Electroencephalography can provide advance warning of technical errors during laparoscopic surgery.

BACKGROUND: Intraoperative adverse events lead to patient injury and death, and are increasing. Early warning systems (EWSs) have been used to detect patient deterioration and save lives. However, few studies have used EWSs to monitor surgical performance and caution about imminent technical errors. Previous (non-surgical) research has investigated neural activity to predict future motor errors using electroencephalography (EEG). The present proof-of-concept cohort study investigates whether EEG could predict technical errors in surgery. METHODS: In a large academic hospital, three surgical fellows performed 12 elective laparoscopic general surgeries. Audiovisual data of the operating room and the surgeon's neural activity were recorded. Technical errors and epochs of good surgical performance were coded into events. Neural activity was observed 40 s prior and 10 s after errors and good events to determine how far in advance errors were detected. A hierarchical regression model was used to account for possible clustering within surgeons. This prospective, proof-of-concept, cohort study was conducted from July to November 2021, with a pilot period from February to March 2020 used to optimize the technique of data capture and included participants who were blinded from study hypotheses. RESULTS: Forty-five technical errors, mainly due to too little force or distance (n = 39), and 27 good surgical events were coded during grasping and dissection. Neural activity representing error monitoring (p = .008) and motor uncertainty (p = .034) was detected 17 s prior to errors, but not prior to good surgical performance. CONCLUSIONS: These results show that distinct neural signatures are predictive of technical error in laparoscopic surgery. If replicated with low false-alarm rates, an EEG-based EWS of technical errors could be used to improve individualized surgical training by flagging imminent unsafe actions-before errors occur and cause patient harm.

Image reconstruction reveals the impact of aging on face perception.

Extensive work has demonstrated an age-related decline in face recognition, but the nature and the extent of aging-related alterations in face representations remain unclear. Here, we address these issues using an image reconstruction approach to reveal the content of visual representations. Healthy young and older adults provided similarity judgments for pairs of face images. Facial shape and surface features were subsequently derived and combined into image reconstructions of facial appearance. Both objective and experimental evaluations revealed that reconstructions were successful for every participant. Critically, shape and surface properties, such as eye shape and skin tone, were less accurately represented in older than young individuals. Yet, age-related differences in face representations, though significant, were less pronounced than those due to individual variability. Our results provide novel insights into age-related changes in visual perception and demonstrate the utility of image reconstruction to uncovering internal representations across a variety of populations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A multivariate investigation of visual word, face, and ensemble processing: Perspectives from EEG-based decoding and feature selection.

Recent investigations have focused on the spatiotemporal dynamics of visual recognition by appealing to pattern analysis of EEG signals. While this work has established the ability to decode identity-level information (such as the identity of a face or of a word) from neural signals, much less is known about the precise nature of the signals that support such feats, their robustness across visual categories, or their consistency across human participants. Here, we address these questions through the use of EEG-based decoding and multivariate feature selection as applied to three visual categories: words, faces and face ensembles (i.e., crowds of faces). Specifically, we use recursive feature elimination to estimate the diagnosticity of time and frequency-based EEG features for identity-level decoding across three datasets targeting each of the three categories. We then relate feature diagnosticity across categories and across participants while, also, aiming to increase decoding performance and reliability. Our investigation shows that word and face processing are similar in their reliance on spatiotemporal information provided by occipitotemporal channels. In contrast, ensemble processing appears to also rely on central channels and exhibits a similar profile with word processing in the frequency domain. Further, we find that feature diagnosticity is stable across participants and is even capable of supporting cross-participant feature selection, as demonstrated by systematic boosts in decoding accuracy and feature reduction. Thus, our investigation sheds new light on the nature and the structure of the information underlying identity-level visual processing as well as on its generality across categories and participants.

Multivariate Analysis of Electrophysiological Signals Reveals the Temporal Properties of Visuomotor Computations for Precision Grips.

