Analog-brain interfaces and the obsession for control: coupled dynamics through real-time image rendering of chaotic systems

Develop a closed-loop system in which EEG signals from a participant dynamically modulate the parameters of an analog computer implementing chaotic dynamics. The resulting system behavior is visualized in real time (e.g., via an oscilloscope), forming a perceptual feedback channel back to the participant. In this configuration, brain activity influences the evolution of the chaotic system, whose output in turn perturbs the participant’s neural dynamics—effectively closing the loop between brain and machine. This creates a hybrid dynamical system spanning biological and physical substrates, enabled by the near-real-time property of analog computers. Key question to explore: Can the brain implicitly learn to stabilize or “tame” chaotic dynamics through this feedback? Does the system converge to structured, controllable regimes, or does it amplify instability and loss of control? More broadly, what kinds of joint dynamics emerge when two complex, partially unpredictable systems are tightly coupled in real time? And how do people emotionally react to those joint emergent dynamics? The key motivation for using an EEG interface, rather than an explicit control device (e.g., a joystick or parameter knobs), is to probe implicit learning and a desire for control directly at the level of neural dynamics. By bypassing deliberate, goal-directed control (our little 'interpreter), the system shifts the interaction away from conscious strategy and toward more intrinsic, possibly subconscious responses to instability and control.