Activity Patterns Research Articles

Neural dynamics of shifting attention between perception and working-memory contents

In everyday tasks, our focus of attention shifts seamlessly between contents in the sensory environment and internal memory representations. Yet, research has mainly considered external and internal attention in isolation. We used magnetoencephalography to compare the neural dynamics of shifting attention to visual contents within vs. between the external and internal domains. Participants performed a combined perception and working-memory task in which two sequential cues guided attention to upcoming (external) or memorized (internal) sensory information. Critically, the second cue could redirect attention to visual content within the same or alternative domain as the first cue. Multivariate decoding unveiled distinct patterns of human brain activity when shifting attention within vs. between domains. Brain activity distinguishing within- from between-domain shifts was broadly distributed and highly dynamic. Intriguingly, crossing domains did not invoke an additional stage prior to shifting attention. Alpha lateralization, a canonical marker of shifting spatial attention, showed no delay when cues redirected attention to the same vs. alternative domain. Instead, evidence suggested that neural states associated with a given domain linger and influence subsequent shifts of attention within vs. between domains. Our findings provide critical insights into the neural dynamics that govern attentional shifts between perception and working memory.

Contrastive learning for neural fingerprinting from limited neuroimaging data

IntroductionNeural fingerprinting is a technique used to identify individuals based on their unique brain activity patterns. While deep learning techniques have been demonstrated to outperform traditional correlation-based methods, they often require retraining to accommodate new subjects. Furthermore, the limited availability of samples in neuroscience research can impede the quick adoption of deep learning methods, presenting a challenge for their broader application in neural fingerprinting.MethodsThis study addresses these challenges by using contrastive learning to eliminate the need for retraining with new subjects and developing a data augmentation methodology to enhance model robustness in limited sample size conditions. We utilized the LEMON dataset, comprising 3 Tesla MRI and resting-state fMRI scans from 138 subjects, to compute functional connectivity as a baseline for fingerprinting performance based on correlation metrics. We adapted a recent deep learning model by incorporating data augmentation with short random temporal segments for training and reformulated the fingerprinting task as a contrastive problem, comparing the efficacy of contrastive triplet loss against conventional cross-entropy loss.ResultsThe results of this study confirm that deep learning methods can significantly improve fingerprinting performance over correlation-based methods, achieving an accuracy of about 98% in identifying a single subject out of 138 subjects utilizing 39 different functional connectivity profiles.DiscussionThe contrastive method showed added value in the “leave subject out” scenario, demonstrating flexibility comparable to correlation-based methods and robustness across different data sizes. These findings suggest that contrastive learning and data augmentation offer a scalable solution for neural fingerprinting, even with limited sample sizes.

Association between physical activity patterns of working-age adults and social jetlag, depressive symptoms, and presenteeism

Abstract Objectives: This study aimed to evaluate the association of physical activity with social jetlag, depressive symptoms, and presenteeism. Methods: This cross-sectional study included 8,247 working-age adults (females, 44.6%; age, 20–64 years). Social jetlag was defined as the absolute difference between the midpoint of bedtime and wake time on workdays and free days. Depression symptoms were assessed using the Center for Epidemiologic Studies Depression Scale, and presenteeism was evaluated using the Work Functioning Impairment Scale. Exercise habits were classified into four groups based on the World Health Organization guidelines: non-active (NA; n=4,223), insufficiently active (IA; n=3,009: exercise below guideline levels), weekend warriors (WW; n=220: exercise 1–2 times per week meeting guideline levels), and regularly active (RA; n=793: exercise at least 3 days per week meeting guideline levels). Using multiple and Poisson regression analyses, we examined the association between exercise habits and each outcome. Results: Social jetlag, depression, and presenteeism were more favorable with shorter sedentary times and longer durations of moderate- and vigorous-intensity exercise. Compared with the RA group, the NA group had a significantly higher prevalence of social jetlag (prevalence ratio [PR]=1.30), depression (PR=1.31), and presenteeism (PR=1.35). The IA group had a significantly higher prevalence of depression (PR=1.33) and presenteeism (PR=1.38). Conclusions: Exercising with a certain frequency and intensity may help prevent symptoms of depression and social jetlag, and consequently prevent presenteeism.