The frontoparietal networks underlying grasping movements have been extensively studied, especially using fMRI. Accordingly, whereas much is known about their cortical locus much less is known about the temporal dynamics of visuomotor transformations. Here, we show that multivariate EEG analysis allows for detailed insights into the time course of visual and visuomotor computations of precision grasps. Male and female human participants first previewed one of several objects and, upon its reappearance, reached to grasp it with the thumb and index finger along one of its two symmetry axes. Object shape classifiers reached transient accuracies of 70% at ∼105 ms, especially based on scalp sites over visual cortex, dropping to lower levels thereafter. Grasp orientation classifiers relied on a system of occipital-to-frontal electrodes. Their accuracy rose concurrently with shape classification but ramped up more gradually, and the slope of the classification curve predicted individual reaction times. Further, cross-temporal generalization revealed that dynamic shape representation involved early and late neural generators that reactivated one another. In contrast, grasp computations involved a chain of generators attaining a sustained state about 100 ms before movement onset. Our results reveal the progression of visual and visuomotor representations over the course of planning and executing grasp movements.SIGNIFICANCE STATEMENT Grasping an object requires the brain to perform visual-to-motor transformations of the object's properties. Although much of the neuroanatomic basis of visuomotor transformations has been uncovered, little is known about its time course. Here, we orthogonally manipulated object visual characteristics and grasp orientation, and used multivariate EEG analysis to reveal that visual and visuomotor computations follow similar time courses but display different properties and dynamics.

Multimodal evidence on shape and surface information in individual face processing.

The significance of shape and surface information for face perception is well established, yet their relative contribution to recognition and their neural underpinnings await clarification. Here, we employ image reconstruction to retrieve, assess and visualize such information using behavioral, electroencephalography and functional magnetic resonance imaging data. Our results indicate that both shape and surface information can be successfully recovered from each modality but that the latter is better recovered than the former, consistent with its key role for face representations. Further, shape and surface information exhibit similar spatiotemporal profiles, rely on the extraction of specific visual features, such as eye shape or skin tone, and reveal a systematic representational structure, albeit with more cross-modal consistency for shape than surface. More generally, the present work illustrates a novel approach to relating and comparing different modalities in terms of perceptual information content. Thus, our results help elucidate the representational basis of individual face recognition while, methodologically, they showcase the utility of image reconstruction and clarify its reliance on diagnostic visual information.

The Neural Dynamics of Facial Identity Processing: Insights from EEG-Based Pattern Analysis and Image Reconstruction.

Uncovering the neural dynamics of facial identity processing along with its representational basis outlines a major endeavor in the study of visual processing. To this end, here, we record human electroencephalography (EEG) data associated with viewing face stimuli; then, we exploit spatiotemporal EEG information to determine the neural correlates of facial identity representations and to reconstruct the appearance of the corresponding stimuli. Our findings indicate that multiple temporal intervals support: facial identity classification, face space estimation, visual feature extraction and image reconstruction. In particular, we note that both classification and reconstruction accuracy peak in the proximity of the N170 component. Further, aggregate data from a larger interval (50-650 ms after stimulus onset) support robust reconstruction results, consistent with the availability of distinct visual information over time. Thus, theoretically, our findings shed light on the time course of face processing while, methodologically, they demonstrate the feasibility of EEG-based image reconstruction.

Memory and Perception-based Facial Image Reconstruction.

Visual memory for faces has been extensively researched, especially regarding the main factors that influence face memorability. However, what we remember exactly about a face, namely, the pictorial content of visual memory, remains largely unclear. The current work aims to elucidate this issue by reconstructing face images from both perceptual and memory-based behavioural data. Specifically, our work builds upon and further validates the hypothesis that visual memory and perception share a common representational basis underlying facial identity recognition. To this end, we derived facial features directly from perceptual data and then used such features for image reconstruction separately from perception and memory data. Successful levels of reconstruction were achieved in both cases for newly-learned faces as well as for familiar faces retrieved from long-term memory. Theoretically, this work provides insights into the content of memory-based representations while, practically, it may open the path to novel applications, such as computer-based 'sketch artists'.

The time course of individual face recognition: A pattern analysis of ERP signals.

An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition.

Temporal dynamics of repetition suppression to individual faces presented at a fast periodic rate.

