New insights into name category-related effects: is the Age of Acquisition a possible factor?

The role of experience for abstract concepts: Expertise modulates the electrophysiological correlates of mathematical word processing

Embodied theories assign experience a crucial role in shaping conceptual representations. Supporting evidence comes mostly from studies on concrete concepts, where e.g., motor expertise facilitated action concept processing. This study examined experience-dependent effects on abstract concept processing. We asked participants with high and low mathematical expertise to perform a lexical decision task on mathematical and nonmathematical abstract words, while acquiring event-related potentials. Analyses revealed an interaction of expertise and word type on the amplitude of a fronto-central N400 and a centro-parietal late positive component (LPC). For mathematical words, we found a trend for a lower N400 and a significantly higher LPC amplitude in experts compared to nonexperts. No differences between groups were found for nonmathematical words. The results suggest that expertise affects the processing stages of semantic integration and memory retrieval specifically for expertise-related concepts. This study supports the generalization of experience-dependent conceptual processing mechanisms to the abstract domain.

EEG-based analysis of human driving performance in turning left and right using Hopfield neural network

In this article a quantitative analysis was devised assessing driver's cognition responses by exploring the neurobiological information underlying electroencephalographic (EEG) brain signals in a left and right turning experiment on simulator environment. Driving brain signals have been collected by a 19-channel electroencephalogram recording system. The driving pathway has been selected with no obstacles, a set of indicators are used to inform the subjects when they had to turn left or right by means of keyboard left and right arrows. Subsequently in order to remove artifacts, preprocessing is performed on data to achieve high accuracy. Features of signals are extracted by using Fast Fourier Transform (FFT). Absolute power of FFT is used as a basic feature. Scalar Feature selection method is applied to reduce feature dimension. Thereafter dimension-reduced features are fed to Hopfield Neural Network (HNN) recognizing different brain potentials stimulated by turning to left and right. The performances of HNN are evaluated by considering five conditions; before feature extraction, after feature extraction, before reduction of features, after analyzing reduced features and finally subject-wise Hopfield performances respectively. An increase occurred in each level and continued until it has reached its highest 97.6% of accuracy on last condition.

Neural mechanisms of attentional control in mindfulness meditation

The scientific interest in meditation and mindfulness practice has recently seen an unprecedented surge. After an initial phase of presenting beneficial effects of mindfulness practice in various domains, research is now seeking to unravel the underlying psychological and neurophysiological mechanisms. Advances in understanding these processes are required for improving and fine-tuning mindfulness-based interventions that target specific conditions such as eating disorders or attention deficit hyperactivity disorders. This review presents a theoretical framework that emphasizes the central role of attentional control mechanisms in the development of mindfulness skills. It discusses the phenomenological level of experience during meditation, the different attentional functions that are involved, and relates these to the brain networks that subserve these functions. On the basis of currently available empirical evidence specific processes as to how attention exerts its positive influence are considered and it is concluded that meditation practice appears to positively impact attentional functions by improving resource allocation processes. As a result, attentional resources are allocated more fully during early processing phases which subsequently enhance further processing. Neural changes resulting from a pure form of mindfulness practice that is central to most mindfulness programs are considered from the perspective that they constitute a useful reference point for future research. Furthermore, possible interrelations between the improvement of attentional control and emotion regulation skills are discussed.

EEG Signature of Object Categorization from Event-related Potentials

Human visual system recognizes objects in a fast manner and the neural activity of the human brain generates signals which provide information about objects categories seen by the subjects. The brain signals can be recorded using different systems like the electroencephalogram (EEG). The EEG signals carry significant information about the stimuli that stimulate the brain. In order to translate information derived from the EEG for the object recognition mechanism, in this study, twelve various categories were selected as visual stimuli and were presented to the subjects in a controlled task and the signals were recorded through 19-channel EEG recording system. Analysis of signals was performed using two different event-related potential (ERP) computations namely the "target/rest" and "target/non-target" tasks. Comparing ERP of target with rest time indicated that the most involved electrodes in our task were F3, F4, C3, C4, Fz, Cz, among others. ERP of "target/non-target" resulted that in target stimuli two positive peaks occurred about 400 ms and 520 ms after stimulus onset; however, in non-target stimuli only one positive peak appeared about 400 ms after stimulus onset. Moreover, reaction times of subjects were computed and the results showed that the category of flower had the lowest reaction time; however, the stationery category had the maximum reaction time among others. The results provide useful information about the channels and the part of the signals that are affected by different object categories in terms of ERP brain signals. This study can be considered as the first step in the context of human-computer interface applications.

