Modulating Driver Alertness via Ambient Olfactory Stimulation: A Wearable Electroencephalography Study.

Poor alertness levels and related changes in cognitive efficiency are common when performing monotonous tasks such as extended driving. Recent studies have investigated driver alertness decrement and possible strategies for modulating alertness with the goal of improving reaction times to safety critical events. However, most studies rely on subjective measures in assessing alertness changes, while the use of olfactory stimuli, which are known to be strong modulators of cognitive states, has not been commensurately explored in driving alertness settings. To address this gap, in the present study we investigated the effectiveness of olfactory stimuli in modulating the alertness state of drivers and explored the utility of electroencephalography (EEG) in developing objective brain-based tools for assessing the resulting changes in cortical activity. Olfactory stimulation induced a significant differential effect on braking reaction time. The corresponding effect to the cortical activity was characterized using EEG-derived metrics and the devised machine learning framework yielded a high discriminating accuracy (92.1%). Furthermore, neural activity in the alpha frequency band was found to be significantly associated with the observed drivers' behavioral changes. Overall, our results demonstrate the potential of olfactory stimuli to modulate the alertness state and the efficiency of EEG in objectively assessing the resulting cognitive changes.

Odor Pleasantness Modulates Functional Connectivity in the Olfactory Hedonic Processing Network.

Olfactory hedonic evaluation is the primary dimension of olfactory perception and thus central to our sense of smell. It involves complex interactions between brain regions associated with sensory, affective and reward processing. Despite a recent increase in interest, several aspects of olfactory hedonic evaluation remain ambiguous: uncertainty surrounds the communication between, and interaction among, brain areas during hedonic evaluation of olfactory stimuli with different levels of pleasantness, as well as the corresponding supporting oscillatory mechanisms. In our study we investigated changes in functional interactions among brain areas in response to odor stimuli using electroencephalography (EEG). To this goal, functional connectivity networks were estimated based on phase synchronization between EEG signals using the weighted phase lag index (wPLI). Graph theoretic metrics were subsequently used to quantify the resulting changes in functional connectivity of relevant brain regions involved in olfactory hedonic evaluation. Our results indicate that odor stimuli of different hedonic values evoke significantly different interaction patterns among brain regions within the olfactory cortex, as well as in the anterior cingulate and orbitofrontal cortices. Furthermore, significant hemispheric laterality effects have been observed in the prefrontal and anterior cingulate cortices, specifically in the beta ((13-30) Hz) and gamma ((30-40) Hz) frequency bands.

Multilayer Network Framework Reveals Cross-Frequency Coupling Hubs in Cortical Olfactory Perception.

Olfactory perception is shaped by dynamic in-teractions among networks of widely distributed brain regions involved in several neurocognitive processes. However, the neural mechanisms that enable effective coordination and integrative processing across these brain regions, which have different functions and operating characteristics, are not yet fully understood. In this study we use electroencephalography (EEG) signals and a multilayer network formalism to model cross-frequency coupling across the brain and identify brain regions that operate as connecting hubs, thus facilitating inte-grative function. To this goal, we investigate α-γ coupling and θ-γ coupling during exposure to olfactory stimuli of different pleasantness levels. We found that a wider distributed network of hubs emerges in the higher pleasantness condition and that significant differences in the hub connectivity are located in the middle frontal and central regions. Our results indicate the consistent functional role that γ band activity plays in information integration in olfactory perception.

Objective assessment of trait attentional control predicts driver response to emergency failures of vehicular automation.

With the advent of autonomous driving, the issue of human intervention during safety-critical events is an urgent topic of research. Supervisory monitoring, taking over vehicle control during automation failures and then bringing the vehicle to safety under time pressure are cognitively demanding tasks that pose varying difficulties across the driving population. This underpins a need to investigate individual differences (i.e., how people differ in their dispositional traits) in driver responses to automation system limits, so that autonomous vehicle design can be tailored to meet the safety-critical needs of higher-risk drivers. However, few studies thus far have examined individual differences, with self-report measures showing limited ability to predict driver takeover performance. To address this gap, the present study explored the utility of an established brain activity-based objective index of trait attentional control (frontal theta/beta ratio; TBR) in predicting driver interactions with conditional automation. Frontal TBR predicted drivers' average takeover reaction time, as well as the likelihood of accident after takeover. Moving towards practical applications, this study also demonstrated the utility of streamlined estimates of frontal TBR measured from the forehead electrodes and from a single crown electrode, with the latter showing better fidelity and predictive value. Overall, TBR is behaviourally relevant, measurable with minimal sensors and easily computable, rendering it a promising candidate for practical and objective assessment of drivers' neurocognitive traits that contribute to their AV driving readiness.

