Brain-in-the-Loop Learning Using fNIR and Simulated Virtual Reality Surgical Tasks: Hemodynamic and Behavioral Effects

Abstract

Abstract. Functional near infrared spectroscopy (fNIR) is a noninvasive, portable optical imaging tool to monitor changes in hemodynamic responses (i.e., oxygenated hemoglobin (HbO)) within the prefrontal cortex (PFC) in response to sensory, motor or cognitive activation. We used fNIR for monitoring PFC activation during learning of simulated laparoscopic surgical tasks throughout 4 days of training and testing. Blocked (BLK) and random (RND) practice orders were used to test the practice schedule effect on behavioral, hemodynamic responses and relative neural efficiency (EFF rel-neural ) measures during transfer. Left and right PFC for both tasks showed significant differences with RND using less HbO than BLK. Cognitive workload showed RND exhibiting high EFF rel-neural across the PFC for the coordination task while the more difficult cholecystectomy task showed EFF rel-neural differences only in the left PFC. Use of brain activation, behavioral and EFF rel-neural measures can provide a more accurate depiction of the generalization or transfer of learning.

Acquisition, retention and transfer of simulated laparoscopic tasks using fNIR and a contextual interference paradigm

“…Our findings support Seymour and colleagues 4,42 and set the stage for additional learning scenarios using applications of simulation and practice organization within surgical training and medical education. 4,6,10,11,[20][21][22][23][24][33][34][35]42 In conclusion, we demonstrate that novice learners practicing in a random practice order will learn multiple simulated laparoscopic tasks more efficiently and effectively than learners practicing in a blocked practice order. Our results indicate that optical imaging can be used to capture learning effects in a simulated laparoscopic environment.…”

“…25 The positioning of the light sources and detectors on the sensor pad, anatomical landmarks for sensor placement consistency, data acquisition and visualization specifics and data processing details have been described. 5,11,25 fNIR data epochs for each surgery simulation trial were extracted using time synchronization markers received through a serial port during the experiment. Hemodynamic changes for each of the 16 optodes during each trial were calculated separately using the Modified Beer Lambert Law.…”

“…These results help to extend our understanding of the contextual interference effect regarding the influences of the practice order and task type on neural function. 11,25,32,35,37,38,40,41 fNIR, because it is non-invasive, portable, small and mobile, has the potential to be used in future learning/training environments to provide objective, task related brain-based measures for assessing cognitive effort and neural processing during the learning process. Our findings support Seymour and colleagues 4,42 and set the stage for additional learning scenarios using applications of simulation and practice organization within surgical training and medical education.…”

“…Functional near infrared spectroscopy (fNIR) is a noninvasive, optical brain imaging tool that monitors changes in total hemoglobin within the prefrontal cortex (PFC) in response to cognitive, motor and sensory activation ( Figure 1). [5][6][7][8][9][10][11][12][13] The PFC is responsible for motor planning, organization and regulation. It controls cognitive function and action, and works with other cortical circuits with executive functions including attention and working memory.…”

Examining Mental Workload in a Spatial Navigation Transfer Game via Functional near Infrared Spectroscopy

“…To understand the complex nature of these cognitive processes within the PFC area, it is important to examine mental workload that is taxed by various cognitive tasks. Mental workload was defined as the cognitive and psychological effort that is required from a subject to complete a given task [ 4 , 5 ]. Previous studies indicated that mental workload is sensitive to task-related features including the difficulty level of the task, the order in which the tasks were presented (e.g., blocked vs. random practice), and the type of the task (e.g., learning vs. transfer task) [ 6 , 7 , 8 ].…”