We have developed a prototype optical brain-computer interface (BCI) system that can be used by an operator to manipulate external, electrically controlled equipment. Our optical BCI uses near-infrared spectroscopy and functions as a compact, practical, unrestrictive, non-invasive brain-switch. The optical BCI system measured spatiotemporal changes in the hemoglobin concentrations in the blood flow of a subject's prefrontal cortex at 22 measurement points. An exponential moving average (EMA) filter was applied to the data, and then their weighted sum with a task-related parameter derived from a pretest is utilized for time-indicated control (GO-STOP) of an external object. In experiments using untrained subjects, the system achieved control patterns within an accuracy of 6 sec for more than 80% control.

A model of the prefrontal cortical circuit has been constructed to investigate the dynamics for working memory processing. The model circuit is multi-layered and consists of a number of circuit modules or columns, each of which has local, excitatory and inhibitory connections as well as feedback connections. The columns interact with each other via the long-range horizontal connections. Besides these intrinsic connections, the pyramidal and spiny cells in the superficial layers receive the specific cue-related input and all the cortical neurons receive a hypothetical bias input. The model cortical circuit amplifies the response to the transient, cue-related input. The dynamics of the circuit evolves autonomously after the termination of the input. As a result, the circuit reaches in several hundred milliseconds an equilibrium state, in which the neurons exhibit graded-level, sustained activity. The sustained activity varies gradually with the cue direction, thus forming memory fields. In the formation of the memory fields, the feedback connections, the horizontal connections, and the bias input all play important roles. Varying the level of the bias input dramatically changes the dynamics of the model cortical neurons. The computer simulations show that there is an optimum level of the input for the formation of well-defined memory fields during the delay period.