Neurobiological models of long-term memory propose a mechanism by which initially weak memories are strengthened through subsequent activation that engages common neural pathways minutes to hours later1. This synaptic tag-and-capture model has been hypothesized to explain how inconsequential information is selectively consolidated following salient experiences. Behavioural evidence for tag-and-capture is provided by rodent studies in which weak early memories are strengthened by future behavioural training2,3. Whether a process of behavioural tagging occurs in humans to transform weak episodic memories into stable long-term memories is unknown. Here we show, in humans, that information is selectively consolidated if conceptually related information, putatively represented in a common neural substrate, is made salient through an emotional learning experience. Memory for neutral objects was selectively enhanced if other objects from the same category were paired with shock. Retroactive enhancements as a result of emotional learning were observed following a period of consolidation, but were not observed in an immediate memory test or for items strongly encoded before fear conditioning. These findings provide new evidence for a generalized retroactive memory enhancement, whereby inconsequential information can be retroactively credited as relevant, and therefore selectively remembered, if conceptually related information acquires salience in the future.

Over the past decade, fMRI techniques have been increasingly used to interrogate the neural correlates of successful emotional memory encoding. These investigations have typically aimed to either characterize the contributions of the amygdala and medial temporal lobe (MTL) memory system, replicating results in animals, or delineate the neural correlates of specific behavioral phenomena. It has remained difficult, however, to synthesize these findings into a systems neuroscience account of how networks across the whole brain support the enhancing effects of emotion on memory encoding. To this end, the present study employed a meta-analytic approach using activation likelihood estimates to assess the anatomical specificity and reliability of event-related fMRI activations related to successful memory encoding for emotional versus neutral information. The meta-analysis revealed consistent clusters within bilateral amygdala, anterior hippocampus, anterior and posterior parahippocampal gyrus, the ventral visual stream, left lateral prefrontal cortex and right ventral parietal cortex. The results within the amygdala and MTL support a wealth of findings from the animal literature linking these regions to arousal-mediated memory effects. The consistency of findings in cortical targets, including the visual, prefrontal, and parietal cortices, underscores the importance of generating hypotheses regarding their participation in emotional memory formation. In particular, we propose that the amygdala interacts with these structures to promote enhancements in perceptual processing, semantic elaboration, and attention, which serve to benefit subsequent memory for emotional material. These findings may motivate future research on emotional modulation of widespread neural systems and the implications of this modulation for cognition.

Dopaminergic networks modulate neural processing across a spectrum of function from perception to learning to action. Multiple organizational schemes based on anatomy and function have been proposed for dopaminergic nuclei in the midbrain. One schema originating in rodent models delineated ventral tegmental area (VTA), implicated in complex behaviors like addiction, from more lateral substantia nigra (SN), preferentially implicated in movement. However, because anatomy and function in rodent midbrain differs from the primate midbrain in important ways, the utility of this distinction for human neuroscience has been questioned. We asked whether functional definition of networks within the human dopaminergic midbrain would recapitulate this traditional anatomical topology. We first developed a method for reliably defining SN and VTA in humans at conventional MRI resolution. Hand-drawn VTA and SN regions-of-interest (ROIs) were constructed for 50 participants, using individually-localized anatomical landmarks and signal intensity. Individual segmentation was used in seed-based functional connectivity analysis of resting-state functional MRI data; results of this analysis recapitulated traditional anatomical targets of the VTA versus SN. Next, we constructed a probabilistic atlas of the VTA, SN, and the dopaminergic midbrain region comprised (SN plus VTA) from individual hand-drawn ROIs. The combined probabilistic (VTA plus SN) ROI was then used for connectivity-based dual-regression analysis in two independent resting-state datasets (n=69 and n=79). Results of the connectivity-based, dual-regression functional segmentation recapitulated results of the anatomical segmentation, validating the utility of this probabilistic atlas for future research.

How does the brain translate information signaling potential rewards into motivation to get them? Motivation to obtain reward is thought to depend on the midbrain, (particularly the ventral tegmental area, VTA), the nucleus accumbens (NAcc), and the dorsolateral prefrontal cortex (dlPFC), but it is not clear how the interactions amongst these regions relate to reward-motivated behavior. To study the influence of motivation on these reward-responsive regions and on their interactions, we used Dynamic Causal Modeling (DCM) to analyze functional magnetic resonance imaging (fMRI) data from humans performing a simple task designed to isolate reward anticipation. The use of fMRI permitted the simultaneous measurement of multiple brain regions while human participants anticipated and prepared for opportunities to obtain reward, thus allowing characterization of how information about reward changes physiology underlying motivational drive. Further, we modeled the impact of external reward cues on causal relationships within this network, thus elaborating a link between physiology, connectivity, and motivation. Specifically, our results indicated that dlPFC was the exclusive entry point of information about reward in this network, and that anticipated reward availability caused VTA activation only via its effect on the dlPFC. Anticipated reward thus increased dlPFC activation directly, whereas it influenced VTA and NAcc only indirectly, by enhancing intrinsically weak or inactive pathways from the dlPFC. Our findings of a directional prefrontal influence on dopaminergic regions during reward anticipation suggest a model in which the dlPFC integrates and transmits representations of reward to the mesolimbic and mesocortical dopamine systems, thereby initiating motivated behavior.