Human and predator presence shape diel activity of urban red squirrels

In urban areas, wildlife has to adapt to human presence and novel predators such as pet species, including the altered conditions of the environment. In such novel settings, the timing of activity is crucial to minimize the risk of mortality. To do so, species may reduce total activity time by increasing activity peaks at specific moments or shifting activity times. We analyzed camera trap data from a citizen science project over four project phases, including spring and autumn before and during the SARS-CoV-2 lockdown, to understand the effects of human, pet (cat, dog), and predator (marten) presence on the activity patterns of urban red squirrels (Sciurus vulgaris; hereafter ‘squirrel’). We examined squirrel activity at seasonal and hourly resolutions in relation to human, garden, urban, and predator factors. We considered human presence as both a direct effect of lockdown and an indirect disturbance measured through urban variables. Results show that direct human presence during lockdown increased squirrel activity intensity in both seasonal and hourly patterns without reducing total activity time. Predator presence affected timing of activity, decreasing total daily activity. Pets, like cats, decreased activity at both resolutions, while martens had a limited effect detected only at the hourly resolution. During lockdown, squirrels may have increased their activity in gardens due to more anthropogenic resources (food or nesting material), but constant threats from pets force them to avoid certain areas despite the benefits. This highlights the delicate balance squirrels must maintain in adapting to human-altered environments while managing predation risks.

Cognitive reserve against Alzheimer’s pathology is linked to brain activity during memory formation

AbstractThe cognitive reserve (CR) hypothesis posits that individuals can differ in how their brain function is disrupted by pathology associated with aging and neurodegeneration. Here, we test this hypothesis in the continuum from cognitively normal to at-risk stages for Alzheimer’s Disease (AD) to AD dementia using longitudinal data from 490 participants of the DELCODE multicentric observational study. Brain function is measured using task fMRI of visual memory encoding. Using a multivariate moderation analysis, we identify a CR-related activity pattern underlying successful memory encoding that moderates the detrimental effect of AD pathological load on cognitive performance. CR is mainly represented by a more pronounced expression of the task-active network encompassing deactivation of the default mode network (DMN) and activation of inferior temporal regions including the fusiform gyrus. We devise personalized fMRI-based CR scores that moderate the impact of AD pathology on cognitive performance and are positively associated with years of education. Furthermore, higher CR scores attenuate the effect of AD pathology on cognitive decline over time. Our findings primarily provide evidence for the maintenance of core cognitive circuits including the DMN as the neural basis of CR. Individual brain activity levels of these areas during memory encoding have prognostic value for future cognitive decline.

Increasing detections of the margay: occupancy, density, and activity patterns in Madre de Dios, Peru

This study provides novel insights into the ecology of the margay (Leopardus wiedii), focusing on its occupancy, density, and activity patterns in the Madre de Dios region, Peru, by utilizing both arboreal and terrestrial camera traps. Conducted across 10 km2, the research achieved 47 detections, utilizing semi-arboreal, lower canopy cameras for the first time to capture margay activities. Occupancy models revealed a mean occupancy probability of 53.82% and a detection probability of 6.57%. Among the environmental covariates, diameter at breast height (DBH) was identified as a significant predictor, negatively impacting occupancy, suggesting margays favor areas with smaller tree diameters. Contrary to expectations, the Normalized Difference Vegetation Index (NDVI) did not significantly influence occupancy. Tree density exhibited a positive, though non-significant, association with margay presence. Spatial capture-recapture (SECR) models estimated a margay density of 71.46 individuals per 100 km², with significant sex-based differences in spatial behavior. Males demonstrated larger home ranges (approximately 13.50 km²) compared to females (approximately 3.79 km²). Activity pattern analyses indicated primary nocturnal behavior with peaks at midnight to 3 am, 5 am, and 6 pm. Temporal overlap analysis revealed a low overlap coefficient with jaguarundis (Dhat1 = 0.21) and a higher overlap with ocelots (Dhat4 = 0.79), reflecting intricate interspecies dynamics. Our findings highlight important ecological aspects of margay behavior, including habitat preferences, nocturnal activity patterns, and interspecies interactions, which were effectively captured through the combined use of terrestrial and arboreal camera traps. The study emphasizes the importance of habitat preservation and the development of conservation strategies tailored to the ecological needs of margays, potentially influencing global practices for the management and protection of lesser-studied semi-arboreal wild cats.