Reconstructing EOG From EEG Timeseries: A Spatial Filtering Approach.

Unobtrusive mental state monitoring based on neurosphysiological signals has seen thriving developments over the past decade, with a wide area of applications, from rehabilitation to neuroergonomics and neuromarketing. Particularly, electroencephalography (EEG) and electrooculography (EOG) have been popular techniques to obtain cognitive-relevant biosignals. However, current wearable systems may still pose practical inconvenience, motivating further interest to integrate EOG+EEG recording into streamlined frontal-only sensor montages with sufficient signal fidelity. We propose, here, a spatial filtering approach to reliably extract EOG signals from a reduced set of frontal EEG electrodes, placed on non-hair-bearing (NHB) areas. Within a common signal analytic framework, two distinct schemes are examined. The one is based on standard linear least squares (LLS) and the other on Least Absolute Shrinkage and Selection Operator (LASSO). Both schemes are data-driven techniques, require a small amount of training data, and lead to reliable estimators of EOG activity from EEG signals. The LASSO-based technique, in addition, provides guidelines that generalize well across subjects. Using experimental data, we provide some empirical evidence that our estimators can replace the actual EOG signals in algorithmic pipelines that automatically detect oculographic events, like blinks and saccades.

Community Analysis of Brain Functional Networks Reveals Systems-Level Integration in Olfactory Hedonic Perception.

Olfactory hedonic perception involves complex interplay among an ensemble of neurocognitive systems implicated in sensory, affective and reward processing. However, the mechanisms of these inter-system interactions have yet to be well-characterized. Here, we employ directed functional connectivity networks estimated from source-localized EEG to uncover how brain regions across the olfactory, emotion and reward systems integrate organically into cross-system communities. Using the integration coefficient, a graph theoretic measure, we quantified the effect of exposure to fragrance stimuli of different hedonic values (high vs low pleasantness levels) on inter-systems interactions. Our analysis focused on beta band activity (13-30 Hz), which is known to facilitate integration of cortical areas involved in sensory perception. Higher-pleasantness stimuli induced elevated integration for the reward system, but not for the emotion and olfactory systems. Furthermore, the nodes of reward system showed more outward connections to the emotion and olfactory systems than inward connections from the respective systems. These results suggest the centrality of the reward system-supported by beta oscillations-in actively coordinating multi-system interactivity to give rise to hedonic experiences during olfactory perception.

Wearable EEG Entropy and Spectral Measures for Classification of Consumer Reward-based Evaluation of Odor Stimuli.

Consumer neuroscience is a rapidly emerging field, with the ability to detect consumer attitudes and states via real-time passive technologies being highly valuable. While many studies have attempted to classify consumer emotions and perceived pleasantness of olfactory products, no known machine learning approach has yet been developed to directly predict consumer reward-based decision-making, which has greater behavioral relevance. In this proof-of-concept study, participants indicated their decision to have fragrance products repeated after fixed exposures to them. Single-trial power spectral density (PSD) and approximate entropy (ApEn) features were extracted from EEG signals recorded using a wearable device during fragrance exposures, and served as subject-independent inputs for 4 supervised learning algorithms (kNN, Linear-SVM, RBF- SVM, XGBoost). Using a cross-validation procedure, kNN yielded the best classification accuracy (77.6%) using both PSD and ApEn features. Acknowledging the challenging prospects of single-trial classification of high-order cognitive states especially with wearable EEG devices, this study is the first to demonstrate the viability of using sensor-level features towards practical objective prediction of consumer reward experience.

Repetition blindness for words and pictures: A failure to form stable type representations?