Periodic presentation of visual stimuli leads to a robust electrophysiological response on the human scalp exactly at the periodic stimulation frequency, a response defined as a "steady-state visual evoked potential" (SSVEP, Regan, 1966). However, recent studies have shown that SSVEPs over the (right) occipito-temporal cortex are reduced when the same individual face is repeated at periodic rates of 3 to 9 Hz compared to when different faces are presented (Rossion, 2014). Here, we characterized the temporal dynamics of this repetition suppression effect. We presented different face identities at a rate of 5.88 Hz (stimulus onset asynchrony of 170 ms) for 15 s, followed by the repetition of the exact same face at this rate for 35 s. Compared to a stimulation sequence with different faces only, there was a large and specific decrease of the 5.88 Hz response when the same face was repeated at that rate. This effect was observed over the left and right occipito-temporal cortex, but not over medial occipital electrode sites where SSVEPs are typically measured. In the right hemisphere, this decrease occurred abruptly, i.e., within half a second following the introduction of the same-identity stimulation, with no further decrease until the end of the stimulation. These observations indicate that the SSVEP recorded over high-level visual areas to periodic stimulation is not steady but rather adapts immediately and fully following the repetition of the same individual face, supporting a bottom-up, stimulus-driven account of repetition suppression effects.

Early sensitivity for eyes within faces: a new neuronal account of holistic and featural processing.

Eyes are central to face processing however their role in early face encoding as reflected by the N170 ERP component is unclear. Using eye tracking to enforce fixation on specific facial features, we found that the N170 was larger for fixation on the eyes compared to fixation on the forehead, nasion, nose or mouth, which all yielded similar amplitudes. This eye sensitivity was seen in both upright and inverted faces and was lost in eyeless faces, demonstrating it was due to the presence of eyes at fovea. Upright eyeless faces elicited largest N170 at nose fixation. Importantly, the N170 face inversion effect (FIE) was strongly attenuated in eyeless faces when fixation was on the eyes but was less attenuated for nose fixation and was normal when fixation was on the mouth. These results suggest the impact of eye removal on the N170 FIE is a function of the angular distance between the fixated feature and the eye location. We propose the Lateral Inhibition, Face Template and Eye Detector based (LIFTED) model which accounts for all the present N170 results including the FIE and its interaction with eye removal. Although eyes elicit the largest N170 response, reflecting the activity of an eye detector, the processing of upright faces is holistic and entails an inhibitory mechanism from neurons coding parafoveal information onto neurons coding foveal information. The LIFTED model provides a neuronal account of holistic and featural processing involved in upright and inverted faces and offers precise predictions for further testing.

Is the rapid adaptation paradigm too rapid? Implications for face and object processing.

Rapid adaptation is an adaptation procedure in which adaptors and test stimuli are presented in rapid succession. The current study tested the validity of this method for early ERP components by investigating the specificity of the adaptation effect on the face-sensitive N170 ERP component across multiple test stimuli. Experiments 1 and 2 showed identical response patterns for house and upright face test stimuli using the same adaptor stimuli. The results were also identical to those reported in a previous study using inverted face test stimuli (Nemrodov and Itier, 2011). In Experiment 3 all possible adaptor-test combinations between upright face, house, chair and car stimuli were used and no interaction between adaptor and test category, expected in the case of test-specific adaptation, was found. These results demonstrate that the rapid adaptation paradigm does not produce category-specific adaptation effects around 170-200 ms following test stimulus onset, a necessary condition for the interpretation of adaptation results. These results suggest the rapid categorical adaptation paradigm does not work.

The role of eyes in early face processing: a rapid adaptation study of the inversion effect.

The current study employed a rapid adaptation procedure to test the neuronal mechanisms of the face inversion effect (FIE) on the early face-sensitive event-related potential (ERP) component N170. Five categories of face-related stimuli (isolated eyes, isolated mouths, eyeless faces, mouthless faces, and full faces) and houses were presented in upright and inverted orientations as adaptors for inverted full face test stimuli. Strong adaptation was found for all face-related stimuli except mouths. The adaptation effect was larger for inverted than upright stimuli, but only when eyes were present. These results underline an important role of eyes in early face processing. A mechanism of eye-dependent orientation sensitivity during the structural encoding stage of faces is proposed.

