LORRAINE KOMISARJEVSKY TYLER

The paper identifies a distributed neural substrate for early speech interpretation using MEG data and Representational Similarity Analysis, showing simultaneous processing of phonology, lexical form, and semantics.

This study investigates how recurrent connectivity in the brain supports visual and semantic object representations during recognition using fMRI and MEG data.

This study uses BERT to model incremental speech comprehension and finds that coherent interpretations emerge through the integration of linguistic and non-linguistic constraints in bilateral brain regions.

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.

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.

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 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 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 how visual information transforms into semantic representations in the ventral visual pathway using computational models and MEG data, finding distinct oscillatory patterns for visual and semantic information.

The paper combines deep visual and semantic attractor networks to model fMRI data from object processing, showing how visual input influences semantic representations in the ventral stream.

The paper investigates age-related differences in visual and auditory evoked responses using MEG and MRI, finding distinct structural correlates for each type of delay.