First Grand Challenge: The Physical Basis of Consciousness
The goal of our first Grand Challenge was to devise a theoretical framework for understanding consciousness in accordance with physical laws – as a form of non-deterministic computation.
Izi Stoll kicked off this Grand Challenge by applying mathematical toolkits from the field of computational physics to model the voltage shifts in cortical neurons. Classically, the neuron is viewed like a transistor, either firing or not firing at any given time, encoding Shannon entropy. The new approach involves viewing the voltage of the cortical neuron membrane as the mixed sum of all component microstates, thereby encoding von Neumann entropy. So, rather than being considered a binary computational unit, always in an off-state or an on-state, the cortical neuron encodes the probability of shifting from an off-state to an on-state.
This new approach to modeling probabilistic signaling outcomes in cortical neurons naturally yields perceivable information content, the spontaneous emergence of a more ordered system state during predictive processing, and contextually-appropriate behaviors resulting from a system-wide non-deterministic (but fully mechanistic) decision process. More generally, this approach yields a theoretical framework for semi-Markovian systems achieving Bayesian inference at any scale, through a hardware-instantiated non-deterministic computation that cannot be replicated in classical computing architecture.
The next step involves resolving this new theoretical framework for ambient-temperature quantum computation with the previously-established framework for active inference devised by Karl Friston. The goal of that effort is to fold Stoll's deeply mechanistic neural implementation into the overarching framework of Bayesian neural computation that has been laid out by Friston. The next step is testing the predictions of the new theory, in partnership with neuroscientists Dave Redish, Stuart Firestein, and Amy Wachholtz. The goal of this effort is to evaluate whether the theory holds up when tested in the laboratory, then to help clinical researchers develop improved treatments for their patients. Redish and Firestein are leading on assessing the neurophysiological predictions of this new theory, and Wachholtz is leading on developing integrated treatments for patients struggling with addiction and mental illness. In addition, philosophers Asger Kirkeby-Hinrup, Christopher Viger, and Marco Nathan are exploring the philosophical implications of this theoretical framework, and evaluating its explanatory power, in an effort to bridge the gap between science and philosophy.