Words as social tools (WAT): A reprise.

The paper presents new evidence collected in the last five years supporting the Words As social Tools proposal on abstract concepts. We discuss findings revolving around three central tenets. First, we show that-like concrete concepts-also abstract concepts evoke sensorimotor experiences, even if to a lower extent, and that they are linked to inner experiences (e.

Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.

Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.

Why social norms may fail us when we need them most.

Where social norms are the 'glue' guiding behavior, people hardly think of their behavior as an act of norm compliance. They do consciously look for social norms in situations of environmental or social uncertainty, because i) norms provide behavioral cues that reduce uncertainty and ii) the uncertainty is partially induced by the lack or instability of social norms themselves-creating the (flawed) perception that social norms often fail us when we need them most. We discuss several state-of-the-art conceptualizations of social norms-abstract and specific norms, the social norms life cycle, and social norms in changing contexts-to highlight where and how uncertainty comes into play within each of these approaches, and consequently where the success of social norms might be hindered.

Generative models for sequential dynamics in active inference.

A central theme of theoretical neurobiology is that most of our cognitive operations require processing of discrete sequences of items. This processing in turn emerges from continuous neuronal dynamics. Notable examples are sequences of words during linguistic communication or sequences of locations during navigation.

Co-evolution of behaviour and beliefs in social dilemmas: estimating material, social, cognitive and cultural determinants.

Understanding and predicting human cooperative behaviour and belief dynamics remains a major challenge both from the scientific and practical perspectives. Because of the complexity and multiplicity of material, social and cognitive factors involved, both empirical and theoretical work tends to focus only on some snippets of the puzzle. Recently, a mathematical theory has been proposed that integrates material, social and cognitive aspects of behaviour and beliefs dynamics to explain how people make decisions in social dilemmas within heterogeneous groups.

Predictive Strategies for the Control of Complex Motor Skills: Recent Insights into Individual and Joint Actions.

Humans can perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The "predictive brain" framework suggests that mastering these tasks relies on predictive mechanisms, raising the question of how we deploy such predictions for real-time control and coordination. This review highlights two lines of research: one showing that during the control of complex objects people make the interaction with 'tools' predictable; the second one examines dyadic coordination showing that people make their behavior predictable for their partners.

Sex-related differences in amyotrophic lateral sclerosis: A 2-[F]FDG-PET study.

Purpose: We investigated sex-related brain metabolic differences in Amyotrophic Lateral Sclerosis (ALS) and healthy controls (HC).

Methods: We collected two equal-sized groups of male (m-ALS) and female ALS (f-ALS) patients (n = 130 each), who underwent 2-[F]FDG-PET at diagnosis, matched for site of onset, cognitive status and King's stage. We included 168 age-matched healthy controls, half female (f-HC) and half male (m-HC).

Deafness and Specific Learning Disorder: towards a possible comorbidity.

Background And Aim: Most children and adolescents with deafness receive one or two cochlear implants (CIs). Despite the CI expanding the potential for auditory rehabilitation in deaf children, the improvements in language and literacy skills of some of these children do not align with the expected outcomes. As the main research question, we wondered if the reading and writing deficits reported in some deaf children with CIs may be characterized as a domain-specific learning disorder, rather than only a consequence of deafness.

Croplands proximity is associated with amyotrophic lateral sclerosis incidence and age at onset.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease resulting from an intricate interplay between genetics and environmental factors. Many studies have explored living in rural areas as a possible risk factor for ALS, without focusing simultaneously on incidence, age at onset and phenotypic features.

Objective: To evaluate the effect of croplands residential proximity on ALS incidence and phenotype, focusing on age of onset, site of onset and progression rate.

A hierarchical active inference model of spatial alternation tasks and the hippocampal-prefrontal circuit.

Cognitive problem-solving benefits from cognitive maps aiding navigation and planning. Physical space navigation involves hippocampal (HC) allocentric codes, while abstract task space engages medial prefrontal cortex (mPFC) task-specific codes. Previous studies show that challenging tasks, like spatial alternation, require integrating these two types of maps.

