Julia Mossbridge is an American researcher, author and educator with a background in neuroscience who has carried out parapsychological studies, notably on precognition and presentiment effects.
Mossbridge holds several positions in academia and industry, including visiting scholar in the psychology department at Northwestern University, fellow at the Institute of Noetic Sciences, science director at Focus@Will Labs, and associated professor in Integral and Transpersonal Psychology at the California Institute of Integral Studies.
Mossbridge received her PhD in communication sciences and disorders at Northwestern University. She earned an MA in neuroscience at the University of California at San Francisco and a BA in neuroscience from Oberlin College. She invented and patented Choice Compass, a physiologically-based decision-making smartphone app. She is the author of books including The Calling and co-author of Transcendent Mind: Re-thinking the Science of Consciousness1 and most recently The Premonition Code.2
Mossbridge started her career as a psychophysicist and cognitive neuroscientist at Northwestern University in Evanston, Illinois in 1998. During her graduate years, she examined the relationship between cognitive mechanisms governing order versus synchrony effects in the auditory systems. During her post-doctoral years, also at Northwestern, her contributions included the discovery of brain activity corresponding to reading comprehension ability and the illumination of processes underpinning the Gambler’s fallacy3 (that in a series of independent, binary outcomes, after a sequence of the same outcome, most people inaccurately believe the alternative outcome should prevail).
Sense of Being Stared At
In 2009, Mossbridge designed and conducted studies investigating the sense of being stared at.4 Physiological data were obtained during a forced-choice task in which the subjects were asked to guess if they were being observed or not. An additional precognition condition involved conscious guessing an image to be later revealed as the target. The overall result was not significant for conscious responses for either detection of remote staring or precognition; however, there was significant support for subconscious psi effects occurring in both conditions.
In three experiments that focused on both heart pulse and skin conductance, Mossbridge tested the hypothesis that both measures would show differences between correct and incorrect guesses in a forced-choice precognition guessing task. Mossbridge did confirm that the heart rate in the first two experiments was higher before correct guesses than incorrect guesses. However, there was no significant difference in skin conductance. The third experiment found no significant differences in either measure. Additional analyses revealed clear gender differences: males showed higher skin conductance before correct guesses while females showed this before incorrect guesses (p = 0.0005).5
Mossbridge had been a student of precognition most of her life, recording her dreams daily from childhood. Her first formal research in parapsychology was at Northwestern, investigating the presentiment effect (she terms it AAA – Anomalous Anticipatory Activity, or sometimes PAA – Predictive Anticipatory Activity). She applied a pattern classification (random forest ensemble) algorithm to EEG data that she gathered prior to a random stimulus presentation. It was found that EEG activity moments before (550 milliseconds; around the time of Libet’s Type 1 readiness potential)6 could predict which stimulus would be presented, with some measures giving extreme significance across 40 subjects (p = 2.5 x 10-6).7
In later presentiment research, Mossbridge concentrated on single-trial experiments in order to eliminate expectancy effects – considered a small risk8 during multiple-trial experiments. She first re-analyzed data she’d obtained in the laboratory to examine gender differences in the first trial of multiple-trial experiments. She found clear gender differences in skin conductance9 before a random number generator determined whether the participant’s prediction was correct or not. Specifically, men had significantly higher skin conductance before being correct vs. incorrect about a prediction; women showed the opposite trend, with a significant gender interaction. Then she designed experiments in which hundreds of subjects were offered a payment on the Internet in return for performing a smartphone task in which their heartbeats were measured before and after being told whether they had won $2USD. Again, a similar effect was obtained in the heartbeat data prior to the random number generator determining whether the person won the extra reward; a significant gender interaction, with men showing significantly greater increases in heart rate prior to winning versus losing and women showing the opposite trend. Increasing the monetary reward to $4USD obliterated these effects; Mossbridge suspects this is due to pushing the differences out beyond the time window in which she obtained consistent heartbeat data (10 seconds prior to the announcement of the reward or lack thereof).10
Mossbridge has helped evaluate the evidence base for presentiment. In 2012, she co-authored a major meta-analysis of 26 presentiment studies conducted between 1978 and 2010 that utilized a wide range of measures, including heart rate, skin conductance and brain imaging techniques.11 The overall results were astronomically significant (fixed effect: p < 2.7 x 1012); there was no clear evidence of a possible conventional explanation in terms of poor methodology, selective reporting practices and expectancy effects, although the authors took measures to counteract the expected ‘filedrawer effect’. Also, the successful results could not be attributed to one or two unusually successful investigators: the results were distributed across all of them. Duggan and Tressoldi repeated the meta-analysis in 2018, reaching the same conclusions.12
Mossbridge has investigated unconscious behavioural responses to future information in humans, continuing research begun by Daryl Bem in 2011.13 In one study, the ability of subjects to recall words from a list that would randomly be chosen to be displayed again in the future was tested under two conditions: listening to ‘streamlined music’ in which disharmonious chords are removed with a slower more rhythmic tempo versus regular music. Mossbridge found that retroactive word recall was favoured significantly under the streamlined music condition rather than the regular music condition, p < 0.018.14 In another series of studies again using word recall, Mossbridge found complex and variable indications of hormonal and gender influences on precognition performance in women, across a long series of internet-based studies examining more than 2000 participants.15
Mossbridge is active in developing technology related to precognition and decision making, women in science, and unconditional love.
