Fatigue modulates dopamine availability and promotes flexible choice reversals during decision making

Abstract

During decisions, animals balance goal achievement and effort management. Despite physical exercise and fatigue significantly affecting the levels of effort that an animal exerts to obtain a reward, their role in effort-based choice and the underlying neurochemistry are incompletely known. In particular, it is unclear whether fatigue influences decision (cost-benefit) strategies flexibly or only post-decision action execution and learning. To answer this question, we trained mice on a T-maze task in which they chose between a high-cost, high-reward arm (HR), which included a barrier, and a low-cost, low-reward arm (LR), with no barrier. The animals were parametrically fatigued immediately before the behavioural tasks by running on a treadmill. We report a sharp choice reversal, from the HR to LR arm, at 80% of their peak workload (PW), which was temporary and specific, as the mice returned to choose the HC when the animals were successively tested at 60% PW or in a two-barrier task. These rapid reversals are signatures of flexible choice. We also observed increased subcortical dopamine levels in fatigued mice: a marker of individual bias to use model-based control in humans. Our results indicate that fatigue levels can be incorporated in flexible cost-benefits computations that improve foraging efficiency.

Figure 1

Experimental apparatus. (a) Treadmill schematic side view used throughout the running period of the study. The humidity and temperature of treadmill chamber were constant during each session. (b) T-maze schematic top view, mice were placed in the start arms and allowed to choose between the two arm goals. To obtain 0.1 ml of sweetened condensed milk, the animals could climb over a wire mesh barrier (HR arm); otherwise, mice could choose the low reward arm (reward = 0.03 ml). In experiment 4, a second barrier was also placed in the LR arm.

Figure 2

Results of the Effort-Based Decision Making task. The figure reports the behavioural performance of the Experimental group across the three decision experiments, as the mean (±SEM) number of trials in which mice chose the high effort HR arm. Experiment 1 was composed of four blocks (A–D), each consisting of eight trials. A mesh 10-cm barrier was placed in the HR arm. Immediately before the behavioural tasks the animals performed a 40 min run on a mechanical treadmill. The intensity of physical effort was parameterized on maximal power load (PW) of each animal. Intensity of run was improved each block with this progression: negligible (block A); 40%PW (block B); 60%PW (block C); 80%PW (block D). (Note that mice in the CtrlDec group also performed block A, with the same performance as the Experimental group). In experiment 2, the intensity of the run period was decreased to 60%PW as in block C. In experiment 3, there were 10-cm barriers in both arms. In experiment 4, the procedure was the same as block D, but for only 1 day.

Figure 3

Behavioural strategy changes were evident from the first trial. When highly fatigued (blocks D and F), mice of the Exp group showed a clear preference for LR (thus, a reversal of choice from HR to LR) from the very first trial every day, corroborating the idea that they were performing a cost-benefit computation rather than learning to avoid the costly HR choice by trial and error. The graph also shows that this preference for LR was maintained (on average) until the 8^th trial, suggesting that this was a good window to investigate the phenomenon.

Figure 4

Effects of fatigue on dopamine and serotonin levels. Tissue levels of serotonin (5-HT) and dopamine (DA) (ng/mg tissue; mean ± SEM) of three mice groups: Exp (Experimental: performed 40 min run on treadmill at 80% of their maximal power load, and then the T-maze choice), CtrlDec (Control Decision: performed 40 min run on treadmill at low intensity, and then the T-maze choice), and CtrlRun (Control Run: performed 40 min run on treadmill at 80% of their maximal power load, but not the T-maze choice). Tissue levels were analysed in four brain areas: Frontal cortex, hippocampus, midbrain and nucleus accumbens. Post-hoc analysis significance: *p < 0.05; **p < 0.01; ***p < 0.001. Note that DA levels in the frontal cortex - which are generally in an inverse relationship with DA levels in the accumbens - were higher in all three groups compared to naive mice (0.15 ng/mg in a group of 4 naive female C57BL/6 mice we tested) but this activation did not significantly vary across the conditions we studied.