Parapyschology has increasingly drawn on neuroscience, online testing and consumer technology as investigators look for effects that appear small, elusive and physiologically subtle. Julia Mossbridge has studied presentiment, covert anticipation, remote viewing and practical tools meant to translate anomalous timing into everyday decisions.
- Mossbridge’s EEG work reported anticipatory brain activity before random emotional stimuli, which she terms anomalous anticipatory activity.
- Her 2025 lucid dreaming case study introduced AI text-embedding as a scoring method for free-response psi tasks, comparing it directly with human judges.
- Recently Mossbridge has utilized artificial intelligence measurements in free-response psi tasks, in addition to exploring the telepathic abilities of non-speaking autistic individuals.
Life and Career
Julia Mossbridge was born in 1969 in the United States. She is a senior distinguished fellow in human potential at the Center for the Future of AI, Mind and Society at Florida Atlantic University, a member of the Loomis Council at the nonpartisan Stimson Center, the co-founder and board chair of Applied Love Labs (previously called TILT: The Institute for Love and Time), the founder and CEO of American Electrodynamics, a research company developing technology based around retrocausal information transfer in photons (see CADS effect below). AEC has two patents filed. 1Julia Mossbridge (personal communication 2o September 2026).Mossbridge is also the founder/principal of Mossbridge Institute and the author/co-author of multiple books and scientific articles related to time travel, artificial intelligence and unconditional love.
Julia Mossbridge was previously an affiliate professor in the Department of Biophysics and Physics at University of San Diego, a fellow at the Institute of Noetic Sciences, and principal consultant for the Blue Sky Task Force at California Institute for Integral Studies. Her PhD is in communication sciences and disorders (Northwestern University) and her MA is in neuroscience (UC San Francisco). She was awarded her BA in neuroscience with highest honours (Oberlin College).
Mainstream Research
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 fallacy2Ayton & Fischer (2004). (that in a series of independent, binary outcomes, after a sequence of the same outcome, most people inaccurately believe the alternative outcome should prevail).
General Parapsychology
Sense of Being Stared At
In 2009, Mossbridge designed and conducted studies investigating the Sense of being stared at.3Mossbridge et al. (2009). 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.
Covert Psi
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).4Mossbridge et al. (2011).
Climate Intuition
In 2021 Mossbridge and John Vivanco reported an investigation into remote viewing the climate of the future. Seven intuitives were tasked to use their intuition to answer questions they would be shown in the future regarding various aspects of the climate. Analysis of responses found several independently converging forecasts, in particular to the effect of geo-engineering (the use of large-scale modifications to the environment to mitigate global warming), in which serious caveats towards the technology were advanced.5 Mossbridge & Vivanco (2021).
Hypnotic Suggestion
With Adam Crabtree and Marcia Nisam, Mossbridge reports an investigation into using hypnotic suggestion to induce a self-transcendent state of unconditional love, with the aim of producing evidence for psychic functioning in unscreened volunteers. Thirty-five participants received two hypnotic suggestions – separated by two days – one to experience unconditional love, and the other to access both precognition and psychokinetic abilities. Although hypnotic induction increased feelings of unconditional love there were no significant increases in any psi measure. Interestingly a post-hoc analysis revealed significant scoring (p = 0.0121) in one psi measure – precognitive remote viewing – before hypnotic induction. This significant result was highly correlated with feelings of unconditional love: participants scoring in the top half of UL performed extremely well (p = 0.0005), whereas those falling below the median cut off scored at chance only (p = 0.77). The authors speculate about the existence of retrocausal influences creating this unexpected finding.6 Mossbridge et al. (2020).
Authorship and Telepathy in Non-Speaking Autistic Individuals
In collaboration with Damon Abraham and colleagues, Mossbridge is developing a study of authorship and possible telepathy in non-speaking autistic individuals, applying AI text-embedding scoring methods similar to those used in the lucid dreaming study. This work connects with a broader research programme arising from The Telepathy Tapes podcast. A paper is forthcoming.7Julia Mossbridge, personal communication, 20 September 2026.
