Scalp current density mapping: value and estimation from potential data

Decoding the content of working memory in school-aged children

Developmental improvements in working memory (WM) maintenance predict many real-world outcomes, including educational attainment. It is thus critical to understand which WM mechanisms support these behavioral improvements, and how WM maintenance strategies might change through development. One challenge is that specific WM neural mechanisms cannot easily be measured behaviorally, especially in a child population. However, new multivariate decoding techniques have been designed, primarily in adult populations, that can sensitively decode the contents of WM. The goal of this study was to deploy multivariate decoding techniques known to decode memory representations in adults to decode the contents of WM in children. We created a simple computerized WM game for children, in which children maintained different categories of information (visual, spatial or verbal). We collected electroencephalography (EEG) data from 20 children (7-12-year-olds) while they played the game. Using Multivariate Pattern Analysis (MVPA) on children's EEG signals, we reliably decoded the category of the maintained information during the sensory and maintenance period. Across exploratory reliability and validity analyses, we examined the robustness of these results when trained on less data, and how these patterns generalized within individuals throughout the testing session. Furthermore, these results matched theory-based predictions of WM across individuals and across ages. Our proof-of-concept study proposes a direct and age-appropriate potential alternative to exclusively behavioral WM maintenance measures in children. Our study demonstrates the utility of MVPA to measure and track the uninstructed representational content of children's WM. Future research could use our technique to investigate children's WM maintenance and strategies.

The Role of Stimuli-Driven and Goal-Driven Attention in Shopping Decision-Making Behaviors-An EEG and VR Study

The human attention system, similar to other networks in the brain, is of a complex nature. At any moment, our attention can shift between external and internal stimuli. In this study, we aimed to assess three EEG-based measures of attention (Power Spectral Density, Connectivity, and Spectral Entropy) in decision-making situations involving goal-directed and stimulus-driven attention using a Virtual Reality supermarket. We collected the EEG data of 29 participants in 2 shopping phases, planned and unplanned purchases. The three mentioned features were extracted and a statistical analysis was conducted. We evaluated the discriminatory power of these features using an SVM classifier. The results showed a significant (p-value < 0.001) increase in theta power over frontal, central, and temporal lobes for the planned purchase phase. There was also a significant decrease in alpha power over frontal and parietal lobes in the unplanned purchase phase. A significant increase in the frontoparietal connectivity during the planned purchase was observed. Additionally, an increase in spectral entropy was observed in the frontoparietal region for the unplanned purchase phase. The classification results showed that spectral entropy has the highest discriminatory power. This study can provide further insights into the attentional behaviors of consumers and how their type of attentional control can affect their decision-making processes.

The temporal dynamics of the Stroop effect from childhood to young and older adulthood

The processes involved in the Stroop task/effect are thought to involve conflict detection and resolution stages. Little is known about the evolution of these two components over the lifespan. It is well admitted that children and older adults tend to show longer response latencies than young adults. The present study aims at clarifying the rational of such changes from childhood to adulthood and in aging by comparing the impacted cognitive processes across age groups. More precisely, the aim was to clarify if all processes take more time to be executed, hence implying that longer latencies rely mainly on processing speed or if an additional process lengthens the resolution of the conflict in children and/or older adults. To this aim we recorded brain electrical activity using EEG in school-age children, young and older adults while they performed a classic verbal Stroop task. The signal was decomposed in microstate brain networks, and age groups and conditions were compared. Behavioral results evolved following an inverted U-shaped curve. In children, different brain states from the ones observed in adults were highlighted, both in the conflict detection and resolution time-windows. Longer latencies in the incongruent condition were mainly attributed to an overly increased duration of the microstates involved in the conflict resolution time window. In aging, the same microstate maps were reported for both young and older adult groups. The differences in performances between groups could be explained by a disproportionally long conflict detection phase, even compressing the latest stage of response articulation. These results tend to favor a specific immaturity of the brain networks involved coupled with a slowing of the processes in children, while cognitive decline could be mostly explained by a general slowing.

Lateralization of orthographic processing in fixed-gaze and natural reading conditions

Lateralized processing of orthographic information is a hallmark of proficient reading. However, how this finding obtained for fixed-gaze processing of orthographic stimuli translates to ecologically valid reading conditions remained to be clarified. To address this shortcoming, here we assessed the lateralization of early orthographic processing in fixed-gaze and natural reading conditions using concurrent eye-tracking and EEG data recorded from young adults without reading difficulties. Sensor-space analyses confirmed the well-known left-lateralized negative-going deflection of fixed-gaze EEG activity throughout the period of early orthographic processing. At the same time, fixation-related EEG activity exhibited left-lateralized followed by right-lateralized processing of text stimuli during natural reading. A strong positive relationship was found between the early leftward lateralization in fixed-gaze and natural reading conditions. Using source-space analyses, early left-lateralized brain activity was obtained in lateraloccipital and posterior ventral occipito-temporal cortices reflecting letter-level processing in both conditions. In addition, in the same time interval, left-lateralized source activity was found also in premotor and parietal brain regions during natural reading. While brain activity remained left-lateralized in later stages representing word-level processing in posterior and middle ventral temporal regions in the fixed-gaze condition, fixation-related source activity became stronger in the right hemisphere in medial and more anterior ventral temporal brain regions indicating higher-level processing of orthographic information. Although our results show a strong positive relationship between the lateralization of letter-level processing in the two reading modes and suggest lateralized brain activity as a general marker for processing of orthographic information, they also clearly indicate the need for reading research in ecologically valid conditions to identify the neural basis of visuospatial attentional, oculomotor and higher-level processes specific to natural reading.

Decoding continuous variables from event-related potential (ERP) data with linear support vector regression using the Decision Decoding Toolbox (DDTBOX)

Multivariate classification analysis for event-related potential (ERP) data is a powerful tool for predicting cognitive variables. However, classification is often restricted to categorical variables and under-utilises continuous data, such as response times, response force, or subjective ratings. An alternative approach is support vector regression (SVR), which uses single-trial data to predict continuous variables of interest. In this tutorial-style paper, we demonstrate how SVR is implemented in the Decision Decoding Toolbox (DDTBOX). To illustrate in more detail how results depend on specific toolbox settings and data features, we report results from two simulation studies resembling real EEG data, and one real ERP-data set, in which we predicted continuous variables across a range of analysis parameters. Across all studies, we demonstrate that SVR is effective for analysis windows ranging from 2 to 100 ms, and relatively unaffected by temporal averaging. Prediction is still successful when only a small number of channels encode true information, and the analysis is robust to temporal jittering of the relevant information in the signal. Our results show that SVR as implemented in DDTBOX can reliably predict continuous, more nuanced variables, which may not be well-captured by classification analysis. In sum, we demonstrate that linear SVR is a powerful tool for the investigation of single-trial EEG data in relation to continuous variables, and we provide practical guidance for users.

