The effects of two Alzheimer's disease related genes and in healthy young adults: An attentional blink study.

Background: Genetic risk factors start to affect the brain and behavior in Alzheimer's disease (AD) before clinical symptoms occur. Although AD is mainly associated with memory deficits, attention and executive dysfunctions can present at the early presymptomatic stages in middle age for those with non-modifiable risks.

Objective: Here, we investigated whether known risk genes for AD already affected attention in young adulthood.

Sensitization and Habituation of Hyper-Excitation to Constant Presentation of Pattern-Glare Stimuli.

Background/objectives: Pattern glare, associated with cortical hyperexcitability, induces visual distortions and discomfort, particularly in individuals susceptible to migraines or epilepsy. While previous research has primarily focused on transient EEG responses to patterned stimuli, this study aims to investigate how continuous presentation of pattern-glare stimuli affects neural adaptation over both fine (seconds) and coarse (entire experiment) temporal scales.

Methods: EEG recordings were obtained from 40 healthy participants exposed to horizontal square-wave gratings at three spatial frequencies presented continuously for three seconds each across multiple trials.

Ecological implications of row width and cultivar selection on rice (Oryza sativa) and barnyardgrass (Echinochloa crus-galli).

Rice (Oryza sativa L.) producers in the Mid-south are experiencing difficulties with herbicide-resistant weeds such as barnyardgrass [Echinochloa crus-galli (L.) P.

Multimodal and Multifactor Branching Time Active Inference.

Active inference is a state-of-the-art framework for modeling the brain that explains a wide range of mechanisms. Recently, two versions of branching time active inference (BTAI) have been developed to handle the exponential (space and time) complexity class that occurs when computing the prior over all possible policies up to the time horizon. However, those two versions of BTAI still suffer from an exponential complexity class with regard to the number of observed and latent variables being modeled.

Deconstructing Deep Active Inference: A Contrarian Information Gatherer.

Active inference is a theory of perception, learning, and decision making that can be applied to neuroscience, robotics, psychology, and machine learning. Recently, intensive research has been taking place to scale up this framework using Monte Carlo tree search and deep learning. The goal of this activity is to solve more complicated tasks using deep active inference.

Quantifying error in effect size estimates in attention, executive function, and implicit learning.

Accurate quantification of effect sizes has the power to motivate theory and reduce misinvestment of scientific resources by informing power calculations during study planning. However, a combination of publication bias and small sample sizes (∼ = 25) hampers certainty in current effect size estimates. We sought to determine the extent to which sample sizes may produce errors in effect size estimates for four commonly used paradigms assessing attention, executive function, and implicit learning (attentional blink, multitasking, contextual cueing, and serial response task).

Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.

Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of the datasets available for learning and interpreting the predictive features, as well as, how to effectively combine neuroimaging and tabular data (e.g.

Transient Attention Gates Access Consciousness: Coupling N2pc and P3 Latencies Using Dynamic Time Warping.

The N2pc and P3 event-related potentials (ERPs), used to index selective attention and access to working memory and conscious awareness, respectively, have been important tools in cognitive sciences. Although it is likely that these two components and the underlying cognitive processes are temporally and functionally linked, such links have not yet been convincingly demonstrated. Adopting a novel methodological approach based on dynamic time warping (DTW), we provide evidence that the N2pc and P3 ERP components are temporally linked.

Hippocampal neurons code individual episodic memories in humans.

The hippocampus is an essential hub for episodic memory processing. However, how human hippocampal single neurons code multi-element associations remains unknown. In particular, it is debated whether each hippocampal neuron represents an invariant element within an episode or whether single neurons bind together all the elements of a discrete episodic memory.

Is predictive coding falsifiable?

Predictive-coding has justifiably become a highly influential theory in Neuroscience. However, the possibility of its unfalsifiability has been raised. We argue that if predictive-coding were unfalsifiable, it would be a problem, but there are patterns of behavioural and neuroimaging data that would stand against predictive-coding.

Piezo1 opposes age-associated cortical bone loss.

As we age, our bones undergo a process of loss, often accompanied by muscle weakness and reduced physical activity. This is exacerbated by decreased responsiveness to mechanical stimulation in aged skeleton, leading to the hypothesis that decreased mechanical stimulation plays an important role in age-related bone loss. Piezo1, a mechanosensitive ion channel, is critical for bone homeostasis and mechanotransduction.

Cardiovascular implantable electronic device lead safety: Harnessing real-world remote monitoring data for medical device evaluation.

Background: Current methods to identify cardiovascular implantable electronic device lead failure include postapproval studies, which may be limited in scope, participant numbers, and attrition; studies relying on administrative codes, which lack specificity; and voluntary adverse event reporting, which cannot determine incidence or attribution to the lead.

