Expertise reversal effect: Cost of generating new schemas

Long-Term Bridge Training Induces Functional Plasticity Changes in the Brain of Early-Adult Individuals

The aim of this study was to investigate the impact of extended bridge expertise on rapid perceptual processing and brain functional plasticity in early adulthood, utilizing functional magnetic resonance imaging (fMRI). In this investigation, we compared 6 high-level college bridge players with 25 college students lacking bridge experience, assessing their intelligence and working memory. Additionally, we scrutinized behavioral performance and whole-brain activation patterns during an image perceptual judgment task. Findings indicated significant group and interaction effects at the behavioral level. Bridge players exhibited prolonged reaction times and enhanced accuracy on card tasks. At the neural level, the activation level of bridge players in the occipital lobe exceeded that of ordinary college students, with more pronounced group effects in the motor area and inferior parietal lobule during card tasks. This implies that bridge expertise in early adulthood induces functional plasticity changes in regions associated with visual processing and automated mathematical computation.

Neuromonitoring Correlates of Expertise Level in Surgical Performers: A Systematic Review

Surgical expertise does not have a clear definition and is often culturally associated with power, authority, prestige, and case number rather than more objective proxies of excellence. Multiple models of expertise progression have been proposed including the Dreyfus model, however, they all currently require subjective evaluation of skill. Recently, efforts have been made to improve the ways in which surgical excellence is measured and expertise is defined using artificial intelligence, video recordings, and accelerometers. However, these aforementioned methods of assessment are still subjective or indirect proxies of expertise, thus uncovering the neural mechanisms that differentiate expert surgeons from trainees may enhance the objectivity of surgical expertise validation. In fact, some researchers have already suggested that their neural imaging-based expertise classification methods outperform currently used methods of surgical skill certification such as the Fundamentals of Laparoscopic Surgery (FLS) scores. Such imaging biomarkers would not only help better identify the highest performing surgeons, but could also improve residency programs by providing more objective, evidence-based feedback and developmental milestones for those in training and perhaps act as a marker of surgical potential in medical students. Despite the potential advantages of using neural imaging in the assessment of surgical expertise, this field of research remains in its infancy. This systematic review identifies studies that have applied neuromonitoring in assessing surgical skill across levels of expertise. The goals of this review are to identify (1) the strongest neural indicators of surgical expertise, (2) the limitations of the current literature on this subject, (3) the most sensible future directions for further study. We found substantial evidence that surgical expertise can be delineated by differential activation and connectivity in the prefrontal cortex (PFC) across multiple task and neuroimaging modalities. Specifically, novices tend to have greater PFC activation than experts under standard conditions in bimanual and decision-making tasks. However, under high temporal demand tasks, experts had increased PFC activation whereas novices had decreased PFC activation. Common limitations uncovered in this review were that task difficulty was often insufficient to delineate between residents and attending. Moreover, attending level involvement was also low in multiple studies which may also have contributed to this issue. Most studies did not analyze the ability of their neuromonitoring findings to accurately classify subjects by level of expertise. Finally, the predominance of fNIRS as the neuromonitoring modality limits our ability to uncover the neural correlates of surgical expertise in non-cortical brain regions. Future studies should first strive to address these limitations. In the longer term, longitudinal within-subjects design over the course of a residency or even a career will also advance the field. Although logistically arduous, such studies would likely be most beneficial in demonstrating effects of increasing surgical expertise on regional brain activation and inter-region connectivity.

In search of a naturalistic neuroimaging approach: Exploration of general feasibility through the case of VR-fMRI and application in the domain of episodic memory

Virtual Reality (VR) is an increasingly widespread tool for research as it allows the creation of experiments taking place in multimodal and daily-life-like environments, while keeping a strong experimental control. Adding neuroimaging to VR leads to a better understanding of the underlying brain networks activated during a naturalistic task, whether for research purposes or rehabilitation. The present paper focuses on the specific use of concurrent VR and fMRI and its technical challenges and feasibility, with a brief examination of the general existing solutions. Following the PRISMA guidelines, the review investigates the particular case of how VR-fMRI has explored episodic memory so far, with a comparison of object- and place-based episodic memory. This review confirms the involvement of cerebral regions well-known to be implicated in episodic memory and unravels other regions devoted to bodily and narrative aspects of the self, promoting new avenues of research in the domain of naturalistic episodic memory. Future studies should develop more immersive and interactive virtual neuroimaging features to increase ecological and embodied neurocognition aspects.

High density optical neuroimaging predicts surgeons's subjective experience and skill levels

Measuring cognitive load is important for surgical education and patient safety. Traditional approaches of measuring cognitive load of surgeons utilise behavioural metrics to measure performance and surveys and questionnaires to collect reports of subjective experience. These have disadvantages such as sporadic data, occasionally intrusive methodologies, subjective or misleading self-reporting. In addition, traditional approaches use subjective metrics that cannot distinguish between skill levels. Functional neuroimaging data was collected using a high density, wireless NIRS device from sixteen surgeons (11 attending surgeons and 5 surgery resident) and 17 students while they performed two laparoscopic tasks (Peg transfer and String pass). Participant’s subjective mental load was assessed using the NASA-TLX survey. Machine learning approaches were used for predicting the subjective experience and skill levels. The Prefrontal cortex (PFC) activations were greater in students who reported higher-than-median task load, as measured by the NASA-TLX survey. However in the case of attending surgeons the opposite tendency was observed, namely higher activations in the lower v higher task loaded subjects. We found that response was greater in the left PFC of students particularly near the dorso- and ventrolateral areas. We quantified the ability of PFC activation to predict the differences in skill and task load using machine learning while focussing on the effects of NIRS channel separation distance on the results. Our results showed that the classification of skill level and subjective task load could be predicted based on PFC activation with an accuracy of nearly 90%. Our finding shows that there is sufficient information available in the optical signals to make accurate predictions about the surgeons’ subjective experiences and skill levels. The high accuracy of results is encouraging and suggest the integration of the strategy developed in this study as a promising approach to design automated, more accurate and objective evaluation methods.