A related paper by Abrarham, Marina Weiler and David Acunzo published in 2026 applied the same AI text-embedding scoring pipeline to out-of-body experience target matching.8Weiler et al. (2026). Twenty-one participants attempted to perceive a concealed visual target during induced OBEs. The main target-identification analysis was null across thirteen trials, though two participants spontaneously reported accurate details about experimenters’ activities in an adjacent room – a finding the authors suggest warrants systematic investigation.
Precognition and Presentiment
Overview
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)9Libet (1999). could predict which stimulus would be presented, with some measures giving extreme significance across 40 subjects (p = 2.5 x 10-6).10Mossbridge (2017).
In later presentiment research, Mossbridge concentrated on single-trial experiments in order to eliminate expectancy effects – considered a small risk11Mossbridge et al. (2015). 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 conductance12These data are shown in Fig 6 of the 2012 meta-analysis. 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 $2 USD. 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 $4 USD obliterated these effects; Mossbridge suspects this is due to pushing the differences out beyond the time window in which she obtained consistent heartbeat data (ten seconds prior to the announcement of the reward or lack thereof).13Mossbridge (2014). http://www.koestler-parapsychology.psy.ed.ac.uk/Documents/KPU_Registry_1005.pdf
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.14Mossbridge (2012).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 ‘file-drawer effect’. Also, the successful results could not be attributed to one or two unusually successful investigators: the results were distributed across all of them. Michael Duggan and Patrizio Tressoldi repeated the meta-analysis in 2018, reaching the same conclusions.15Duggan & Tressoldi (2018). Her recent comprehensive review titled ‘precognition at the boundaries’ explored both empirical findings and theoretical discussions, positioning this work within a broader framework of consciousness research.16Mossbridge (2023a).
Implicit Precognition
Mossbridge has investigated unconscious behavioural responses to future information in humans, continuing research begun by Daryl Bem in 2011.17Bem (2011). 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 < 0.018.18Mossbridge (2016). 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 two thousand participants.19Mossbridge (2018).
Recent replication efforts with colleagues have examined Bem’s retroactive priming experiments using German translations, revealing mixed findings characteristic of parapsychological research. Study 1 failed to replicate the overall effect but found significant positive retroactive priming in male participants only (p = 0.014), while Study 2 employed a sham control condition and found an overall negative priming effect (p = 0.022). These contradictory results suggest potential cultural or linguistic factors may influence psi effects, with interpretations drawing on generalized quantum theory to explain inconsistent correlation patterns. 20Wittmann et al. (2024).
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 Vivanco in remote viewing and adapted this method to a precognitive-only method she calls ‘premonition’, described in her book for lay audiences written with Theresa Cheung, The Premonition Code.21Cheung & Mossbridge (2018). Mossbridge and Mark Boccuzzi at the Windbridge Institute 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. Her critical review of Sam Knight’s The Premonitions Bureau highlights the importance of objective investigation of spontaneous precognition phenomena, critiquing Knight’s bias against exploring unconventional scientific ideas regarding nonlinear time and precognitive experiences.22Mossbridge (2023b).
Precognitive Remote Viewing Online Testing
Two studies conducted in 2021 with Boccuzzi and Kirsten Cameron (California Institute of Integral Studies) investigated precognitive remote viewing (PRV). The first experiment utilized a forced-choice design employing 682 unpaid subjects guessing in 5,432 trials. The second experiment utilized a free-response design in which 307 paid volunteers each contributed a single trial. Both experiments investigated the influence of trait (age, gender and sex-at-birth), state (levels of anxiety, unconditional love) and target (measures of ‘interestingness’). Experiment 1 found chance scoring overall and no effect of age on precognition performance, but targets independently rated as interesting were more likely to be correctly predicted than less interesting targets (p = 0.0007) which was confirmed in a second pre-registered analysis (p = 0.000008). In the second experiment, overall scoring above chance was found (p = 0.002) with gender having no effect on performance. Feelings of unconditional love (p = 0.007) and anxiety (p = 0.048) were correlated with accurate psi performance. Interesting targets were again positively correlated with psi accuracy (p = 0.047).23Mossbridge et al. (2024).
