Little is known about the neurological underpinnings of deliberate deception. Recent advances in the detection of deception have examined brain responses during experimental deception protocols. A consensus has begun to emerge across the handful of functional magnetic resonance imaging (fMRI) studies that have examined deception implicating areas of the dorsolateral and inferior prefrontal cortex as active during deliberate deception. The purpose of the current study was to determine the utility of functional near-infrared spectroscopy (fNIR), a neuroimaging technique that allows reasonable ecological utility, for the detection of deception. Using a modified version of the Guilty Knowledge Task, participants attempted to conceal the identity of a playing card they were holding while dorsolateral and inferior frontal cortices were monitored with fNIR. The results revealed increased activation in bilateral inferior frontal gyri (BA 47/45) and middle frontal gyri (BA 46/10) when participants were lying. The results provide evidence that inferior and middle prefrontal cortical areas are associated at least some forms of deliberate deception. fNIR has the potential to provide a field-deployable brain-based method for the detection of deception.
Previous research has examined the relationships between physiological parameters and frequency oscillations in hemodynamic activity of brain. The current study used functional near infrared spectroscopy (fNIRS) to examine the relationship between oscillatory hemodynamics and performance measures during a standard cognitive task. fNIR data (n=7) were collected from 16 optodes distributed over dorsolateral prefrontal and inferior frontal cortex during a standard visual "oddball" task while behavioral reaction times to each stimulus were recorded. A frequency analysis of the fNIRS data revealed that the ratio of the power at 0-30 mHz to the power at 30-150 mHz was correlated with the number of mistakes a subject made as, well as their reaction times. Relatively greater low-frequency oscillations were associated with more mistakes and increased behavioral reaction times.
Near infrared spectroscopy as a neuroimaging modality is a recent development. Near infrared neuroimagers are typically safe, portable, relatively affordable and non-invasive. The ease of sensor setup and non-intrusiveness make functional near infrared (fNIR) imaging an ideal candidate for monitoring human cortical function in a wide range of real world situations. However optical signals are susceptible to motion-artifacts, hindering the application of fNIR in studies where subject mobility cannot be controlled. In this paper, we present a filtering framework for motion-artifact cancellation to facilitate the deployment of fNIR imaging in real-world scenarios. We simulate a generic field environment by having subjects walk on a treadmill while performing a cognitive task and demonstrate that measurements can be effectively cleaned of motion-artifacts.