This smartphone app uses the camera to detect and measure heart rate patterns. Users are asked to meditate on life dilemmas, for example, to leave the country for a new job or stay at home, whilst the heart rate data is compared between the two choices. Multiple experiments with the algorithm, taking into account gender differences, indicate that it separates positive from negative choices at a rate significantly above chance. However, those data were based on experiments run by Mossbridge using a pre-arranged set of known positive and negative choices; it is difficult to test for unknown life choices. Mossbridge hypothesizes that unconscious emotional states will be picked up by the app’s algorithms, therefore helping the user to decide on which option to take.16
When Mossbridge was the director of the Innovation Lab at the Institute of Noetic Sciences (2016-2018), she helped lead the development of the Psi-Q app17 (now called Psi3) that contains a series of tests aimed at exploring a number of psi abilities – precognition, psychokinesis, clairvoyance. Results from the first 200 subjects were significant for some measures. A larger dataset with over 300,000 trials has been analysed, and Mossbridge presented results from this analysis at the 2019 meeting of the Society for Scientific Exploration, with publication in preparation as of Fall 2019.18
Mossbridge was the team leader and principal investigator of the Loving A.I project19 (2016-2018), an initiative to ultimately develop altruistic and empathetic motivations and behaviors in artificially intelligent systems. The beginnings of the program were aimed at fostering machine – human conversational exchanges that improve the psychological well-being of those engaged. The artificial intelligence code is still channelled through Sophia, a humanoid looking robot who interacts with the outside world, when she sits in meditation with humans. In that project, Julia was collaborating with artificial intelligence expert Ben Goertzel, who also has a deep interest in parapsychology.20
Premonition Code Controlled Precognition Training
In 2017, Mossbridge became interested in conscious forms of precognition that could predict future events with delays longer than the typical time between pre-responses and feedback in unconscious behavioural and physiology experiments. She received training from military-method-trained remote viewer John Vivanco21 in remote viewing, and adapted this method to a precognitive-only method she calls ‘precognition’, described in her book for lay audiences written with Theresa Cheung, The Premonition Code (Watkins 2018). Mossbridge and Mark Boccuzzi at the Windbridge Institute22 created a practice/training/testing portion of the website supporting the book that uses a true random number generator to select targets that users are invited to attempt to predict. Mossbridge presented her first analysis of the data from this website, showing significant precognition performance, at the 2019 Society for Scientific Exploration meeting.
Debate and Controversy
Mossbridge has engaged in high-level debate with critics regarding the genuineness of the presentiment effect. Neuroscientist Sam Schwarzkopf, alleged shortcomings in a critique of a presentiment study,23 including unresolved expectancy effects, inadequate randomization and non-standard baseline measurements.24 Mossbridge and colleagues rejected these criticisms in detail.25
Mossbridge is continuing her precognition research, investigating the behavioural implicit domain as well as conscious, long-delay precognition. More recently she has been investigating retrocausal, precognition-like behaviour in photons, work that was presented at the 2019 meeting of the American Physical Society.26
Ayton, P, & Fischer, I. (2004). The hot hand fallacy and the gambler’s fallacy: two faces of subjective randomness? Memory & Cognition 32, 1369-78.
Baruss, I. Mossbridge, J. (2016) Transcendent Mind: Re-thinking the Science of Consciousness. American Psychological Association. Washington D.C.Bem, D.J. (2011). Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect. Journal of Personality and Social Psychology 100, 407-425.
Cheung, T., Mossbridge, J. (2018). The Premonition Code: The Science of Precognition, How Sensing the Future Can Change Your Life. Watkins Media limited. London.
Dalkvist, J., Mossbridge, J., & Westerlund, J. (2013). How to handle expectation bias in presentiment experiments: A recommendation. Abstracts of Presented Papers: The Parapsychological Association 56th Annual Convention, 19.
Duggan, M., Tressoldi, P. (2018). Predictive physiological anticipation preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis. F1000 Research 7, 407.
Libet, B. (1999). Do we have free will? Journal of Consciousness Studies 6, 47–57.
