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The Ai Generation : Learning Human Consciousness

Learning Human Consciousness

The Ai Generation : Learning Human Consciousness. The debate over the origin of human consciousness is one ripe with proponents on either side. With the concept of a soul and the development of countless religions throughout the annals of history. However, if there is one thing learned by the achievements of neuroscience and clinical research, it is that the human consciousness is at its core essence, the way our brains intercept, parse, and interpret external information. To that extent, whenever awake, our brains are bombarded with an excess of information at any given time and consequently information is either processed consciously, subconsciously, or ignored altogether.

Within the growing literature of neuroscience investigating the extent of human consciousness and informational processing, is a technique of binocular rivalry known as the continuous flash suppression paradigm. Through the use of this paradigm, the presentation of distinct color images (Mondrians) are presented successively and rapidly to one eye can reliably suppress the conscious awareness of any image presented to the other eye for a relatively long duration.

Hubble Space Telescope Director & Max Planck Institute for Astronomy Director Dr. Steven Beckwith

This flash suppression model, as used and established within the neuroscience literature is utilized to demonstrate a significant level of unconscious processing despite a lack of conscious awareness.

In this paper, I present a study utilizing the continuous flash suppression paradigm, extend a study of my own based on the findings, as well as express what knowledge regarding either the model or general human consciousness we can learn from this that we may have not known previously. In a study conducted at Vanderbilt University by Yang et al., titled, “Fearful Expressions Gain Preferential Access to Awareness during Continuous Flash Suppression”, researchers studied whether fearful expressions emerge from suppression into awareness faster than that of neutral or happy faces during the presentation of the continuous flash suppression model (CFS).

Researchers conducted a simple CFS study wherein one eye viewed a high contrast continual flash whilst the other viewed a particular facial expression as well as the same image inverted (happy, neutral, fearful). Observers were instructed to simply press a key as soon as any part of the face came into dominance. Furthermore, two more experimental procedures were carried out which mirrored the methodology of the first. The second experiment introduced a forced choice scenario wherein the face was shown in a particular quadrant of the frame, and observers were instructed only to press the key should the quadrant be identified. The final experiment modified the face stimuli to only show the eyes.

This study found statistically significant results supporting their hypothesis that fearful expressions are detected more quickly than neutral or happy expressions both across tasks of simple detection (Experiment 1) and location identification (Experiment 2). Yang et al., writes, “Using continuous flash suppression, we found that fearful expressions are detected more quickly than neutral or happy expressions.” (Yang, 884).

I wish to further extend these findings that negative charged facial expressions gain preferential access to awareness by introducing a followup study which incorporates an emotional prime before CFS, to test if this preference for fearful expressions can be modulated, and to what degree.

The breadth of emotions will remain the same as within the Yang study (neutral, happy, fearful) with the one addition of an anger condition. I hope that with the presence of a happy or angry subconscious prime before the presentation, participants’preferential access of fearful expressions into awareness may be modulated to deviate from the standard. I hypothesized that under the presence of an incongruent emotional prime before the introduction of the CFS, the response time (RT) will be significantly affected so as to favor the primed emotion.

This would show us that the relative strength of fearful expressions insofar as they enter the conscious mind faster, is modulated by previous environmental primes, and furthermore exemplify that emotional primes can significantly affect the methodology and speed with which certain facial expressions enter human awareness. This hypothesis is informed by the idea that subconscious processing of one’s environment will ultimately have a significant effect on the reported perception of the participant.

The Ai Generation : Learning Human Consciousness


The methods of the study closely mirrored that of Yang’s with the introduction of an emotional prime as well as a greater range of emotions. Stimuli will consist of four faces (two women), displaying the same emotions as in the underlying study (happy, neutral, fearful) with the addition of anger, as laid out by Ekman’s set of facial expressions. The prime will be operationalized as specific signage and posters across the testing facility to either represent a happy prime or an anger prime, with the neutral condition being an empty room.

The happy prime consisted of motivational posters and pictures of cute animals strung across the room undeniably within view for the participant, whilst the anger prime included images of weapons, volcanoes, and flames across the room. Participants within the happy condition were also gifted with cookies and treats before the study whilst those in the angry condition were treated quite rudely and coldly.

Stimuli was stereoscopically presented to observers on the left and right halves of a video monitor against a grayscale background, with images being cropped to remove features outside of the face.

