Value, Confidence, Deliberation: A Functional Partition of the Medial Prefrontal Cortex Demonstrated across Rating and Choice Tasks

A neurometabolic mechanism involving dmPFC/dACC lactate in physical effort-based decision-making

Motivation levels vary across individuals, yet the underlying mechanisms driving these differences remain elusive. The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) and the anterior insula (aIns) play crucial roles in effort-based decision-making. Here, we investigate the influence of lactate, a key metabolite involved in energy metabolism and signaling, on decisions involving both physical and mental effort, as well as its effects on neural activation. Using proton magnetic resonance spectroscopy and functional MRI in 63 participants, we find that higher lactate levels in the dmPFC/dACC are associated with reduced motivation for physical effort, a relationship mediated by neural activity within this region. Additionally, plasma and dmPFC/dACC lactate levels correlate, suggesting a systemic influence on brain metabolism. Supported by path analysis, our results highlight lactate's role as a modulator of dmPFC/dACC activity, hinting at a neurometabolic mechanism that integrates both peripheral and central metabolic states with brain function in effort-based decision-making.

Orthogonal neural encoding of targets and distractors supports multivariate cognitive control

The complex challenges of our mental life require us to coordinate multiple forms of neural information processing. Recent behavioural studies have found that people can coordinate multiple forms of attention, but the underlying neural control process remains obscure. We hypothesized that the brain implements multivariate control by independently monitoring feature-specific difficulty and independently prioritizing feature-specific processing. During functional MRI, participants performed a parametric conflict task that separately tags target and distractor processing. Consistent with feature-specific monitoring, univariate analyses revealed spatially segregated encoding of target and distractor difficulty in the dorsal anterior cingulate cortex. Consistent with feature-specific attentional priority, our encoding geometry analysis revealed overlapping but orthogonal representations of target and distractor coherence in the intraparietal sulcus. Coherence representations were mediated by control demands and aligned with both performance and frontoparietal activity, consistent with top-down attention. Together, these findings provide evidence for the neural geometry necessary to coordinate multivariate cognitive control.

Value Estimation versus Effort Mobilization: A General Dissociation between Ventromedial and Dorsomedial Prefrontal Cortex

Deciding on a course of action requires both an accurate estimation of option values and the right amount of effort invested in deliberation to reach sufficient confidence in the final choice. In a previous study, we have provided evidence, across a series of judgment and choice tasks, for a dissociation between the ventromedial prefrontal cortex (vmPFC), which would represent option values, and the dorsomedial prefrontal cortex (dmPFC), which would represent the duration of deliberation. Here, we first replicate this dissociation and extend it to the case of an instrumental learning task, in which 24 human volunteers (13 women) choose between options associated with probabilistic gains and losses. According to fMRI data recorded during decision-making, vmPFC activity reflects the sum of option values generated by a reinforcement learning model and dmPFC activity the deliberation time. To further generalize the role of the dmPFC in mobilizing effort, we then analyze fMRI data recorded in the same participants while they prepare to perform motor and cognitive tasks (squeezing a handgrip or making numerical comparisons) to maximize gains or minimize losses. In both cases, dmPFC activity is associated with the output of an effort regulation model, and not with response time. Taken together, these results strengthen a general theory of behavioral control that implicates the vmPFC in the estimation of option values and the dmPFC in the energization of relevant motor and cognitive processes.

The neural correlates of memory integration in value-based decision-making during human spatial navigation

In daily life, we often make decisions based on relative value of the options, and we often derive these values from segmenting or integrating the outcomes of past episodes in memory. The neural correlates involved in value-based decision-making have been extensively studied in the literature, but few studies have investigated this topic in decisions that require segmenting or integrating episodic memory from related sources, and even fewer studies examine it in the context of spatial navigation. Building on the computational models from our previous studies, the current study investigates the neural substrates involved in decisions that require people either segment or integrate wayfinding outcomes involving different goals, across virtual spatial navigation tasks with differing demands. We find that when decisions require computation of spatial distances for navigation options, but also evaluation of one's prior spatial navigation ability with the task, the estimated value of navigational choices (EV) modulates neural activity in the dorsomedial prefrontal (dmPFC) cortex and ventrolateral prefrontal (vlFPC) cortex. However, superior parietal cortex tracked EV when decision-making tasks only require spatial distance memory but not evaluation of spatial navigation ability. Our findings reveal divergent neural substrates of memory integration in value-based decision-making under different spatial processing demands.

