The basolateral amygdala in reward learning and addiction

Abstract

Sophisticated behavioral paradigms partnered with the emergence of increasingly selective techniques to target the basolateral amygdala (BLA) have resulted in an enhanced understanding of the role of this nucleus in learning and using reward information. Due to the wide variety of behavioral approaches many questions remain on the circumscribed role of BLA in appetitive behavior. In this review, we integrate conclusions of BLA function in reward-related behavior using traditional interference techniques (lesion, pharmacological inactivation) with those using newer methodological approaches in experimental animals that allow in vivo manipulation of cell type-specific populations and neural recordings. Secondly, from a review of appetitive behavioral tasks in rodents and monkeys and recent computational models of reward procurement, we derive evidence for BLA as a neural integrator of reward value, history, and cost parameters. Taken together, BLA codes specific and temporally dynamic outcome representations in a distributed network to orchestrate adaptive responses. We provide evidence that experiences with opiates and psychostimulants alter these outcome representations in BLA, resulting in long-term modified action.

Keywords: Amphetamine; Basolateral amygdala; Discounting; Opiate; Orbitofrontal cortex; Outcome devaluation; Reversal learning.

Figure 1. Amygdala and reward

Pubmed search terms “amygdala” and “reward” or “amygdala” and “fear” from 1960–2014, excluding 2015. A steeper rise in the number of publications on the amygdala in appetitive behavior now accounts for approximately half of the reports in the 2010s.

Figure 2. Rodent and monkey amygdala nuclei

Coronal sections of amygdala nuclei in the mouse and the macaque monkey. Modified from John et al. 2013.

Figure 3. An adapted model of reward procurement for the integration of incentive value, reward history, and costs by the basolateral amygdala (BLA)

According to this model, a signal of subjective reward intensity (RI), which we call incentive value, gets integrated from the past into the present (a vertical line denotes past and present). In the present, there is an integration of cost parameters (risk, delay, effort). The evidence we review suggests this integration occurs dynamically in the BLA, as part of a distributed network. The putative product of BLA signaling (to areas like the dorsomedial striatum, nucleus accumbens, and orbitofrontal cortex) is a position on the “reward mountain” (A through E). The mountain is a scalar representation of “cost” and “payoff.” Modified from Breton et al. 2014.