A post-hoc analysis of online remote viewing data spanning two years revealed striking correlations with lunar phases. Participants were significantly more likely to initiate trials during last quarter/waning crescent phases (33–35% of trials, p < 1×10⁻⁶) and less likely during full/waning gibbous phases (19–21%). More remarkably, performance accuracy correlated with these participation preferences, with higher hit rates during favored lunar phases (0.83–0.90 ratio) compared to avoided periods (0.58–0.68 ratio, p < 0.01–0.017), suggesting potential gravitational or geomagnetic influences on psi abilities.24Mossbridge (2024).
Future-Photons (CADS Effect)
Since 2019, Mossbridge has developed a novel paradigm in which the ‘precognitive’ ability of photons is probed by measuring the difference in photon counts in the seconds before a randomly decided run length dubbed the CADS effect (Causally Ambiguous Duration Sorting). She has found consistent differences in photon counts based on future run length (p = 10-10) – an indication of an influence percolating back in time. Physicists call this ‘retrocausation’ but it can be interpreted as supporting precognition. The effect has recently been independently replicated by University of California, Berkeley, physicist Winthrop Williams (p = 10-8).
Mossbridge is developing ever more sophisticated protocols which are continuing to show the same effect.25 Mossbridge (2021). In a peer-reviewed 2025 paper26 , she analyzed Williams’ data taking into account periodic oscillations in the effect and was able to show the relationship between photon absorptions and lunar phase as well as derive the linear CADS equation.
Precognitive Dreaming and AI Scoring
Mossbridge and colleagues reported a case study of a possibly precognitive lucid dreamer in the International Journal of Dream Research in 2025.27Mossbridge et al. (2025a). The team analysed five pairs of dream transcripts and corresponding future target events, employing three independent judging approaches: two skilled human judges (pre-registered), unskilled judges, and five AI text-embedding models. The skilled human judges correctly matched three of the five dreams to their targets whilst the unskilled judges only managed one successful match. Several of the AI embedding models both confirmed and extended those matches. The publication describes the first comparison of human versus AI scoring performance within a free-response paradigm.
Theoretical Models
In a wide-ranging overview of the evidence for precognition, Mossbridge describes both implicit research (presentiment experiments) and explicit research (precognitive remote viewing – PRV). Mossbridge explains that presentiment and precognitive remote viewing have very different characteristics, which alludes to different mechanisms. The paper (which is based on a presentation at the Bial Foundation in 2022) describes a physical-time-symmetry (PTS) model that could explain presentiment, and a pervasive universal-consciousness (PUC) model that may be required to explain precognitive remote viewing. Importantly, each model produces testable predictions that are falsifiable – and therefore scientific in the Popperian sense.28Mossbridge (2022).
Debate
A 2014 critique by neuroscientist Sam Schwarzkopf alleged shortcomings in a critique of a presentiment study,29Mossbridge et al. (2014a). including unresolved expectancy effects, inadequate randomization and non-standard baseline measurements.30Schwarzkopf D. (2014). Mossbridge and colleagues answered these criticisms in detail.31Mossbridge et al. (2014b).
Technology and AI in Research
Mossbridge is active in developing technology and employing artificial intelligence tools in research on precognition and other topics.
Choice Compass
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.32Mossbridge (2016).