Neuromodulation of choice-induced preference changes: the tDCS study of cognitive dissonance

Introduction

Difficult choices between two equally attractive options result in a cognitive discrepancy between dissonant cognitions such as preferences and actions often followed by a sense of psychological discomfort known as cognitive dissonance. It can lead to changes in the desirability of options: the chosen option becomes more desirable, whereas the rejected option is devalued. Despite the ample experimental evidence to show this effect, the neural mechanisms and timing of such choice-induced preference changes are not fully understood.

Methods

In this study, we used transcranial direct current stimulation (tDCS) to modulate the activity of the posterior medial frontal cortex (pMFC), which has been associated with conflict monitoring and choice-induced preference changes in neuroimaging studies. Prior to a revised version of Brehm's free-choice paradigm, participants in two experiments underwent cathodal (inhibitory) or anodal (excitatory) tDCS of the pMFC compared to sham (placebo) stimulation prior to the choice phase.

Results

Our results showed that cathodal tDCS significantly decreased the choice-induced preference change relative to a sham, but only in direct comparisons of rejected options. No significant effect of anodal tDCS in comparison with sham was observed.

Discussion

This study replicates the general behavioral effect of cognitive dissonance and provide partial support for the theory of the pMFC contribution to choice-related cognitive dissonance and subsequent preference changes, with possible limitations of an under-sampling for the obtained effect size and an asymmetry in the inhibitory-excitatory effects of non-invasive tDCS.

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) is a brain area subject to many theories and debates over its function(s). Even its precise anatomical borders are subject to much controversy. In the past decades, the dmPFC/dACC has been associated with more than 15 different cognitive processes, which sometimes appear quite unrelated (e.g. body perception, cognitive conflict). As a result, understanding what the dmPFC/dACC does has become a real challenge for many neuroscientists. Several theories of this brain area's function(s) have been developed, leading to successive and competitive publications bearing different models, which sometimes contradict each other. During the last two decades, the lively scientific exchanges around the dmPFC/dACC have promoted fruitful research in cognitive neuroscience. In this review, we provide an overview of the anatomy of the dmPFC/dACC, summarize the state of the art of functions that have been associated with this brain area and present the main theories aiming at explaining the dmPFC/dACC function(s). We explore the commonalities and the arguments between the different theories. Finally, we explain what can be learned from these debates for future investigations of the dmPFC/dACC and other brain regions' functions.

Neural and computational underpinnings of biased confidence in human reinforcement learning

While navigating a fundamentally uncertain world, humans and animals constantly evaluate the probability of their decisions, actions or statements being correct. When explicitly elicited, these confidence estimates typically correlates positively with neural activity in a ventromedial-prefrontal (VMPFC) network and negatively in a dorsolateral and dorsomedial prefrontal network. Here, combining fMRI with a reinforcement-learning paradigm, we leverage the fact that humans are more confident in their choices when seeking gains than avoiding losses to reveal a functional dissociation: whereas the dorsal prefrontal network correlates negatively with a condition-specific confidence signal, the VMPFC network positively encodes task-wide confidence signal incorporating the valence-induced bias. Challenging dominant neuro-computational models, we found that decision-related VMPFC activity better correlates with confidence than with option-values inferred from reinforcement-learning models. Altogether, these results identify the VMPFC as a key node in the neuro-computational architecture that builds global feeling-of-confidence signals from latent decision variables and contextual biases during reinforcement-learning.