Using a Device-Free Wi-Fi Sensing System to Assess Daily Activities and Mobility in Low-Income Older Adults: Protocol for a Feasibility Study

Background Older adults belonging to racial or ethnic minorities with low socioeconomic status are at an elevated risk of developing dementia, but resources for assessing functional decline and detecting cognitive impairment are limited. Cognitive impairment affects the ability to perform daily activities and mobility behaviors. Traditional assessment methods have drawbacks, so smart home technologies (SmHT) have emerged to offer objective, high-frequency, and remote monitoring. However, these technologies usually rely on motion sensors that cannot identify specific activity types. This group often lacks access to these technologies due to limited resources and technology experience. There is a need to develop new sensing technology that is discreet, affordable, and requires minimal user engagement to characterize and quantify various in-home activities. Furthermore, it is essential to explore the feasibility of developing machine learning (ML) algorithms for SmHT through collaborations between clinical researchers and engineers and involving minority, low-income older adults for novel sensor development. Objective This study aims to examine the feasibility of developing a novel channel state information–based device-free, low-cost Wi-Fi sensing system, and associated ML algorithms for localizing and recognizing different patterns of in-home activities and mobility in residents of low-income senior housing with and without mild cognitive impairment. Methods This feasibility study was conducted in collaboration with a wellness care group, which serves the healthy aging needs of low-income housing residents. Prior to this feasibility study, we conducted a pilot study to collect channel state information data from several activity scenarios (eg, sitting, walking, and preparing meals) using the proposed Wi-Fi sensing system continuously over a week in apartments of low-income housing residents. These activities were videotaped to generate ground truth annotations to test the accuracy of the ML algorithms derived from the proposed system. Using qualitative individual interviews, we explored the acceptability of the Wi-Fi sensing system and implementation barriers in the low-income housing setting. We use the same study protocol for the proposed feasibility study. Results The Wi-Fi sensing system deployment began in November 2022, with participant recruitment starting in July 2023. Preliminary results will be available in the summer of 2025. Preliminary results are focused on the feasibility of developing ML models for Wi-Fi sensing–based activity and mobility assessment, community-based recruitment and data collection, ground truth, and older adults’ Wi-Fi sensing technology acceptance. Conclusions This feasibility study can make a contribution to SmHT science and ML capabilities for early detection of cognitive decline among socially vulnerable older adults. Currently, sensing devices are not readily available to this population due to cost and information barriers. Our sensing device has the potential to identify individuals at risk for cognitive decline by assessing their level of physical function by tracking their in-home activities and mobility behaviors, at a low cost. International Registered Report Identifier (IRRID) DERR1-10.2196/53447

Does Windbreak Enhancement With Floral Resources Increase Pollinator Communities in Citrus Orchards?

ABSTRACTAgricultural practices and landscape simplification contribute to the ongoing global decline in wildlife. A more integrated approach such as cultivating flowering plants by agricultural fields can enhance wildlife habitat, especially for beneficial arthropods like pollinators. In Florida, citrus orchards are commonly bordered by living windbreaks, single lines of trees designed to buffer orchards from weather extremes as well as pest and pathogen movement. Although these windbreaks act as alternative habitats for residential arthropods, they can be improved with additional floral resources and vegetational complexity. In this study, we explored whether enhancing these field margins by planting flowering herbs, vines and shrubs would lead to higher pollinator abundance and diversity in citrus orchards in north and central Florida. We also investigated the role of naturally occurring wildflowers in attracting pollinators. We found that floral plantings by citrus orchard edges were utilised by pollinators. Cultivated blanketflower (Gaillardia pulchella) was particularly attractive to various wild bees, while commercially managed honey bees were primarily found on a common weedy flowering plant, Spanish needles (Bidens alba). We ultimately found differing patterns of pollinator activity in the adjacent citrus orchards across regions; while more bees, including honey bees, were found within the enhanced orchard compared to control orchard in central Florida, this was not true in north Florida. This study highlights the pollinator resources provided by wild flowers in and around orchards in addition to the conservation potential of cultivated, pollinator‐friendly plants.

