Figure 3.

Representational and dynamical systems perspectives on movement coding. (a) With endpoint coding, planning centers on specifying the desired position, or state, without taking into account the agent’s initial state. (b) With vector coding, planning entails a computation of the difference vector between the target and the initial position of the hand. (c) According to a representational approach, preparatory neural activity should reflect a subthreshold directional preference. During execution, this preference would be maintained, with movement ensuing when the activity level reaches a threshold for initiation. (d) At odds with this hypothesis is the finding that many premotor and primary motor neurons do not exhibit the same pattern of activity during the preparatory and execution phases (Churchland et al. 2010). (e) Schematic illustration of the combined dynamics of neural activity of three neurons, presented in a state space. According to a dynamical system approach, the pattern of neural activity of the neurons over time (black arrows) converges to a state, reflecting the upcoming reach direction. Abbreviation: a.u., arbitrary units.