Electrophysiological and haemodynamic biomarkers of rapid acquisition of novel wordforms

Humans are unique in developing large lexicons; to achieve this, they are able to learn new words rapidly. However, the neural bases of this rapid learning, which may be an expression of a more general mechanism rooted in plasticity at cellular and synaptic levels, are not yet understood. Here, we highlight a selection of recent EEG and fMRI studies that attempted to trace word-learning in the human brain non-invasively. They show a rapid development of cortical memory traces for novel wordforms over a short session of auditory exposure to these items. Moreover, they demonstrate that this effect appears to be independent of attention, reflecting the largely automatic nature of word acquisition. At the same time, it seems to be limited to stimuli with native phonology, likely benefiting from pre-existing perception-articulation links in the brain, and thus suggesting different neural strategies for learning words in native and non-native languages. We also show a complex interplay between overnight consolidation, amount of exposure to novel vocabulary and attention to speech input, all of which influence learning outcomes. In sum, the available evidence suggests that the brain may effectively form new cortical circuits online, as it gets exposed to novel linguistic elements in the sensory input. A number of brain areas, most notably in the hippocampus and neocortex, appear to take part in word acquisition. Critically, the currently available data not only demonstrate a hippocampal role in rapid encoding followed by slow-rate consolidation of cortical memory traces, but also suggest immediate neocortical involvement in the word memory trace formation

Functional connectivity of spoken language processing in early-stage Parkinson’s disease : an MEG study

Parkinson's disease (PD) is a neurodegenerative disorder, well-known for its motor symptoms; however, it also adversely affects cognitive functions, including language, a highly important human ability. PD pathology is associated, even in the early stage of the disease, with alterations in the functional connectivity within corticosubcortical circuitry of the basal ganglia as well as within cortical networks. Here, we investigated functional cortical connectivity related to spoken language processing in early-stage PD patients. We employed a patientfriendly passive attention-free paradigm to probe neurophysiological correlates of language processing in PD patients without confounds related to active attention and overt motor responses. MEG data were recorded from a group of newly diagnosed PD patients and age-matched healthy controls who were passively presented with spoken word stimuli (action and abstract verbs, as well as grammatically correct and incorrect inflectional forms) while focussing on watching a silent movie. For each of the examined linguistic aspects, a logistic regression classifier was used to classify participants as either PD patients or healthy controls based on functional connectivity within the temporo-fronto-parietal cortical language networks. Classification was successful for action verbs (accuracy = 0.781, p-value = 0.003) and, with lower accuracy, for abstract verbs (accuracy = 0.688, pvalue = 0.041) and incorrectly inflected forms (accuracy = 0.648, p-value = 0.021), but not for correctly inflected forms (accuracy = 0.523, p-value = 0.384). Our findings point to quantifiable differences in functional connectivity within the cortical systems underpinning language processing in newly diagnosed PD patients compared to healthy controls, which arise early, in the absence of clinical evidence of deficits in cognitive or general language functions. The techniques presented here may aid future work on establishing neurolinguistic markers to objectively and noninvasively identify functional changes in the brain's language networks even before clinical symptoms emerge.Peer reviewe

Addressing Ethical Challenges of Creating New Technology for Criminal Investigation: The VALCRI Project

In developing a semi-automated decision support system using cutting-edge visual technologies to aid police intelligence analysts (the VALCRI project) it was recognised that addressing ethical, privacy and legal issues would need to be considered from the start. From the beginning, experts in these fields were embedded in the project and externally an independent ethics board was established and a number of ethical concerns were identified. Addressing the concerns presented some challenges both in terms of process and product and are the subject of this paper. Insights about these problems can contribute to other research projects beyond the area of crime visualization, for instance addressing concerns such as logging processes for auditing and evidence in other sensitive projects

A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia

Developmental Dyslexia (DD) is a learning disability related to the acquisition of reading skills that affects about 5% of the population. DD can have an enormous impact on the intellectual and personal development of affected children, so early detection is key to implementing preventive strategies for teaching language. Research has shown that there may be biological underpinnings to DD that affect phoneme processing, and hence these symptoms may be identifiable before reading ability is acquired, allowing for early intervention. In this paper we propose a new methodology to assess the risk of DD before students learn to read. For this purpose, we propose a mixed neural model that calculates risk levels of dyslexia from tests that can be completed at the age of 5 years. Our method first trains an auto-encoder, and then combines the trained encoder with an optimized ordinal regression neural network devised to ensure consistency of predictions. Our experiments show that the system is able to detect unaffected subjects two years before it can assess the risk of DD based mainly on phonological processing, giving a specificity of 0.969 and a correct rate of more than 0.92. In addition, the trained encoder can be used to transform test results into an interpretable subject spatial distribution that facilitates risk assessment and validates methodology.Comment: 12 pages, 4 figure

Competitors' envy, gamers' pride: An exploration of gamers' divergent behavior

Cheating in games has existed since the beginning of video games. The landscape of gaming and cheating has changed profoundly with its migration to the online environment. This study aims to investigate the unethical behavioral intention of online gamers. The Theory of Planned Behavior and Social Comparison Theory is used to develop a comprehensive framework to understand gamers' cheating intention. This study employs a quantitative approach to collect data from 404 gamers using a random sampling technique. Results show that attitude, subjective norms, perceived behavioral control, hedonic motivation, and benign envy influences gamers' online cheating intention. Online cheating intention was found to influence online cheating behavior positively. Looking at the moderating effect of ethical judgment, this study revealed that ethical judgment dampens the positive relationship between attitude, benign envy, and perceived behavioral control on gamers' online cheating intention. This study is the first to explore the impact of different types of envy on divergent gaming behavior. It contributes to the literature by generating insights into an under‐researched area of divergent online gaming behavior