bioRxiv Science⌕ Search

bioRxiv · 10.1101/802488

Amphetamine disrupts haemodynamic correlates of prediction errors in nucleus accumbens and orbitofrontal cortex

Abstract

In an uncertain world, the ability to predict and update the relationships between environmental cues and outcomes is a fundamental element of adaptive behaviour. This type of learning is typically thought to depend on prediction error, the difference between expected and experienced events, and in the reward domain this has been closely linked to mesolimbic dopamine. There is also increasing behavioural and neuroimaging evidence that disruption to this process may be a cross-diagnostic feature of several neuropsychiatric and neurological disorders in which dopamine is dysregulated. However, the precise relationship between haemodynamic measures, dopamine and reward-guided learning remains unclear. To help address this issue, we used a translational technique, oxygen amperometry, to record haemodynamic signals in the nucleus accumbens (NAc) and orbitofrontal cortex (OFC) while freely-moving rats performed a probabilistic Pavlovian learning task. Using a model-based analysis approach to account for individual variations in learning, we found that the oxygen signal in the NAc correlated with a reward prediction error, whereas in the OFC it correlated with an unsigned prediction error or salience signal. Furthermore, an acute dose of amphetamine, creating a hyperdopaminergic state, disrupted rats ability to discriminate between cues associated with either a high or a low probability of reward and concomitantly corrupted prediction error signalling. These results demonstrate parallel but distinct prediction error signals in NAc and OFC during learning, both of which are affected by psychostimulant administration. Furthermore, they establish the viability of tracking and manipulating haemodynamic signatures of reward-guided learning observed in human fMRI studies using a proxy signal for BOLD in a freely behaving rodent.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Werlen, E., Shin, S.-L., Gastambide, F., Tricklebank, M. D., Marston, H. M., Huxter, J. R., Gilmour, G., Walton, M. E.. 2019-10-13. Amphetamine disrupts haemodynamic correlates of prediction errors in nucleus accumbens and orbitofrontal cortex. https://doi.org/10.1101/802488

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Next generation Human Neocortical Neurosolver model with biophysically realistic somatic, dendritic and synaptic dynamics

The Human Neocortical Neurosolver (HNN) is an open-source biophysical modeling tool for multiscale interpretation of human electroencephalography (EEG) and magnetoencephalography (MEG) signals. HNN's foundation is a pre-tuned canonical neocortical circuit model consisting of excitatory pyramidal neurons and inhibitory interneurons in supra- (L2/3) and infragranular (L5) layers. This model was originally developed based on studies in rodent and non-human primate cortices when dynamics of human neurons were poorly characterized. Yet recent advances in recordings from human tissue now provide unprecedented detail to update the model. Here, we present a significantly updated model for use in the HNN software, with electrophysiological properties and synaptic connections tuned to human tissue. Beyond reproducing biologically realistic somatic dynamics, the pyramidal cells simulate dendritic calcium (Ca2+) spikes in the L5 extratelencephalic-projecting (ET) neurons, and shorter dendritic spikes in the L2/3 pyramidal neurons. We demonstrate how the updated circuitry and new features in the HNN software can be used to disentangle somatic, synaptic, and dendritic contributions to human E-/MEG signatures. The model is distributed with workflows to simulate event-related responses and oscillations, and tutorials demonstrating how membrane potentials, Ca2+ dynamics, and synaptic currents can be recorded and visualized. These enhancements allow extensive model validations based on in vitro and in vivo electrophysiology, voltage and Ca2+ imaging, and provide users with novel insights on the mechanisms underlying E-/MEG signals.

neuroscience↗

A biological light sheet links cellular voltage to mesoscopic brain dynamics

Membrane voltage is the fundamental currency of neural computation, yet cellular-resolution voltage imaging of large neuronal populations in vivo remains limited by trade-offs among imaging speed, field of view, and optical sectioning. We overcome this challenge by encoding a biological light sheet in the brain: Selective Plane Expression (SPress) restricts fluorescent indicator expression to a user-defined, 20-m-thick plane, suppressing background at its source. Following one-time two-photon photoactivation, SPress enables standard widefield microscopes to capture high-contrast kilohertz voltage dynamics from hundreds of densely labeled neurons across millimeter-scale cortical sheets and columns in vivo. These recordings reveal mesoscopic subthreshold waves that flexibly reorganize population-wide spike timing, together with cellularscale wavefront microstructure that preserves stereotyped local recruitment biases. By shifting optical sectioning from instrumentation to gene expression, SPress makes kilohertz cellular resolution voltage imaging accessible across mesoscopic scales.

neuroscience↗

Persistent hippocampal traces of lifelong spatial memory

Memory presents a biological paradox: the brain changes continuously, yet a brief experience can influence behavior for a lifetime. How such memories are stored in brain circuits remains unclear. Here we show that two days in a binary-tree maze leave mice with spatial memories that survive repeated 90-day absences over as much as a year. Across return visits, mice explored the maze more efficiently than when naive and resumed direct runs to a reward location sooner, both by a factor of 3. Chronic calcium imaging of the same hippocampal CA1 neurons showed that although most neurons had changed their preferred locations, the population activity at a given maze location still resembled the pattern from 90 days earlier. Furthermore, even when a neuron's place fields changed location, they tended to remain at the same branching level of the binary tree, reflecting the local geometry of the maze. In return sessions where the neural tuning for branching level was preserved more accurately, the mouse explored the environment more efficiently. Population patterns were best preserved near the reward location, and more reliable neural activity there accompanied earlier direct runs to the reward. With repeated experience, spatial representations changed less, both within a visit and across the long absences. A brief experience thus left selective hippocampal traces that survived months of absence despite drift, grew more durable with each return, and were correlated with memory in navigation behavior.

neuroscience↗