Multiscale Investigation of Neural Circuitry of Visual Cognition in Primates

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How the brain guides attention and monitors errors to govern behavior has been investigated in humans with noninvasive measures of brain function like the electro-encephalogram (EEG) and in monkeys with invasive measurements of brain cell (neuron) discharges and synaptic local field potentials. We know that the EEG is produced by the brain. But, using the EEG on the head to locate sources in the brain (known as the inverse problem) allows multiple solutions. But deriving the EEG from particular sources in the brain (known as the forward problem) has one solution. This research program seeks the brain mechanisms of human attention and monitoring by building a bridge between human EEG findings and monkey brain function. Our research has verified that monkeys have EEG measures like humans. We have obtained a comprehensive and unique dataset consisting of simultaneous measurements of EEG with discharges and field potentials from four areas of the cerebral cortex of macaque monkeys performing tasks demanding visual attention and error monitoring. Two areas consist of the typical 6 cortical layers. Two lack the dense layer 4. Funds are requested to characterize the diversity of signals found across cortical layers in each of the 4 areas and then to determine how these brain signals produce the EEG signals. High confidence in feasibility is engendered by our application of advanced biophysical theory, sophisticated mathematical approaches, and tractable models of single neurons applied to a dataset that is unique in behavioral relevance, diversity of brain regions, and relevance for understanding human processes. Understanding how brain circuits produce EEG measures will solve a long-standing problem, establish an empirical bridge between two research domains, and improve brain-machine interface technology. Understanding how the brain guides attention and monitors errors will resolve competing theories of human perception and performance and translate into more effective machine vision and robotic systems.