1
|
Del Campo VL, Morán JFO, Cagigal VM, Martín JM, Pagador JB, Hornero R. The use of the eye-fixation-related potential to investigate visual perception in professional domains with high attentional demand: a literature review. Neurol Sci 2024; 45:1849-1860. [PMID: 38157102 DOI: 10.1007/s10072-023-07275-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 12/17/2023] [Indexed: 01/03/2024]
Abstract
INTRODUCTION Visual attention is a cognitive skill related to visual perception and neural activity, and also moderated by expertise, in time-constrained professional domains (e.g., aviation, driving, sport, surgery). However, the contribution of both perceptual and neural processes on performance has been studied separately in the literature. DEVELOPMENT We defend an integration of visual and neural signals to offer a more complete picture of the visual attention displayed by professionals of different skill levels when performing free-viewing tasks. Specifically, we propose to zoom the analysis in data related to the quiet eye and P300 component jointly, as a novel signal processing approach to evaluate professionals' visual attention. CONCLUSION This review highlights the advantages of using portable eye trackers and electroencephalogram systems altogether, as a promising technique for a better understanding of early cognitive components related to attentional processes. Altogether, the eye-fixation-related potentials method may provide a better understanding of the cognitive mechanisms employed by the participants in natural settings, revealing what visual information is of interest for participants and distinguishing the neural bases of visual attention between targets and non-targets whenever they perceive a stimulus during free viewing experiments.
Collapse
Affiliation(s)
- Vicente Luis Del Campo
- Laboratorio de Aprendizaje y Control Motor, Facultad de Ciencias del Deporte, Universidad de Extremadura, Avda. de La Universidad, S/N, 10003, Cáceres, Spain.
| | | | - Víctor Martínez Cagigal
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, E.T.S.I. Telecomunicación, Paseo Belén 15, 47011, Valladolid, Spain
- Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Biomedicina (CIBER-BBN), E.T.S.I. Telecomunicación, Paseo Belén 15, 47011, Valladolid, Spain
| | - Jesús Morenas Martín
- Laboratorio de Aprendizaje y Control Motor, Facultad de Ciencias del Deporte, Universidad de Extremadura, Avda. de La Universidad, S/N, 10003, Cáceres, Spain
| | - J Blas Pagador
- Centro de Cirugía de Mínima Invasión Jesús Usón, Ctra. N-521, Km. 41,8, 10071, Cáceres, Spain
| | - Roberto Hornero
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, E.T.S.I. Telecomunicación, Paseo Belén 15, 47011, Valladolid, Spain
- Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Biomedicina (CIBER-BBN), E.T.S.I. Telecomunicación, Paseo Belén 15, 47011, Valladolid, Spain
| |
Collapse
|
2
|
Walia P, Fu Y, Norfleet J, Schwaitzberg SD, Intes X, De S, Cavuoto L, Dutta A. Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task. FRONTIERS IN NEUROERGONOMICS 2024; 4:1135729. [PMID: 38234492 PMCID: PMC10790853 DOI: 10.3389/fnrgo.2023.1135729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024]
Abstract
Transcranial Direct Current Stimulation (tDCS) has demonstrated its potential in enhancing surgical training and performance compared to sham tDCS. However, optimizing its efficacy requires the selection of appropriate brain targets informed by neuroimaging and mechanistic understanding. Previous studies have established the feasibility of using portable brain imaging, combining functional near-infrared spectroscopy (fNIRS) with tDCS during Fundamentals of Laparoscopic Surgery (FLS) tasks. This allows concurrent monitoring of cortical activations. Building on these foundations, our study aimed to explore the multi-modal imaging of the brain response using fNIRS and electroencephalogram (EEG) to tDCS targeting the right cerebellar (CER) and left ventrolateral prefrontal cortex (PFC) during a challenging FLS suturing with intracorporeal knot tying task. Involving twelve novices with a medical/premedical background (age: 22-28 years, two males, 10 females with one female with left-hand dominance), our investigation sought mechanistic insights into tDCS effects on brain areas related to error-based learning, a fundamental skill acquisition mechanism. The results revealed that right CER tDCS applied to the posterior lobe elicited a statistically significant (q < 0.05) brain response in bilateral prefrontal areas at the onset of the FLS task, surpassing the response seen with sham tDCS. Additionally, right CER tDCS led to a significant (p < 0.05) improvement in FLS scores compared to sham tDCS. Conversely, the left PFC tDCS did not yield a statistically significant brain response or improvement in FLS performance. In conclusion, right CER tDCS demonstrated the activation of bilateral prefrontal brain areas, providing valuable mechanistic insights into the effects of CER tDCS on FLS peformance. These insights motivate future investigations into the effects of CER tDCS on error-related perception-action coupling through directed functional connectivity studies.
