Single-trial fluctuations in the EEG signal have been shown to temporally correlate with the fMRI BOLD response and are valuable for modeling trial-to-trial fluctuations in responses. The P1 and N1 components of the visual ERP are sensitive to different attentional modulations, suggesting that different aspects of stimulus processing can be modeled with these ERP parameters. As such, different patterns of BOLD covariation for P1 and N1 informed regressors would be expected; however, current findings are equivocal. We investigate the effects of variations in attention on P1 and N1 informed BOLD activation in a visual oddball task. Simultaneous EEG-fMRI data were recorded from 13 healthy participants during three conditions of a visual oddball task: Passive, Count, and Respond. We show that the P1 and N1 components of the visual ERP can be used in the integration-by-prediction method of EEG-fMRI data integration to highlight brain regions related to target detection and response production. Our data suggest that the P1 component of the ERP reflects changes in sensory encoding of stimulus features and is more informative for the Passive and Count conditions. The N1, on the other hand, was more informative for the Respond condition, suggesting that it can be used to model the processing of stimulus, meaning specifically discriminating one type of stimulus from another, and processes involved in integrating sensory information with response selection. Our results show that an understanding of the underlying electrophysiology is necessary for a thorough interpretation of EEG-informed fMRI analysis.
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iScience
January 2025
Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France.
Recent studies showed that humans, regardless of age, education, and culture, can extract the linear trend of a noisy scatterplot. Although this capacity looks sophisticated, it may simply reflect the extraction of the principal trend of the graph, as if the cloud of dots was processed as an oriented object. To test this idea, we trained Guinea baboons to associate arbitrary shapes with the increasing or decreasing trends of noiseless and noisy scatterplots, while varying the number of points, the noise level, and the regression slope.
View Article and Find Full Text PDFFront Psychol
January 2025
Department of Psychosomatic Medicine and Psychotherapy, LWL-University Hospital, Ruhr-Universität Bochum, Bochum, Germany.
Introduction: Intrusive memories occur frequently after potentially traumatic events and form a core symptom of posttraumatic stress disorder (PTSD) if they persist. The translational approach of visuospatial interventions tries to target those intrusive memories in order to reduce their frequency predominantly using an intervention including as one component the computer game Despite promising results, the application of has critical drawbacks, e.g.
View Article and Find Full Text PDFBioinform Adv
January 2025
Digital Technologies Research Centre, National Research Council of Canada, Ottawa, ON K1K 4P7, Canada.
Motivation: Missing values are prevalent in high-throughput measurements due to various experimental or analytical reasons. Imputation, the process of replacing missing values in a dataset with estimated values, plays an important role in multivariate and machine learning analyses. The three missingness patterns, including missing completely at random, missing at random, and missing not at random, describe unique dependencies between the missing and observed data.
View Article and Find Full Text PDFIndian J Psychiatry
December 2024
Department of Psychiatry, Government Medical College and Hospital, Chandigarh, India.
Background: Postpartum depression (PPD) is a serious concern with multifactorial etiology. Association between prenatal anxiety, pain, and depression has been theorized.
Aim: In this randomized controlled trial, we studied the effect of pain relief by combined spinal epidural (CSE) and other factors influencing PPD.
Cureus
December 2024
Cornea and Refractive Surgery, Al-Shifa Trust Eye Hospital, Rawalpindi, PAK.
Background: Glaucoma, particularly open-angle glaucoma (OAG), is a leading cause of irreversible blindness, associated with optic nerve damage, retinal ganglion cell death, and visual field defects. Corneal biomechanical properties and cellular components, such as corneal nerve and keratocyte densities assessed by in vivo confocal microscopy (IVCM), may serve as biomarkers for glaucoma progression. This study aimed to explore the relationship between corneal nerve parameters, keratocyte density, and optical coherence tomography (OCT)-derived retinal nerve fiber layer (RNFL) thickness in primary open-angle glaucoma (POAG) patients and controls.
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