Taxonomic and thematic semantic relationships in picture naming as revealed by Laplacian-transformed event-related potentials

Semantically related concepts co-activate when we speak. Prior research reported both behavioral interference and facilitation due to co-activation during picture naming. Different word relationships may account for some of this discrepancy. Taxonomically related words (e.g., WOLF-DOG) have been associated with semantic interference; thematically related words (e.g., BONE-DOG) have been associated with facilitation. Although these different semantic relationships have been associated with opposite behavioral outcomes, electrophysiological studies have found inconsistent effects on event-related potentials. We conducted a picture-word interference electroencephalography experiment to examine word retrieval dynamics in these different semantic relationships. Importantly, we used traditional monopolar analysis as well as Laplacian transformation allowing us to examine spatially deblurred event-related components. Both analyses revealed greater negativity (150-250 ms) for unrelated than related taxonomic pairs, though more restricted in space for thematic pairs. Critically, Laplacian analyses revealed a larger negative-going component in the 300 to 500 ms time window in taxonomically related versus unrelated pairs which were restricted to a left frontal recording site. In parallel, an opposite effect was found in the same time window but localized to a left parietal site. Finding these opposite effects in the same time window was feasible thanks to the use of the Laplacian transformation and suggests that frontal control processes are concurrently engaged with cascading effects of the spread of activation through semantically related representations.

Neural dynamics differentially encode phrases and sentences during spoken language comprehension

Human language stands out in the natural world as a biological signal that uses a structured system to combine the meanings of small linguistic units (e.g., words) into larger constituents (e.g., phrases and sentences). However, the physical dynamics of speech (or sign) do not stand in a one-to-one relationship with the meanings listeners perceive. Instead, listeners infer meaning based on their knowledge of the language. The neural readouts of the perceptual and cognitive processes underlying these inferences are still poorly understood. In the present study, we used scalp electroencephalography (EEG) to compare the neural response to phrases (e.g., the red vase) and sentences (e.g., the vase is red), which were close in semantic meaning and had been synthesized to be physically indistinguishable. Differences in structure were well captured in the reorganization of neural phase responses in delta (approximately <2 Hz) and theta bands (approximately 2 to 7 Hz),and in power and power connectivity changes in the alpha band (approximately 7.5 to 13.5 Hz). Consistent with predictions from a computational model, sentences showed more power, more power connectivity, and more phase synchronization than phrases did. Theta–gamma phase–amplitude coupling occurred, but did not differ between the syntactic structures. Spectral–temporal response function (STRF) modeling revealed different encoding states for phrases and sentences, over and above the acoustically driven neural response. Our findings provide a comprehensive description of how the brain encodes and separates linguistic structures in the dynamics of neural responses. They imply that phase synchronization and strength of connectivity are readouts for the constituent structure of language. The results provide a novel basis for future neurophysiological research on linguistic structure representation in the brain, and, together with our simulations, support time-based binding as a mechanism of structure encoding in neural dynamics.

Lateralization of early orthographic processing during natural reading is impaired in developmental dyslexia

Skilled reading requires specialized visual cortical processing of orthographic information and its impairment has been proposed as a potential correlate of compromised reading in dyslexia. However, which stage of orthographic information processing during natural reading is disturbed in dyslexics remains unexplored. Here we addressed this question by simultaneously measuring the eye movements and EEG of dyslexic and control young adults during natural reading. Isolated meaningful sentences were presented at five inter-letter spacing levels spanning the range from minimal to extra-large spacing, and participants were instructed to read the text silently at their own pace. Control participants read faster, performed larger saccades and shorter fixations compared to dyslexics. While reading speed peaked around the default letter spacing, saccade amplitude increased and fixation duration decreased with the increase of letter spacing in both groups. Lateralization of occipito-temporal fixation-related EEG activity (FREA) was found in three consecutive time intervals corresponding to early orthographic processing in control readers. Importantly, the lateralization in the time range of the first negative left occipito-temporal FREA peak was specific for first fixations and exhibited an interaction effect between reading ability and letter spacing. The interaction originated in the significant decrease of FREA lateralization at extra-large compared to default letter spacing in control readers and the lack of lateralization in both letter spacing conditions in the case of dyslexics. These findings suggest that expertise-driven hemispheric functional specialization for early orthographic processing thought to be responsible for letter identity extraction during natural reading is compromised in dyslexia.

Electrophysiological Evidence of Enhanced Auditory Retrieval in Musically Trained Children

Abstract. Musical practice enhances auditory processing in children as related to pitch perception or tonal discrimination. The purpose of this study was to examine whether these benefits also occur in auditory working memory by influencing its neural substrates. Two groups of children aged between 7 and 11 years old were compared using an auditory retrieval task with three conditions: frequency retrieval, duration retrieval, and control. Musician children had weekly private violin or cello lessons for at least 14 months, whereas non-musician children had no musical training. Results showed that musicians’ scores on the Gordon’s Primary Measure of Music Audiation test were significantly higher than non-musicians’ scores in the rhythm and tone conditions. On memory tasks, musicians outperformed non-musicians in frequency retrieval but not in duration retrieval. Differences in retrieval performance were associated with a larger P200-like waveform over frontal sites in musicians and a larger N400-like waveform over centro-parietal sites in non-musicians. A source current density analysis revealed differences in frontal activities between musicians and non-musicians, suggesting that musical training influenced the neural mechanisms supporting auditory retrieval in children. These results are in agreement with previous studies that showed a better auditory memory in musicians. Furthermore, they suggest that in children, the effect of musical training can be strong enough to positively influence higher-order auditory memory processes such as active retrieval, as well as their neural correlates.

