Information seeking mechanism of neural populations in the lateral prefrontal cortex

Information seeking criteria: artificial intelligence, economics, psychology, and neuroscience

There has been an enormous amount of interest in how the brain seeks information. The study of this issue is a rapidly growing field in neuroscience. Information seeking is to make informative choices among multiple alternatives. A central issue in information seeking is how the value of information is assessed in order to choose informative alternatives. This issue has been studied in psychology, economics, and artificial intelligence. The present review is focused on information assessment and summarizes the psychological and computational criteria with which humans and computers assess information. Based on the summary, neurophysiological findings are discussed. In addition, a computational view of the relationships between these criteria is presented.

Reward uncertainty asymmetrically affects information transmission within the monkey fronto-parietal network

A central hypothesis in research on executive function is that controlled information processing is costly and is allocated according to the behavioral benefits it brings. However, while computational theories predict that the benefits of new information depend on prior uncertainty, the cellular effects of uncertainty on the executive network are incompletely understood. Using simultaneous recordings in monkeys, we describe several mechanisms by which the fronto-parietal network reacts to uncertainty. We show that the variance of expected rewards, independently of the value of the rewards, was encoded in single neuron and population spiking activity and local field potential (LFP) oscillations, and, importantly, asymmetrically affected fronto-parietal information transmission (measured through the coherence between spikes and LFPs). Higher uncertainty selectively enhanced information transmission from the parietal to the frontal lobe and suppressed it in the opposite direction, consistent with Bayesian principles that prioritize sensory information according to a decision maker’s prior uncertainty.

Bahareh Taghizadeh and Nicholas Foley et al. show that individual neuronal responses, population spiking activity, and local field potential oscillations encode the variance of expected rewards independent of their value. They also demonstrate that reward uncertainty asymmetrically affects neuronal transmission within the monkey fronto-parietal network.

Neural circuitry of information seeking

Humans and animals navigate uncertain environments by seeking information about the future. Remarkably, we often seek information even when it has no instrumental value for aiding our decisions - as if the information is a source of value in its own right. In recent years, there has been a flourishing of research into these non-instrumental information preferences and their implementation in the brain. Individuals value information about uncertain future rewards, and do so for multiple reasons, including valuing resolution of uncertainty and overweighting desirable information. The brain motivates this information seeking by tapping into some of the same circuitry as primary rewards like food and water. However, it also employs cortex and basal ganglia circuitry that predicts and values information as distinct from primary reward. Uncovering how these circuits cooperate will be fundamental to understanding information seeking and motivated behavior as a whole, in our increasingly complex and information-rich world.