Imagine unlocking your office in the morning. Within milliseconds you will be able to tell whether the furniture, computer, and papers on the desk are still where they are expected to be. You will also quickly detect if something unexpected is in the room, for example a box of chocolates an appreciative colleague has left for you. The mechanism proposed to underlie our mind’s efficient ability to grasp the environment converges on the notion of predictive brain. Put forward as a universal principle of the brain, the crux of the notion is that brains are essentially prediction machines that constantly attempt to match incoming inputs with top-down predictions. This provides us a powerful means to streamline the massive amount of continuous incoming information from the environment. Furthermore, when actual input is discrepant from the predicted input, a prediction error (PE) is elaborated to drive learning, i.e. updating internal models that will help to improve future predictions.
If the predictive brain is indeed a unifying principle, two critical issues need to be resolved. First, the predictive processing framework has not yet delineated the nature of internal models on which predictions are based (e.g. memory of prior experience) and how our actual experiences shape them in turn. Second, how does such a universal brain principle play out in diverse brains (e.g. young versus old brains)? Addressing these knowledge gaps is important in order to make a breakthrough in our understanding of the fundamental nature of the human mind and brain and to test the adaptivity of the predictive brain principle in accommodating inherent diversities of human brains.
By connecting three separate strands of research (i.e. predictive processing, memory systems, and lifespan development), the PIVOTAL research program aims to unravel the cognitive and neural mechanisms that enable the brain to (i) generate predictions based on memory of prior experience (episodic memory) and knowledge about the world (semantic memory); (ii) verify its predictions given the actual event, and (iii) engage in subsequent processes that in turn modify the memory representation. Using cognitive neuroscience methodology (functional magnetic resonance imaging), experimental research designs, and computational modelling, these mechanisms are being systematically examined in children, younger adults, and older adults, whose neurocognitive landscapes are highly different from each other. The gain in knowledge will characterize the cognitive architectures that allow the human brain to perform predictive processing as a fundamental operation in its interaction with the environment.