Learning spatial filters from EEG signals with Graph Signal Processing methods

In this paper, we propose to learn a spatial filter directly from Electroencephalography (EEG) signals using graph signal processing tools. We combine a graph learning algorithm with a high-pass graph filter to remove spatially large signals from the raw data. This approach increases topographical localization, and attenuates volume-conducted features. We empirically show that our method gives similar results that the surface Laplacian in the noiseless case while being more robust to noise or defective electrodes.Clinical relevance- The proposed method is an alternative to the surface Laplacian filter that is commonly used for processing EEG signals. It could be used in cases where this standard approach does not provide satisfying results (low signal-to-noise ratios due to a low number of epochs, defective electrodes). This could be particularly interesting in case of an electrode defect, as it can happen in clinical practice.

Visualizing spatial differences in corneal electroretinogram potentials using a three-dimensional surface spline

Objective. The spatial distribution of activity at the retina determines the spatial distribution of electroretinogram potentials at the cornea. Here a three-dimensional surface spline method is evaluated for interpolating corneal potentials between measurement points in multi-electrode electroretinography (meERG) data sets.Approach. 25-channel meERG responses were obtained from rat eyes before and after treatment to create local lesions. A 3rd order surface spline was used to interpolate meERG values resulting in smooth color-coded maps of corneal potentials. Potential maps were normalized using standard score values. Pre- and post-treatment responses were characterized by spatial standard deviation and by difference-from-normal plots.Main results. The spatial standard deviation for eyes with local lesions were significantly higher than for healthy eyes. The 3rd order spline resulted in well-behaved corneal potential maps that maintained low error rate when up to 30% of recording channels were excluded from analysis. Post-normalization, responses could be combined within experimental groups, and individual eyes with lesions were clearly distinguished from the healthy-eye mean response. A 3rd order surface spline is an acceptable means of interpolating meERG potentials to create corneal potential maps. The spatial standard deviation is more sensitive to local dysfunction than absolute amplitudes.Significance. This work demonstrates solutions to key challenges in the recording and analysis of meERG responses: visualization, normalization, channel loss, and identification of abnormal responses. Continued development of the meERG technique is relevant to research and clinical applications, especially where local dysfunction (early progressive disease) or local therapeutic effect (subretinal injection) is of interest.

Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication

During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. Most studies have investigated emotions using functional magnetic resonance imaging (fMRI), including the real-time application in neurofeedback training. However, the electroencephalogram (EEG) is a more suitable tool for therapeutic application. Our study aims at establishing a method to classify discrete complex emotions (e.g., tenderness and anguish) elicited through a near-immersive scenario that can be later used for EEG-neurofeedback. EEG-based affective computing studies have mainly focused on emotion classification based on dimensions, commonly using passive elicitation through single-modality stimuli. Here, we integrated both passive and active elicitation methods. We recorded electrophysiological data during emotion-evoking trials, combining emotional self-induction with a multimodal virtual environment. We extracted correlational and time-frequency features, including frontal-alpha asymmetry (FAA), using Complex Morlet Wavelet convolution. Thinking about future real-time applications, we performed within-subject classification using 1-s windows as samples and we applied trial-specific cross-validation. We opted for a traditional machine-learning classifier with low computational complexity and sufficient validation in online settings, the Support Vector Machine. Results of individual-based cross-validation using the whole feature sets showed considerable between-subject variability. The individual accuracies ranged from 59.2 to 92.9% using time-frequency/FAA and 62.4 to 92.4% using correlational features. We found that features of the temporal, occipital, and left-frontal channels were the most discriminative between the two emotions. Our results show that the suggested pipeline is suitable for individual-based classification of discrete emotions, paving the way for future personalized EEG-neurofeedback training.

The interplay between domain-general and domain-specific mechanisms during the time-course of verbal associative learning: An event-related potential study

Humans continuously learn new information. Here, we examined the temporal brain dynamics of explicit verbal associative learning between unfamiliar items. In the first experiment, 25 adults learned object-pseudoword associations during a 5-day training program allowing us to track the N400 dynamics across learning blocks within and across days. Successful learning was accompanied by an initial frontal N400 that decreased in amplitude across blocks during the first day and shifted to parietal sites during the last training day. In Experiment 2, we replicated our findings with 38 new participants randomly assigned to a consistent learning or an inconsistent learning group. The N400 amplitude modulations that we found, both within and between learning sessions, are taken to reflect the emergence of novel lexical traces even when learning concerns items for which no semantic information is provided. The shift in N400 topography suggests that different N400 neural generators may contribute to specific word learning steps through a balance between domain-general and language-specific mechanisms.

Towards a Functional Neuromarker of Impulsivity: Feedback-Related Brain Potential during Risky Decision-Making Associated with Self-Reported Impulsivity in a Non-Clinical Sample

Risk-taking is part of the multidimensional nature of impulsivity, consisting of an active engagement in behaviors or choices with potentially undesirable results, with probability as the cost for an expected reward. In order to understand the neurophysiological activity during risky behavior and its relationship with other dimensions of impulsivity, we have acquired event-related-potential (ERP) data and self-reported impulsivity scores from 17 non-clinical volunteers. They underwent high-resolution electroencephalography (HR-EEG) combined with an adapted version of the Balloon Analogue Risk Task (BART), and completed the Barratt Impulsiveness Scale (BIS-10) and the Urgency, Premeditation, Perseverance, Sensation Seeking, Impulsive Behavior Scale (UPPS). The ERP components were sensitive to valence (FRN, P300) and risk/reward magnitude (SPN, RewP). Our main finding evidenced a positive correlation between the amplitude of the P300 component following positive feedback and both the global UPPS score and the (lack of) perseverance UPPS subscale, significant for several adjacent electrodes. This finding might suggest an adaptive form of impulsive behavior, which could be associated to the reduction on the difference of the P300 amplitude following negative and positive feedback. However, further investigation with both larger clinical and non-clinical samples is required.

Event-Related Potentials (ERP) Indices of Motivation during the Effort Expenditure for Reward Task

Dynamic and temporal facets of the various constructs that comprise motivation remain to be explored. Here, we adapted the Effort Expenditure for Reward Task, a well-known laboratory task used to evaluate motivation, to study the event-related potentials associated with reward processing. The Stimulus Preceding Negativity (SPN) and the P300 were utilized as motivation indicators with high density electroencephalography. The SPN was found to be more negative for difficult choices compared to easy choices, suggesting a greater level of motivation, at a neurophysiological level. The insula, a structure previously associated with both effort discounting and prediction error, was concomitantly activated during the generation of the SPN. Processing a gain significantly altered the amplitude of the P300 compared to an absence of gain, particularly on centroparietal electrodes. One of the generators of the P300 was located on the vmPFC, a cerebral structure involved in the choice between two positive results and their predictions, during loss processing. Both the SPN and the P300 appear to be reliable neural markers of motivation. We postulate that the SPN represents the strength of the motivational level, while the P300 represents the impact of motivation on updating memories of the feedback.

