Emancipatory Learning of a Hermeneutic Phenomenology Methodology Course.

The loss of control over movement is one of the most devastating consequences of Parkinson’s disease (PD). The loss of control largely results from the gradual but inexorable destruction of dopamine-producing neurons in the . As dopamine levels fall, the ability to initiate, control, learn, and sustain actions declines. Treatment with the dopamine precursor levodopa can partly overcome motor impairments; however, years of use often leads to levodopa-induced dyskinesia (LID), a debilitating condition characterized by uncontrolled writhing and ballistic movements, making continued treatment difficult or impossible. While progress has been made towards unraveling the molecular and cellular processes driving the development of LID, far less is known about the changes in ongoing neuronal activity that contribute to LID expression. While LID involves many interconnected cortical and subcortical systems, the primary motor cortex (M1) is often implicated. What follows is a review and perspective of the role M1 single-unit and neural ensemble activity play in LID expression and how low-dose ketamine may exert anti-dyskinetic effects by reconfiguring between-neuron interactions. Understanding the role of M1 in LID requires an understanding of the role of M1 in the normal control of movement. The original work of Penfield and Boldrey (1937) indicated that M1 is organized as a “motor homunculus,” where localized groups of neurons form a one-to-one somatotopic map with downstream spinal neurons and associated muscle groups. This view has largely shifted in favor of a population-based interpretation. While M1 does indeed express a coarse topography, movements, and motor plans appear to be controlled by the weighted activities of populations of neurons distributed throughout the motor cortex. This ensemble-level perspective is supported by anterograde and retrograde tracing studies indicating that M1 neurons connect to a diverse set of downstream regions, as well as by the original work of Georgopoulos et al. (1986) demonstrating that arm movements can be faithfully predicted by the weighted activities of ensembles of neurons.