Smartphone Testing PK and Precognition
In 2021, Mossbridge (with Dean Radin) reported an investigation into the possibility of capturing psi ability using an iPhone app. Between 2017 and 2020, participants were tested for PK and precognition. Analysis of nearly a million trials performed by 2,613 unique visitors found significant PK effects in the opposite direction to that predicted, which was repeated with a confirmatory pre-registered replication (p < 0.02). Interestingly, randomly generated reference bits (used as a kind of control) showed marked deviations from chance (p = 2 x 10-10), that were repeated in a pre-registered analysis (p = 0.001). Mossbridge speculates about either an unknown source of bias or PK influence to explain these extreme deviations. Additionally, psi performance was found to be correlated with psi belief on all three tasks and gender influenced performance on two of the three tasks.33Mossbridge & Radin (2021).
Disclosure Oracle
Mossbridge created Disclosure Oracle, an interactive tool on her website that pulls random sentences from her book Have a Nice Disclosure! Whatever the user types; a passage is returned that often appears uncannily apt to the user’s situation.34Mossbridge, personal communication, 20 September 2026.
AI Research and Ethics
Mossbridge has become active in AI design and ethics. In a 2024 preprint, she proposed a ‘binary stream’ taxonomy of AI systems organised around ten high-level design factors – including relationship with humans, sentience, nonlocal access and serendipity yielding 1,024 possible system types.35Mossbridge (2024b). In a related paper co-authored with an AI system she argued for treating AI as a ‘dynamic relational learning partner’ rather than a passive tool.36Mossbridge (2024c). She also contributed guidance to the Computing Research Association’s 2026 white paper on computing education in the age of AI.37CRA-E (2026). In addition, she has published widely read public articles on AI on Medium.
Future Plans (October 2026)
In terms of future activities, Mossbridge plans to:
- • Continue examining the links between physical models of time and ordinary human experiences of temporality.
- • Investigate how practical training and application of precognitive remote viewing can enhance analytic thinking, reduce cognitive biases, and promote wellbeing.
- • Ethically explore the psi gifts of selected populations, including nonspeakers (with any diagnosis).
- • Investigate methods for accessing and directing unconditional love at a distance through remote-influencing techniques aimed at situations in the past, present, and future.
- • Persist in efforts to develop an informational time-travel process or device capable of transmitting information backward in time, with the aim of enabling beneficial decisions about future events that serve humanity and the planet.
- * Understand how the quality of human-AI relationships influences the work performed by a human-AI team.
Publications and Media Appearances
Several of Mossbridge’s many publications are listed included in Works Cited, below. For a comprehensive list of her publications, see here.
In 2025–26, Mossbridge appeared on the Joe Rogan Experience and on Chris Ramsey’s podcast, reaching large general audiences with discussion of psi research and non-speaking autism.
Michael Duggan
Works Cited
Ayton, P., & Fischer, I. (2004). The hot hand fallacy and the gambler’s fallacy: Two faces of subjective randomness? Memory & Cognition 32, 1369-78.
Barusš, I., & Mossbridge, J. (2016). Transcendent Mind: Rethinking the Science of Consciousness. Washington, D.C., USA: American Psychological Association.
Bem, D.J. (2011). Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect. Journal of Personality and Social Psychology 100, 407-25.
Broderick, D., & Goertzel, B. (eds.). (2014). Evidence for Psi: Thirteen Empirical Research Reports. Jefferson, North Carolina, USA: McFarland.
Cheung, T., & Mossbridge, J. (2018). The Premonition Code: The Science of Precognition. How Sensing the Future Can Change Your Life. London: Watkins Media limited.
CRA-E (2026). Guiding computing education in the age of A: New CRA-E white paper offers principles for program leaders. [Full text.] Computing Research Association, August 2026.
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.
Knight, S. (2022). The Premonitions Bureau: A True Account of Death Foretold. London: Penguin Press.
Libet, B. (1999). Do we have free will? Journal of Consciousness Studies 6, 47-57.
Mossbridge, J. (2017). Characteristic alpha reflects predictive anticipatory activity (PAA) in an auditory-visual task. [Full text.] 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.
