Topography of Visuomotor Parameters in the Frontal and Premotor Eye Fields.

To determine whether the periarcuate frontal cortex spatially encodes visual and oculomotor parameters, we trained monkeys to repeatedly execute saccades of the same amplitude and direction toward visual targets and we obtained quantitative images of the distribution of metabolic activity in 2D flattened reconstructions of the arcuate sulcus (As) and prearcuate convexity. We found two topographic maps of contraversive saccades to visual targets, separated by a region representing the vertical meridian: the first region straddled the fundus of the As and occupied areas 44 and 6-ventral, whereas the second one occupied areas 8A and 45 in the anterior bank of the As and the prearcuate convexity. The representation of the vertical meridian runs along the posterior borders of areas 8A and 45 (deep in the As). In both maps, the upper part of visuo-oculomotor space is represented ventrally and laterally and the lower part dorsally and medially whereas dorsal and ventral regions are separated by the representation of the horizontal meridian.

The place code of saccade metrics in the lateral bank of the intraparietal sulcus.

The lateral intraparietal area (LIP) of monkeys is known to participate in the guidance of rapid eye movements (saccades), but the means it uses to specify movement variables are poorly understood. To determine whether area LIP devotes neural space to encode saccade metrics spatially, we used the quantitative [(14)C]deoxyglucose method to obtain images of the distribution of metabolic activity in the intraparietal sulcus (IPs) of rhesus monkeys trained to repeatedly execute saccades of the same amplitude and direction for the duration of the experiment. Different monkeys were trained to perform saccades of different sizes and in different directions. A clear topography of saccade metrics was found in the cytoarchitectonically identified area LIP ventral (LIPv) contralateral to the direction of the eye movements. We demonstrate that the representation of the vertical meridian runs parallel to the fundus of the IPs and that it is not orthogonal to the representation of the horizontal meridian. Instead, the latter runs through the middle of LIPv parallel to its border with area LIP dorsal (LIPd). The upper part of oculomotor space is represented rostrally and dorsally relative to the horizontal meridian toward the LIPv-LIPd border, whereas the lower part of oculomotor space is represented caudally and ventrally toward the caudal edge of the IPs. Saccade amplitude is also represented in an orderly manner.

Optimal control of gaze shifts.

To explore the visible world, human beings and other primates often rely on gaze shifts. These are coordinated movements of the eyes and head characterized by stereotypical metrics and kinematics. It is possible to determine the rules that the effectors must obey to execute them rapidly and accurately and the neural commands needed to implement these rules with the help of optimal control theory. In this study, we demonstrate that head-fixed saccades and head-free gaze shifts obey a simple physical principle, "the minimum effort rule." By direct comparison with existing models of the neural control of gaze shifts, we conclude that the neural circuitry that implements the minimum effort rule is one that uses inhibitory cross talk between independent eye and head controllers.

Saccade-related information in the superior temporal motion complex: quantitative functional mapping in the monkey.

Although the role of the motion complex [cortical areas middle temporal (V5/MT), medial superior temporal (MST), and fundus of the superior temporal (FST)] in visual motion and smooth-pursuit eye movements is well understood, little is known about its involvement in rapid eye movements (saccades). To address this issue, we used the quantitative 14C-deoxyglucose method to obtain functional maps of the cerebral cortex lying in the superior temporal sulcus of rhesus monkeys executing saccades to visual targets and saccades to memorized targets in complete darkness. Fixational effects were observed in MT-foveal, FST, the anterior part of V4-transitional (V4t), and temporal-occipital areas. Saccades to memorized targets activated areas V5/MT, MST, and V4t, which were also activated for saccades to visual targets. Regions activated in the light and in the dark overlapped extensively. In addition, saccades to visual targets activated areas FST and the intermediate part of the polysensory temporal-parietal-occipital area. Cortical activity related to visually guided saccades could be explained, at least in part, by visual motion. Because only oculomotor signals can account for the equally robust activations induced by memory saccades in complete darkness, we suggest that areas V5/MT, MST, and V4t receive and/or process saccade-related oculomotor information.

Control of orienting movements: role of multiple tectal projections to the lower brainstem.

In movement neuroscience this past decade, a conceptual approach that puts emphasis on population coding was clearly dominant. The purpose of numerous studies has been to define presumably homogeneous groups of neurons on the basis of the correlation of their discharges with sensory and motor events. The goal of this chapter is to stress the importance of taking into account individual properties of neurons, this being an essential prerequisite for a biologically meaningful definition of neuron populations. Taking as an example the executive limb of the neural network controlling gaze movements, we demonstrate the functional and anatomical diversity of tectal and reticular neurons, which are generally considered as homogeneous populations and used, accordingly, as lumped elements in models. We argue that the extraction of effector-specific signals from the global command of gaze displacement is based not on the interplay between discrete neural modules, but rather on a gradual process of signal specification at all levels of the executive network. An eventual accurate description of this network will require knowledge of the unique combinations of afferent inputs and efferent connections for as many subsets of its constituent neurons as is conceivably possible.