Multiphasic Temporal Dynamics in Responses of Midbrain Dopamine Neurons to Appetitive and Aversive Stimuli

By Christopher D. Fiorillo, Minryung R. Song, Sora R. Yun. 2013

106 citations recorded by the source corpus.

The transient response of dopamine neurons has been described as reward prediction error (RPE), with activation or suppression by events that are better or worse than expected, respectively. However, at least a minority of neurons are activated by aversive or high-intensity stimuli, casting doubt on the generality of RPE in describing the dopamine signal. To overcome limitations of previous studies, we studied neuronal responses to a wider variety of high-intensity and aversive stimuli, and we quantified and controlled aversiveness through a choice task in which macaques sacrificed juice to avoid aversive stimuli. Whereas most previous work has portrayed the RPE as a single impulse or “phase,” here we demonstrate its multiphasic temporal dynamics. Aversive or high-intensity stimuli evoked a triphasic sequence of activation-suppression-activation extending over a period of 40–700 ms. The initial activation at short latencies (40–120 ms) reflected sensory intensity. The influence of motivational value became dominant between 150 and 250 ms, with activation in the case of appetitive stimuli, and suppression in the case of aversive and neutral stimuli. The previously unreported late activation appeared to be a modest “rebound” after strong suppression. Similarly, strong activation by reward was often followed by suppression. We suggest that these “rebounds” may result from overcompensation by homeostatic mechanisms in some cells. Our results are consistent with a realistic RPE, which evolves over time through a dynamic balance of excitation and inhibition.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Molecular Biology

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Citations in the corpus

Coordinated and Compartmentalized Neuromodulation Shapes Sensory Processing in Drosophila (2015, neutral): “…of flexible circuit processing, their anatomic and functional heterogeneity and the intricate wiring of their target neuropils (Beier et al., 2015; Fiorillo et al., 2013; Lammel et al., 2014; Lerner et al., 2015) have made it difficult to resolve how they can selectively alter synaptic signaling…”
Pain-relief learning in flies, rats, and man: basic research and applied perspectives (2014, background): “…activity of their target regions, such as the ventral striatum, can be increased not only by reward (for review, see Schultz 2013) but also by the reduction (Seymour et al. 2005) or upon the termination (Becerra and Borsook 2008; Brischoux et al. 2009; Fiorillo et al. 2013a,b) of an adverse event.”
Dopamine and Cognitive Control in Prefrontal Cortex. (2019, background): “In agreementwiththisidea, visualresponse latenciesofPFCneuronsare around150ms,and closely follow the typically observed 100 – 150 ms latencies of phasic dopamine signals [71,80,81].”
Neuronal Reward and Decision Signals: From Theories to Data. (2015, methodology): “Amygdala and dopamine neurons show faster sensory and slower value responses (160, 422).”