. He says that after centuries of trial and error, writing systems evolved to a form adapted to our brain circuits. (from post Toward a Culture of Neurons)
An interesting example of the hierarchical predictive coding model is binocular rivalry. Binocular rivalry is a form of visual experience that occurs when, using a special experimental set-up, each eye is presented (simultaneously) with a different visual stimulus. Thus, the right eye might be presented with an image of a house, while the left receives an image of a face. Under these albeit artificial conditions, subjective experience unfolds in a surprising, “bi-stable” manner. Instead of visually experiencing a confusing all-points merger of house and face information, subjects report a kind of perceptual alternation between seeing the house and seeing the face.
This is the second of three posts about the brain having a singular purpose of prediction error minimization. PEM literature has many contributors. Karl Friston is probably the strongest idea man, but Andy Clark and Jakob Hohwy are more understandable. Hohwy’s papers include: Hohwy, J. (2015). “The Neural Organ Explains the Mind”. In T. Metzinger & J. M. Windt (Eds). Open MIND: 19(T). Frankfurt am Main: MIND Group. Hohwy, J., Roepstorff, A., & Friston, K.(2008). “Predictive coding explains binocular rivalry: an epistemological review.” Cognition 108, 687-701. Hohwy, J. (2012). “Attention and conscious perception in the hypothesis testing brain.” Frontiers in Psychology/Consciousness Research, April 2012, Volume 3, Article 96. Paton, B., Skewes, J., Firth, C., & Hohwy, J(2013). “Skull-bound perception and precision optimization through culture.” Commentary in Behavioral and Brain Sciences (2013) 36:3, p 42.
Both Clark and Hohwy use “explaining away” to illustrate the concept of cancelling out sensory prediction error. Perception thus involves “explaining away” the driving (incoming) sensory signal by matching it with a cascade of predictions pitched at a variety of spatial and temporal scales. These predictions reflect what the system already knows about the world (including the
body) and the uncertainties associated with its own processing. What we perceive depends heavily upon the set of priors that the brain brings to bear in its best attempt to predict the current sensory signal.