Sexual Dimorphism in Hemispheric Processing of Faces in Humans: A Meta-Analysis of 817 Cases

Effective connectivity of working memory performance: a DCM study of MEG data

Visual working memory (WM) engages several nodes of a large-scale network that includes frontal, parietal, and visual regions; however, little is understood about how these regions interact to support WM behavior. In particular, it is unclear whether network dynamics during WM maintenance primarily represent feedforward or feedback connections. This question has important implications for current debates about the relative roles of frontoparietal and visual regions in WM maintenance. In the current study, we investigated the network activity supporting WM using MEG data acquired while healthy subjects performed a multi-item delayed estimation WM task. We used computational modeling of behavior to discriminate correct responses (high accuracy trials) from two different types of incorrect responses (low accuracy and swap trials), and dynamic causal modeling of MEG data to measure effective connectivity. We observed behaviorally dependent changes in effective connectivity in a brain network comprising frontoparietal and early visual areas. In comparison with high accuracy trials, frontoparietal and frontooccipital networks showed disrupted signals depending on type of behavioral error. Low accuracy trials showed disrupted feedback signals during early portions of WM maintenance and disrupted feedforward signals during later portions of maintenance delay, while swap errors showed disrupted feedback signals during the whole delay period. These results support a distributed model of WM that emphasizes the role of visual regions in WM storage and where changes in large scale network configurations can have important consequences for memory-guided behavior.

Music literacy improves reading skills via bilateral orthographic development

Considerable evidence suggests that musical education induces structural and functional neuroplasticity in the brain. This study aimed to explore the potential impact of such changes on word-reading proficiency. We investigated whether musical training promotes the development of uncharted orthographic regions in the right hemisphere leading to better reading abilities. A total of 60 healthy, right-handed culturally matched professional musicians and controls took part in this research. They were categorised as normo-typical readers based on their reading speed (syl/sec) and subdivided into two groups of relatively good and poor readers. High density EEG/ERPs were recorded while participants engaged in a note or letter detection task. Musicians were more fluent in word, non-word and text reading tests, and faster in detecting both notes and words. They also exhibited greater N170 and P300 responses, and target-non target differences for words than controls. Similarly, good readers showed larger N170 and P300 responses than poor readers. Increased reading skills were associated to a bilateral activation of the occipito/temporal cortex, during music and word reading. Source reconstruction also showed a reduced activation of the left fusiform gyrus, and of areas devoted to attentional/ocular shifting in poor vs. good readers, and in controls vs. musicians. Data suggest that music literacy acquired early in time can shape reading circuits by promoting the specialization of a right-sided reading area, whose activity was here associated with enhanced reading proficiency. In conclusion, music literacy induces measurable neuroplastic changes in the left and right OT cortex responsible for improved word reading ability.

Eyelash length attractiveness across ethnicities

Eyelashes evolved to protect eyes. An optimum eyelash length functions to protect eyes from external hazards such as contaminations, excessive evaporation or shear stress from airflow. They can also be an indicator of a person's health as various congenital and noncongenital diseases can lead to short or long eyelashes. The current study aimed to extend a recent investigation on the preference for eyelash length in humans from an evolutionary adaptive perspective. Specifically, the current study tested whether the inverted-U function for eyelash length preference recently reported for White faces, generalises to other ethnicities, and whether ethnic background modulates preference for eyelash lengths. To investigate this question, men and women of Asian, Black, and White ethnicities from the U.S. rated the attractiveness of female Indian, Asian, Black, and White faces with varying eyelash lengths. The eyelashes ranged in length from no eyelashes to half the width of an eye. Results showed that Asian, Black, and White men and women preference for eyelash length followed an inverted-U function across all four ethnicities, supporting a general preference for human eyelash length that is approximately one-third the width of an eye. In addition, the results showed that the most attractive eyelashes for Black women were skewed toward a greater eyelash-length to eye-width ratio when compared to the other images. The source of this skew is presently unknown, as it could reflect a change in perceptual sensitivity to eyelash length with skin colour or changes in preference related to perceptions of participants' ethnicity.

Emojis Are Comprehended Better than Facial Expressions, by Male Participants

Emojis are colorful ideograms resembling stylized faces commonly used for expressing emotions in instant messaging, on social network sites, and in email communication. Notwithstanding their increasing and pervasive use in electronic communication, they are not much investigated in terms of their psychological properties and communicative efficacy. Here, we presented 112 different human facial expressions and emojis (expressing neutrality, happiness, surprise, sadness, anger, fear, and disgust) to a group of 96 female and male university students engaged in the recognition of their emotional meaning. Analyses of variance showed that male participants were significantly better than female participants at recognizing emojis (especially negative ones) while the latter were better than male participants at recognizing human facial expressions. Quite interestingly, male participants were better at recognizing emojis than human facial expressions per se. These findings are in line with more recent evidence suggesting that male individuals may be more competent and inclined to use emojis to express their emotions in messaging (especially sarcasm, teasing, and love) than previously thought. Finally, the data indicate that emojis are less ambiguous than facial expressions (except for neutral and surprise emotions), possibly because of the limited number of fine-grained details and the lack of morphological features conveying facial identity.

Event-related brain potential markers of visual and auditory perception: A useful tool for brain computer interface systems

Objective

A majority of BCI systems, enabling communication with patients with locked-in syndrome, are based on electroencephalogram (EEG) frequency analysis (e.g., linked to motor imagery) or P300 detection. Only recently, the use of event-related brain potentials (ERPs) has received much attention, especially for face or music recognition, but neuro-engineering research into this new approach has not been carried out yet. The aim of this study was to provide a variety of reliable ERP markers of visual and auditory perception for the development of new and more complex mind-reading systems for reconstructing the mental content from brain activity.

Methods

A total of 30 participants were shown 280 color pictures (adult, infant, and animal faces; human bodies; written words; checkerboards; and objects) and 120 auditory files (speech, music, and affective vocalizations). This paradigm did not involve target selection to avoid artifactual waves linked to decision-making and response preparation (e.g., P300 and motor potentials), masking the neural signature of semantic representation. Overall, 12,000 ERP waveforms × 126 electrode channels (1 million 512,000 ERP waveforms) were processed and artifact-rejected.

Results

Clear and distinct category-dependent markers of perceptual and cognitive processing were identified through statistical analyses, some of which were novel to the literature. Results are discussed from the view of current knowledge of ERP functional properties and with respect to machine learning classification methods previously applied to similar data.

Conclusion

The data showed a high level of accuracy (p ≤ 0.01) in the discriminating the perceptual categories eliciting the various electrical potentials by statistical analyses. Therefore, the ERP markers identified in this study could be significant tools for optimizing BCI systems [pattern recognition or artificial intelligence (AI) algorithms] applied to EEG/ERP signals.