Collapse
Affiliation(s)
- Pushpinder Walia
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, United States
| | - Yaoyu Fu
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, United States
| | - Jack Norfleet
- U.S. Army Futures Command, Combat Capabilities Development Command Soldier Center STTC, Orlando, FL, United States
| | - Steven D. Schwaitzberg
- University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, United States
| | - Xavier Intes
- Center for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, United States
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States
| | - Suvranu De
- Center for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, United States
| | - Lora Cavuoto
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, United States
| | - Anirban Dutta
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, United States
| |
Collapse
|
3
|
Manabe T, Rahul F, Fu Y, Intes X, Schwaitzberg SD, De S, Cavuoto L, Dutta A. Distinguishing Laparoscopic Surgery Experts from Novices Using EEG Topographic Features. Brain Sci 2023; 13:1706. [PMID: 38137154 PMCID: PMC10742221 DOI: 10.3390/brainsci13121706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 11/27/2023] [Accepted: 12/01/2023] [Indexed: 12/24/2023] Open
Abstract
The study aimed to differentiate experts from novices in laparoscopic surgery tasks using electroencephalogram (EEG) topographic features. A microstate-based common spatial pattern (CSP) analysis with linear discriminant analysis (LDA) was compared to a topography-preserving convolutional neural network (CNN) approach. Expert surgeons (N = 10) and novice medical residents (N = 13) performed laparoscopic suturing tasks, and EEG data from 8 experts and 13 novices were analysed. Microstate-based CSP with LDA revealed distinct spatial patterns in the frontal and parietal cortices for experts, while novices showed frontal cortex involvement. The 3D CNN model (ESNet) demonstrated a superior classification performance (accuracy > 98%, sensitivity 99.30%, specificity 99.70%, F1 score 98.51%, MCC 97.56%) compared to the microstate based CSP analysis with LDA (accuracy ~90%). Combining spatial and temporal information in the 3D CNN model enhanced classifier accuracy and highlighted the importance of the parietal-temporal-occipital association region in differentiating experts and novices.
Collapse
Affiliation(s)
- Takahiro Manabe
- School of Engineering, University of Lincoln, Lincoln LN6 7TS, UK;
| | - F.N.U. Rahul
- Centre for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, MI 12180, USA; (F.R.); (X.I.)
| | - Yaoyu Fu
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY 14260, USA; (Y.F.); (L.C.)
| | - Xavier Intes
- Centre for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, MI 12180, USA; (F.R.); (X.I.)
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, MI 12180, USA
| | - Steven D. Schwaitzberg
- School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA;
| | - Suvranu De
- College of Engineering, Florida A&M University-Florida State University, Tallahassee, FL 32310, USA;
| | - Lora Cavuoto
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY 14260, USA; (Y.F.); (L.C.)