Disruption of gamma-delta relationship related to working memory deficits in first-episode psychosis

Working memory (WM) deficits constitute a core symptom of schizophrenia. Inadequacy of WM maintenance in schizophrenia has been reported to reflect abnormalities in the excitation/inhibition (E/I) balance between pyramidal neurons and parvalbumin basket cells, which may explain alterations of the dynamics of gamma and delta oscillations. To address this issue, we assessed event-related gamma (35-45 Hz) and delta (0.5-4 Hz) oscillatory responses in a visual n-back WM task in patients with first-episode psychosis (FEP) and healthy controls (HC). Periodicity analyses of oscillations were computed to explore the relationship between the psychiatric status and the WM load-related processes reflected by each frequency range. The correspondence between nested delta-gamma oscillations was estimated to assess the strength of the frontal E/I balance. In HC, gamma oscillations were synchronized by the stimulus in a 50-150 ms time range for all tasks, and periodicity of the delta cycle was comparable between the tasks. In addition, synchronization of gamma oscillations in HC occurred at the maximal descending phase of the delta cycle half-period, supporting the coexistence of delta-nested gamma oscillations. Compared with controls, FEP patients showed a lack of gamma synchronization independently of the nature of the task, and the period of delta oscillation increased significantly with the difficulty of the WM task. We thus demonstrated in FEP an inability to encode multiple items in short-term memory associated with abnormalities in the relationship between oscillations related to the difficulty of the WM task. These results argue in favor of a dysfunction of the E/I balance in psychosis.

Error processing and mindfulness meditation in female students

Mindfulness seems to have an impact on error processing in simple response tasks, as former studies reported both an effect of mindfulness meditation on, as well as relationships to trait mindfulness with behavioral and neural correlates of error processing. However, the results of these studies showed no consistent pattern. To dismantle some of these findings, this study investigated the impact in female students of a four-week, smartphone-based mindfulness training program (N = 22) in comparison with an active control group that did progressive muscle relaxation (PMR; N = 20). In addition to behavioral data, two error-related components of the event-related potential were measured with electroencephalogram while performing a combination of a modified Simon task and an error detection paradigm, namely error-related negativity and error positivity. Mindfulness meditation did not have a differential effect on error components in comparison to PMR. For both, we found a reduction of stress symptoms, an increase in mindfulness and an increase in error positivity.

Efficient but less active monitoring system in individuals with high aggressive predispositions

Aggressive behaviors in pathological and healthy populations have been largely related to poor cognitive control functioning. However, few studies have investigated the influence of aggressive traits (i.e., aggressiveness) on cognitive control. In the current study, we investigated the effects of aggressiveness on cognitive control abilities and particularly, on performance monitoring. Thirty-two participants performed a Simon task while electroencephalography (EEG) and electromyography (EMG) were recorded. Participants were classified as having high and low levels of aggressiveness using the BPAQ questionnaire (Buss and Perry, 1992). EMG recordings were used to reveal three response types by uncovering small incorrect muscular activations in ~15% of correct trials (i.e., partial-errors) that must be distinguished from full-error and pure-correct responses. For these three response types, EEG recordings were used to extract fronto-central negativities indicative of performance monitoring, the error and correct (-related) negativities (ERN/Ne and CRN/Nc). Behavioral results indicated that the high aggressiveness group had a larger congruency effect compared to the low aggressiveness group, but there were no differences in accuracy. EEG results revealed a global reduction in performance-related negativity amplitudes in all the response types in the high aggressiveness group compared to the low aggressiveness group. Interestingly, the distinction between the ERN/Ne and the CRN/Nc components was preserved both in high and low aggressiveness groups. In sum, high aggressive traits do not affect the capacity to self-evaluate erroneous from correct actions but are associated with a decrease in the importance given to one's own performance. The implication of these findings are discussed in relation to pathological aggressiveness.

Neural correlates of reality filtering in schizophrenia spectrum disorder

BACKGROUND

A false sense of reality is a characteristic of schizophrenia spectrum disorders (SSD). Reality confusion may also emanate from posterior orbitofrontal cortex (OFC) lesions, as evident in confabulations that patients act upon and disorientation. This confusion can be measured by repeated runs of a continuous recognition task (CRT): patients increase their false positive rate from the second run on, failing to realize that an item is not a repetition within the current run. Correct handling of these stimuli, a faculty called orbitofrontal reality filtering (ORFi), induces a distinct frontal potential at 200-300 ms, the "ORFi potential". Patients with schizophrenia have been reported to fail in this task, too. Here, we explored the electrophysiology of ORFi in SSD.

METHODS

Evoked potentials, source, and connectivity analyses derived from high-density electroencephalograms of 17 patients with SSD and 15 age-matched healthy controls performing two runs of a CRT.

RESULTS

Although the patients obtained normal performance, they did not normally express the frontal potential typical of ORFi between 200 and 300 ms. Coherence analysis demonstrated virtually absent functional connectivity in the theta band within the memory network in this period. Source analysis showed increased activity in left medial temporal and prefrontal regions in patients.

CONCLUSIONS

SSD patients appear to invoke compensatory resources to handle the challenges of reality filtering. An abnormal ORFi potential may be an early biomarker of SSD.

Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review

A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuine sources occur at the micro scale of cell surfaces. Equivalent sources provide identical experimental outcomes over a range of scales and applications. In contrast, each representative source distribution is just one of many possible source distributions that yield similar experimental outcomes. Macro sources ("dipoles") may be defined at the macrocolumn (mm) scale and depend on several features of the micro sources-magnitudes, micro synchrony within columns, and distribution through the cortical depths. These micro source properties are determined by brain dynamics and the columnar structure of cortical tissue. The number of representative sources underlying EEG data depends on the spatial scale of neural tissue under study. EEG inverse solutions (e.g. dipole localization) and high resolution estimates (e.g. Laplacian, dura imaging) have both strengths and limitations that depend on experimental conditions. The proposed theoretical framework informs studies of EEG source localization, source characterization, and low pass filtering. It also facilitates interpretations of brain dynamics and cognition, including measures of synchrony, functional connections between cortical locations, and other aspects of brain complexity.

