Kamen A. Tsvetanov

The paper identifies a latent variable linking resting-state functional connectivity and psychopathology in children and adolescents, revealing a neurotypical-neurodivergent continuum.

The paper identifies latent factors underlying white matter metrics using MRI data from a cohort of healthy adults and links these factors to cardiovascular health and cognitive performance.

This study investigates how brain health and cardiorespiratory fitness influence age-related word-finding failures in older adults using neuroimaging and fitness data.

The paper examines brain activity and cognitive performance in older adults during a problem-solving task, finding increased cuneal cortex activity with age and performance, suggesting functional compensation for fluid intelligence.

This study evaluates hemodynamic models of the BOLD response across the adult lifespan, finding that three-parameter models and biophysical models like HDM capture age-related changes effectively.

This study shows that cognitive function in older adults depends on the alignment between functional and structural brain networks, with this dependency being strongest in high-order and subcortical networks.

The paper examines how age affects load-modulated functional connectivity during visual short-term memory tasks across a lifespan cohort.

This study evaluates GAN-generated brain MRI images using human ratings and image quality metrics, finding that human experts detect quality changes better than most metrics, except a deep QA model trained on human data.

This study investigates how locus coeruleus noradrenergic integrity influences inhibitory control in older adults through prefrontal cortical connectivity.

This study uses resting-state MEG data to show that age-related changes in neural network dynamics are linked to sleep quality and cognitive decline.

This study uses linked ICA to analyze multimodal neuroimaging data from healthy ageing subjects, finding correlations between brain structure, vascular dynamics, and fluid intelligence.

This study shows that baseline cerebral blood flow predicts multiple-demand network activity and fluid intelligence across the lifespan, with non-neuronal CBF effects confounding BOLD signals.

The paper uses MEG and HMMs to analyze resting-state brain network dynamics in aging, finding that older adults show reduced lower-order networks and increased higher-order networks linked to cognitive decline.

This study shows that age-related changes in resting-state BOLD signal variability are fully explained by cardiovascular and cerebrovascular factors, not neural activity or atrophy.

This study creates a probabilistic atlas of the human locus coeruleus using ultra-high field MRI, revealing spatial gradients and providing a resource for future research.

The paper examines age-related changes in functional brain networks using gradient mapping techniques in a cohort of 643 participants, finding shifts in network positions and increased dispersion linked to cognitive decline.

This study compares GWAS and relatedness-based regression for identifying genetic variants associated with brain structure, finding they perform differently based on linkage disequilibrium levels.

This study investigates how neuroinflammation interacts with functional brain connectivity in Alzheimer's disease and its impact on cognitive performance.

This study investigates how dopamine levels in Parkinson’s disease patients affect sensory attenuation during voluntary movements, finding a negative correlation with motor severity and a positive correlation with dopamine dose.

This study examines the associations between cardiovascular risk factors and white matter structure in aging, finding that systolic blood pressure, diastolic blood pressure, and heart rate independently impact white matter health.

The paper shows that physical activity preserves frontal white matter integrity and reduces age-related slowing in a population-based sample.

The paper investigates age-related decline in motor adaptation, finding that explicit memory performance and associated brain regions become stronger predictors of motor learning in older adults.