| | - Anirban Dutta
- School of Engineering, University of Lincoln, Lincoln LN6 7TS, UK;
| |
Collapse
|
4
|
Goble M, Caddick V, Patel R, Modi H, Darzi A, Orihuela-Espina F, Leff DR. Optical neuroimaging and neurostimulation in surgical training and assessment: A state-of-the-art review. FRONTIERS IN NEUROERGONOMICS 2023; 4:1142182. [PMID: 38234498 PMCID: PMC10790870 DOI: 10.3389/fnrgo.2023.1142182] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 03/03/2023] [Indexed: 01/19/2024]
Abstract
Introduction Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical neuroimaging technique used to assess surgeons' brain function. The aim of this narrative review is to outline the effect of expertise, stress, surgical technology, and neurostimulation on surgeons' neural activation patterns, and highlight key progress areas required in surgical neuroergonomics to modulate training and performance. Methods A literature search of PubMed and Embase was conducted to identify neuroimaging studies using fNIRS and neurostimulation in surgeons performing simulated tasks. Results Novice surgeons exhibit greater haemodynamic responses across the pre-frontal cortex than experts during simple surgical tasks, whilst expert surgical performance is characterized by relative prefrontal attenuation and upregulation of activation foci across other regions such as the supplementary motor area. The association between PFC activation and mental workload follows an inverted-U shaped curve, activation increasing then attenuating past a critical inflection point at which demands outstrip cognitive capacity Neuroimages are sensitive to the impact of laparoscopic and robotic tools on cognitive workload, helping inform the development of training programs which target neural learning curves. FNIRS differs in comparison to current tools to assess proficiency by depicting a cognitive state during surgery, enabling the development of cognitive benchmarks of expertise. Finally, neurostimulation using transcranial direct-current-stimulation may accelerate skill acquisition and enhance technical performance. Conclusion FNIRS can inform the development of surgical training programs which modulate stress responses, cognitive learning curves, and motor skill performance. Improved data processing with machine learning offers the possibility of live feedback regarding surgeons' cognitive states during operative procedures.
Collapse
Affiliation(s)
- Mary Goble
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | | | | | | | | | | | | |
Collapse
|
5
|
Walia P, Fu Y, Norfleet J, Schwaitzberg SD, Intes X, De S, Cavuoto L, Dutta A. Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task. Brain Inform 2022; 9:29. [PMID: 36484977 PMCID: PMC9733771 DOI: 10.1186/s40708-022-00179-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 11/14/2022] [Indexed: 12/13/2022] Open
Abstract
Error-based learning is one of the basic skill acquisition mechanisms that can be modeled as a perception-action system and investigated based on brain-behavior analysis during skill training. Here, the error-related chain of mental processes is postulated to depend on the skill level leading to a difference in the contextual switching of the brain states on error commission. Therefore, the objective of this paper was to compare error-related brain states, measured with multi-modal portable brain imaging, between experts and novices during the Fundamentals of Laparoscopic Surgery (FLS) "suturing and intracorporeal knot-tying" task (FLS complex task)-the most difficult among the five psychomotor FLS tasks. The multi-modal portable brain imaging combined functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) for brain-behavior analysis in thirteen right-handed novice medical students and nine expert surgeons. The brain state changes were defined by quasi-stable EEG scalp topography (called microstates) changes using 32-channel EEG data acquired at 250 Hz. Six microstate prototypes were identified from the combined EEG data from experts and novices during the FLS complex task that explained 77.14% of the global variance. Analysis of variance (ANOVA) found that the proportion of the total time spent in different microstates during the 10-s error epoch was significantly affected by the skill level (p < 0.01), the microstate type (p < 0.01), and the interaction between the skill level and the microstate type (p < 0.01). Brain activation based on the slower oxyhemoglobin (HbO) changes corresponding to the EEG band power (1-40 Hz) changes were found using the regularized temporally embedded Canonical Correlation Analysis of the simultaneously acquired fNIRS-EEG signals. The HbO signal from the overlying the left inferior frontal gyrus-opercular part, left superior frontal gyrus-medial orbital, left postcentral gyrus, left superior temporal gyrus, right superior frontal gyrus-medial orbital cortical areas showed significant (p < 0.05) difference between experts and novices in the 10-s error epoch. We conclude that the difference in the error-related chain of mental processes was the activation of cognitive top-down attention-related brain areas, including left dorsolateral prefrontal/frontal eye field and left frontopolar brain regions, along with a 'focusing' effect of global suppression of hemodynamic activation in the experts, while the novices had a widespread stimulus(error)-driven hemodynamic activation without the 'focusing' effect.
