Robert Leech

Brain-thought states during movie-watching reflect shared sensory anchors and film- and person- specific processes in association cortex

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.

Thoughts and cortical responses are shaped by the type of change at event boundaries

The paper examines how different types of event boundaries during movie-watching relate to visual, auditory, semantic features, thought patterns, and cortical states.

RADIAL AND TANGENTIAL FIBER COMPONENTS IN HUMAN SUPERFICIAL WHITE MATTER AND THEIR ASSOCIATIONS WITH MACROSCALE FUNCTION

This paper develops a framework to distinguish radial and tangential fiber components in human superficial white matter and examines their microstructural and functional properties.

HippoGenes: A robust workflow for subregional transcriptomic profiling of the human hippocampus

HippoGenes creates transcriptomic maps of the human hippocampus using spatial statistical models and the Allen Human Brain Atlas, enabling subregional gene expression analysis and disease-related molecular decoding.

Neural feature spaces: characterizing the geometry of brain activity across development

The paper characterizes the geometry of brain activity across development by analyzing neural feature spaces in children and adults using EEG data.

Reorganisation of Functional Connectivity Gradients in Post-Stroke Aphasia

This study examines how stroke-induced changes in functional connectivity gradients relate to language outcomes in aphasia patients.

The stability of thought: using experience sampling and brain imaging to determine the contextually bound nature of human cognition.

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.

AutoNeuro: An Open-Source fMRI Toolbox for Real-Time Neuroadaptive Task Design

AutoNeuro enables real-time fMRI with adaptive task design by integrating acquisition, preprocessing, and Bayesian optimization for closed-loop neuroimaging.

Human cortical dynamics reflect graded contributions of local geometry and network topography

This study shows that human cortical dynamics are influenced by both local geometry and network topology, with transmodal regions showing additional dependence on microstructural and connectivity factors.

Auditory Cortical Gradients Integrate Bottom-Up and Top-Down Structure During Natural Sound Categorisation

The paper shows natural sound categories are organized across continuous cortical gradients integrating acoustic and semantic information, revealing a new framework for understanding auditory perception.

Spatial layout of visual specialization is shaped by competing default mode and sensory networks

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

Patterns of Ongoing Thought in the Real World and Their Link to Mental Health and Well-Being

This study uses experience sampling to measure daily thought patterns and links them to mental health, finding an 'Intrusive Distraction' pattern associated with anxiety and linked to social connectedness.

The spatial layout of antagonistic brain regions is explicable based on geometric principles

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

MULTIMODAL GRADIENTS UNIFY LOCAL AND GLOBAL CORTICAL ORGANIZATION

This paper maps global cortical organization by integrating microstructural, connectivity, and functional data with cytoarchitectural maps, revealing a sensory-fugal gradient and functional diversity across brain areas.

The intrinsic cortical geometry of reading

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

DySCo: a general framework for dynamic Functional Connectivity

DySCo introduces a framework for dynamic functional connectivity analysis, providing a unified theoretical approach and efficient algorithms for processing high-dimensional brain data.

Ultra-low-field brain MRI morphometry: test-retest reliability and correspondence to high-field MRI

This study evaluates the reliability and correspondence of ultra-low-field MRI morphometry to high-field MRI, showing high reliability and correspondence across scan resolutions and contrasts.

Exploring functional connectivity in clinical and data-driven groups of preterm and term adults

This study examines functional connectivity differences between preterm and term adults and identifies behavioral subgroups with distinct connectivity patterns.

Individual brain activity patterns during task are predicted by distinct resting-state networks that may reflect local neurobiological features

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

Personality traits vary in their association with brain activity across situations.

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 impact of heterogeneous spatial autocorrelation on comparisons of brain maps

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

Distinctive and complementary roles of default mode network subsystems in semantic cognition

This study investigates how different subsystems of the default mode network (DMN) contribute to semantic cognition across various tasks and modalities, revealing distinct activation and deactivation patterns.

Mapping patterns of thought onto brain activity during movie-watching

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.

Experience sampling reveals the role that covert goal states play in task-relevant behavior.

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.

Variation in spatial dependencies across the cortical mantle discriminates the functional behaviour of primary and association cortex

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.

Patterns of Ongoing Thought in the Real-World

This study uses real-world experience sampling to analyze how daily activities influence thought patterns, finding that socializing and environmental factors shape ongoing thought.

Tissue volume estimation and age prediction using rapid structural brain scans

This study compares EPImix and conventional T1-weighted MRI scans for tissue volume estimation and brain-age prediction, finding similar results but a systematic age offset that can be corrected.

Estimating anisotropy directly via neural timeseries

This paper introduces a method to estimate anisotropy from neural timeseries using a generalized Lagrangian model and applies it to murine calcium imaging data.

Investigating the interaction between white matter and brain state on tDCS-induced changes in brain network activity

This study examines how white matter structure and brain state interact to influence tDCS-induced changes in brain network activity in healthy and TBI participants.

Identifying components that vary in space and time from resting-state functional MRI

The paper applies a spatiotemporal ICA technique to resting-state fMRI data to identify spatiotemporally evolving brain components, finding that stable ICNs serve as building blocks of these patterns.