Regular, brief mindfulness meditation practice improves electrophysiological markers of attentional control

Mindfulness-based meditation practices involve various attentional skills, including the ability to sustain and focus ones attention. During a simple mindful breathing practice, sustained attention is required to maintain focus on the breath while cognitive control is required to detect mind wandering. We thus hypothesized that regular, brief mindfulness training would result in improvements in the self-regulation of attention and foster changes in neuronal activity related to attentional control. A longitudinal randomized control group EEG study was conducted. At baseline (T1), 40 meditation naïve participants were randomized into a wait list group and a meditation group, who received three hours mindfulness meditation training. Twenty-eight participants remained in the final analysis. At T1, after eight weeks (T2) and after 16 weeks (T3), all participants performed a computerized Stroop task (a measure of attentional control) while the 64-channel EEG was recorded. Between T1 and T3 the meditators were requested to meditate daily for 10 min. Event-related potential (ERP) analysis highlighted two between group effects that developed over the course of the 16-week mindfulness training. An early effect at left and right posterior sites 160-240 ms post-stimulus indicated that meditation practice improved the focusing of attentional resources. A second effect at central posterior sites 310-380 ms post-stimulus reflects that meditation practice reduced the recruitment of resources during object recognition processes, especially for incongruent stimuli. Scalp topographies and source analyses (Variable Resolution Electromagnetic Tomography, VARETA) indicate relevant changes in neural sources, pertaining to left medial and lateral occipitotemporal areas for the early effect and right lateral occipitotemporal and inferior temporal areas for the later effect. The results suggest that mindfulness meditation may alter the efficiency of allocating cognitive resources, leading to improved self-regulation of attention.

The neural manifestation of the word concreteness effect: an electrical neuroimaging study

Previous studies have provided controversial evidence about the way in which words with different degrees of concreteness are represented in the brain. The aim of the present study was to investigate whether the processing of abstract vs. concrete words differently affected the timing and topographical distribution of ERP components. Participants were engaged in a lexical decision task (word/non-word discrimination) while EEG was recorded from 128 scalp sites. Reaction times (RTs) to words were faster than RTs to pseudowords. Words were discriminated from pseudowords since larger N2 responses to words than to pseudowords were observed over the left occipito-temporal areas at 300 ms post-stimulus. Concrete words and abstract words were discriminated as early as 350 ms post-stimulus, with larger responses to concrete than to abstract words over the mesial occipital regions. Concreteness-related ERP differences were also observed in the amplitudes of the later anterior LP component (between 370 and 570 ms), with larger responses to abstract words than to concrete words. The LORETA source localization technique was also applied to identify the intra-cranial generators of surface potentials reflecting lexico-semantic processing. Results showed that words (both abstract and concrete) were associated with a stronger activation of the left fusiform gyrus and the left temporal cortex, as compared to pseudowords. Concrete word processing was associated with a stronger activation of the left extrastriate visual areas (namely BA 18 and BA 19) as compared to abstract word processing. By revealing the neural markers of the concreteness effect, our study contributes to the understanding of the neurogenesis of verbal semantic knowledge impairments and the incidence of these impairments in clinical populations.

Identifying object categories from event-related EEG: toward decoding of conceptual representations

Multivariate pattern analysis is a technique that allows the decoding of conceptual information such as the semantic category of a perceived object from neuroimaging data. Impressive single-trial classification results have been reported in studies that used fMRI. Here, we investigate the possibility to identify conceptual representations from event-related EEG based on the presentation of an object in different modalities: its spoken name, its visual representation and its written name. We used Bayesian logistic regression with a multivariate Laplace prior for classification. Marked differences in classification performance were observed for the tested modalities. Highest accuracies (89% correctly classified trials) were attained when classifying object drawings. In auditory and orthographical modalities, results were lower though still significant for some subjects. The employed classification method allowed for a precise temporal localization of the features that contributed to the performance of the classifier for three modalities. These findings could help to further understand the mechanisms underlying conceptual representations. The study also provides a first step towards the use of concept decoding in the context of real-time brain-computer interface applications.

Electrophysiological correlates of early processing of visual word recognition: N2 as an index of visual category feature processing

A fundamental question in second language learning is how the brain separates inputs from different languages into distinct representation systems prior to semantic activation. The present study investigated this question using a silent reading task in which Latin letters and simple Chinese characters (including real characters and pseudocharacters) appeared randomly for 100 milliseconds (ms). High-density event-related potentials were employed to record the electrophysiological correlates of visual word recognition prior to motor response. The results showed that real Chinese characters and pseudocharacters produced a larger N2 response than letters within 200-300ms time window. However, no significant differences between real Chinese characters and pseudocharacters were found. The separation of two languages into their own systems might occur in the time window when N2 was elicited. The segregation of real Chinese characters and pseudocharacters was observed in a later time window (350-450ms). The category feature processing of stimuli might be responsible for the N2 response; the processing allows stimuli of the same category to be analyzed in their specific units and distinguishes different stimuli.