Mossbridge, J. (2021). Long time-frame causally ambiguous behaviour demonstrated in an optical system. [Full text.] ResearchGate.
Mossbridge, J. (2022). Precognition at the boundaries: An invited summary. [Full text.] ResearchGate.
Mossbridge, J. (2023a). Precognition at the boundaries: An empirical review and theoretical discussion. [Full text.] Journal of Anomalous Experience and Cognition 3/2, 5-41.
Mossbridge, J. (2023b). Sam Knight details how not to build a premonitions bureau. [Download PDF.] Journal of Anomalous Experience and Cognition 3/2, 369-75.
Mossbridge, J. (2024a). Moon phases and online tests of precognition: Letter to the Editor. [Download PDF.] Journal of Anomalous Experience and Cognition, 4/1, 142-43.
Mossbridge, J. (2024b). Making high-level AI design decisions explicit using a ‘binary stream’ system-designation approach. [Full text.] arXiv preprint.
Mossbridge, J. (2024c). Dynamic relational learning partners: Toward more ethical human-AI relationships. [Full text.] arXiv preprint (with AI co-author).
Mossbridge, J. (2025). Replication and characterization of the causally ambiguous duration-Ssorting (CADS) effect. [Abstract.] Applied Physics Research 17, 85.
Mossbridge, J., Cameron, K., & Boccuzzi, M. (2024). State, trait, and target parameters associated with accuracy in two online tests of precognitive remote viewing. [Download PDF.] Journal of Anomalous Experience and Cognition 4/1, 88-121.
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., Green, D., French, C.C., Pickering, A., & Abraham, D. (2025a). Future dreams of electric sheep: Case study of a possibly precognitive lucid dreamer with AI scoring. [Abstract.] International Journal of Dream Research 18/2, 151-68.
Mossbridge, J., Nisam, M., & Crabtree, A. (2020). Can hypnotic suggestion induce feelings of unconditional love and supernormal performance? [Download PDF.] Spirituality in Clinical Practice 8.
Mossbridge, J., & Radin, D. (2021). Psi performance as a function of demographic and personality factors in smartphone-based tests: Using a “SEARCH” approach. [Full text.] Journal of Anomalous Experience and Cognition 1/1-2, 78-113.
Mossbridge, J., Tressoldi, P., & Utts, J. (2012). Predictive physiological anticipation preceding seemingly unpredictable stimuli: A meta-analysis. Frontiers in Psychology 3, 390.
Mossbridge, J., Tressoldi, P., Utts, J., Ives, J.A., Radin, D., & Jonas, W.B. (2014a). Predicting the unpredictable: Critical analysis and practical implications of predictive anticipatory activity. [Full text.] Frontiers in Human Neuroscience 8, 146.
Mossbridge, J., Tressoldi, P., Utts, J., Ives, J.A., Radin, D., & Jonas, W.B. (2014b). We did see this coming: Response to, ‘We should have seen this coming’, by D. Sam Schwarzkopf. [Abstract.] Quantitative Biology: Neurons and Cognition
Mossbridge, J., & Vivanco, J. (2021). Can we heal the Earth with intuition? Case report of an intuition-guided approach to enhancing exploration in climate science. [Full text.] ResearchGate.
Schwarzkopf, D.S. (2014). We should have seen this coming. [Full text.] Frontiers in Human Neuroscience 8.
Weiler, M., Abraham, D., Acunzo, D.J.P., & Hermansson, N. (2026). Assessing correspondence between subjective reports and visual targets during attempted out-of-body experiences. [Abstract.] EXPLORE: The Journal of Science and Healing 22/6, art. 103506.
Wittmann, M., Scheck, F., Feldmann, J., Glaesmann, A., Mossbridge, J., & Bem, D. (2024). The German version of a retroactive priming task shows mixed effects. [Abstract.] Psychology of Consciousness: Theory, Research, and Practice 11/4, 392-40.