Collapse
Affiliation(s)
- Pushpinder Walia
- grid.273335.30000 0004 1936 9887Neuroengineering and Informatics for Rehabilitation Laboratory, Department of Biomedical Engineering, University at Buffalo, Buffalo, USA
| | - Yaoyu Fu
- grid.273335.30000 0004 1936 9887Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, USA
| | - Jack Norfleet
- U.S. Army Futures Command, Combat Capabilities Development Command Soldier Center STTC, Orlando, USA
| | - Steven D. Schwaitzberg
- grid.273335.30000 0004 1936 9887University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, USA
| | - Xavier Intes
- grid.33647.350000 0001 2160 9198Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY USA ,grid.33647.350000 0001 2160 9198Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, USA
| | - Suvranu De
- grid.33647.350000 0001 2160 9198Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY USA ,grid.33647.350000 0001 2160 9198Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, USA
| | - Lora Cavuoto
- grid.273335.30000 0004 1936 9887Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, USA
| | - Anirban Dutta
- grid.36511.300000 0004 0420 4262Neuroengineering and Informatics for Rehabilitation and Simulation-Based Learning, University of Lincoln, Lincoln, UK
| |
Collapse
|
6
|
Walia P, Fu Y, Schwaitzberg SD, Intes X, De S, Dutta A, Cavuoto L. Portable neuroimaging differentiates novices from those with experience for the Fundamentals of Laparoscopic Surgery (FLS) suturing with intracorporeal knot tying task. Surg Endosc 2022:10.1007/s00464-022-09727-4. [DOI: 10.1007/s00464-022-09727-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
|
7
|
Kamat A, Makled B, Norfleet J, Schwaitzberg SD, Intes X, De S, Dutta A. Directed information flow during laparoscopic surgical skill acquisition dissociated skill level and medical simulation technology. NPJ SCIENCE OF LEARNING 2022; 7:19. [PMID: 36008451 PMCID: PMC9411170 DOI: 10.1038/s41539-022-00138-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 08/04/2022] [Indexed: 05/11/2023]
Abstract
Virtual reality (VR) simulator has emerged as a laparoscopic surgical skill training tool that needs validation using brain-behavior analysis. Therefore, brain network and skilled behavior relationship were evaluated using functional near-infrared spectroscopy (fNIRS) from seven experienced right-handed surgeons and six right-handed medical students during the performance of Fundamentals of Laparoscopic Surgery (FLS) pattern of cutting tasks in a physical and a VR simulator. Multiple regression and path analysis (MRPA) found that the FLS performance score was statistically significantly related to the interregional directed functional connectivity from the right prefrontal cortex to the supplementary motor area with F (2, 114) = 9, p < 0.001, and R2 = 0.136. Additionally, a two-way multivariate analysis of variance (MANOVA) found a statistically significant effect of the simulator technology on the interregional directed functional connectivity from the right prefrontal cortex to the left primary motor cortex (F (1, 15) = 6.002, p = 0.027; partial η2 = 0.286) that can be related to differential right-lateralized executive control of attention. Then, MRPA found that the coefficient of variation (CoV) of the FLS performance score was statistically significantly associated with the CoV of the interregionally directed functional connectivity from the right primary motor cortex to the left primary motor cortex and the left primary motor cortex to the left prefrontal cortex with F (2, 22) = 3.912, p = 0.035, and R2 = 0.262. This highlighted the importance of the efference copy information from the motor cortices to the prefrontal cortex for postulated left-lateralized perceptual decision-making to reduce behavioral variability.
Collapse
Affiliation(s)
- Anil Kamat
- Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Basiel Makled
- US Army Futures Command, Combat Capabilities Development Command Soldier Center STTC, Orlando, FL, USA
| | - Jack Norfleet
- US Army Futures Command, Combat Capabilities Development Command Soldier Center STTC, Orlando, FL, USA
| | | | - Xavier Intes
- Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Suvranu De
- Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Anirban Dutta
- Neuroengineering and Informatics for Rehabilitation Laboratory, Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA.
| |
Collapse
|