Repetition blindness (RB) is the failure to detect and report a repeated item during rapid serial visual presentation (RSVP). The RB literature reveals consistent and robust RB for word stimuli, but somewhat variable RB effects for pictorial stimuli. We directly compared RB for object pictures and their word labels, using exactly the same procedure in the same participants. Experiment 1 used a large pool of stimuli that only occurred once during the experiment and found significant RB for words, but significant repetition facilitation for pictures. These differential repetition effects were replicated when the task required participants to only report the last item of the stream. Experiment 2 used a small pool of stimuli presented several times throughout the experiment. Significant RB was found for both words and pictures, although it was more pronounced for words. These findings present a challenge to the token individuation hypothesis (Kanwisher, Cognition, 27, 117-143, 1987) and suggest that RB is more likely to be due to a difficulty in establishing a robust type representation. We propose that an experimental context that contains high levels of overlap in visual features (e.g., letters in the case of words, visual fragments in the case of repeatedly presented pictures) may prevent the formation of distinct object-level episodic representations, resulting in RB.

Olfactory-induced Positive Affect and Autonomic Response as a Function of Hedonic and Intensity Attributes of Fragrances.

Olfactory perception is intrinsically tied to emotional processing, in both behavior and neurophysiology. Despite advances in olfactory-affective neuroscience, it is unclear how separate attributes of odor stimuli contribute to olfactoryinduced emotions, especially within the positive segment of the hedonic dimension to avoid potential cross-valence confounds. In this study, we examined how pleasantness and intensity of fragrances relate to different grades of positive affect. Our results show that greater odor pleasantness and intensity are independently associated with stronger positive affect. Pleasantness has a greater influence than intensity in evoking a positive vs. neutral affect, whereas intensity is more impactful than pleasantness in evoking an extreme positive vs. positive response. Autonomic response, as assessed by the galvanic skin response (GSR) was found to decrease with increasing pleasantness but not intensity. This clarifies how olfactory and affective processing induce significant downstream effects in peripheral physiology and self-reported affective experience, pertinent to the thriving field of olfactory neuromarkerting.

Sensory Feedback in Upper Limb Amputees Impacts Cortical Activity as Revealed by Multiscale Connectivity Analysis.

Sensory feedback in upper limb amputees is crucial for improving movement decoding and also to enhance embodiment of the prosthetic limb. Recently, an increasing number of invasive and noninvasive solutions for sensory stimulation have demonstrated the capability of providing a range of sensations to upper limb amputees. However, the cortical impact of restored sensation is not clearly understood. Particularly, understanding the cortical connectivity changes at multiple scales (nodal and modular) in response to sensory stimulation, can reveal crucial information on how amputees brain process the sensory stimuli. Using Electroencephalography (EEG) signals, we compared the cortical connectivity network in response to sensory feedback provided by targeted transcutaneous electrical nerve stimulation (tTENS) in an upper limb amputee during phantom upper limb movements. We focused our cortical connectivity analysis on four functional modules comprising of 20 brain regions that are primarily associated with a visually guided motor task (visual, motor, somatosensory and multisensory integration (MI)) used in this study. At the modular level, we observed that the hubness (a graph theoretic measure quantifying the importance of brain regions in integrating brain function) of the motor module decreases whereas that of the somatosensory module increases in presence of tTENS feedback. At the nodal level, similar observations were made for the visual and MI regions. This is the first work to reveal the impact of sensory feedback at multiple scales in the cortex of amputees in response to sensory stimulation.

Towards machine to brain interfaces: sensory stimulation enhances sensorimotor dynamic functional connectivity in upper limb amputees.

OBJECTIVE: Recent development of sensory stimulation techniques demonstrates the ability to elicit touch-like phantom sensations in upper limb amputees. The cortical processing of this phantom sensation and the corresponding influences on sensorimotor functional connectivity have not been studied. We hypothesize that sensory stimulation has a profound impact on the sensorimotor cortical functional interactions, which will be uncovered by dynamic functional connectivity (dFC) analysis of amputees' electroencephalogram (EEG) recordings. APPROACH: We investigated dFC between cortical areas associated with somatosensory, motor, visual, and multisensory processing functions using EEG signals. We applied dFC to the EEG of two amputees performing hand movements with and without sensory stimulation and compared the results with those from three able-bodied subjects. We quantified the changes due to sensory stimulation using dFC metrics, namely temporal distance, number of connection paths, temporal global and local efficiencies, and clustering coefficient. MAIN RESULTS: We show a significant effect of sensory stimulation on functional connectivity in the amputee brains, with notable facilitation on multisensory processing among the cortical systems involved in sensorimotor processing. The dFC metrics reveal that sensory stimulation enhances the speed of information transfer (shown by decreases in temporal distance) and the number of connection paths between the brain systems involved in sensorimotor processing, including primary somatosensory and motor, and higher order processing regions. SIGNIFICANCE: This is the first work to reveal dynamic communication between somatosensory, motor, and higher order processing regions in the cortex of amputees in response to sensory stimulation. We believe that our work provides crucial insights into the cortical impact of sensory stimulation in amputees, which may lead to the design of personalized brain-informed sensory feedback paradigms. This in turn may lead to building novel Machine to Brain Interfaces involving sensory feedback and the resultant enhanced motor performance.

