Biology subjects

Hulme, O. J.

Publications and source records attributed to Hulme, O. J..

3 recordsLinked to original sources

bioRxiv2023

Brain network reconfiguration during prediction error processing

Learning from experience is driven by reward prediction errors--signals that reflect updates to our expectations of reward. Despite numerous studies on neural correlates of reward prediction errors, the question of how large-scale brain networks reconfigure in response to reward prediction error signalling remains open. Here we ask how functional networks change in response to reward prediction errors depending on the context. In our study participants performed the probabilistic reversal learning task in functional magnetic resonance imaging (fMRI) scanner in two experimental contexts: a reward-seeking setting and a punishment-avoiding. We found that the participants learning speed depended on the sign of the prediction error but not on the experimental context. Whole-brain network analysis revealed a multi-scale community structure with a separate striatal reward network emerging at a finer topological scale and a ventromedial prefrontal network emerging at a coarser scale. We also found that the integration between large-scale networks increased when switching from positive to negative prediction error events. This pattern of large-scale network reconfiguration aligns with the broad range of research showing increased network integration with increased cognitive demands. Our findings offer a first sketch of how processing reward prediction error affects the functional connectivity of brain-wide networks.

neuroscience↗

bioRxiv2018

The Homeostatic Logic of Reward

Energy homeostasis depends on behavior to predictively regulate metabolic states within narrow bounds. Here we review three theories of homeostatic control and ask how they provide insight into the circuitry underlying energy homeostasis. We offer two contributions. First, we detail how control theory and reinforcement learning are applied to homeostatic control. We show how these schemes rest on implausible assumptions; either via circular definitions, unprincipled drive functions, or by ignoring environmental volatility. We argue active inference can elude these shortcomings while retaining important features of each model. Second, we review the neural basis of energetic control. We focus on a subset of arcuate subpopulations that project directly to, and are thus in a privileged position to opponently modulate, dopaminergic cells as a function of energetic predictions over a spectrum of time horizons. We discuss how this can be interpreted under these theories, and how this can resolve paradoxes that have arisen. We propose this circuit constitutes a homeostatic-reward interface that underwrites the conjoint optimisation of physiological and behavioural homeostasis.

neuroscience↗

bioRxiv2018

Reward signalling in brainstem nuclei under glycemic flux

Phasic dopamine release from mid-brain dopaminergic neurons signals errors of reward prediction (RPE). If reward maximisation is to maintain homeostasis, then the value of primary rewards should be coupled to the homeostatic errors they remediate. This leads to the prediction that RPE signals should be configured as a function of homeostatic state and thus, diminish with the attenuation of homeostatic error. To test this hypothesis, we collected a large volume of functional MRI data from five human volunteers on four separate days. After fasting for 12 hours, subjects consumed preloads that differed in glucose concentration. Participants then underwent a Pavlovian cue-conditioning paradigm in which the colour of a fixation-cross was stochastically associated with the delivery of water or glucose via a gustometer. This design afforded computation of RPE separately for better- and worse-than expected outcomes during ascending and descending trajectories of physiological serum glucose fluctuations. In the parabrachial nuclei, variations in regional activity coding positive RPEs scaled positively with serum glucose for ascending and descending glucose levels. The ventral tegmental area and substantia nigra became more sensitive to negative RPEs when glucose levels were ascending. Together, the results show that RPE signals in key brainstem structures are modulated by homeostatic trajectories of naturally occurring glycemic flux, revealing a tight interplay between homeostatic state and the neural encoding of primary reward in the human brain.

neuroscience↗