Daniel S. Margulies

This study examines brain-thought relationships during movie-watching, finding that sensory-related neural signatures are consistent across films, while memory-related processes vary with context and modeling approaches.

The paper identifies a topographic organization of mental imagery in the human parietal cortex, showing modality-specific regions and a central hub for multisensory imagery.

This study shows that the development of long-range cortical connections leads to the emergence of hierarchical functional modes in the human cortex, shifting from geometrically driven patterns to sensory-association organization.

This study introduces a neuroimaging framework to discover state-dependent signal flow hierarchy in the human cerebral cortex using integrated effective connectivity and signal flow mapping.

This study examines how nondual meditation affects self-representation and brain connectivity in expert meditators compared to novices.

This study shows early sensory deprivation causes localized reorganization near deprived primary sensory areas while preserving the overall cortical hierarchy.

The paper tests if cortical geometry encodes sensory function by modeling multisensory integration from geometric eigenmodes, finding they align with sensory domains but require additional modes for full hierarchy.

The paper examines the relationship between task context, thought patterns, and neural activity, finding that thought reliability varies with task context and is associated with MDN activity.

The paper examines how age and pubertal stage independently influence the refinement of the functional cortical hierarchy during adolescence using longitudinal data.

The paper introduces SCD to analyze spatial influences on cortical functional specialization, revealing a dominant gradient and competitive suppression from other brain regions.

The paper investigates individual uniqueness in brain connectivity gradients using resting-state fMRI data, finding that network complexity and dispersion influence identification rates.

The paper uses kriging to show that task-induced brain activity increases can be predicted from activity decreases, revealing topographically determined antagonistic relationships.

Precon_all is a pipeline for non-human cortical surface reconstruction that generalizes human methods to multiple species, enabling comparative neuroimaging studies.

The paper uses predictive modeling to show that stronger oral reading ability correlates with closer proximity between visual and association cortex in the brain.

This study links functional connectivity profiles to fluid intelligence using dimensionality reduction and graph analysis, showing that functional distance from sensory and high-cognition systems correlates with intelligence.

The paper identifies two distinct pathways between visual and default mode networks that support semantic and spatial cognition, showing their dissociation in functional connectivity and task responses.

The paper shows that cell type distributions in the cortex are spatially aligned with functional organization patterns from fMRI.

The paper examines macro-scale brain activity patterns during wakeful rest, linking them to personality traits and ongoing thoughts by analyzing interactions between brain networks.

The paper predicts individual brain activity patterns during tasks using resting-state networks, showing task-specificity and relevance of cortical microstructure/morphology.

The paper shows that personality traits are more strongly associated with brain activity in specific tasks than in others, highlighting the need for context-specific analyses.

The paper links ventral attention network connectivity to cortical maturation and cognitive ability in children using independent datasets.

The paper investigates the neural correlates of meditation expertise by comparing functional connectivity patterns between long-term meditators and novices, finding increased integration of brain networks associated with embodied cognition.

This paper shows how heterogeneous spatial autocorrelation affects brain map comparisons and introduces a Bayesian spatial regression approach for valid statistical inference.

This paper introduces a method to estimate spatially fine-grained connectivity gradients efficiently, enhancing brain-behavior predictions without reducing spatial resolution.

The paper maps developmental changes in structural and functional brain organisation across neurotypical and neurodivergent individuals, showing stable gradients with plastic coupling in higher-order networks.

The paper analyzes intracortical recordings to show exogenous attention emerges as cortical gradients, with neural activity reflecting visual attributes and response timing.

The paper develops a method to map thought patterns onto brain activity during movie-watching and finds sensory and association cortex play key roles in engagement and distraction.

This study compares machine learning models using functional connectivity and its derivatives to predict schizophrenia, finding that raw connectivity outperforms low-dimensional features.

This study uses experience sampling to examine covert goal-relevant states during task performance, finding that fronto-parietal network activity is linked to better task performance.

The paper uses variograms to show that function changes more rapidly in association cortex than in sensory and motor cortex, linked to intracortical myelin levels.