Assessing Appropriation of Space in Urban Green Spaces: Three Case Studies in Downtown Shanghai

This study investigated patterns of activities in urban green spaces (UGSs) in downtown Shanghai. UGSs are essential public infrastructure, contributing to urban sustainability, quality of life, and social cohesion. Although widely studied, there is a gap in the literature regarding Chinese UGSs when the object of study is the nature the activities. In this sense, we aimed to investigate the activities from the perspective of appropriation of the space, considered here as different from the use of space. This study addressed this by analyzing user demographics, frequency, and spatial activity patterns to assess how these activities could be classified and scored according to a varying levels of appropriation. Through a mixed-methods design based on non-participant observation and behavior mapping, the study was conducted across three comprehensive parks in Shanghai, divided into nine observation zones. The data were analyzed through descriptive statistics, IBM SPSS, and qualitative coding, revealing, as the main findings, sixty distinct activity types, a soft to moderate level of appropriation, and notable variations in demographic presence and temporal trends. This research underscores the effectiveness of observational methods, validates appropriation as an analytical category, and emphasizes the importance of structured classification systems for improving the understanding of UGSs’ socio-spatial performance and their societal role.

Entropy of Neuronal Spike Patterns

Neuronal spike patterns are the fundamental units of neural communication in the brain, which is still not fully understood. Entropy measures offer a quantitative framework to assess the variability and information content of these spike patterns. By quantifying the uncertainty and informational content of neuronal patterns, entropy measures provide insights into neural coding strategies, synaptic plasticity, network dynamics, and cognitive processes. Here, we review basic entropy metrics and then we provide examples of recent advancements in using entropy as a tool to improve our understanding of neuronal processing. It focuses especially on studies on critical dynamics in neural networks and the relation of entropy to predictive coding and cortical communication. We highlight the necessity of expanding entropy measures from single neurons to encompass multi-neuronal activity patterns, as cortical circuits communicate through coordinated spatiotemporal activity patterns, called neuronal packets. We discuss how the sequential and partially stereotypical nature of neuronal packets influences the entropy of cortical communication. Stereotypy reduces entropy by enhancing reliability and predictability in neural signaling, while variability within packets increases entropy, allowing for greater information capacity. This balance between stereotypy and variability supports both robustness and flexibility in cortical information processing. We also review challenges in applying entropy to analyze such spatiotemporal neuronal spike patterns, notably, the “curse of dimensionality” in estimating entropy for high-dimensional neuronal data. Finally, we discuss strategies to overcome these challenges, including dimensionality reduction techniques, advanced entropy estimators, sparse coding schemes, and the integration of machine learning approaches. Thus, this work summarizes the most recent developments on how entropy measures contribute to our understanding of principles underlying neural coding.

Correction: Diurnal patterns of accelerometer-measured physical activity and sleep and risk of all-cause mortality: a follow-up of the National Health and Nutrition Examination Surveys (NHANES)

Correction: Diurnal patterns of accelerometer-measured physical activity and sleep and risk of all-cause mortality: a follow-up of the National Health and Nutrition Examination Surveys (NHANES)

Temporal patterns of energy intake and physical activity and cross-sectional associations with body weight status in children and adolescents: results from the Portuguese National Food, Nutrition and Physical Activity Survey 2015–2016

