The effects of dopaminergic medication on dynamic decision making in Parkinson's disease

Advances in iPSC Technology in Neural Disease Modeling, Drug Screening, and Therapy

Neurodegenerative disorders (NDs) including Alzheimer's Disease, Parkinson's Disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease are all incurable and can only be managed with drugs for the associated symptoms. Animal models of human illnesses help to advance our understanding of the pathogenic processes of diseases. Understanding the pathogenesis as well as drug screening using appropriate disease models of neurodegenerative diseases (NDs) are vital for identifying novel therapies. Human-derived induced pluripotent stem cell (iPSC) models can be an efficient model to create disease in a dish and thereby can proceed with drug screening and identifying appropriate drugs. This technology has many benefits, including efficient reprogramming and regeneration potential, multidirectional differentiation, and the lack of ethical concerns, which open up new avenues for studying neurological illnesses in greater depth. The review mainly focuses on the use of iPSC technology in neuronal disease modeling, drug screening, and cell therapy.

Dopaminergic medication normalizes aberrant cognitive control circuit signalling in Parkinson's disease

Dopaminergic medication is widely used to alleviate motor symptoms of Parkinson's disease, but these medications also impact cognition with significant variability across patients. It is hypothesized that dopaminergic medication impacts cognition and working memory in Parkinson's disease by modulating frontoparietal-basal ganglia cognitive control circuits, but little is known about the underlying causal signalling mechanisms and their relation to individual differences in response to dopaminergic medication. Here we use a novel state-space computational model with ultra-fast (490 ms resolution) functional MRI to investigate dynamic causal signalling in frontoparietal-basal ganglia circuits associated with working memory in 44 Parkinson's disease patients ON and OFF dopaminergic medication, as well as matched 36 healthy controls. Our analysis revealed aberrant causal signalling in frontoparietal-basal ganglia circuits in Parkinson's disease patients OFF medication. Importantly, aberrant signalling was normalized by dopaminergic medication and a novel quantitative distance measure predicted individual differences in cognitive change associated with medication in Parkinson's disease patients. These findings were specific to causal signalling measures, as no such effects were detected with conventional non-causal connectivity measures. Our analysis also identified a specific frontoparietal causal signalling pathway from right middle frontal gyrus to right posterior parietal cortex that is impaired in Parkinson's disease. Unlike in healthy controls, the strength of causal interactions in this pathway did not increase with working memory load and the strength of load-dependent causal weights was not related to individual differences in working memory task performance in Parkinson's disease patients OFF medication. However, dopaminergic medication in Parkinson's disease patients reinstated the relation with working memory performance. Our findings provide new insights into aberrant causal brain circuit dynamics during working memory and identify mechanisms by which dopaminergic medication normalizes cognitive control circuits.

Current concepts in treating mild cognitive impairment in Parkinson's disease

Impairment in various aspects of cognition is recognized as an important non-motor symptom of Parkinson's disease (PD). Mild cognitive impairment in PD (PD-MCI) is common in non-demented PD patients and is often associated with severity of motor symptoms, disease duration and increasing age. Further, PD-MCI can have a significant negative effect on performance of daily life activities and may be a harbinger of development of PD dementia. Thus, there is significant interest in developing therapeutic strategies to ameliorate cognitive deficits in PD and improve cognitive functioning of PD patients. However, due to significant questions that remain regarding the pathophysiology of cognitive dysfunction in PD, remediation of cognitive dysfunction in PD has proven difficult. In this paper, we will focus on PD-MCI and will review some of the current therapeutic approaches being taken to try to improve cognitive functioning in patients with PD-MCI.

Neuropsychiatric aspects of Parkinson disease psychopharmacology: Insights from circuit dynamics

Parkinson disease (PD) is a neurodegenerative disorder with a complex pathophysiology characterized by the progressive loss of dopaminergic neurons within the substantia nigra. Persons with PD experience several motoric and neuropsychiatric symptoms. Neuropsychiatric features of PD include depression, anxiety, psychosis, impulse control disorders, and apathy. In this chapter, we will utilize the National Institutes of Mental Health Research Domain Criteria (RDoC) to frame and integrate observations from two prevailing disease constructions: neurotransmitter anomalies and circuit physiology. When there is available evidence, we posit how unified translational observations may have clinical relevance and postulate importance outside of PD. Finally, we review the limited evidence available for pharmacologic management of these symptoms.

Neural and neurochemical basis of reinforcement-guided decision making

Decision making is an adaptive behavior that takes into account several internal and external input variables and leads to the choice of a course of action over other available and often competing alternatives. While it has been studied in diverse fields ranging from mathematics, economics, ecology, and ethology to psychology and neuroscience, recent cross talk among perspectives from different fields has yielded novel descriptions of decision processes. Reinforcement-guided decision making models are based on economic and reinforcement learning theories, and their focus is on the maximization of acquired benefit over a defined period of time. Studies based on reinforcement-guided decision making have implicated a large network of neural circuits across the brain. This network includes a wide range of cortical (e.g., orbitofrontal cortex and anterior cingulate cortex) and subcortical (e.g., nucleus accumbens and subthalamic nucleus) brain areas and uses several neurotransmitter systems (e.g., dopaminergic and serotonergic systems) to communicate and process decision-related information. This review discusses distinct as well as overlapping contributions of these networks and neurotransmitter systems to the processing of decision making. We end the review by touching on neural circuitry and neuromodulatory regulation of exploratory decision making.