Human posterior parietal cortex responds to visual stimuli as early as peristriate occipital cortex

Much of what is known about the timing of visual processing in the brain is inferred from intracranial studies in monkeys, with human data limited to mainly noninvasive methods with lower spatial resolution. Here, we estimated visual onset latencies from electrocorticographic (ECoG) recordings in a patient who was implanted with 112 subdural electrodes, distributed across the posterior cortex of the right hemisphere, for presurgical evaluation of intractable epilepsy. Functional MRI prior to surgery was used to determine boundaries of visual areas. The patient was presented with images of objects from several categories. Event-related potentials (ERPs) were calculated across all categories excluding targets, and statistically reliable onset latencies were determined, using a bootstrapping procedure over the single trial baseline activity in individual electrodes. The distribution of onset latencies broadly reflected the known hierarchy of visual areas, with the earliest cortical responses in primary visual cortex, and higher areas showing later responses. A clear exception to this pattern was a robust, statistically reliable and spatially localized, very early response, on the bank of the posterior intraparietal sulcus (IPS). The response in the IPS started nearly simultaneously with responses detected in peristriate visual areas, around 60 ms poststimulus onset. Our results support the notion of early visual processing in the posterior parietal lobe, not respecting traditional hierarchies, and give direct evidence for onset times of visual responses across the human cortex.

Suppression of overlearning in independent component analysis used for removal of muscular artifacts from electroencephalographic records

This paper addresses the overlearning problem in the independent component analysis (ICA) used for the removal of muscular artifacts from electroencephalographic (EEG) records. We note that for short EEG records with high number of channels the ICA fails to separate artifact-free EEG and muscular artifacts, which has been previously attributed to the phenomenon called overlearning. We address this problem by projecting an EEG record into several subspaces with a lower dimension, and perform the ICA on each subspace separately. Due to a reduced dimension of the subspaces, the overlearning is suppressed, and muscular artifacts are better separated. Once the muscular artifacts are removed, the signals in the individual subspaces are combined to provide an artifact free EEG record. We show that for short signals and high number of EEG channels our approach outperforms the currently available ICA based algorithms for muscular artifact removal. The proposed technique can efficiently suppress ICA overlearning for short signal segments of high density EEG signals.

Propofol-induced sedation diminishes the strength of frontal-parietal-occipital EEG network

The level of conscious experience can be effectively and reversibly altered by the administration of sedative agents. Several studies attempted to explore the variations in frontal-parietal network during propofol-induced sedation. However, contradictory outcomes warrant further investigations. In this study, we implemented the Neural Gas algorithm-based delay symbolic transfer entropy (NG-dSTE) for investigation of frontal-parietal-occipital (F-P-O) network using scalp EEG signals recorded during altered levels of consciousness. Our results show significant disruption of the F-P-O network during mild and moderate levels of propofol sedation. In particular, the interaction between frontal and parietal-occipital region is highly disturbed. Moreover, we found measurable effect of sedation on local interactions in the frontal network whereas parietal-occipital network experienced least variations. The results support the conclusion that the connectivity based features can be utilized as reliable biomarker for assessment of sedation levels effectively.

When Wine and Apple Both Help the Production of Grapes: ERP Evidence for Post-lexical Semantic Facilitation in Picture Naming

Background: Producing a word in referential naming requires to select the right word in our mental lexicon among co-activated semantically related words. The mechanisms underlying semantic context effects during speech planning are still controversial, particularly for semantic facilitation which investigation remains under-represented in contrast to the plethora of studies dealing with interference. Our aim is to study the time-course of semantic facilitation in picture naming, using a picture-word "interference" paradigm and event-related potentials (ERPs). Methods: We compared two different types of semantic relationships, associative and categorical, in a single word priming and a double word priming paradigm. The primes were presented visually with a long negative Stimulus Onset Asynchrony (SOA), which is expected to cause facilitation. Results: Shorter naming latencies were observed after both associative and categorical primes, as compared to unrelated primes, and even shorter latencies after two primes. Electrophysiological results showed relatively late modulations of waveform amplitudes for both types of primes (beginning ~330 ms post picture onset with a single prime and ~275 ms post picture onset with two primes), corresponding to a shift in latency of similar topographic maps across conditions. Conclusion: The present results are in favor of a post-lexical locus of semantic facilitation for associative and categorical priming in picture naming and confirm that semantic facilitation is as relevant as semantic interference to inform on word production. The post-lexical locus argued here might be related to self-monitoting or/and to modulations at the level of word-form planning, without excluding the participation of strategic processes.

Dopamine and response selection: an Acute Phenylalanine/Tyrosine Depletion study

The role of dopaminergic system in decision-making is well documented, and evidence suggests that it could play a significant role in response selection processes. The N-40 is a fronto-central event-related potential, generated by the supplementary motor areas (SMAs) and a physiological index of response selection processes. The aim of the present study was to determine whether infraclinical effects of dopamine depletion on response selection processes could be evidenced via alterations of the N-40. We obtained a dopamine depletion in healthy volunteers with the acute phenylalanine and tyrosine depletion (APTD) method which consists in decreasing the availability of dopamine precursors. Subjects realized a Simon task in the APTD condition and in the control condition. When the stimulus was presented on the same side as the required response, the stimulus-response association was congruent and when the stimulus was presented on the opposite side of the required response, the stimulus-response association was incongruent. The N-40 was smaller for congruent associations than for incongruent associations. Moreover, the N-40 was sensitive to the level of dopaminergic activity with a decrease in APTD condition compared to control condition. This modulation of the N-40 by dopaminergic level could not be explained by a global decrease of cerebral electrogenesis, since negativities and positivities indexing the recruitment of the primary motor cortex (anatomically adjacent to the SMA) were unaffected by APTD. The specific sensitivity of N-40 to ATPD supports the model of Keeler et al. (Neuroscience 282:156-175, 2014) according to which the dopaminergic system is involved in response selection.

Simultaneous Reality Filtering and Encoding of Thoughts: The Substrate for Distinguishing between Memories of Real Events and Imaginations?

