Neuroscience

ARDA discovers the governing equations of neural dynamics directly from recording data, identifying the mathematical laws that describe how neural populations interact, synchronize, and transition between activity states. Rather than reducing neural data to static summary measures, ARDA captures the full dynamical structure — oscillatory coupling, regime transitions, and directed causal interactions — as typed scientific claims. This approach reveals governing relationships that standard analyses structurally miss: state-dependent connectivity changes, nonlinear coupling dynamics, and the transition rules governing shifts between distinct neural activity regimes.

ARDA's regime classification automatically identifies distinct brain states and characterizes their transition dynamics — essential for understanding how neural systems switch between resting, task-engaged, and pathological states. The Symbolic mode discovers oscillatory laws governing neural rhythms and coupling relationships between frequency bands. The Causal mode maps effective connectivity — directed causal relationships between brain regions — from observational recordings without requiring invasive interventions. Negative Controls including time shuffle and phase randomization ensure that discovered connectivity reflects genuine causal influence rather than volume conduction, shared input, or statistical artifacts in the recording.