In the initial 1000ms, one eye will be presented with the full contrast continuous flash suppression while the other eye viewed whichever face was presented to him/her. The contrast for the image of the face was ramped up at a rate of 2% every 20ms to avoid abrupt transitions. The experiment will ask participants to press a key as soon as the face enters awareness and will serve as the face recognition task for this study. There will be 60 trials in each condition (neutral, happy, fearful, angry) with 15 repeats of each stimulus. To clarify, the type of posters and signage on the wall will be manipulated in hopes of measuring a significant difference in the time it takes for certain facial expressions to enter into human awareness. In this case, the neutral condition for signage wherein the walls were left bare acted as the control, while the anger and happy prime conditions were the active manipulators.


To reiterate the general hypothesis of this study, I had hypothesized that the subconsciously primed introduction of a congruent emotion (happy) would effectively decrease the time it takes for happy facial expressions to enter one’s awareness, to comparable levels of that of fearful expressions. The results were in line with this hypothesis.

Participants within the anger prime, fearful/angry expression condition were the quickest to bring the face to awareness (M: 1.3s), however there was no significant difference between that of the anger prime and the happy prime with the happy facial expressions (M: 1.2s). This supports my hypothesis that despite human evolutionary proclivities to subconsciously screen for fearful and panic inducing expressions quickest, a subconscious prime of congruent emotions, specifically within the scope of this study, happiness, significantly modulates this effect.

Furthermore, I had hypothesized that incongruently primed emotions (ie. angry prime, happy facial expression vice versa) would yield the longest time to enter awareness relative to congruently matched primes, however the results only reflected half of this prediction.

On average, results showed that participants within the angry prime condition had a significantly reduced response time (M: 1.7s) across the identification of all facial expressions compared to those within the happy prime (M: 3s) and neutral prime (M: 3.1s). The significance of these results lie in the difference within the happy facial expression group, wherein the congruent prime of a happy environment and the CFS of a happy expression, did not significantly yield a lesser response time than the incongruent prime of an angrier environment and the CFS of an angry expression.

The Ai Generation : Learning Human Consciousness

This goes against our hypothesis that conditions with congruently primed emotions would exhibit the smallest response time, so as to rival the preferential access to awareness of fearful expressions as outlined by Yang. Consistent with the hypothesis however was the incongruent prime condition of a happy environment with an angry facial expression, and a happy environment with a fearful facial expression, which yielded the longest significant reaction times relative to all other conditions (M: 4.0s).

To summate, the results support the hypothesis that with congruent primes of happy environments on continually flash suppressed happy facial expressions, there is a significant decrease in response time to an extent where there is almost no distinguishable difference between this condition and that of congruently primed angry/fearful conditions. This decreased response time also represents statistical significance between congruently primed happy conditions (M: 1.5s) and neutral angry and fearful conditions (M: 2.6s), indicating that despite natural human nature to make fearful facial expressions first, with proper priming this effect can indeed be modulated. However the hypothesis is only partly supported as the incongruent primes did not necessarily always yield the highest response times as evidenced by the angry prime, happy face condition (M: 1.9s). All data for this experiment depicted in fig. 1.


This experiment found that the subconscious environmental priming of congruent emotions works to counteract the preferential access to awareness of fearful expressions as prefaced in the underlying Yang et al. study. This was in line with our hypothesis as the difference in response times between congruently primed happy environments and happy facial expressions, and both congruently and neutrally primed anger/fearful expressions, were negligible.

The Ai Generation : Learning Human Consciousness

However my secondary hypothesis that incongruently primed emotions and expressions would yield the longest response time was proven otherwise, with the angry prime condition marking significantly lower response times, even despite its incongruent prime with happy facial expressions. Although more studies must be conducted to measure the effect of this, I would hypothesize that the introduction of an angrier and more aggressive environment made the participants more subconsciously primed and ready for any type of facial expression to be shown. Further studies should test for this to truly see if an angry or aggressive environmental prime truly does decrease response times for CFS in a general sense.

This study would benefit from possibly including a larger range of emotions, possibly the full seven universal emotions, to truly chart the effectiveness of certain emotional expressions to break into the human consciousness during CFS. Furthermore, further research would benefit from operationalizing the emotional prime in alternative methods, to test for the reliability of environmental primes.

Overall, these results imply that despite Yang’s findings that the human mind is able to bring to consciousness fearful expressions faster than others, with proper emotional priming before the necessary task, this preference for negative emotions can be modulated. This has real life implications for decision making and the ways in which coercive and emotionally pliable environments can be leveraged to influence human choices.

The Ai Generation : Learning Human Consciousness

The Ai Generation : Learning Human Consciousness

References Yang, Eunice, et al. “Fearful Expressions Gain Preferential Access to Awareness during Continuous Flash Suppression.” Emotion, vol. 7, no. 4, 2007, pp. 882–886., doi:10.1037/1528-3542.7.4.882.

Leading Artificial Intelligence and Financial Advisor – Rebellion Research

The Ai Generation : Learning Human Consciousness