A biophysical model for dopamine modulating working memory through reward system in obsessive-compulsive disorder

Behavior Changes in Quinpirole Obsessive-Compulsive Disorder Rats Treated with 6-Hydroxydopamine and the Corresponding Dopaminergic Compulsive Loop Mechanism

BACKGROUND

Recent studies suggest that the anterior limb of the internal capsule may be an area of convergence for multiple compulsion loops. In this study, the role of different dopaminergic compulsion loops in the mechanism of obsessive-compulsive disorder (OCD) was investigated by selectively damaging dopaminergic neurons or fibers in the corresponding targets with 6-hydroxydopamine (6-OHDA) and depicting the anatomical map of various compulsion loops located in the anterior limb of the internal capsule.

METHODS

A total of 52 male Sprague Dawley (SD) rats were exposed to either saline (1 mL/kg, NS group, n = 6) or quinpirole (QNP, dopamine D2-agonist, 0.5 mg/kg, n = 46) twice weekly for 5 weeks. After each injection, the rats were placed on an open field to analyze aspects of their behaviour, including the number of home base visits (NOH), average time between each home base visit (ATBO), and total distance travelled (TDM). After model setup, 46 QNP rats were divided randomly into five groups: 6-OHDA anterior limb of internal capsule (AC) stereotactic injection group (QNP+AC group, n = 10), 6-OHDA mediodorsal thalamic nucleus (MD) stereotactic injection group (QNP+MD group, n = 10), 6-OHDA nucleus accumbens (NAC) stereotactic injection group (QNP+NAC group, n = 10), saline stereotactic injection group (QNP+NS-S group, n = 10), and non-surgical group (QNP+Non-S group, n = 6). In the NS group, rats simultaneously received a 6-OHDA stereotactic injection (NS+6-OHDA-S group, n = 6: AC2, MD2, NAC2). All QNP-treated rats were then continued to be given QNP twice a week for 4 weeks, and their behaviour was observed after each infusion. After 4 weeks, immunofluorescence staining was used to monitor the distribution of dopamine neurons and nerve fibers in different areas of the intervention nerve loops, and quantitative analysis was performed.

RESULTS

Compulsive behaviour declined gradually in the QNP+AC and QNP+NAC groups 3 and 4 weeks after surgery, with the QNP+AC group decreasing more rapidly. The QNP+MD group had decreased by 3 weeks after surgery but increased to almost the same level as pre-surgery at 4 weeks post-surgery. Postoperative fluorescence staining and quantitative analysis suggested the number of dopamine (DA) neurons or nerve fibers in the corresponding target area of the 6-OHDA injection were significantly reduced compared with the QNP+Non-S group.

CONCLUSIONS

6-OHDA selectively damages the targets of dopaminergic neurons or nerve fibers within the OCD loop, which somewhat alleviates compulsive behaviours. The results suggest that the AC might be the best target for therapeutic interventions for OCD.

The Neurobehavioral State hypothesis

Since the early attempts to understand the brain made by Greek philosophers more than 2000 years ago, one of the main questions in neuroscience has been how the brain perceives all the stimuli in the environment and uses this information to implement a response. Recent hypotheses of the neural code rely on the existence of an ideal observer, whether on specific areas of the cerebral cortex or distributed network composed of cortical and subcortical elements. The Neurobehavioral State hypothesis stipulates that neurons are in a quasi-stable state due to the dynamic interaction of their molecular components. This increases their computational capabilities and electrophysiological behavior further than a binary active/inactive state. Together, neuronal populations across the brain learn to identify and associate internal and external stimuli with actions and emotions. Furthermore, such associations can be stored through the regulation of neuronal components as new quasi-stable states. Using this framework, behavior arises as the result of the dynamic interaction between internal and external stimuli together with previously established quasi-stable states that delineate the behavioral response. Finally, the Neurobehavioral State hypothesis is firmly grounded on present evidence of the complex dynamics within the brain, from the molecular to the network level, and avoids the need for a central observer by proposing the brain configures itself through experience-driven associations.

A working memory model based on recurrent neural networks using reinforcement learning

Numerous electrophysiological experiments have reported that the prefrontal cortex (PFC) is involved in the process of working memory. PFC neurons continue firing to maintain stimulus information in the delay period without external stimuli in working memory tasks. Further findings indicate that while the activity of single neurons exhibits strong temporal and spatial dynamics (heterogeneity), the activity of population neurons can encode spatiotemporal information of stimuli stably and reliably. From the perspective of neural networks, the computational mechanism underlying this phenomenon is not well demonstrated. The main purpose of this paper is to adopt a new strategy to explore the neural computation mechanism of working memory. We used reinforcement learning to train a recurrent neural network model to learn a spatial working memory task. The model is composed of a decision network and a baseline network. The decision network is responsible for updating strategies to make action choices, while the baseline network evaluates action choices to predict rewards. Simulated results demonstrate that the model can perform the spatial working memory task. The activity of the recurrent units has characteristics such as temporal dynamics and preferred direction selectivity, but their population activity encodes the stimulus information stably during the delay period in a low-dimensional subspace. These activity characteristics displayed by the model units are similar to those of PFC neurons observed in the same experiments. Meanwhile, as the network model continued learning the task, the temporal stability and spatial separability of the stimulus information encoded by the activity of model units in the low-dimensional subspace gradually strengthened, and the accuracy of the network's action choices also increased. In summary, this network model provides a new simulation method for spatial working memory tasks and a new perspective for understanding the characteristics of neuron activity in the PFC.

Unveiling serotonergic dysfunction of obsessive-compulsive disorder on prefrontal network dynamics: a computational perspective

Serotonin (5-HT) regulates working memory within the prefrontal cortex network, which is crucial for understanding obsessive-compulsive disorder. However, the mechanisms how network dynamics and serotonin interact in obsessive-compulsive disorder remain elusive. Here, we incorporate 5-HT receptors (5-HT1A, 5-HT2A) and dopamine receptors into a multistable prefrontal cortex network model, replicating the experimentally observed inverted U-curve phenomenon. We show how the two 5-HT receptors antagonize neuronal activity and modulate network multistability. Reduced binding of 5-HT1A receptors increases global firing, while reduced binding of 5-HT2A receptors deepens attractors. The obtained results suggest reward-dependent synaptic plasticity mechanisms may attenuate 5-HT related network impairments. Integrating serotonin-mediated dopamine release into circuit, we observe that decreased serotonin concentration triggers the network into a deep attractor state, expanding the domain of attraction of stable nodes with high firing rate, potentially causing aberrant reverse learning. This suggests a hypothesis wherein elevated dopamine concentrations in obsessive-compulsive disorder might result from primary deficits in serotonin levels. Findings of this work underscore the pivotal role of serotonergic dysregulation in modulating synaptic plasticity through dopamine pathways, potentially contributing to learned obsessions. Interestingly, serotonin reuptake inhibitors and antidopaminergic potentiators can counteract the over-stable state of high-firing stable points, providing new insights into obsessive-compulsive disorder treatment.