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This chapter focuses on the differential involvement of multiple areas of the lateral frontal cortex in rule‐based behavior. It presents evidence obtained from physiological and anatomical studies of monkeys and discusses the specific role played by each area from the viewpoint of a hierarchical network within the lateral frontal cortex. It introduces several key types of neuronal activity found in the prefrontal, premotor, and primary motor cortices of macaque monkeys performing a variety of rule‐based behaviors, such as following location‐matching rules or shape‐matching rules.

This chapter reviews the results of a large body of studies that examined the cerebral plasticity in the primary motor cortex (M1) using neurophysiological approaches in monkeys and rodents, or behavioral experiments using modern brain mapping techniques such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS) in human adults. It describes the plastic changes that occur within M1 over the course of learning in order to determine their role in the acquisition, consolidation, and long-term retention of new motor skilled behaviors. It discusses the physiological and neurobiological correlates of such plasticity to give insights into the underlying mechanisms for the representational functional changes associated with the learning and retention of a motor skill.

This chapter begins by discussing the question of whether the musculature of the hand is controlled in a decomposed or in an integrated manner in the primary motor cortex. It then discusses integration among other body-part representations, and how this integration may develop through experience with complex actions.

The primary motor cortex (M1) maintains a dynamic representation of higher-order features of movement, most notably the direction of reaching. In fact, almost half of the cells in the arm region of the motor cortex show an orderly variation in activity as a function of the movement direction, with a peak of activity in their preferred direction (PD), and progressively lower rates for movements farther and farther away from the PD. This orderly variation of cell activity is characterized by the directional tuning curve that can be approximated by a cosine function. This chapter addresses the question: What are the anatomical bases for directional tuning? The micro- and macro-anatomical architecture of directional tuning in the motor cortex are discussed.

This chapter focuses on the individual ability to imagine the physical execution of an action, for example, considering the body as a generator of acting forces. It describes neuroimaging results by integrating a discussion on the structural equivalence between motor imagery and motor execution. It demonstrates that motor imagery and motor execution share many anatomical substrates but are not completely overlapping, especially when sensorial cues on which motor imagery is constructed are considered. It explores the contribution of the primary motor cortex to motor imagery.

This chapter explores how typological findings about action concepts can inform neuroscientific work on their cortical implementation. Because common representational patterns in the cross-linguistic treatment of actions are likely to reflect fundamental properties of this intricate semantic sphere, they provide neuroscientists with important “targets” to search for in the brain. And because less frequent and downright rare patterns reveal the scope of cultural variation, they show neuroscientists how much conceptual diversity must ultimately be accommodated by any comprehensive brain-based theory. The first section concentrates on motion events. Then the next section discusses events of cutting, breaking, and opening. After that, the chapter turns to events of putting and taking. Finally, the last two sections deal with serial verb constructions and verbal classification systems.

This chapter offers a novel method for estimating local field potentials (LFPs) via a newly developed solution for the neuroelectromagnetic inverse problem, and discusses an approach to construct individual images of brain areas that significantly differ between two or more experimental conditions. It describes the experimental paradigm used to record the electoencephalography data, and explains in more detail the alternatives used to perform statistical analysis over LFPs estimated from single trials in the temporal and spectral domains. The chapter shows a stable differentiation between the laterality of the movements within parietal areas and primary motor, and premotor cortex and the spinal muscular atrophy.