Prospective memory is memory for the realization of delayed intention. Researchers distinguish 2 kinds of prospective memory: event- and time-based (G. O. Einstein & M. A. McDaniel, 1990). Taking that distinction into account, the present authors explored participants' comparative performance under event- and time-based tasks. In an experimental study of 80 participants, the authors investigated the roles of cognitive load and task condition in prospective memory. Cognitive load (low vs. high) and task condition (event- vs. time-based task) were the independent variables. Accuracy in prospective memory was the dependent variable. Results showed significant differential effects under event- and time-based tasks. However, the effect of cognitive load was more detrimental in time-based prospective memory. Results also revealed that time monitoring is critical in successful performance of time estimation and so in time-based prospective memory. Similarly, participants' better performance on the event-based pr...

Developmental dyscalculia is a neurodevelopmental disorder, influencing the learning of mathematics in developing children. In the last two decades, continuous growth of research has helped in the advancement of the state of knowledge of dyscalculia. This upsurge in the number of studies makes it relevant to conduct a systematic review, covering all the empirical evidence, but there is a dearth of review studies synthesizing findings of the studies in the recent past. Therefore, the current study aims to systematically review studies investigating the underlying cognitive causal factors associated with developmental dyscalculia in the last two decades. To investigate the underlying cognitive factors associated with dyscalculia, two prominent approaches have been used: domain-general and domain-specific. While the domain-general approach argues for the deficit in general cognitive abilities, the domain-specific approach argues for the deficit in core numerical abilities. In the present review, the PRISMA method is followed. Articles were searched using two methods: firstly, through database sources of Google Scholar, Web of Science, and ScienceDirect, 1738 abstracts were screened, of which 46 articles met the specific inclusion criteria; and secondly, through recently published systematic reviews and meta-analyses, 29 studies were included. A total of 75 studies, 48 studies from domain-general and 27 studies from domain-specific approaches, have been selected. This review discusses domain-general and domain-specific approaches of developmental dyscalculia, along with specific theories associated with both approaches. Based on the discussed findings, visuospatial working memory and symbolic number processing abilities emerged as the best predictor of math ability in children with dyscalculia.

Imagined speech can be used to send commands without any muscle movement or emitting audio. The current status of research is in the early stage, and there is a shortage of open-access datasets for imagined speech analysis. We have proposed an openly accessible electroencephalograph (EEG) dataset for six imagined words in this work. We have selected six phonetically distributed, monosyllabic, and emotionally neutral words from W-22 CID word lists. The phonetic distribution of words consisted of the different places of consonants’ articulation and different positions of tongue advancement for vowel pronunciation. The selected words were “could,” “yard,” “give,” “him,” “there,” and “toe.” The experiment was performed over 15 subjects who performed the overt and imagined speech task for the displayed word. Each word was presented 50 times in random order. EEG signals were recorded during the experiment using a 64-channel EEG acquisition system with a sampling rate of 2,048 Hz. A preliminary analysis of the recorded data is presented by performing the classification of EEGs corresponding to the imagined words. The achieved accuracy is above the chance level for all subjects, which suggests that the recorded EEGs contain distinctive information about the imagined words.

The leftward cradling bias is the tendency to cradle infants on the left side of the body and it has been linked with hemispheric asymmetry for emotional processing. This study examines this phenomenon using a real-size infant doll in typically developing adults who score high in the Reading the Mind in the Eyes, the Autistic Spectrum Quotient and the Empathy Quotient, measures that assess autistic traits among typically developing individuals. Results revealed that this group showed a reduced tendency to cradle on the left compared to participants who score within the normal range on the above measurements. This study provides further support for the justification of the leftward cradling bias upon brain lateralization on emotional processing. Study limitations and suggestions for future research are discussed.

Twitter’s popularity has exploded in the previous few years, making it one of the most widely used social media sites. As a result of this development, the strategies described in this study are now more beneficial. Additionally, there has been an increase in the number of people who express their views in demeaning ways to others. As a result, hate speech has piqued interest in the subject of sentiment analysis, which has developed various algorithms for detecting emotions in social networks using intuitive means. This paper proposes the deep learning model to classify the sentiments in two separate analyses. In the first analysis, the tweets are classified based on the hate speech against the migrants and the women. In the second analysis, the detection is performed using a deep learning model to organise whether the hate speech is performed by a single or a group of users. During the text analysis, word embedding is implemented using the combination of deep learning models such as BiLSTM, CNN, and MLP. These models are integrated with word embedding methods such as inverse glove (global vector), document frequency (TF-IDF), and transformer-based embedding.