The book presents the case that cognitive science should turn its attention to developing theories of human cognition that cover the full range of human perceptual, cognitive, and action phenomena. Cognitive science has now produced a massive number of high-quality regularities with many microtheories that reveal important mechanisms. The need for integration is pressing and will continue to increase. Equally important, cognitive science now has the theoretical concepts and tools to support serious attempts at unified theories. The argument is made (...) entirely by presenting an exemplar unified theory of cognition both to show what a real unified theory would be like and to provide convincing evidence that such theories are feasible. The exemplar is SOAR, a cognitive architecture, which is realized as a software system. After a detailed discussion of the architecture and its properties, with its relation to the constraints on cognition in the real world and to existing ideas in cognitive science, SOAR is used as theory for a wide range of cognitive phenomena: immediate responses ; discrete motor skills ; memory and learning ; problem solving ; language ; and development. The treatments vary in depth and adequacy, but they clearly reveal a single, highly specific, operational theory that works over the entire range of human cognition, SOAR is presented as an exemplar unified theory, not as the sole candidate. Cognitive science is not ready yet for a single theory – there must be multiple attempts. But cognitive science must begin to work toward such unified theories. (shrink)

A theory is presented to explain how accurate, single-joint movements are controlled. The theory applies to movements across different distances, with different inertial loads, toward targets of different widths over a wide range of experimentally manipulated velocities. The theory is based on three propositions. (1) Movements are planned according to “strategies” of which there are at least two: a speed-insensitive (SI) and a speed-sensitive (SS) one. (2) These strategies can be equated with sets of rules for performing diverse movement tasks. (...) The choice between SI and SS depends on whether movement speed and/or movement time (and hence appropriate muscle forces) must be constrained to meet task requirements. (3) The electromyogram can be interpreted as a low-pass filtered version of the controlling signal to the motoneuron pools. This controlling signal can be modelled as a rectangular excitation pulse in which modulation occurs in either pulse amplitude or pulse width. Movements to different distances and with loads are controlled by the SI strategy, which modulates pulse width. Movements in which speed must be explicitly regulated are controlled by the SS strategy, which modulates pulse amplitude. The distinction between the two movement strategies reconciles many apparent conflicts in the motor control literature. (shrink)

Information about positions, from which differences in position are computed (as proposed in the vector-integration-to-endpoint model), provides a more plausible perceptual basis for the control of goal-directed arm movements than information about distance (as proposed in the kinematic model).

Many activities of daily living require that we physically interact with one or more objects. Object manipulation provides an intriguing domain in which the presence and extent of manual asymmetries can be studied on a motor planning and a motor execution level. In this literature review we present a state of the art for manual asymmetries at the level of motor planning during object manipulation. First, we introduce pioneering work on grasp posture planning. We then sketch the studies investigating the (...) impact of future task demands during unimanual and bimanual object manipulation tasks in healthy adult populations. In sum, in contrast to motor execution, there is little evidence for hand-based performance differences in grasp posture planning. We discuss potential reasons for the lack of manual asymmetries in motor planning and outline potential avenues of future research. (shrink)

Sensorimotor learning refers to improvements that occur through practice in the performance of sensory-guided motor behaviors. Leveraging novel technical capabilities of an immersive virtual environment, we probed the component kinematic processes that mediate sensorimotor learning. Twenty naïve subjects performed a simulated marksmanship task modeled after Olympic Trap Shooting standards. We measured movement kinematics and shooting performance as participants practiced 350 trials while receiving trial-by-trial feedback about shooting success. Spatiotemporal analysis of motion tracking elucidated the ballistic and refinement phases of hand (...) movements. We found systematic changes in movement kinematics that accompanied improvements in shot accuracy during training, though reaction and response times did not change over blocks. In particular, we observed longer, slower, and more precise ballistic movements that replaced effort spent on corrections and refinement. Collectively, these results leverage developments in immersive virtual reality technology to quantify and compare the kinematics of movement during early learning of full-body sensorimotor orienting. (shrink)

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The (...) experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: the performance of the minority of participants who did not find boundedly optimal adaptations, and the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training. (shrink)