ABSTRACT Temporal energy intake (EI) and physical activity (PA) patterns may be associated with obesity. We aimed to derive and characterise temporal EI and PA patterns and assess their cross-sectional association with weight status in participants aged 6–14 years from the Portuguese National Food, Nutrition and Physical Activity Survey 2015-2016. We extracted times and EI of all eating occasions from two 1-day food diaries/24-hour recalls, while types and times of PA from 4-day PA diaries. We derived EI patterns (n=714) and PA patterns (n=595), using, respectively, a hierarchical and K-means cluster analysis, considering the average proportion of total daily EI (%TEI) and PA intensity (%TPA), within each 2-hour interval across the 24-hour day. We assessed the association between patterns and Overweight or obesity (Body Mass Index z-score ≥+1 Standard Deviation) using adjusted logistic regressions [Odds ratio (95% Confidence Interval)]. Three EI patterns were identified and labelled based on the 2-h interval of %TEI peaks: 1–“Early afternoon & Early evening”; 2–“Early afternoon & Late evening”, and 3–"Late morning, Early and Mid-afternoon & Late evening”. EI Pattern 3 vs. 1 was negatively associated with overweight or obesity [0.49 (0.26,0.92)]. PA pattern 1–“Late Morning, Mid-afternoon & Early evening” vs. Pattern 2–“Late afternoon”, was not associated with weight status [0.95 (0.65,1.38)]. A daily EI pattern characterised by more and even %TEI peaks at earlier daytime periods, instead of less, may be negatively associated with overweight or obesity amongst Portuguese 6-to-14-year-olds, whereas the identified PA patterns might have no relationship.

Light Walking Patterns and Postprandial Cardiometabolic Responses in Young Obese Adults: A Randomized Crossover Study

Abstract Context Recent studies suggest that light-intensity physical activity may enhance cardiometabolic health and reduce mortality risk in adults. However, more information is required to understand the patterns of light-intensity physical activity and postprandial cardiometabolic health. Objective This study examined the effects of different light-intensity walking patterns on postprandial cardiometabolic responses in young obese adults. Design A randomized crossover trial was conducted. Setting The study was conducted in the laboratory. Participants The study analyzed baseline (fasting) and 6-hour postprandial concentrations of glucose, insulin, triglycerides, and blood pressure (BP) in 16 young obese adults. Interventions Participants underwent four 7-hour experimental conditions with a 7–20-day washout period: uninterrupted sitting (SIT), 30-minute light-intensity walking (EX+SIT), 3-minute light-intensity walking every 30 minutes (BR), and 30-minute light-intensity walking with 3-minute light-intensity walking every 30 minutes (EX+BR). Main Outcome Measures Incremental areas under the curve (iAUC) for each outcome and average BP were compared between SIT and walking conditions. Results Compared with SIT, all walking conditions reduced iAUCs for glucose and average diastolic BP (all p<0.05). Only EX+SIT and EX+BR reduced iAUCs for insulin (p<0.05). No significant differences were found for triglycerides iAUC and systolic BP between the four conditions (all p>0.05). Conclusions All patterns of light-intensity walking reduced postprandial glucose concentrations and diastolic BP in young obese adults, suggesting benefits for glycemic control. Continuous 30-minute light-intensity walking alone, or combined with brief 3-min bouts also attenuated postprandial insulin concentrations, highlighting light-intensity walking as a promising strategy for improving cardiometabolic health in young obese adults.

Examining how brief mindfulness training influences communication within the brain of musicians with music performance anxiety: A resting state fMRI study

Many musicians live with music performance anxiety (MPA), which may affect their psychological and physiological functioning. Mindfulness, being aware in the present moment without judgment, has been found to help ease anxiety. Mindfulness may also help alleviate the negative effects of MPA, but what is the neurophysiological basis for this effect? Core components of mindfulness, including emotional processing and acceptance, are related to specific patterns of brain activity. In the current study, 20 musicians with MPA underwent a resting-state functional magnetic resonance imaging (MRI) scan (Time 1), a method to examine the communication between brain regions at rest. Notably, 10 musicians then underwent 2 weeks of mindfulness training, while 10 did not. The same scan sequence was repeated in all participants 2 weeks later (Time 2). Compared with Time 1, participants in the mindfulness group exhibited decreased resting-state functional connectivity between areas of the prefrontal cortex and the vermis-6 and crus-II at Time 2. These two areas of the cerebellum are related to emotional processing and acceptance. Changes in communication between these brain regions and the prefrontal cortex suggest the neurophysiological influences of mindfulness and how mindfulness can be used to strengthen emotion regulation networks in musicians with MPA.

