Induced dissociations: Opposite time courses of priming and masking induced by custom-made mask-contrast functions

Abstract

We present a new experimental technique to induce dissociations between the visibility of a masked prime and its ability to induce a priming effect in response times. In three experiments, we systematically couple an independent variable known to influence the priming effect (prime-mask SOA) with a variable expected to influence prime visibility but not priming (mask contrast). This way, we create mask-contrast functions where mask contrast either increases with SOA, decreases, or remains constant at maximum or minimum levels. We show that different mask-contrast functions can lead to qualitatively different time courses of masking without affecting the time course of priming, allowing for double dissociations (e.g., increasing priming effects under decreasing prime visibility). For the first time, we demonstrate such double dissociations for response priming by color as well as shape stimuli. We also show that the technique requires stimuli that decouple the mask’s ability to mask the prime from its ability to activate the response. We conclude that mask-contrast functions can accentuate or even induce dissociations between priming and masking, opening new possibilities for studying perception without awareness.

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Notes

  1. 1.

    The null-hypothesis corroboration problem does not disappear with the use of Bayes factors, because this technique requires decisions about the shape of the prior distribution of the null hypothesis as well as the set of admissible alternative hypotheses that are to be compared with the null. Depending on settings, the test can either be strict or lenient.

  2. 2.

    There is an alternative set of assumptions to interpret a simple dissociation as evidence for unconscious perception. Instead of the assumption that the direct measure is exhaustive for conscious information, we can alternatively assume that the indirect measure is exclusive for unconscious information. Such an indirect measure would be weakly monotonic with respect to u and not respond to any changes in c (T. Schmidt & Vorberg, 2006). T Schmidt (2007) argues that the plausibility of such a measure is an empirical question, whereas the assumption of an exhaustive measure is inadequate on measurement-theoretical grounds alone.

  3. 3.

    In the present experiments, the 40-ms SOA shows the strongest masking effects. This is in line with Breitmeyer and Öğmen’s (2006) conclusion that the optimal SOA for metacontrast is between 10 and 40 ms (cf. Macknik & Livingstone, 1998; van Aalderen-Smeets, Oostenveld, & Schwarzbach, 2006).

  4. 4.

    However, this might be difficult to demonstrate with pattern masks, which seem to interfere with prime processing (Wernicke & Mattler, 2019). Most successful demonstrations of double dissociations employ metacontrast masks.

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Author note

We thank our participants and our colleagues Sven Panis and Maximilian Wolkersdorfer. We also thank Jens Schwarzbach and Dirk Vorberg for fruitful discussions. Thanks to Lisa Reiner and Patrizia Psota for carrying out preliminary studies in their bachelor theses. Thanks to Jennifer Prodan for improving on our graphical art. All data, materials, and analyses are available upon request.

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Correspondence to Melanie Biafora.

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Mathematical appendix: Simple and double dissociations

Mathematical appendix: Simple and double dissociations

The following proofs are modified from T. Schmidt and Vorberg (2006), where additional details are provided. Original proofs are by Dirk Vorberg.

Definitions and assumptions

Let a and b index the magnitudes of two types of sensory information, A and B, with a, b ≥ 0. Let M be a measure that may respond to either type of information, MM(a,b). M is weakly monotonic for Type A information if for all a'a and all b, M(a',b)M(a,b), and strictly monotonic for Type A information if for all a' > a and all b, M(a',b) > M(a,b). M is exclusive for Type A information if it is sensitive to this type of information only, M(a,b) = M(a,0) for all a and b. M is exhaustive for Type A information if it is strictly monotonic in a. Exhaustiveness implies that a measure is able to respond to any change in the relevant information, no matter how small. We define effects on a measure by the difference from a no-information baseline, M* = M(a,b) − M(0,0).

Without loss of generality, let c and u index the magnitudes of one source of conscious information, C, and another source of unconscious information, U, with c, u ≥ 0. Let D and I be the direct and indirect measures, where D is intended to measure conscious information. Because we do not assume either of these measures to be process-pure, we start from the assumption that either measure may be influenced by either type of information, DD(c,u) and II(c,u). Note that these functions are specified on the level of expected values (i.e., the behavior of measures in the long run irrespective of trial-by-trial fluctuations). Unless stated otherwise, we assume either measure to be weakly monotonic in either argument.

Simple dissociation

An observed dissociation I*> 0 and D*= 0 implies u > 0 if the direct measure is exhaustive for conscious information.

Proof: If D is exhaustive for c, D* = D(c,u) − D(0,u) = 0 implies c = 0. Then,

I* > 0 ⇔ I(c,u) = I(0,u) > 0 implies u > 0.

This derivation requires weak monotonicity of the indirect measure for unconscious information.

Double dissociation

Let D*i and I*i denote the direct and the indirect effects observed under experimental conditions i, i{1, 2}. The joint observation of D*1< D*2 and I*1> I*2 implies u > 0 in at least one of the conditions.

Proof

We prove that u1u2 by showing that the assumption u1 = u2 = u leads to a contradiction. By the assumption, observing D*1< D*2 implies D(c1,u) < D(c2,u), which implies c1 < c2. At the same time, observing I*1> I*2 implies I(c1,u) > I(c2,u), which implies c1 > c2. The contradiction implies that u1 and u2 cannot be equal, |u1− u2|> 0. Moreover, as u1, u2 ≥ 0 by assumption, u1≠ u2 implies max(u1,u2) > 0, which completes the proof.

Remarkably, the proof requires weak monotonicity of D and I in the c argument only, while the measures may depend on u in an arbitrary way. Therefore, we can allow C and U to interact in an arbitrary fashion, as in reciprocal inhibition (T. Schmidt & Vorberg, 2006). Note that the proof requires strict inequalities if the exhaustiveness assumption is to be avoided. Mere invariance in one of the measures is thus insufficient to produce a double dissociation.

Importantly, the mechanics of the proof are agnostic as to how the arguments of the functions are labeled. A double dissociation refutes any model stating that both direct and indirect measures are driven weakly monotonically by only a single source of information, whatever that may be.

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Biafora, M., Schmidt, T. Induced dissociations: Opposite time courses of priming and masking induced by custom-made mask-contrast functions. Atten Percept Psychophys 82, 1333–1354 (2020). https://doi.org/10.3758/s13414-019-01822-4

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Keywords

  • Response priming
  • Metacontrast
  • Double dissociation
  • Induced dissociations
  • Mask-contrast function
  • Perception without awareness