Objective: The purpose of this study was to determine whether adjudicated remote monitoring (RM) data can address these limitations and augment lead safety evaluation.

Methods: Among 48,191 actively monitored patients with a cardiovascular implantable electronic device, we identified RM transmissions signifying incident lead abnormalities and, separately, identified all leads abandoned or extracted between April 1, 2019, and April 1, 2021.

Dysregulated Polycomb Repressive Complex 2 contributes to chronic obstructive pulmonary disease by rewiring stem cell fate.

Aberrant lung cell differentiation is a hallmark of many lung diseases including chronic obstructive pulmonary disease (COPD). The EZH2-containing Polycomb Repressive Complex 2 (PRC2) regulates embryonic lung stem cell fate, but its role in adult lung is obscure. Histological analysis of patient tissues revealed that loss of PRC2 activity was correlated with aberrant bronchiolar cell differentiation in COPD lung.

Branching Time Active Inference with Bayesian Filtering.

Branching time active inference is a framework proposing to look at planning as a form of Bayesian model expansion. Its root can be found in active inference, a neuroscientific framework widely used for brain modeling, as well as in Monte Carlo tree search, a method broadly applied in the reinforcement learning literature. Up to now, the inference of the latent variables was carried out by taking advantage of the flexibility offered by variational message passing, an iterative process that can be understood as sending messages along the edges of a factor graph.

Concealed identity information detection with pupillometry in rapid serial visual presentation.

The concealed information test (CIT) relies on bodily reactions to stimuli that are hidden in mind. However, people can use countermeasures, such as purposely focusing on irrelevant things, to confound the CIT. A new method designed to prevent countermeasures uses rapid serial visual presentation (RSVP) to present stimuli on the fringe of awareness.

Assessing the Intention, Attitudes, and Social Influences on COVID-19 Preventive Behaviors Among Non-rural Black and Rural Appalachian White Populations: A Faith-Based Community Study.

Introduction: The COVID-19 pandemic has had detrimental impacts in non-rural Black and rural Appalachian populations. Yet despite the pandemic's magnitude, there is a scarcity of research exploring potential influences of attitudes and social influences within these populations on their adherence to COVID-19 public health preventive behaviors.

Purpose: This study examines the intention, attitudes, and social influences to adhere to COVID-19 preventive behaviors among non-rural Black and rural Appalachian congregants in Kentucky by integrating the Theory of Planned Behavior (TPB).

Branching time active inference: Empirical study and complexity class analysis.

Active inference is a state-of-the-art framework for modelling the brain that explains a wide range of mechanisms such as habit formation, dopaminergic discharge and curiosity. However, recent implementations suffer from an exponential (space and time) complexity class when computing the prior over all the possible policies up to the time horizon. Fountas et al.

Branching Time Active Inference: The theory and its generality.

Over the last 10 to 15 years, active inference has helped to explain various brain mechanisms from habit formation to dopaminergic discharge and even modelling curiosity. However, the current implementations suffer from an exponential (space and time) complexity class when computing the prior over all the possible policies up to the time-horizon. Fountas et al.

Quaternary Structure and Deoxyribonucleic Acid-Binding Properties of the Heme-Dependent, CO-Sensing Transcriptional Regulator RcoM.

RcoM, a heme-containing, CO-sensing transcription factor, is one of two known bacterial regulators of CO metabolism. Unlike its analogue CooA, the structure and DNA-binding properties of RcoM remain largely uncharacterized. Using a combination of size exclusion chromatography and sedimentation equilibrium, we demonstrate that RcoM-1 from is a dimer, wherein the heme-binding domain mediates dimerization.

Modelling the simultaneous encoding/serial experience theory of the perceptual moment: a blink of meta-experience.

One way to understand a system is to explore how its behaviour degrades when it is overloaded. This approach can be applied to understanding conscious perception by presenting stimuli in rapid succession in the 'same' perceptual event/moment. In previous work, we have identified a striking dissociation during the perceptual moment, between what is encoded into working memory [Lag-1 sparing in the attentional blink (AB)] and what is consciously perceived (Lag-1 impairing in the experiential blink).

Recovery after stroke: the severely impaired are a distinct group.

Introduction: Stroke causes different levels of impairment and the degree of recovery varies greatly between patients. The majority of recovery studies are biased towards patients with mild-to-moderate impairments, challenging a unified recovery process framework. Our aim was to develop a statistical framework to analyse recovery patterns in patients with severe and non-severe initial impairment and concurrently investigate whether they recovered differently.