Fight or Flight in the Faraday Cage

The brain's prefrontal-limbic system plays a critical role in identifying potential threats. As per the predator camouflaged at right, often sensory cues to danger are obscured and difficult to discern. Evidence from our earlier fMRI-based threat detection studies suggests that the inferior frontal gyrus (IFG) plays a unique role within the prefrontal-limbic circuit, providing a gating mechanism within an "Information Loop" that processes visual stimuli by the visual cortex in cycles. These cycles represent a trade-off between accuracy and speed. By processing stimuli in stages, the brain maximizes its efficiency by permitting just enough processing to make an accurate decision—but no more. The IFG effectively allows sensory input from the thalamus and visual cortex to exit the Information Loop and proceed to the ventromedial prefrontal cortex (vmPFC) only once the threshold of information necessary for decision making has been met. The caveat here is that this threshold is not the same for everyone; our studies suggest that the IFG’s gating mechanism may hold the key to understanding why some individuals’ processing of ambiguous threat cues predispose them to anxiety while others’ make them oblivious to risk. The high temporal resolution provided by EEG allows us to use circuit dynamics to validate candidate architectures suggested by fMRI. More generally, we’re using these experiments to develop a new class of AI and engineering-based analytical tools designed to identify, computationally model, and predict the behavior of control circuits in the brain.

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Work currently in progress; stay tuned for a preprint!

After first conditioning fear to a target stimulus, we then measure how the Information Loop processes stimuli that are safe but perceptually similar to cues signaling threat.

After first conditioning fear to a target stimulus, we then measure how the Information Loop processes stimuli that are safe but perceptually similar to cues signaling threat.

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Individualized prediction of human pattern detection under conditions of “unknown unknowns”

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Making Sense of Computational Psychiatry