Neural correlates of cognitive workload and anesthetic depth

Functional near-infrared spectroscopy (fNIR), a non-invasive neuroimaging modality designed to monitor the hemodynamic change, can help identify neural correlates of human brain functioning mediated by different events. In this thesis, fNIR has been used to monitor prefrontal cortical activity with the primary objective to determine a set of neurophysiological markers that detect changes in neural activation elicited by levels of mental engagement. Two studies were selected to assess change in the cognitive state of mental engagement at both high and low levels of neural activation. At the high end of neural activation, human performance studies were conducted to assess cognitive workload, in particular signal changes associated with overload. At the low end of cognitive engagement, the capacity of fNIR to detect changes associate with the depth of anesthesia was investigated using patients undergoing general anesthesia. In the human performance study, participants were cognitively challenged by a complex task. By contrast, in the anesthetic depth assessment study, cognitive activity was deliberately suppressed by anesthetic agents. In both studies, neurophysiological markers of hemodynamic changes were extracted from the fNIR measurements. The hypothesis underlying the human performance study is the positive correlation of blood oxygenation in the prefrontal cortex with increasing task difficulty and sustained cognitive effort. In addition, increased blood oxygenation demonstrates a positive relationship with behavioral performance measures in this task. A naval air warfare management and control task with varying levels of difficulty has been chosen to test this engagement condition. The results of this study showed that changes in blood oxygenation in relevant areas of the prefrontal cortex are associated with increasing cognitive workload, defined as sustained attention in a verbal and spatial working memory and decision-making task. The results suggest a reliable, positive association between cognitive workload and increases in cortical oxygenation responses (r=0.89 & p<0.001). The data analysis also supports the hypothesis that the rate of oxygenation change in the dorsolateral prefrontal cortex as measured by fNIR can provide an index of sustained attention in a complex working memory and decision-making task. Furthermore, this study reveals that an abrupt drop in the rate of oxygenation change in dorsolateral prefrontal cortex under high workload conditions is associated with a user's decline in performance. Awareness is an unintended mental state during general anesthesia. An accurate, objective measure of return to consciousness would provide an important safeguard for patients and physicians alike. This exploratory investigation on predicting awareness under general anesthesia examines the hypothesis that the transition from deep to light anesthetic stages is associated with reliable changes in oxygenated, deoxygenated, and total hemoglobin in frontal cortex. Hemodynamic changes during deep and light anesthesia were examined in 26 patients. The results suggest that the rate of deoxygenated hemoglobin change can be used as a descriptive neuromarker to differentiate between deep and light anesthesia stages (F1,25 = 7.61, p<0.01). This marker is proposed for further development as an index of the depth of anesthesia for the purpose of monitoring awareness under general anesthesia. In addition to the neuropsychological findings, this research demonstrates engineering and signal processing solutions in the form of customized algorithms and procedures that allow fNIR to measure usable signals under field conditions. Independent and principal component analyses (ICA, PCA) were combined in a novel procedure that employed dark current (i.e., signal from non-cortical sources) as a reference measurement. This method provided improved signal-to-noise ratio for the hemodynamic measurements acquired in the operating room, and can be used to increase the signal quality of fNIR for many other applications and field situations.