Is Signal Strength a Confound in Consciousness Research?

a critique of recent methodological work by Matthias Michel and Hakwan Lau

Matthias Michel is among the sharpest critics of the methods of consciousness science. His forthcoming paper, “Consciousness Doesn’t Do That”, convincingly challenges background assumptions behind recent efforts to discover the causes, correlates, and prevalence of consciousness. It should be required reading for anyone tempted to argue, for example, that trace conditioning correlates with consciousness in humans and thus that nonhuman animals capable of trace conditioning must also be conscious.

But Michel does make one claim that bugs me, and that claim is central to the article. And Hakwan Lau -- another otherwise terrific methodologist -- makes a similar claim in his 2022 book In Consciousness We Trust, and again the claim is central to the argument of that book. So today I’m going to poke at that claim, and maybe it will burst like a sour blueberry.

The claim: Signal strength (performance capacity, in Lau’s version) is a confound in consciousness research.

As Michel uses the phrase, “signal strength” is how discriminable a perceptible feature is to a subject. A sudden, loud blast of noise has high signal strength. It’s very easy to notice. A faint wavy pattern in a gray field, presented for a tenth of second, has low signal strength. It is easy to miss. Importantly, signal strength is not the same as (objective, externally measurable) stimulus intensity, but reflects how well the perceiver responds to the signal.

Signal strength clearly correlates with consciousness. You’re much more likely to be conscious of stimuli that you find easy to discriminate than stimuli that you find difficult to discriminate. The loud blare is consciously experienced. The faint wavy pattern might or might not be. A stimulus with effectively zero signal strength -- say, a gray dot flashed for a millionth of a second and immediately masked -- will normally not be experienced at all.

But signal strength is not the same as consciousness. The two can come apart. The classic example is blindsight. On the standard interpretation (but see Phillips 2020 for an alternative), patients with a specific type of visual cortex damage can discriminate stimuli that they cannot consciously perceive. Flash either an “X” or an “O” in the blind part of their visual field and they will say they have no visual experience of it. But ask them to guess which letter was shown and their performance is well above chance -- up to 90% correct in some tasks. The “X” has some signal strength for them: It’s discriminable but not consciously experienced.

If signal strength is not consciousness but often correlates with it, the following worry arises. When a researcher claims that “trace conditioning is only possible for conscious stimuli” or “consciousness facilitates episodic memory”, how do you know that it’s really consciousness doing the work, rather than signal strength? Maybe stimuli with high signal strength are both more likely to be consciously experienced and more likely to enable trace conditioning and episodic memory. Unless researchers have carefully separated the two, the causal role of consciousness remains unclear.

An understandable methodological response is to try to control for signal strength: Present stimuli of similar discriminability to the subject but which differ in whether (or to what extent) they are consciously experienced. Only then, the reasoning goes, can differences in downstream effects be confidently attributed to consciousness itself rather than differences in signal strength. Lau in particular stresses the importance of such controls. Yet such careful matching is difficult and rarely attempted. On this reasoning, much of the literature on the cognitive role of consciousness is built on sand, not clearly distinguishing the effects of consciousness from the effects of signal strength.

This reasoning is attractive but faces an obvious objection, which both Michel and Lau address directly. What if signal strength just is consciousness? Then trying to “control” for it would erase the phenomenon of interest.

Both Michel and Lau analogize to height and bone length. If you want to test whether height confers an advantage in basketball or dating, you might want to control for skin color, but it would be absurd to control for bone length. If skin color correlates with height and you want to see whether height specifically advantages people in basketball or dating, it makes sense to control for differences in skin color by systematically comparing people with the same skin color but different heights. If the advantage persists, you can infer that height rather than skin color is doing the work. But trying to control for bone length lands you in nonsense. Taller people just are the people with longer bones.

Michel and Lau respond by noting that consciousness and signal strength (or performance capacity) sometimes dissociate, as in blindsight. Therefore, they are not the same thing and it does make sense to control for one in exploring the effects of the other.

But this response is too simple and too fast.

We can see this even in their chosen example. Height and bone length aren’t quite the same thing. They can dissociate. People are about 1-2 cm taller in the morning than at night -- not because their bones have grown but because the tissue between the bones (especially in the spine) compresses during the day.

Now imagine an argument parallel to Michel’s and Lau’s: Since height and bone length can come apart, we should try to control for bone length in examining the effects of height on basketball and dating. We then compare the same people’s basketball and dating outcomes in the morning and at night, “holding bone length fixed” while height varies slightly. This would be a methodological mistake. For one thing, we’ve introduced a new potential confound, time of day. For another, even if the centimeter in the morning really does help a little, we’ve dramatically reduced our ability to detect the real effect of height by “overcontrolling” for a component of the target variable, height.

Consider a psychological example. The personality trait of extraversion can be broken into “facets“, such as sociability, assertiveness, and energy level. Since energy level is only one aspect of extraversion, the two can dissociate. Some people are energetic but not sociable or assertive; others are sociable and assertive but low-energy. If you wanted to measure the influence of extraversion on, say, judgments of likeability in the workplace, you wouldn’t want to control for energy level. That would be overcontrol, like controlling for bone length in attempting to assess the effects of height. It would strip away part of the construct you are trying to measure.

What I hope these examples make clear is that dissociability between correlates A and B does not automatically make B a confound that must be controlled when studying A’s effects. Bone length is dissociable from height, but it is a component, not a confound. Energy level is dissociable from extraversion, but it is a component, not a confound.

The real question, then, is whether signal strength (or performance capacity) is better viewed as a component or facet of consciousness than as a separate variable that needs to be held constant in testing the effects of consciousness.

A case can be made that it is. Consider Global Workspace Theory, one of the leading theories of consciousness. On this view, a process or representation is conscious if it is broadly available for “downstream cognition” such as verbal report, long-term memory, and rational planning. If discrimination judgments are among those downstream capacities, then one facet of being in the global workspace (that is, on this view, being conscious) is enabling such judgments. But recall that signal strength just is discriminability for a subject. If so, things begin to look like the extraversion / energy case. Controlling for discriminability would be overcontrolling, that is, attempting to equalize or cancel the effects not of a separate, confounding process, but of a component of the target process itself. (Similar remarks hold for Lau’s “performance capacity”.)

Global Workspace Theory might not be correct. And if it’s not, maybe signal strength is indeed a confounder, rather than a component of consciousness. But the case for treating signal strength as a confounder can’t be established simply by noticing the possibility of dissociations between consciousness and signal strength. Furthermore, since Michel’s and Lau’s recommended methodology can be trusted not to suffer from overcontrol bias only if Global Workspace Theory is false, it’s circular to rely on that methodology to argue against Global Workspace Theory.