Normalization regulates competition for visual awareness

Abstract

Signals in our brain are in a constant state of competition, including those that vie for motor control, sensory dominance, and awareness. To shed light on the mechanisms underlying neural competition, we exploit binocular rivalry, a phenomenon that allows us to probe the competitive process that ordinarily transpires outside of our awareness. By measuring psychometric functions under different states of rivalry, we discovered a pattern of gain changes that are consistent with a model of competition in which attention interacts with normalization processes, thereby driving the ebb and flow between states of awareness. Moreover, we reveal that attention plays a crucial role in modulating competition; without attention, rivalry suppression for high-contrast stimuli is negligible. We propose a framework whereby our visual awareness of competing sensory representations is governed by a common neural computation: normalization.

Fig. 1

Examples of competing stimuli used in the experiment, and their predicted impact on contrast response functions. (a) In some trials, the probe stimulus was dichoptically suppressed by a large stimulus. Under this configuration, the normalization model predicts a contrast gain shift, with the largest effects occurring at mid-contrasts, and little-to-no effect at low and high contrasts. (b) In other trials, the probe stimulus was the same size as the stimulus in the competing eye. Under this configuration, the normalization framework predicts both a shift in the contrast gain, as well as an attenuation of the response gain, with the largest effects occurring at high contrasts.

Fig 2

Example trial sequence in Experiment 1. Two competing bandpass-filtered noise stimuli were viewed dichoptically. To control rivalry state, we used the flash suppression technique. Following flash-induced suppression, the probe in the suppressed eye changed orientation slightly (4° clockwise or counter-clockwise), and observers reported the direction of tilt of that probe (two-alternative, forced-choice task).

Fig 3

The effect of rivalry on contrast psychometric functions. (a) Example psychometric functions from one observer. When the competing stimulus was the same size as the probe, we found both a reduction in the asymptote, or response gain, as well as a shift in the probe’s psychometric function, or contrast gain. However, as the size of the competitor increased, the response gain modulation decreased, and when the competing stimulus was much larger than the probe, the psychometric functions only shifted in their contrast gain. (b) C50 estimates for each observer, indexing changes in contrast gain. We found decreased contrast gain (higher C50) under suppression relative to an unsuppressed stimulus, regardless of the size of the competing stimulus. (c) d′_max estimates for each observer, indexing changes in response gain. We found the strongest decrease in the response gain (lower d′_max) when the competing stimulus was the same size as the probe stimulus, and this reduction in response gain diminished as the competitor size increased. Error bars are bootstrapped 95% confidence intervals.

Fig 4

(a) Psychometric functions for probes pitted against small competitors, after contrast has been adjusted for the reduction in perceived contrast with a surround. Although the physical contrast of the competitor was lower, we still found a contrast gain shift (b), as well as a drop in the response gain of the psychometric functions (c) –thus ruling out an alternative, surround suppression-based explanation for our large-suppressor results. Error bars are bootstrapped 95% confidence intervals.

Fig 5

(a) Psychometric functions for probes pitted against large competitors, when the probe region was surrounded with an aperture in both eyes, facilitating binocular fusion. (b) Despite the addition of these fusion markers, the largest competitor still only evoked a contrast gain shift in the contrast psychometric function, and no change in the response gain (c). Error bars are bootstrapped 95% confidence intervals.

Fig 6

Normalization model of visual competition. (a) The neural response to a probe stimulus is modulated by attention, and the spatial extent of this attention modulation hinges on the size of the competitor stimulus. When the competitor is small, attention is withdrawn from a small, center region of the probe. When the competitor is larger, attention is withdrawn from a larger swath of space, which includes both the probe and its surroundings. This attention-modulated probe response then undergoes divisive normalization, yielding a population response with signature gain responses that depend on the size of the probe, the size of the competitor, and the amount of attentional modulation. (b) Model predictions for attended stimuli. When the competitor stimuli are attended, a large competitor withdraws attention from the probe equally across both the excitatory and inhibitory components: yielding contrast gain. A small competitor, however, only withdraws attention from the center, excitatory region of the probe, leaving its surround unmolested: yielding both a response gain and contrast gain change, whereby the largest suppressive effects occur at high contrasts. (c) Model predictions for unattended stimuli. When attention is diverted from the competing stimuli, the balance between excitation and inhibition is maintained, regardless of competitor size, and thus the model only predicts a shift in the contrast gain, whereby the only suppressive effects occur at mid-contrasts.

Fig 7

Example trial sequence in Experiment 2. A phase-reversing noise stimulus in one eye (Competitor; 10 Hz) was pitted against a sinusoidal grating in the other eye (Inducer). The ‘Dominant eye’ received one of three possible stimulus arrangements: 1) an uncontoured field that produced no suppression of the inducer, 2) a large (8°) competitor or, 3) small (1.5°) competitor, both of which suppress visibility of the inducer. After viewing this display for 2 seconds, these stimuli disappeared, and a Nuller stimulus appeared in the same eye that the inducer had been in. This was followed by a mask stimulus, during which observers indicated whether or not a grating was seen. To direct attention towards the competing stimuli, observers detected orientation changes that occurred stochastically while the competitor stimulus was dominant. To divert attention away from the competing stimuli, observers performed a letter identification task (RSVP task), detecting target letters within a rapid stream of distractor letters appearing in the periphery.

Fig 8

The effect of attention and rivalry on afterimage formation. Top row (a,b) corresponds to the Attended condition, and the bottom row (c,d) corresponds to the Unattended condition. (a) When attention was directed toward the visual competition, the troughs of the afterimage functions (dotted arrows), which index afterimage strength, changed depending on stimulus size. There was no difference in afterimage strength between the large competitor and no-competitor conditions, yet when the inducer was pitted against the small competitor, the inducer afterimages were weakened. (b) Estimated afterimage strength indices reveal the same pattern of effects for all observers: while afterimage strength was unaltered by a large competitor, afterimage strength was diminished by a small competitor. (c) Without attention, the competitor had no effect on afterimage strength. (d) Afterimage strength estimates revealed a similar pattern of effects across all observers: for none did afterimage strength differ across conditions. Error bars are bootstrapped 95% confidence intervals.