EPCO-11. BIASES IN HEALTHY BRAIN SINGLE-CELL DATASETS: FINDING THE BEST COMPARISON FOR GLIOBLASTOMA STUDIES

Abstract Tumor cells undergo metabolic alterations that support their proliferation and simultaneously modify immune populations, resulting in an immunosuppressive tumor microenvironment. This study aims to compare the metabolic expression of immune cells within the tumor microenvironment to those in a healthy environment. However, there is a lack of single-cell transcriptomic data for normal brain cells, necessitating an analysis of different methods to compare immune cells in tumors with those in a healthy brain. To address this, we explored cell-to-cell metabolic variability using public single-cell RNA-seq (scRNA-seq) data of glioblastoma (n=338564), and from immune cells in the brains of post-mortem individuals (n=14177), fetuses (n=40000), and epilepsy patients (n=466), as well as from immune blood cells (n=329762). We employed ssGSEA to generate activity scores for 70 key metabolic pathways from KEGG for each individual cell. Known marker genes were utilized to identify normal cell populations (macrophages, T cells, oligodendrocytes) in datasets lacking cell type annotations. Our results revealed that blood cells exhibited high metabolic activity in macrophages but showed moderate activity in other cell types. Immune blood cells also demonstrated high oxidative phosphorylation (OXPHOS) but low fatty acid activity. Fetal brain cells displayed a lack of heterogeneity and showed high fatty acid activity with low OXPHOS activity. Brain cells from post-mortem individuals displayed heterogeneity but exhibited low metabolic activity across nearly all cells and pathways. Additionally, the hierarchy of pathway activity differed from the other datasets. Epilepsy data revealed a metabolic activity pattern similar to tumor-infiltrating immune cells, with comparable activity hierarchy and heterogeneity, although the sample size was limited for detailed comparison. Understanding the differences between types of datasets is important to choose the most appropriate comparison, allowing us to observe the metabolic alterations in immune cells caused by glioblastoma and to develop better immunotherapy strategies.

Unique cortical and subcortical activation patterns for different conspecific calls in marmosets

The common marmoset (Callithrix jacchus) is known for its highly vocal nature, displaying a diverse range of calls. Functional imaging in marmosets has shown that the processing of conspecific calls activates a brain network that includes fronto-temporal areas. It is currently unknown whether different call types activate the same or different networks. In this study, nine adult marmosets (four females) were exposed to four common vocalizations (phee, chatter, trill, and twitter), and their brain responses were recorded using event-related fMRI at 9.4T. We found robust activations in the auditory cortices, encompassing core, belt, and parabelt regions, and in subcortical areas like the inferior colliculus, medial geniculate nucleus, and amygdala in response to these calls. Although a common network was engaged, distinct activity patterns were evident for different vocalizations that could be distinguished by a 3D convolution neural network, indicating unique neural processing for each vocalization. Our findings also indicate the involvement of the cerebellum and medial prefrontal cortex (mPFC) in distinguishing particular vocalizations from others.Significance StatementThis study investigates the neural processing of vocal communications in the common marmoset (Callithrix jacchus). Utilizing event-related fMRI at 9.4T, we demonstrate that different calls (phee, chatter, trill, and twitter) elicit distinct brain activation patterns, challenging the notion of a uniform neural network for all vocalizations. Each call type distinctly engages various regions within the auditory cortices and subcortical areas. These findings offer insights into the evolutionary mechanisms of primate vocal perception and provide a foundation for understanding the origins of human speech and language processing.

A Study on the Relationship Between Spiral Motion Illusions and Anxiety Levels: A Comprehensive Analysis of Neural Activity and Visual Stimuli

Abstract. Spiral Motion Illusions (SMIs) are a fascinating phenomenon where static images create a compelling sense of motion, tricking the brain into perceiving movement where there is none. This study investigates the relationship between SMIs and anxiety levels, aiming to uncover how these visual illusions might influence emotional states. The experimental design involved exposing thirty-one participants to two distinct types of SMIsthe "rotating snakes" and "rotating ad-lib" imageswithin a controlled environment. Anxiety levels were assessed both before and after exposure using standardized questionnaires, while neural activity was continuously monitored through the ThinkGear ASIC Module (TGAM) to capture real-time brainwave patterns. The results revealed significant changes in anxiety levels, with each type of SMI eliciting unique neural responses. The "rotating snakes" illusion, characterized by dynamic color contrast, and the "rotating ad-lib" images, defined by contrasting colors, produced distinct patterns of anxiety-related brainwave activity. These findings provide valuable insights into the intricate ways that visual illusions can influence emotional states, particularly anxiety, and highlight the potential of SMIs as tools for both psychological research and therapeutic applications. This study advances our understanding of the neural mechanisms underlying anxiety and offers a new perspective on how visual stimuli can affect mental health.