Any thought, whether it refers to the present moment or reflects an imagination, is again encoded as a new memory trace. Orbitofrontal reality filtering (ORFi) denotes an on-line mechanism which verifies whether upcoming thoughts relate to ongoing reality or not. Its failure induces reality confusion with confabulations and disorientation. If the result of this process were simultaneously encoded, it would easily explain later distinction between memories relating to a past reality and memories relating to imagination, a faculty called reality monitoring. How the brain makes this distinction is unknown but much research suggests that it depends on processes active when information is encoded. Here we explored the precise timing between ORFi and encoding as well as interactions between the involved brain structures. We used high-density evoked potentials and two runs of a continuous recognition task (CRT) combining the challenges of ORFi and encoding. ORFi was measured by the ability to realize that stimuli appearing in the second run had not appeared in this run yet. Encoding was measured with immediately repeated stimuli, which has been previously shown to induce a signal emanating from the medial temporal lobe (MTL), which has a protective effect on the memory trace. We found that encoding, as measured with this task, sets in at about 210 ms after stimulus presentation, 35 ms before ORFi. Both processes end at about 330 ms. Both were characterized by increased coherence in the theta band in the MTL during encoding and in the orbitofrontal cortex (OFC) during ORFi. The study suggests a complex interaction between OFC and MTL allowing for thoughts to be re-encoded while they undergo ORFi. The combined influence of these two processes at 200-300 ms may leave a memory trace that allows for later effortless reality monitoring in most everyday situations.

ERP evidence of distinct processes underlying semantic facilitation and interference in word production

In everyday conversations, we take advantage of lexical-semantic contexts to facilitate speech production, but at the same time, we also have to reduce interference and inhibit semantic competitors. The blocked cyclic naming paradigm (BCNP) has been used to investigate such context effects. Typical results on production latencies showed semantic facilitation (or no effect) during the first presentation cycle, and interference emerging in subsequent cycles. Even if semantic contexts might be just as facilitative as interfering, previous BCNP studies focused on interference, which was interpreted as reflecting lemma selection and self-monitoring processes. Facilitation in the first cycle was rarely considered/analysed, although it potentially informs on word production to the same extent as interference. Here we contrasted the event-related potential (ERP) signatures of both semantic facilitation and interference in a BCNP. ERPs differed between homogeneous and heterogeneous blocks from about 365 msec post picture onset in the first cycle (facilitation) and in an earlier time-window (270 msec post picture onset) in the third cycle (interference). Three different analyses of the ERPs converge towards distinct processes underlying semantic facilitation and interference (post-lexical vs lexical respectively). The loci of semantic facilitation and interference are interpreted in the context of different theoretical frameworks of language production: the post-lexical locus of semantic facilitation involves interactive phonological-semantic processes and/or self-monitoring, whereas the lexical locus of semantic interference is in line with selection through increased lexical competition.

As above, so below? Towards understanding inverse models in BCI

OBJECTIVE

In brain-computer interfaces (BCI), measurements of the user's brain activity are classified into commands for the computer. With EEG-based BCIs, the origins of the classified phenomena are often considered to be spatially localized in the cortical volume and mixed in the EEG. We investigate if more accurate BCIs can be obtained by reconstructing the source activities in the volume.

APPROACH

We contrast the physiology-driven source reconstruction with data-driven representations obtained by statistical machine learning. We explain these approaches in a common linear dictionary framework and review the different ways to obtain the dictionary parameters. We consider the effect of source reconstruction on some major difficulties in BCI classification, namely information loss, feature selection and nonstationarity of the EEG.

MAIN RESULTS

Our analysis suggests that the approaches differ mainly in their parameter estimation. Physiological source reconstruction may thus be expected to improve BCI accuracy if machine learning is not used or where it produces less optimal parameters. We argue that the considered difficulties of surface EEG classification can remain in the reconstructed volume and that data-driven techniques are still necessary. Finally, we provide some suggestions for comparing approaches.

SIGNIFICANCE

The present work illustrates the relationships between source reconstruction and machine learning-based approaches for EEG data representation. The provided analysis and discussion should help in understanding, applying, comparing and improving such techniques in the future.

Back-Projection Cortical Potential Imaging: Theory and Results

Electroencephalography (EEG) is the single brain monitoring technique that is non-invasive, portable, passive, exhibits high-temporal resolution, and gives a directmeasurement of the scalp electrical potential. Amajor disadvantage of the EEG is its low-spatial resolution, which is the result of the low-conductive skull that "smears" the currents coming from within the brain. Recording brain activity with both high temporal and spatial resolution is crucial for the localization of confined brain activations and the study of brainmechanismfunctionality, whichis then followed by diagnosis of brain-related diseases. In this paper, a new cortical potential imaging (CPI) method is presented. The new method gives an estimation of the electrical activity on the cortex surface and thus removes the "smearing effect" caused by the skull. The scalp potentials are back-projected CPI (BP-CPI) onto the cortex surface by building a well-posed problem to the Laplace equation that is solved by means of the finite elements method on a realistic head model. A unique solution to the CPI problem is obtained by introducing a cortical normal current estimation technique. The technique is based on the same mechanism used in the well-known surface Laplacian calculation, followed by a scalp-cortex back-projection routine. The BP-CPI passed four stages of validation, including validation on spherical and realistic head models, probabilistic analysis (Monte Carlo simulation), and noise sensitivity tests. In addition, the BP-CPI was compared with the minimum norm estimate CPI approach and found superior for multi-source cortical potential distributions with very good estimation results (CC >0.97) on a realistic head model in the regions of interest, for two representative cases. The BP-CPI can be easily incorporated in different monitoring tools and help researchers by maintaining an accurate estimation for the cortical potential of ongoing or event-related potentials in order to have better neurological inferences from the EEG.

Single-trial effective brain connectivity patterns enhance discriminability of mental imagery tasks

OBJECTIVE

The majority of the current approaches of connectivity based brain-computer interface (BCI) systems focus on distinguishing between different motor imagery (MI) tasks. Brain regions associated with MI are anatomically close to each other, hence these BCI systems suffer from low performances. Our objective is to introduce single-trial connectivity feature based BCI system for cognition imagery (CI) based tasks wherein the associated brain regions are located relatively far away as compared to those for MI.

APPROACH

We implemented time-domain partial Granger causality (PGC) for the estimation of the connectivity features in a BCI setting. The proposed hypothesis has been verified with two publically available datasets involving MI and CI tasks.

MAIN RESULTS

The results support the conclusion that connectivity based features can provide a better performance than a classical signal processing framework based on bandpass features coupled with spatial filtering for CI tasks, including word generation, subtraction, and spatial navigation. These results show for the first time that connectivity features can provide a reliable performance for imagery-based BCI system.

SIGNIFICANCE

We show that single-trial connectivity features for mixed imagery tasks (i.e. combination of CI and MI) can outperform the features obtained by current state-of-the-art method and hence can be successfully applied for BCI applications.