ERP evidence of hemispheric independence in visual word recognition.

This study examined the capability of the left hemisphere (LH) and the right hemisphere (RH) to perform a visual recognition task independently as formulated by the Direct Access Model (Fernandino, Iacoboni, & Zaidel, 2007). Healthy native Hebrew speakers were asked to categorize nouns and non-words (created from nouns by transposing two middle letters) into man-made and natural categories while their performance and ERPs were recorded. The stimuli were presented parafoveally to the right and left visual fields. As predicted by the Direct Access Model, ERP data showed that both the left hemisphere and right hemisphere were able to differentiate between words and non-words as early as 170 ms post-stimulus; these results were significant only for the contralaterally presented stimuli. The N1 component, which is considered to reflect orthographic processing, was larger in both hemispheres in response to the contralateral than the ipsilateral presented stimuli. This finding provides evidence for the RH capability to access higher level lexical information at the early stages of visual word recognition, thus lending weight to arguments for the relatively independent nature of this process.

Committing driving violations: an observational study comparing city, town and village.

INTRODUCTION: This article compares observed driving behavior in a city, a town, and a village. METHOD: Unobtrusive observations were made at intersections in each residential type. Five violation types were observed: (a) not wearing a seat belt (seat belt violation); (b) not using a safety seat for a child (safety seat violation for children); (c) not using a speaker while speaking on the phone (on-phone violation); (d) failing to comply with a 'give way' sign ('give way' sign violation); and (e) stopping in an undesignated area (undesignated stop violation). It was expected that in accordance with the anonymity hypothesis that the bigger residential areas' rate of traffic violations would be higher. The effects of the residential type, drivers' gender, and age were assessed using the multiple regression model. The stepwise method of evaluation was employed. The model converged on step 3 (Adjusted R square=0.039). Residential type and gender contributed significantly to the model. RESULTS: Consistent with prior research, male drivers committed more violations than female drivers. Chi-square analyses were used to test the distribution of violations by the settlement types. Overall, more drivers committed violations in the two small residential areas than in the city, with 30% of city drivers, 43% of town drivers, and 51% of village drivers committing at least one violation (chi2 (2)=37.65, p<0.001). Moreover, in the town and the village, a combination of one or more violations was committed more often than in the city(chi2 (1)=34.645, p<0.001). Accordingly, more drivers committed violations in the two small settlements (48.4%) than in the city (30.6%). Possible explanations for the observed results were provided in the Discussion section. IMPACT ON INDUSTRY: The conclusions of this paper are that drivers in small villages tend to disobey traffic laws. Therefore, efforts have to be made in companies to take this issue in consideration while running fleets in companies located in small places far from the center.

Fear and danger appraisals of a road-crossing scenario: a developmental perspective.

Children's actual performance of visual timing task is possibly deficient, and road-crossing training programs focusing on visual timing elements result in questionable improvement in performance. The present study focused on conceptual, rather than perceptual, examination of the visual timing elements of distance and speed, as integrated into appraisals of risks related to a traffic scenario. Preschool children, third-grade children and adults appraised pedestrian fear and danger associated with four scenarios conceptually depicted using a table-top model. Each scenario described either a child or an adult pedestrian approached by a vehicle at various distances (near/far) and speeds (slow/fast). Results suggest that whereas the adult subjects integrated the danger and fear appraisals by giving separate weights to both distance and speed concepts, preschoolers failed to properly realize the danger associated with speed, and third-graders failed to integrate both concepts in their appraisals. In addition, children seem to be unaware of their underprivileged pedestrian status compared to adult pedestrians, as evidenced by similar appraisal patterns for both pedestrian age groups. The safety implications of these findings are discussed.

Yielding behavior of Israeli drivers: interaction of age and sex.

The main objective of the present study was to explore the yielding behavior of Israeli drivers. A series of observations were carried out at a busy crosswalk during rush hour to determine the association between demographic factors, i.e., the sex and age of both pedestrians and drivers and the rate of compliance with yielding regulations. The rate of yielding observed did not exceed 53%. Drivers within the 26-50 age range, excluding other age groups, tended to exhibit a higher yielding rate towards the members of their own age group.