A microcircuit model of the frontal eye fields.
The cortical control of eye movements is highly sophisticated. Not only can eye movements be made to the most salient target in a visual scene, but they can also be controlled by top-down rules as is required for visual search or reading. The cortical area called frontal eye fields (FEF) has been shown to play a key role in the visual to oculomotor transformations in tasks requiring an eye movement pattern that is not completely reactive, but follows a previously learned rule. The layered, local cortical circuit, which provides the anatomical substrate for all cortical computation, has been studied extensively in primary sensory cortex. These studies led to the concept of a "canonical circuit" for neocortex (Douglas et al., 1989; Douglas and Martin, 1991), which proposes that all areas of neocortex share a common basic circuit. However, it has not ever been explored whether in principle the detailed canonical circuit derived from cat area 17 (Binzegger et al., 2004) could implement the quite different functions of prefrontal cortex. Here, we show that the canonical circuit can, with a few modifications, model the primate FEF. The spike-based network of integrate-and-fire neurons was tested in tasks that were used in electrophysiological experiments in behaving macaque monkeys. The dynamics of the model matched those of neurons observed in the FEF, and the behavioral results matched those observed in psychophysical experiments. The close relationship between the model and the cortical architecture allows a detailed comparison of the simulation results with physiological data and predicts details of the anatomical circuit of the FEF.
Heinzle
Jakob
J
Institute of Neuroinformatics, University and Swiss Federal Institute of Technology (ETH) Zürich, 8057 Zürich, Switzerland. jakob.heinzle@bccn-berlin.de
Hepp
Klaus
K
Martin
Kevan A C
KA
D000818:Animals; D001931:Brain Mapping; D005133:Eye Movements / Q000502:physiology*; D019579:Neocortex / Q000166:cytology / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology; D016571:Neural Networks, Computer; D009474:Neurons / Q000145:classification / Q000502:physiology; D010775:Photic Stimulation / Q000379:methods; D011930:Reaction Time / Q000502:physiology; D014794:Visual Fields / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology