Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states

Abstract

The basal ganglia (BG) is a collection of nuclei located deep beneath the cerebral cortex that is involved in learning and selection of rewarded actions. Here, we analyzed BG mechanisms that enable these functions. We implemented a rate model of a BG-thalamo-cortical loop and simulated its performance in a standard action selection task. We have shown that potentiation of corticostriatal synapses enables learning of a rewarded option. However, these synapses became redundant later as direct connections between prefrontal and premotor cortices (PFC-PMC) were potentiated by Hebbian learning. After we switched the reward to the previously unrewarded option (reversal), the BG was again responsible for switching to the new option. Due to the potentiated direct cortical connections, the system was biased to the previously rewarded choice, and establishing the new choice required a greater number of trials. Guided by physiological research, we then modified our model to reproduce pathological states of mild Parkinson's and Huntington's diseases. We found that in the Parkinsonian state PMC activity levels become extremely variable, which is caused by oscillations arising in the BG-thalamo-cortical loop. The model reproduced severe impairment of learning and predicted that this is caused by these oscillations as well as a reduced reward prediction signal. In the Huntington state, the potentiation of the PFC-PMC connections produced better learning, but altered BG output disrupted expression of the rewarded choices. This resulted in random switching between rewarded and unrewarded choices resembling an exploratory phase that never ended. Along with other computational studies, our results further reconcile the apparent contradiction between the critical involvement of the BG in execution of previously learned actions and yet no impairment of these actions after BG output is ablated by lesions or deep brain stimulation. We predict that the cortico-BG-thalamo-cortical loop conforms to previously learned choice in healthy conditions, but impedes those choices in disease states.

Neuro4PD: An Initial Neurorobotics Model of Parkinson's Disease

“…We choose thalamic neurons to be injected with external DC currents since they control the flow of information that are transmitted to cortical neurons. However, some other works have decided to explore other regions of the brain (Kim et al, 2017;Mulcahy et al, 2020). In our experiments, the robot was able to sense the environment, process the information and act respecting the same dynamics observed on data sets from animal's brains.…”

A Neurorobotics Approach to Behaviour Selection based on Human Activity Recognition

“…The neurorobotics model embeds the bioinspired computational model and the CNN-based decoder (see Figure 2). It consists of simulating and decoding the neurophysiological mechanisms of the basal ganglia-thalamus-cortex (BG-T-C) circuit in mammals (see Section 2), responsible for abilities such as motor control, decision-making, and learning [12,26,33]. As already stated in Section 2, both the rat-based [22] and the marmoset-based [40] computational models were evaluated as a decision-making mechanism of the neurorobotics model.…”

“…Motivated by the work of [33], two key modifications were introduced to the computational models of the BG-T-C circuit adopted in this work [22,40]. First, an additional structure, called prefrontal cortex (PFC), was included as a variable source of excitatory stimuli towards the striatum (see Figure 3a).…”

“…In this paper, we present a neurorobotics model which embeds computational models of the basal ganglia-thalamuscortex (BG-T-C) circuit [22,40] to provide a decision-making mechanism for a robot -in this context, we may call it a neurorobot. The neurorobotics approach has been proposed for enhancing the decision-making mechanism, as suggested by related researches in neurorobotics [26,33]. It consisted of simulating neurophysiological aspects within a cognitive framework, in which different stimuli was introduced to certain brain structures within the circuit, according to real-time outputs of the activity recognition module.…”

Mitochondrial and Organellar Crosstalk in Parkinson’s Disease

“…Dopamine plays a significant role in the regulation of voluntary movements and its decrease not only affects motor functions but also a spectrum of non-motor functions. Thus, it serves as a biomarker in the premotor phase of PD (Mulcahy et al, 2020; Schneider et al, 2021). Several recent reports suggest that dopaminergic dysfunction is associated with the accumulation of α-syn in the mitochondrial structure (Danyu et al, 2019; Ganjam et al, 2019).…”