Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Movement Planning in Dorsal Premotor Cortex



Science 24 August 2012: Vol. 337 no. 6097 pp. 984-988

Strategy-Dependent Encoding of Planned Arm Movements in the Dorsal Premotor Cortex

Thomas M. Pearce, Daniel W. Moran

Washington University in St. Louis, St. Louis, MO 63130, USA


The kinematic strategy encoded in motor cortical areas for classic straight-line reaching is remarkably simple and consistent across subjects, despite the complicated musculoskeletal dynamics that are involved. As tasks become more challenging, however, different conscious strategies may be used to improve perceived behavioral performance. We identified additional spatial information that appeared both in single neurons and in the population code of monkey dorsal premotor cortex when obstacles impeded direct reach paths. The neural correlate of movement planning varied between subjects in a manner consistent with the use of different strategies to optimize task completion. These distinct planning strategies were manifested in the timing and strength of the information contained in the neural population code.

Humans and other primates are adept at reaching for visually identified targets, an important element of the behavioral repertoire. The neural mechanisms supporting this have long been an active area of investigation. For reaching movements, the output of the motor system is a sequence of muscle activations that guide the hand appropriately through space to achieve the goal of the reach. Before movement initiation, sensory information and cognitive processes interact to form an initial movement plan. During this preparatory period, neural activity relating to the upcoming reach can be seen in a network of frontal and parietal cortical areas, including the premotor (PM) and primary motor (M1) cortices. Instructed-delay reaching tasks, an experimental paradigm in which a monkey is shown a target but must withhold movement until a “go” cue is given, allow this preparatory neural activity to be probed. Electrophysiological, imaging, and transcranial magnetic stimulation studies highlighted dorsal premotor cortex (PMd) as a critical area for planning reaching movements. However, the precise relationship between neural activity in PMd and reaching behavior remains unresolved. Many PMd neurons show a sensitivity of firing rate to direction, be it the direction of arm movement, an effector in visual space, a target location, visuospatial attention, or other parameters. Unfortunately, nearly all of these factors correlate with each other under normal circumstances: The hand movement and visual movement are correlated, the target direction and movement direction are correlated, and so forth. Neural activity related to any of these parameters will thus also correlate with the others.


Population vector (PV) analysis was used to investigate the spatial and temporal aspects of the neuronal population representation of planned and executed movements. Position and velocity encoding of the hand are represented at the single-neuron level within motor cortex. To evaluate contributions of these parameters in PMd, we calculated the preferred movement direction and position gradient of each neuron from delay-period activity in the center-out task. These tuning properties were then used to construct two PV decoders, one for position and another for velocity.


The population analyses reveal that the time course of preparatory neural activity in premotor cortex is subject to top-down modulation suggestive of distinct cognitive strategies. It appears that monkey G waited until all information was known before generating a movement plan, whereas monkey H planned to move directly to the target until the obstacle instructed him otherwise.


Although the monkeys were trained similarly and performed identical tasks, the behavioral and neural lines of evidence indicate that the two animals used different approaches when planning obstacle-avoidance reaches.


The work presented here makes a number of points about the role of PMd in the movement planning and execution process. First, information about multiple independent spatial parameters is often embedded in the firing rate of a single neuron. The precise combination of parameters relevant to each cell is highly variable, leading to heterogeneity in the responses of individual neurons. Despite these spatially and temporally complex responses, a simple linear decoding scheme can meaningfully extract lower-dimensional information from the population as a whole. Second, the timing and strength of spatial information in the population code suggests that PMd activity is modulated both by task demands and by the particular planning strategy being used. The directional tuning observed in classic studies of center-out reaching is predictive of the initial hand movement direction, not the target direction, when those parameters are not separated. The time course with which population activity resolved to a significant directional prediction was consistent with two distinct approaches to the task, in which a trade off between planning speed and reach accuracy could be seen. A target representation, distinct from the initial movement representation, was also seen in the neural population. The strength of this representation was reduced for direct relative to indirect reaches, which suggests that relevant information can be selectively encoded as it is needed for the task. Lastly, the use of position-tuning properties in a population decoder provided a high-fidelity prediction of the hand trajectory during movement, consistent with prior reports of position coding in premotor areas.. Although the velocity-based decoder strongly predicted the initial hand direction before movement initiation, it did not predict the hand velocity particularly well during execution of the movement. These findings contrast with population decoding in M1, which shows good prediction of velocity and relatively worse performance when estimating position.

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