Predictive Neuronal Adaptation as a Basis for Consciousness - Luczak, Artur; Kubo, Yoshimasa (Frontiers in Systems Neuroscience, 2022)
Being able to correctly predict the future and to adjust own actions accordingly, offers great survival advantage. In fact, this could be the main reason for organisms to evolve their brains. The most mysterious feature of brain activity: consciousness, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Even at the single neuron level, predicting future activity and adapting synaptic inputs accordingly, is the best strategy to maximize metabolic energy for a neuron. Following on those ideas, here we examine if surprise minimization by single neurons could be a basis for consciousness. First, we show in simulations that as a neural network learns a task, then the surprise within neurons, defined as: difference between actual and expected activity, changes similarly as consciousness of a learned skill in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of ms), resulted in improved network performance. This improvement is likely due to the fact that adapting activity based on the internal predictive model, allows each neuron for a more “educated” response to stimuli. Based on those results, we propose that: neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. This is because, adapting activity toward a predicted level, allows neurons to exchange not only information about stimulus but also about its internal model predictions and thus, to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this allows for directly testing our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness. In summary, we present a theoretical, computational and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness.