TACO: A Turkish database for abstract concepts.

The organization of abstract concepts reflects different dimensions, grounded in the brain regions coding for the corresponding experience. Normative measures of linguistic stimuli offer noteworthy insights into the organization of conceptual knowledge, but studies differ in the dimensions and classes of concepts considered. Additionally, most of the available information has been collected in English, without considering possible linguistic and cultural differences. Here, we aimed to create a comprehensive Turkish database for abstract concepts (TACO), including rarely investigated classes such as political concepts. We included 503 words-78 concrete (fruits, animals, tools) and 425 abstract (emotions, social, mental states, theoretical, quantity, space, political)-rated by 134 Turkish speakers for familiarity, imageability, age of acquisition, valence, arousal, quantity, space, theoretical, social, mental state, and political dimensions. We calculated dominance and exclusivity, indicating the dimension receiving the highest mean score for each word, and the position of the word along the unidimensional-multidimensional continuum, respectively. A principal component analysis (PCA) was conducted on the semantic dimensions. The results showed that mental state was the dominant dimension for most concepts. Moderate to low levels of exclusivity indicated that the concepts were multidimensional. PCA revealed three components: Component 1 captured the juxtaposition between social/mental state and magnitude polarities, Component 2 highlighted affective components, and Component 3 grouped together political and theoretical dimensions. The introduction of political concepts provided insights into the multidimensional nature of this unexplored class, closely intertwined with the theoretical dimension. TACO constitutes the first comprehensive Turkish database covering several abstract dimensions, paving the way for cross-linguistic and cross-cultural studies of semantic representations.

A Review on the Feasibility and Efficacy of Home-Based Cognitive Remediation in People with Multiple Sclerosis.

Cognitive impairment affects 34-65% of People with Multiple Sclerosis (PwMS), significantly impacting their quality of life. Clinicians routinely address cognitive deficits with in-clinic neuro-behavioural interventions, but accessibility issues exist. Given these challenges, coupled with the lifelong need for continuous assistance in PwMS, researchers have underscored the advantageous role of telerehabilitation in addressing these requirements. Nonetheless, the feasibility and efficacy of home-based cognitive remediation remain to be firmly established. In this narrative review, we aimed to investigate the feasibility and efficacy of digital telerehabilitation for cognition in PwMS. Thirteen relevant studies were identified and carefully assessed. Regarding the feasibility of cognitive telerehabilitation, evidence shows adherence rates are generally good, although, surprisingly, not all studies reported measures of compliance with the cognitive training explored. Considering the efficacy of rehabilitative techniques on cognitive performance in PwMS, findings are generally inconsistent, with only one study reporting uniformly positive results. A range of methodological limitations are reported as potential factors contributing to the variable results. Future research must address these challenges, as more rigorous studies are required to draw definitive conclusions regarding the efficacy of home-based cognitive remediation in PwMS. Researchers must prioritise identifying optimal intervention approaches and exploring the long-term effects of telerehabilitation.

What do you have in mind? ERP markers of visual and auditory imagery.

This study aimed to investigate the psychophysiological markers of imagery processes through EEG/ERP recordings. Visual and auditory stimuli representing 10 different semantic categories were shown to 30 healthy participants. After a given interval and prompted by a light signal, participants were asked to activate a mental image corresponding to the semantic category for recording synchronized electrical potentials. Unprecedented electrophysiological markers of imagination were recorded in the absence of sensory stimulation. The following peaks were identified at specific scalp sites and latencies, during imagination of infants (centroparietal positivity, CPP, and late CPP), human faces (anterior negativity, AN), animals (anterior positivity, AP), music (P300-like), speech (N400-like), affective vocalizations (P2-like) and sensory (visual vs auditory) modality (PN300). Overall, perception and imagery conditions shared some common electro/cortical markers, but during imagery the category-dependent modulation of ERPs was long latency and more anterior, with respect to the perceptual condition. These ERP markers might be precious tools for BCI systems (pattern recognition, classification, or A.I. algorithms) applied to patients affected by consciousness disorders (e.g., in a vegetative or comatose state) or locked-in-patients (e.g., spinal or SLA patients).

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.