Mossbridge, J. (2016). The Influence of Streamlined Music on Cognition and Mood. arXiv preprint arXiv:1610.04255.Mossbridge, J. (2017). Characteristic Alpha Reflects Predictive Anticipatory Activity (PAA) in an Auditory-Visual Task. In Augmented Cognition. Neurocognition and Machine Learning: 11th International Conference, AC 2017, held as part of HCI International 2017, Vancouver, BC, Canada, July 9-14, Proceedings, Part I, 79-89. https://www.researchgate.net/publication/317802052_Characteristic_Alpha_Reflects_Predictive_Anticipatory_Activity_PAA_in_an_Auditory-Visual_Task
Mossbridge, J., Grabowecky, M., & Suzuki, S. (2009). Evidence for subconscious but not conscious psi in remote stare detection and precognition tasks. The Parapsychological Association, 52nd Annual Convention Abstracts of Presented Papers 13-14.
Mossbridge, J., Grabowecky, M., & Suzuki, S. (2011). Physiological markers of future outcomes: Three experiments on subconscious psi perception during concurrent performance of a guessing task. The Parapsychological Association, 54th Annual Convention Abstracts of Presented Papers 17.
Mossbridge, J., Tressoldi, P., & Utts, J. (2012). Predictive physiological anticipation preceding seemingly unpredictable stimuli: a meta-analysis. Frontiers in Psychology 3, 390. doi: 10.3389/fpsyg.2012.00390
Mossbridge, J., Tressoldi, P., Utts, J., Ives, J.A., Radin, D. and Jonas, W.B. (2014a). Predicting the unpredictable: critical analysis and practical implications of predictive anticipatory activity. Frontiers in Human Neuroscience 8, 146.
Mossbridge, J., Tressoldi, P., Utts, J., Ives, J.A., Radin, D., Jonas, W. (2014b) We Did See This Coming: Response to, We Should Have Seen This Coming, by D. Sam Schwarzkopf. https://arxiv.org/abs/1501.03179`
Mossbridge, J., Tressoldi, P., Utts, J., Ives, J. A., Radin, D., & Jonas, W. B. (2015). We did see this coming: Response to, We should have seen this coming, by D. Sam Schwarzkopf. arXiv preprint arXiv:1501.03179.
Mossbridge, J., Goertzel, B., Mayet, R., Monroe, E., Nehat, G., Hanson, D., & Yu, G. (2018). Emotionally-sensitive ai-driven android interactions improve social welfare through helping people access self-transcendent states. vol. In AI for Social Good Workshop at Neural Information Processing Systems 2018 Conference.
See also, Broderick, D., & Goertzel, B. (Eds.). (2014). Evidence for psi: Thirteen empirical research reports. McFarland.
Schwarzkopf D. (2014a). We should have seen this coming. Frontiers in Human Neuroscience, 8-332. doi:10.3389/fnhum.2014.00332.
Schwarzkopf, D.S. (2014b). Why presentiment has not been demonstrated. Available at: http://figshare.com/articles/Why_presentiment_has_not_been_demonstrated/1021480
- 1. Baruss & Mossbridge (2016).
- 2. Cheung & Mossbridge (2018).
- 3. Ayton & Fischer (2004).
- 4. Mossbridge et al (2009).
- 5. Mossbridge et al (2011).
- 6. Libet (1999).
- 7. Mossbridge (2017) https://www.researchgate.net/publication/317802052_Characteristic_Alpha_Reflects_Predictive_Anticipatory_Activity_PAA_in_an_Auditory-Visual_Task
- 8. Mossbridge et al (2015).
- 9. These data are shown in Fig 6 of the 2012 meta-analysis.
- 10. Mossbridge (2014). http://www.koestler-parapsychology.psy.ed.ac.uk/Documents/KPU_Registry_1005.pdf
- 11. Mossbridge (2012).
- 12. Duggan & Tressoldi (2018).
- 13. Bem (2011).
- 14. Mossbridge (2016).
- 15. Mossbridge (2018), http://www.koestler-parapsychology.psy.ed.ac.uk/Documents/KPU_Registry_1043.pdf
- 16. Mossbridge (2016) http://www.choicecompass.com/
- 17. Mossbridge (2018) https://apps.apple.com/us/app/psi3/id1196948825
- 18. Mossbridge (2019, personal communication.
- 19. Mossbridge (2018) https://lovingai.org/#media
- 20. Mossbridge et al (2018).
- 21. www.righthemispheric.com
- 22. www.windbridgeinstitute.com
- 23. Mossbridge et al (2014a).
- 24. Schwarzkopf D. (2014).
- 25. Mossbridge et al (2014b).
- 26. Mossbridge (2019). https://vimeo.com/314577638