Develop your capacity for anomalous cognition through structured exercises, statistical feedback, and biometric correlation
Extended perception training explores the boundaries of human awareness through rigorous, repeatable protocols. Every exercise is scored against statistical chance baselines, so you always know whether your results are meaningful or random.
Sessions integrate with your wearable data to explore how physiological states correlate with perception performance — turning subjective experiences into measurable data.
Four evidence-based protocols, each targeting a different aspect of perception
Select the correct target from a set of options. Results are compared against statistical chance (e.g., 25% for 4 choices) to measure performance objectively.
Predict outcomes before they occur within timed windows. The app records your prediction, then reveals the target — building a dataset of your anticipatory accuracy over time.
Practice subtle perception by describing impressions about hidden targets. Free-response entries are later compared against actual targets for accuracy patterns.
Record intuitive impressions throughout your day. Over time, the app will help you identify patterns in when and where your intuitive hits are most reliable.
A typical forced-choice perception trial
The app cryptographically selects a random target from the candidate pool. The selection is hashed so you can verify fairness after the trial.
Take a moment to quiet your mind. Use breathing techniques or HRV coherence to enter a receptive state. Record your impressions through drawing, notes, or selection.
Select the candidate that best matches your impressions. The actual target is revealed, and the app scores your hit or miss against chance probability.
Over multiple trials, the app builds confidence intervals around your performance. Newton AI provides personalized insights based on your patterns and biometric correlations.
Transparent, statistically grounded performance tracking
All results are scored against mathematical chance baselines. Statistical significance requires sufficient trial volume — typically 50+ trials for meaningful patterns.