NiCLIP: Neuroimaging contrastive language-image pretraining model for predicting text from brain activation images.

Predicting cognitive processes from brain activation maps has remained an open question within the neuroscience community for many years. Meta-analytic functional decoding methods aim to tackle this issue by providing a quantitative estimation of behavioral profiles associated with specific brain regions. Existing methods face intrinsic challenges in neuroimaging meta-analysis, particularly in consolidating textual information from publications, as they rely on limited metrics that do not capture the semantic context of the text.

Methods for decoding cortical gradients of functional connectivity.

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques.

Methods for decoding cortical gradients of functional connectivity.

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques.

Neuroscout, a unified platform for generalizable and reproducible fMRI research.

Functional magnetic resonance imaging (fMRI) has revolutionized cognitive neuroscience, but methodological barriers limit the generalizability of findings from the lab to the real world. Here, we present Neuroscout, an end-to-end platform for analysis of naturalistic fMRI data designed to facilitate the adoption of robust and generalizable research practices. Neuroscout leverages state-of-the-art machine learning models to automatically annotate stimuli from dozens of fMRI studies using naturalistic stimuli-such as movies and narratives-allowing researchers to easily test neuroscientific hypotheses across multiple ecologically-valid datasets.

Hippocampal acidity and volume are differentially associated with spatial navigation in older adults.

The hippocampus is negatively affected by aging and is critical for spatial navigation. While there is evidence that wayfinding navigation tasks are especially sensitive to preclinical hippocampal deterioration, these studies have primarily used volumetric hippocampal imaging without considering microstructural properties or anatomical variation within the hippocampus. T1ρ is an MRI measure sensitive to regional pH, with longer relaxation rates reflecting acidosis as a marker of metabolic dysfunction and neuropathological burden.

Analysis of task-based functional MRI data preprocessed with fMRIPrep.

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study.

Home-Based, Adaptive Cognitive Training for Cognitively Normal Older adults: Initial Efficacy Trial.

Objectives: We examined whether a home-based, adaptive cognitive training (CT) program would lead to cognitive performance changes on a neuropsychological test battery in cognitively normal older adults.

Method: Sixty-eight older adults (age = 70.0, SD = 3.

fMRIPrep: a robust preprocessing pipeline for functional MRI.

Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each dataset, building upon a large inventory of available tools. The complexity of these workflows has snowballed with rapid advances in acquisition and processing.

Carotid β-stiffness index is associated with slower processing speed but not working memory or white matter integrity in healthy middle-aged/older adults.

Aging is associated with increased carotid artery stiffness, a predictor of incident stroke, and reduced cognitive performance and brain white matter integrity (WMI) in humans. Therefore, we hypothesized that higher carotid stiffness/lower compliance would be independently associated with slower processing speed, higher working memory cost, and lower WMI in healthy middle-aged/older (MA/O) adults. Carotid β-stiffness ( < 0.