Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis.

Recent studies show that the integrity of core perceptual and cognitive functions may be tested in a short time with Steady-State Visual Evoked Potentials (SSVEP) with low stimulation frequencies, between 1 and 10 Hz. Wearable EEG systems provide unique opportunities to test these brain functions on diverse populations in out-of-the-lab conditions. However, they also pose significant challenges as the number of EEG channels is typically limited, and the recording conditions might induce high noise levels, particularly for low frequencies.

Adaptable and Robust EEG Bad Channel Detection Using Local Outlier Factor (LOF).

Electroencephalogram (EEG) data are typically affected by artifacts. The detection and removal of bad channels (i.e.

NEAR: An artifact removal pipeline for human newborn EEG data.

Electroencephalography (EEG) is arising as a valuable method to investigate neurocognitive functions shortly after birth. However, obtaining high-quality EEG data from human newborn recordings is challenging. Compared to adults and older infants, datasets are typically much shorter due to newborns' limited attentional span and much noisier due to non-stereotyped artifacts mainly caused by uncontrollable movements.

Efficient Artifact Removal from Low-Density Wearable EEG using Artifacts Subspace Reconstruction.

Light-weight, minimally-obtrusive mobile EEG systems with a small number of electrodes (i.e., low-density) allow for convenient monitoring of the brain activity in out-of-the-lab conditions.

The neural representation of absolute direction during mental navigation in conceptual spaces.

When humans mentally "navigate" bidimensional uniform conceptual spaces, they recruit the same grid-like and distance codes typically evoked when exploring the physical environment. Here, using fMRI, we show evidence that conceptual navigation also elicits another kind of spatial code: that of absolute direction. This code is mostly localized in the medial parietal cortex, where its strength predicts participants' comparative semantic judgments.

Grid-like and distance codes for representing word meaning in the human brain.

Relational information about items in memory is thought to be represented in our brain thanks to an internal comprehensive model, also referred to as a "cognitive map". In the human neuroimaging literature, two signatures of bi-dimensional cognitive maps have been reported: the grid-like code and the distance-dependent code. While these kinds of representation were previously observed during spatial navigation and, more recently, during processing of perceptual stimuli, it is still an open question whether they also underlie the representation of the most basic items of language: words.

Cortical route for facelike pattern processing in human newborns.

Humans are endowed with an exceptional ability for detecting faces, a competence that, in adults, is supported by a set of face-specific cortical patches. Human newborns, already shortly after birth, preferentially orient to faces, even when they are presented in the form of highly schematic geometrical patterns vs. perceptually equivalent nonfacelike stimuli.

Conceptual and Perceptual Dimensions of Word Meaning Are Recovered Rapidly and in Parallel during Reading.

A single word (the noun "") encapsulates a complex multidimensional meaning, including both perceptual ("", "", "") and conceptual ("", "") features. Opposing theories make different predictions as to whether different features (also conceivable as dimensions of the semantic space) are stored in similar neural regions and recovered with similar temporal dynamics during word reading. In this magnetoencephalography study, we tracked the brain activity of healthy human participants while reading single words varying orthogonally across three semantic dimensions: two perceptual ones (i.

A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems.

EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequency-tagging is an increasingly popular experimental paradigm that efficiently tests brain function by measuring EEG responses to periodic stimulation. Recently, frequency-tagging paradigms have proven successful with low stimulation frequencies (0.

Word meaning in the ventral visual path: a perceptual to conceptual gradient of semantic coding.

The meaning of words referring to concrete items is thought of as a multidimensional representation that includes both perceptual (e.g., average size, prototypical color) and conceptual (e.

Disruption of hierarchical predictive coding during sleep.

When presented with an auditory sequence, the brain acts as a predictive-coding device that extracts regularities in the transition probabilities between sounds and detects unexpected deviations from these regularities. Does such prediction require conscious vigilance, or does it continue to unfold automatically in the sleeping brain? The mismatch negativity and P300 components of the auditory event-related potential, reflecting two steps of auditory novelty detection, have been inconsistently observed in the various sleep stages. To clarify whether these steps remain during sleep, we recorded simultaneous electroencephalographic and magnetoencephalographic signals during wakefulness and during sleep in normal subjects listening to a hierarchical auditory paradigm including short-term (local) and long-term (global) regularities.

Contribution of motor representations to action verb processing.

Electrophysiological and brain imaging studies show a somatotopic activation of the premotor cortex while subjects process action verbs. This somatotopic motor activation has been taken as an indication that the meaning of action verbs is embedded in motor representations. However, discrepancies in the literature led to the alternative hypothesis that motor representations are activated during the course of a mental imagery process emerging only after the meaning of the action has been accessed.

Timing the impact of literacy on visual processing.

Learning to read requires the acquisition of an efficient visual procedure for quickly recognizing fine print. Thus, reading practice could induce a perceptual learning effect in early vision. Using functional magnetic resonance imaging (fMRI) in literate and illiterate adults, we previously demonstrated an impact of reading acquisition on both high- and low-level occipitotemporal visual areas, but could not resolve the time course of these effects.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset.

Temporal integration in visual word recognition.

When two displays are presented in close temporal succession at the same location, how does the brain assign them to one versus two conscious percepts? We investigate this issue using a novel reading paradigm in which the odd and even letters of a string are presented alternatively at a variable rate. The results reveal a window of temporal integration during reading, with a nonlinear boundary around approximately 80 msec of presentation duration. Below this limit, the oscillating stimulus is easily fused into a single percept, with all characteristics of normal reading.

The correlated nature of large-scale neural activity unveiled by the resting brain.

Most of functional neuroscience studies investigate the brain's response to a task or stimulus. However, the brain is very active even in the absence of an external or internal input. Recent neuroimaging, electrophysiological and optical imaging studies revealed that the neural activity at rest is structured in functionally specific, temporally correlated, spatially distributed patterns that explain a large part of the variability of event-related responses.

Investigating the neural correlates of continuous speech computation with frequency-tagged neuroelectric responses.

In order to learn an oral language, humans have to discover words from a continuous signal. Streams of artificial monotonous speech can be readily segmented based on the statistical analysis of the syllables' distribution. This parsing is considerably improved when acoustic cues, such as subliminal pauses, are added suggesting that a different mechanism is involved.

Chance vs. necessity in living systems: a false antinomy.

The concepts of order and randomness are crucial to understand 'living systems' structural and dynamical rules. In the history of biology, they lay behind the everlasting debate on the relative roles of chance and determinism in evolution. Jacques Monod [1970] built a theory where chance (randomness) and determinism (order) were considered as two complementary aspects of life.

Variance normalisation: a key mechanism for temporal adaptation in natural vision?

A major problem in natural vision is how neurons in the early visual system encode the widely varying visual input with the limited dynamic range of their activity. Recent experiments suggest that retinal neurons adapt their response not only to the temporal mean but also to the temporal variance of the visual input. Inspired by these results, we propose a simple model in which temporal adaptation can be achieved by a transformation consisting of a linear filtering followed by a variance normalisation.