Activity in Occipito-Temporal Cortex Is Involved in Tool-Use Planning and Contributes to Tool-Related Semantic Neural Representations

Abstract Tool use and language are highly refined human abilities which may show neural commonalities due to their potential reciprocal interaction during evolution. Recent work provided evidence for shared neural resources between tool use and syntax. However, whether activity within the tool-use network also contributes to semantic neural representations of tool nouns remains untested. To this aim, we identified the tool-use planning network with functional magnetic resonance imaging while participants used pliers. The very same participants underwent a semantic priming task including two categories, tool nouns and animal nouns, to highlight the respective underlying networks. With multivariate analyses of the activation neural patterns, we tested whether activity in tool-use brain clusters takes part in the neural representation of tool nouns as compared with animal nouns. The results revealed that word semantic categories were decoded within the left occipito-temporal cortex activated by preparing to use a tool, with similar patterns of brain activity for words within the same category. In addition, in the same area, neural activations for tool nouns were found to be higher than those for animal nouns. These findings suggest that activity in tool-use related brain areas encodes semantic information separately for tool nouns and animal nouns, thus supporting the embodiment of tool-noun processing in the tool-use sensorimotor network.

VTA dopamine neurons are hyperexcitable in 3xTg-AD mice due to casein kinase 2-dependent SK channel dysfunction

Alzheimer’s disease (AD) patients exhibit neuropsychiatric symptoms that extend beyond classical cognitive deficits, suggesting involvement of subcortical areas. Here, we investigated the role of midbrain dopamine (DA) neurons in AD using the amyloid + tau-driven 3xTg-AD mouse model. We found deficits in reward-based operant learning in AD mice, suggesting possible VTA DA neuron dysregulation. Physiological assessment revealed hyperexcitability and disrupted firing in DA neurons caused by reduced activity of small-conductance calcium-activated potassium (SK) channels. RNA sequencing from contents of single patch-clamped DA neurons (Patch-seq) identified up-regulation of the SK channel modulator casein kinase 2 (CK2), which we corroborated by immunohistochemical protein analysis. Pharmacological inhibition of CK2 restored SK channel activity and normal firing patterns in 3xTg-AD mice. These findings identify a mechanism of ion channel dysregulation in VTA DA neurons that could contribute to behavioral abnormalities in AD, paving the way for novel treatment strategies.

Processing demands modulate the activities and functional connectivity patterns of the posterior (VWFA-1) and anterior (VWFA-2) VWFA

Previous studies have shown that the visual word form area (VWFA) has structural and intrinsic functional connectivity with both language and attention networks. Nevertheless, it is still unclear how the functional connectivity pattern of the VWFA is regulated by processing demands induced by experimental tasks, and whether processing demands differentially regulate the posterior (VWFA-1) and anterior (VWFA-2) subregions of the VWFA. To address these questions, the present study adopted two tasks varying in processing demands (i.e., verbal and non-verbal tasks), and used generalized psychophysiological interaction (gPPI) and dynamic causal modeling (DCM) analyses to explore the task-dependent functional connectivity patterns of the two subregions of the VWFA. Activation analysis revealed that the VWFA-2 showed higher activation for the verbal task than the non-verbal task, while there were no activation differences in the VWFA-1 after controlling for the stimulus driven effects. Functional and effective connectivity analyses revealed that, for both VWFA-1 and VWFA-2, the verbal task enhanced connections from VWFAs to the ventral language regions (e.g., the left orbital frontal cortex), while the non-verbal task enhanced connections from VWFAs to the dorsal visuospatial regions (e.g., the left intraparietal sulcus). Results of the present study indicate that processing demands induced by tasks modulate both the local activity and functional connectivity patterns of the VWFA, providing new insights for understanding its domain-general function.