Despite considerable progress in the neuroscience of intelligence, a number of challenges remain. For example, although it is well-established that fronto-parietal networks play an important role in cognitive differences, the... [ view full abstract ]
Despite considerable progress in the neuroscience of intelligence, a number of challenges remain. For example, although it is well-established that fronto-parietal networks play an important role in cognitive differences, the consistency of that role across the cognitive hierarchy and between individuals has not been determined. Similarly, although the Neural Efficiency Hypothesis has helped to motivate and guide much of the literature on activity-ability relationships, it faces limitations in its generalization to all neural networks and cognitive tasks. More broadly, the field as a whole lacks an integrative framework that unites the various sub-areas, and provides a priori, directional predictions for any given study.
Separately, hierarchical predictive processing has recently emerged as a candidate theoretical paradigm with potential to unite much of neuroscience. Reviews of the literature reveal strong support for predictive processing across domains of cognitive psychology, psychophysics, basic and computational neuroscience, and psychopathology. However, this theory has yet to be applied to the neuroscience of intelligence.
On that basis, this presentation will outline the tenets and evidence base for predictive processing theories, and assess their relevance and implications for the neuroscience of intelligence. It will be argued that because predictive processing holds a fundamentally hierarchical view of brain organization, and implies an information-theoretic account of task-related neural recruitment, it appears well-suited to integrate and foster progress in the neuroscience of intelligence. The presentation will conclude by reviewing some of the specific hypotheses that follow from applying predictive processing to EEG and neuroanatomical research on intelligence.
