Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task

Walia, Pushpinder; Fu, Yaoyu; Norfleet, Jack; Schwaitzberg, Steven D.; Intes, Xavier; De, Suvranu; Cavuoto, Lora; Dutta, Anirban

doi:10.1186/s40708-022-00179-z

Cited by 5 publications

(52 citation statements)

References 103 publications

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“…In our prior work (Walia et al, 2022a), we have shown contextual switching of the brain state during laparoscopic suturing with intracorporeal knot tying task-errors that can be related to error perception and corrective action (Benozzo et al, 2021). In the current study, we performed tDCS of the left VLPFC to facilitate subjective task-error awareness (Wessel, 2012) by activating the ventral attention system (Vossel et al, 2014).…”

Section: Introductionmentioning

confidence: 85%

“…The ventral stream (Kamat et al, 2022a), which senses the feedback ( external monitoring ) of the environment in the primary sensory cortex, flows to the sensory association cortex, and then to the posterior association cortex (such as the supramarginal gyrus), leading to the perception of conscious errors in the ventrolateral prefrontal cortex (VLPFC). Here, controlled goaldirected attention may be facilitated with tDCS of the dorsolateral PFC (Ashcroft et al, 2020) while (unexpected) error stimulus-driven attention may need tDCS of the VLPFC (Walia et al, 2022a), (Walia et al, 2021a) indeed, they have dissociable brain connectivity (Seeley et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…Error-based learning is one of the basic skill acquisition mechanisms, which includes error detection, error correction, and subsequent performance adjustments (Seidler et al, 2013). Here, individual differences in error perception and attention reorientation for error correction actions are argued to be different between experts and beginners (Walia et al, 2022a). In particular, errors can be preemptively corrected by prediction mechanisms based on the forward model (Wolpert and Miall, 1996), which are suggested to improve with expertise.…”

Section: Introductionmentioning

confidence: 99%

“…functional near-infrared spectroscopy (fNIRS) (Nemani et al, 2018) and electroencephalography (EEG) (Ciechanski et al, 2019), and relating the brain activation changes to behavior can provide mechanistic insights. In particular, a distinction can be made between based on a predictive forward modeling framework (Wolpert and Miall, 1996) that can be modeled as error perception corrective action coupling (Kamat et al, 2022a;Walia et al, 2022a). Then, tDCS may facilitate mparator system in the cerebellum (Tanaka et al, 2020;Welniarz et al, 2021) event is sensed to drive the attention reorientation for skilled corrective action (Walia et al, 2022a).…”

Section: Introductionmentioning

confidence: 99%

“…In particular, a distinction can be made between based on a predictive forward modeling framework (Wolpert and Miall, 1996) that can be modeled as error perception corrective action coupling (Kamat et al, 2022a;Walia et al, 2022a). Then, tDCS may facilitate mparator system in the cerebellum (Tanaka et al, 2020;Welniarz et al, 2021) event is sensed to drive the attention reorientation for skilled corrective action (Walia et al, 2022a).…”

Section: Introductionmentioning

confidence: 99%

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Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Walia

Norfleet

et al. 2023

Preprint

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Transcranial direct current stimulation (tDCS) has been shown to facilitate surgical training and performance when compared to sham tDCS; however, the potency may be improved by selecting appropriate brain targets based on neuroimaging and mechanistic insights. Published studies have shown the feasibility of portable brain imaging in conjunction with tDCS during Fundamentals of Laparoscopic Surgery (FLS) tasks for concurrently monitoring the cortical activations via functional near-infrared spectroscopy (fNIRS). Then, fNIRS can be combined with electroencephalogram (EEG) where EEG band power changes have been shown to correspond to the changes in oxyhemoglobin (HbO) concentration, found from the fNIRS. In principal accordance with these prior works, our current study aimed to investigate multi-modal imaging of the brain response to cerebellar (CER) and ventrolateral prefrontal cortex (PFC) tDCS that may facilitate the most complex FLS suturing with intracorporal knot tying task. Our healthy human study on twelve novices (age: 22-28 years, 2 males, 1 female with left-hand dominance) from medical/premedical backgrounds aimed for mechanistic insights from neuroimaging brain areas that are related to error-based learning – one of the basic skill acquisition mechanisms. We found that right CER tDCS of the posterior lobe facilitated a statistically significant (q<0.05) brain response at the bilateral prefrontal areas at the start of the FLS task that was higher than sham tDCS. Also, right CER tDCS significantly (p<0.05) improved FLS score when compared to sham tDCS. In contrast, left PFC tDCS failed to facilitate a significant brain response and FLS performance improvement. Moreover, right CER tDCS facilitated activation of the bilateral prefrontal brain areas related to FLS performance improvement provided mechanistic insights into the CER tDCS effects. The mechanistic insights motivated future investigation of CER tDCS effects on the error-related perception action coupling based on directed functional connectivity studies.

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Section: Introductionmentioning

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Walia

Norfleet

et al. 2023

Preprint

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Using neuroimaging to assess brain activity and areas associated with surgical skills: a systematic review

Andersen,

Riparbelli,

Siebner

et al. 2024

Surg Endosc

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EEG topography preserving convolutional neural network approach to assess skill levels during laparoscopic surgical training

Manabe

Rahul

et al. 2023

Preprint

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The study objective was classification of skill level based on the topographical features of the electroencephalogram(EEG) during the most complex Fundamentals of Laparoscopic Surgery(FLS) task. We developed a novel microstate-based Common Spatial Pattern (CSP) analysis with linear discriminant analysis(LDA) classification that was compared with topography-preserving convolutional neural network(CNN) based approach to distinguish experts versus novices based on EEG. Ten expert surgeons and thirteen novice medical residents were recruited at the University at Buffalo. After informed consent, the subjects performed three trials of laparoscopic suturing and knot tying with rest periods in-between. 32-channel EEG during task performance was used to analyze spatial patterns of brain activity in 8 expert surgeons (2 dropouts due to data quality) and 13 novice medical residents. Besides conventional CSP analysis, microstate analysis was applied for preprocessing before CSP analysis for improved classification using LDA with 10-fold cross-validation. Also, a topography-preserving 3D CNN model (ESNet) was applied that considered both spatial and temporal information for the classification. Here, 5-fold cross-validation was repeated 10 times, and the results of each iteration of the testing data set were evaluated using indices, Accuracy, F1 score, Mathews Correlation Coefficient (MCC), sensitivity, and Specificity. Microstate-based CSP analysis found that while novices had primarily the frontal cortex involved for a maximum of spatial pattern vectors, experts had the hotspot of the spatial pattern vectors over the frontal and parietal cortices where the discriminating parietal brain region was supported by the Gradient-weighted Class Activation Mapping (Grad-CAM) of our 3D CNN-based model. Here, LDA with 10-fold cross-validation achieved more than 90% classification accuracy with microstate-based CSP, while conventional regularized CSP could reach around 80% classification accuracy. Then, 3D CNN provided the highest sensitivity of 99.30%, the highest specificity of 99.70%, the highest F1 score of 98.51%, and the highest MCC of 97.56%. Microstate-based CSP analysis improved the LDA classification (~90%) of experts versus novices based on EEG topography during a complex FLS task; however, combining the spatial and temporal information in the EEG topography preserving 3D CNN model significantly improved the classifier accuracy (>98%) in addition to providing mechanistic insights based on Grad-CAM analysis.

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Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task

Cited by 5 publications

References 103 publications

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Using neuroimaging to assess brain activity and areas associated with surgical skills: a systematic review

EEG topography preserving convolutional neural network approach to assess skill levels during laparoscopic surgical training

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