Associatively-Mediated Suppression of Corticospinal Excitability: A Transcranial Magnetic Stimulation (TMS) Study.

Response inhibition - the suppression of prepotent behaviours when they are inappropriate - has been thought to rely on executive control. Against this received wisdom, it has been argued that external cues repeatedly associated with response inhibition can come to trigger response inhibition automatically without top-down command. The current project endeavoured to provide evidence for associatively-mediated motor inhibition. We tested the hypothesis that stop-associated stimuli can, in a bottom-up fashion, directly activate inhibitory mechanisms in the motor cortex. Human subjects were first trained on a stop-signal task. Once trained, the subjects received transcranial magnetic stimulation applied over their primary motor cortex during passive observation of either the stop signal (i.e. without any need to stop a response) or an equally familiar control stimulus never associated with stopping. Analysis of motor-evoked potentials showed that corticospinal excitability was reduced during exposure to the stop signal, which likely involved stimulus-driven activation of intracortical GABAergic interneurons. This result provides evidence that, through associative learning, stop-associated stimuli can engage local inhibitory processes at the level of the motor cortex.

The partial-reinforcement extinction effect does not result from reduced sensitivity to nonreinforcement.

Five experiments used a magazine approach paradigm with rats to investigate whether learning about nonreinforcement is impaired in the presence of a conditioned stimulus (CS) that had been partially reinforced (PRf). Experiment 1 trained rats with a PRf CS and a continuously reinforced (CRf) CS, then extinguished responding to both CSs presented together as a compound. Probe trials of each CS presented alone revealed that extinction was slower for the PRf CS than the CRf CS, despite being extinguished in compound. In Experiment 2, a CRf light was extinguished in compound with either a CRf CS or a PRf CS that had been matched for overall reinforcement rate. Responding to the light extinguished at the same rate regardless of the reinforcement schedule of the other CS. Experiment 3 replicated this result with a PRf light. Thus, we found no evidence that a PRf CS impairs extinction of another CS presented at the same time. Experiments 4 and 5 extended this approach to study the acquisition of conditioned inhibition by training an inhibitor in compound with either a PRf or CRf excitatory CS. The reinforcement schedule of the excitatory CS had no effect on the acquisition of inhibition. In sum, conditioning with a PRf schedule slows subsequent extinction of that CS but does not affect learning about the nonreinforcement of other stimuli presented at the same time. We conclude that the Partial Reinforcement Extinction Effect is not attributable to a decrease in sensitivity to nonreinforcement following presentation of a PRf CS. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Semantic repetition blindness and associative facilitation in the identification of stimuli in rapid serial visual presentation.

Repetition blindness (RB) is the inability to detect both instances of a repeated stimulus during rapid serial visual presentation (RSVP). Prior work has demonstrated RB for semantically related critical items presented as pictures, but not for word stimuli. It is not known whether the type of semantic relationship between critical items (i.e., conceptual similarity or lexical association) determines the manifestation of semantically mediated RB, or how this is affected by the format of the stimuli. These questions provided the motivation for the present study. Participants reported items presented in picture or word RSVP streams in which critical items were either low-associate category coordinates (horse-camel), high-associate noncoordinates (horse-saddle), or unrelated word pairs (horse-umbrella). Report accuracy was reduced for category coordinate critical items only when they were presented in pictorial form; accuracy for coordinate word pairs did not differ from that of their unrelated counterparts. Associated critical items were reported more accurately than unrelated critical items in both the picture and word versions of the task. We suggest that semantic RB for pictorial stimuli results from intracategory interference in the visuosemantic space; words do not reliably suffer from semantic RB because they do not necessitate semantic mediation to be reported successfully. Conversely, the associative facilitation observed in both picture and word versions of the task reflects the spread of activation between the representations of associates in the lexical network.