Differential Recruitment of Parietal Cortex during Spatial and Non-spatial Reach Planning

The planning of goal-directed arm reaching movements is associated with activity in the dorsal parieto-frontal cortex, within which multiple regions subserve the integration of arm- and target-related sensory signals to encode a motor goal. Surprisingly, many of these regions show sustained activity during reach preparation even when target location is not specified, i.e., when a motor goal cannot be unambiguously formed. The functional role of these non-spatial preparatory signals remains unresolved. Here this process was investigated in humans by comparing reach preparatory activity in the presence or absence of information regarding upcoming target location. In order to isolate the processes specific to reaching and to control for visuospatial attentional factors, the reaching task was contrasted to a finger movement task. Functional MRI and electroencephalography (EEG) were used to characterize the spatio-temporal pattern of reach-related activity in the parieto-frontal cortex. Reach planning with advance knowledge of target location induced robust blood oxygenated level dependent and EEG responses across parietal and premotor regions contralateral to the reaching arm. In contrast, reach preparation without knowledge of target location was associated with a significant BOLD response bilaterally in the parietal cortex. Furthermore, EEG alpha- and beta-band activity was restricted to parietal scalp sites, the magnitude of the latter being correlated with reach reaction times. These results suggest an intermediate stage of sensorimotor transformations in bilateral parietal cortex when target location is not specified.

Differences of temporal dynamics and signal complexity of gamma band oscillations in first-episode psychosis during a working memory task

Gamma band oscillations participate in the temporal binding needed to synchronize cortical networks, involved in early sensory and short term memory processes. In earlier studies, alterations of these neurophysiological parameters have been found in psychotic disorders. To date no study has explored the temporal dynamics and signal complexity of gamma band oscillations in first episode psychosis (FEP). To address this issue, gamma band analysis was performed in 15 FEP patients and 18 healthy controls who successfully performed an adapted 2-back working memory task. Multiple linear and logistic regression models were computed to explore the relationship between the cognitive status and gamma oscillation changes over time. Based on regression model results, phase diagrams were constructed and their complexity was estimated using fractal dimension, a mathematical tool that describes shapes as numeric values. When adjusted for gamma values at time lags -3 to -4 ms and -15 to -16 ms, FEP patients displayed significantly higher time-dependent changes than controls, independently of the nature of the task. The present results are consistent with a discoordination of the activity of cortical generators engaged by the stimulus apparition in FEP patients, leading to a global binding deficit. In addition, fractal analysis showing higher complexity of gamma signal, confirmed this deficit. Our results provide evidence for recruitment of supplementary cortical generators as compensating mechanisms and yield further understanding for the pathophysiology cognitive impairments in FEP.

Channel interpolation in TMS-EEG: a quantitative study towards an accurate topographical representation

The co-registration of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a successful technique for causally exploring cortical mechanisms and connections. However, various artefacts could affect TMS-EEG signals. Correct artefacted channels reconstruction is crucial to obtain accurate topographical representation and consequently accurate inverse problem solution, in order to map in a proper way the global brain responses after the stimulation of one particular brain region of interest. In this paper, we discuss the problem of artefacted channels interpolation in TMS-EEG signals. Aim of the study was to investigate two different interpolation methods evaluating their performance in two datasets: one constituted by 19 EEG channels montage (low-density spatial resolution) and the other one by 60 EEG channels montage (high-density spatial resolution). In addition, these evaluations took place in two different contexts of application: after the averaging of TMS Evoked Potentials (TEPs) in a time interval to obtain a global information in the considered range, and at fixed latencies 100 ms and 300 ms after the TMS stimulus. The results showed that the global reconstruction error was lower at fixed latencies for the high-density electrodes spatial resolution montage.

Linking Theoretical Decision-making Mechanisms in the Simon Task with Electrophysiological Data: A Model-based Neuroscience Study in Humans

A current challenge for decision-making research is in extending models of simple decisions to more complex and ecological choice situations. Conflict tasks (e.g., Simon, Stroop, Eriksen flanker) have been the focus of much interest, because they provide a decision-making context representative of everyday life experiences. Modeling efforts have led to an elaborated drift diffusion model for conflict tasks (DMC), which implements a superimposition of automatic and controlled decision activations. The DMC has proven to capture the diversity of behavioral conflict effects across various task contexts. This study combined DMC predictions with EEG and EMG measurements to test a set of linking propositions that specify the relationship between theoretical decision-making mechanisms involved in the Simon task and brain activity. Our results are consistent with a representation of the superimposed decision variable in the primary motor cortices. The decision variable was also observed in the EMG activity of response agonist muscles. These findings provide new insight into the neurophysiology of human decision-making. In return, they provide support for the DMC model framework.

Evaluation of cortical local field potential diffusion in stereotactic electro-encephalography recordings: A glimpse on white matter signal

While there is a strong interest in meso-scale field potential recording using intracranial electroencephalography with penetrating depth electrodes (i.e. stereotactic EEG or S-EEG) in humans, the signal recorded in the white matter remains ignored. White matter is generally considered electrically neutral and often included in the reference montage. Moreover, re-referencing electrophysiological data is a critical preprocessing choice that could drastically impact signal content and consequently the results of any given analysis. In the present stereotactic electroencephalography study, we first illustrate empirically the consequences of commonly used references (subdermal, white matter, global average, local montage) on inter-electrode signal correlation. Since most of these reference montages incorporate white matter signal, we next consider the difference between signals recorded in cortical gray matter and white matter. Our results reveal that electrode contacts located in the white matter record a mixture of activity, with part arising from the volume conduction (zero time delay) of activity from nearby gray matter. Furthermore, our analysis shows that white matter signal may be correlated with distant gray matter signal. While residual passive electrical spread from nearby matter may account for this relationship, our results suggest the possibility that this long distance correlation arises from the white matter fiber tracts themselves (i.e. activity from distant gray matter traveling along axonal fibers with time lag larger than zero); yet definitive conclusions about the origin of the white matter signal would require further experimental substantiation. By characterizing the properties of signals recorded in white matter and in gray matter, this study illustrates the importance of including anatomical prior knowledge when analyzing S-EEG data.