Approach to Complementary Feeding and Infant Language Use: An Observational Study.

Emerging research suggests that a more infant-led approach to complementary feeding may confer benefits for child language, but these findings are based on parent report studies. Using an observational approach this study examines whether different complementary feeding experiences relate to infant language exposure and language use. Fifty-eight parents recorded a typical infant mealtime in the home (mean infant age = 14 months, SD = 4.

A fuzzy-logic approach for longitudinal assessment of patients' psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation.

Understanding the psychophysiological state during robot-aided rehabilitation is crucial for assessing the patient experience during treatments. This paper introduces a psychophysiological estimation approach using a Fuzzy Logic inference model to assess patients' perception of robots during upper-limb robot-aided rehabilitation sessions. The patients were asked to perform nine cycles of 3D point-to-point trajectories toward different targets at varying heights with the assistance of an anthropomorphic robotic arm (i.

Slow but flexible or fast but rigid? Discrete and continuous processes compared.

A tradeoff exists when dealing with complex tasks composed of multiple steps. High-level cognitive processes can find the best sequence of actions to achieve a goal in uncertain environments, but they are slow and require significant computational demand. In contrast, lower-level processing allows reacting to environmental stimuli rapidly, but with limited capacity to determine optimal actions or to replan when expectations are not met.

Abstract concepts and expertise: the case of institutional concepts.

Recent views recognize that abstract concepts encompass a variety of exemplars, each relying on different dimensions, including not only sensorimotor but also inner, linguistic, and social experiences. How these dimensions characterize types of abstract concepts, and whether their weight varies across contexts and individuals remains an open question. We investigated the role of linguistic and social situations in the processing of institutional concepts, such as justice, by individuals with different levels of expertise.

Resting-state EEG spectral and fractal features in dementia with Lewy bodies with and without visual hallucinations.

Objective: Complex visual hallucinations (VH) are a core feature of dementia with Lewy bodies (DLB), though they may not occur in all patients. Power spectral density (PSD) analysis of resting-state EEG (rs-EEG) shows associations between some frequency bands (e.g.

Transitive inference as probabilistic preference learning.

Transitive inference (TI) is a cognitive task that assesses an organism's ability to infer novel relations between items based on previously acquired knowledge. TI is known for exhibiting various behavioral and neural signatures, such as the serial position effect (SPE), symbolic distance effect (SDE), and the brain's capacity to maintain and merge separate ranking models. We propose a novel framework that casts TI as a probabilistic preference learning task, using one-parameter Mallows models.

PanicRoom: a virtual reality-based Pavlovian fear conditioning paradigm.

Introduction: Pavlovian fear conditioning is an experimental paradigm used to study the acquisition and extinction of fear responses and the various aspects of fear and anxiety. We developed a virtual reality (VR) version of this paradigm to leverage the benefits of virtual reality, such as ecological validity, standardization, safety, and therapeutic applications. Our objective was to create an open-source and immersive environment for studying fear-related responses using Unity Engine 3D and the Oculus Rift device.

Enhancing EEG-Based MI-BCIs with Class-Specific and Subject-Specific Features Detected by Neural Manifold Analysis.

This paper presents an innovative approach leveraging Neuronal Manifold Analysis of EEG data to identify specific time intervals for feature extraction, effectively capturing both class-specific and subject-specific characteristics. Different pipelines were constructed and employed to extract distinctive features within these intervals, specifically for motor imagery (MI) tasks. The methodology was validated using the Graz Competition IV datasets 2A (four-class) and 2B (two-class) motor imagery classification, demonstrating an improvement in classification accuracy that surpasses state-of-the-art algorithms designed for MI tasks.

Expressivity attributed to music affects the smoothness of bowing movements in violinists.

Playing music is a complex task that relies on the combination of musicians' technical and expressive skills. While the literature has investigated the effects of musical expressivity on the listeners, the way how technical difficulty and emotional expressivity affect musicians during playing has surprisingly received no attention. In an attempt to fill this gap in the literature, we collected behavioral and physiological data from twelve violinists playing 29 pieces that included both technical exercises and excerpts from classical repertoire for violin.