The realization that the human brain is dynamic and constantly changing arises from the seminal work of Hebb (1949) which posits how the strengths of synaptic connections between neurons change over time based on their correlated activity with the insightful phrase - 'fire together, wire together'. This Hebbian 'learning’, reflecting the brain's ability to change and adapt based on prior experiences, has led to the predictive plasticity hypothesis (Rao and Sejnowski, 2001; Magee and Grienberger, 2020; Halvagal and Zenke, 2023) which points to a synaptic level mechanism underpinning the brain's proactive tendency to seek causal understanding by anticipating future events beyond reacting to stimuli as they arise. A tiger's roar must not be confused with the harmless chirp of a bird. The ability to anticipate future contingencies without being overly surprised is crucial for survival while minimizing energy expenditures by our miserly brain (Friston, 2010; Clark, 2013; Hohwy, 2013).
In situations involving risk and uncertainty, how available choices are perceived has fundamental influence on the eventual decision and the corresponding outcomes. Building on predictive plasticity together with the neurochemistry of attention and valuation, we outline a neurobiological approach to model choice perception from sensation (of stimuli) to perception (especially the consequentialist aspects of specific choices) through attention and memory (necessarily selective) prior to their evaluation in which cognition has a natural role. Given the inherent scarcity of attention, sensory inputs are allocated attention in proportion to their degree of surprise (when deviation from the predictive prior surpasses a certain threshold) which is inherently costly. This triggers the formation of new priors modulated by a tendency to resist change (inertia).
Our miserly brain minimizes mental efforts in seeking to update predictive priors through synaptic weights. The resulting perceived choices - as stable representations of sensory inputs - may be linked to observable decision making through a utility model in which the attention-modulated weights play a central role (Chew, Wang, Zhong, 2023). This points to the need to derive testable implications linking predictive plasticity to observed choice anomalies with roots in choice perception, e.g., loss-gain framing, independent versus correlated Allais behavior, and source and ambiguity preference.