Preventing (impulsive) errors: Electrophysiological evidence for online inhibitory control over incorrect responses

In a rich environment, with multiple action affordances, selective action inhibition is critical in preventing the execution of inappropriate responses. Here, we studied the origin and the dynamics of incorrect response inhibition and how it can be modulated by task demands. We used EEG in a conflict task where the probability of compatible and incompatible trials was varied. This allowed us to modulate the strength of the prepotent response, and hence to increase the risk of errors, while keeping the probability of the two responses equal. The correct response activation and execution was not affected by compatibility or by probability. In contrast, incorrect response inhibition in the primary motor cortex ipsilateral to the correct response was more pronounced on incompatible trials, especially in the condition where most of the trials were compatible, indicating a modulation of inhibitory strength within the course of the action. Two prefrontal activities, one medial and one lateral, were also observed before the response, and their potential links with the observed inhibitory pattern observed are discussed.

Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes

Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected.

High-Resolution Electrogastrogram: A Novel, Noninvasive Method for Determining Gastric Slow-Wave Direction and Speed

Despite its simplicity and noninvasiveness, the use of the electrogastrogram (EGG) remains limited in clinical practice for assessing gastric disorders. Recent studies have characterized the occurrence of spatial gastric myoelectric abnormalities that are ignored by typical approaches relying on time-frequency analysis of single channels. In this paper we present the highresolution (HR) EGG, which utilizes an array of electrodes to estimate the direction and speed of gastric slow-waves. The approach was verified on a forward electrophysiology model of the stomach, demonstrating that an accurate assessment of slow-wave propagation can be made. Furthermore, we tested the methodology on eight healthy adults and calculated propagation directions (181 ± 29 degrees) and speeds (3.7 ± 0.5 mm/s) that are consistent with serosal recordings of slow-waves described in the literature. By overcoming the limitations of current methods, HR-EGG is a fully automated tool that may unveil new classes of gastric abnormalities. This could lead to a better diagnosis of diseases and inspire novel drugs and therapies, ultimately improving clinical outcomes.

Visual processing during natural reading

Reading is a unique human ability that plays a pivotal role in the development and functioning of our modern society. However, its neural basis remains poorly understood since previous research was focused on reading words with fixed gaze. Here we developed a methodological framework for single-trial analysis of fixation onset-related EEG activity (FOREA) that enabled us to investigate visual information processing during natural reading. To reveal the effect of reading skills on orthographic processing during natural reading, we measured how altering the configural properties of the written text by modifying inter-letter spacing affects FOREA. We found that orthographic processing is reflected in FOREA in three consecutive time windows (120–175 ms, 230–265 ms, 345–380 ms after fixation onset) and the magnitude of FOREA effects in the two later time intervals showed a close association with the participants’ reading speed: FOREA effects were larger in fast than in slow readers. Furthermore, these expertise-driven configural effects were clearly dissociable from the FOREA signatures of visual perceptual processes engaged to handle the increased crowding (155–220 ms) as a result of decreasing letter spacing. Our findings revealed that with increased reading skills orthographic processing becomes more sensitive to the configural properties of the written text.

Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes

Conventional electroencephalography with disc electrodes has major drawbacks including poor spatial resolution, selectivity and low signal-to-noise ratio that are critically limiting its use. Concentric ring electrodes, consisting of several elements including the central disc and a number of concentric rings, are a promising alternative with potential to improve all of the aforementioned aspects significantly. In our previous work, the tripolar concentric ring electrode was successfully used in a wide range of applications demonstrating its superiority to conventional disc electrode, in particular, in accuracy of Laplacian estimation. This paper takes the next step toward further improving the Laplacian estimation with novel multipolar concentric ring electrodes by completing and validating a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2n. An explicit formula based on inversion of a square Vandermonde matrix is derived to make computation of multipolar Laplacian more efficient. To confirm the analytic result of the accuracy of Laplacian estimate increasing with the increase of n and to assess the significance of this gain in accuracy for practical applications finite element method model analysis has been performed. Multipolar concentric ring electrode configurations with n ranging from 1 ring (bipolar electrode configuration) to 6 rings (septapolar electrode configuration) were directly compared and obtained results suggest the significance of the increase in Laplacian accuracy caused by increase of n.

The neural dynamics of somatosensory processing and adaptation across childhood: a high-density electrical mapping study

Young children are often hyperreactive to somatosensory inputs hardly noticed by adults, as exemplified by irritation to seams or labels in clothing. The neurodevelopmental mechanisms underlying changes in sensory reactivity are not well understood. Based on the idea that neurodevelopmental changes in somatosensory processing and/or changes in sensory adaptation might underlie developmental differences in somatosensory reactivity, high-density electroencephalography was used to examine how the nervous system responds and adapts to repeated vibrotactile stimulation over childhood. Participants aged 6-18 yr old were presented with 50-ms vibrotactile stimuli to the right wrist over the median nerve at 5 blocked interstimulus intervals (ranging from ∼7 to ∼1 stimulus per second). Somatosensory evoked potentials (SEPs) revealed three major phases of activation within the first 200 ms, with scalp topographies suggestive of neural generators in contralateral somatosensory cortex. Although overall SEPs were highly similar for younger, middle, and older age groups (6.1-9.8, 10.0-12.9, and 13.0-17.8 yr old), there were significant age-related amplitude differences in initial and later phases of the SEP. In contrast, robust adaptation effects for fast vs. slow presentation rates were observed that did not differ as a function of age. A greater amplitude response in the later portion of the SEP was observed for the youngest group and may be related to developmental changes in responsivity to somatosensory stimuli. These data suggest the protracted development of the somatosensory system over childhood, whereas adaptation, as assayed in this study, is largely in place by ∼7 yr of age.

Somatosensory Event-related Potentials from Orofacial Skin Stretch Stimulation

Cortical processing associated with orofacial somatosensory function in speech has received limited experimental attention due to the difficulty of providing precise and controlled stimulation. This article introduces a technique for recording somatosensory event-related potentials (ERP) that uses a novel mechanical stimulation method involving skin deformation using a robotic device. Controlled deformation of the facial skin is used to modulate kinesthetic inputs through excitation of cutaneous mechanoreceptors. By combining somatosensory stimulation with electroencephalographic recording, somatosensory evoked responses can be successfully measured at the level of the cortex. Somatosensory stimulation can be combined with the stimulation of other sensory modalities to assess multisensory interactions. For speech, orofacial stimulation is combined with speech sound stimulation to assess the contribution of multi-sensory processing including the effects of timing differences. The ability to precisely control orofacial somatosensory stimulation during speech perception and speech production with ERP recording is an important tool that provides new insight into the neural organization and neural representations for speech.