Boris C. Bernhardt

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.

This study identifies distinct subcortical-cortical circuit disruptions in autism and ADHD using functional connectivity and dynamic causal modeling in a multi-site cohort.

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

This study examines how connector hubs in temporal lobe epilepsy patients reorganize compared to healthy controls, finding widespread hub reductions and new hub emergence in contralateral regions.

This paper introduces the R-ratio to quantify the balance between local and distributed excitation in the brain, showing it increases with aging and Alzheimer's disease.

This study links higher hippocampal 18F-MK6240 uptake in TLE to increased seizure burden, altered NREM sleep microstructure, and impaired memory.

The paper identifies distinct hippocampal subfield signals for novelty detection, showing CA1 supports local associative mismatch while subiculum supports global item-based matching.

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.

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.

This paper investigates thalamocortical dynamics during theory of mind tasks using fMRI and sEEG, finding that the thalamus coordinates default network activity through phase-amplitude coupling without local activation.

The paper examines how different types of adversity relate to hippocampal macro- and microstructure in early adolescents, finding distinct spatial associations across brain regions.

This paper introduces a surface-intrinsic framework for hippocampal unfolding that improves alignment accuracy and morphology preservation compared to volumetric methods.

This paper quantifies multiscale MRI changes in focal cortical dysplasia lesions and links them to macroscale brain organization patterns.

This study maps hippocampal and amygdala subregions using resting-state fMRI from 722 participants, revealing structured co-representation patterns and divergence in functional connectivity.

This study examines thalamo-cortical and thalamo-hippocampal functional connectivity in temporal lobe epilepsy, finding reduced connectivity in TLE patients and its association with seizure generalization and surgical outcomes.

The paper presents an open dataset of cerebral tau deposition in young healthy adults using [18F]MK6240 PET to support imaging biomarker studies in non-geriatric populations.

The paper examines thalamocortical maturation by analyzing FA changes and functional connectivity in 10 thalamic nuclei across childhood and adolescence.

The paper examines histopathology in FDG-PET hypometabolic regions of pediatric epilepsy patients with FCD type II, finding fFCD concentrated at the lesion epicenter and DNO present in both epicenter and hypometabolic borders.

This study examines sex differences in structural brain alterations in common epilepsies using neuroimaging data from a large international cohort, finding some regional differences but no significant sex-by-diagnosis interactions.

The paper identifies a reproducible functional connectivity signature in temporal lobe epilepsy through a large-scale connectome-wide analysis.

The paper identifies patient-specific structural deviations and disease epicenters in temporal lobe epilepsy using multimodal MRI data, linking resection overlap with seizure freedom.

This study identifies hierarchical neural signatures of language by linking semantic and phonological processing to brain networks using fMRI, myelin measures, and AI models.

electro-MICA projects electrophysiological features onto cortical surfaces using numerical solutions to electromagnetic equations, outperforming conventional models in iEEG validation.

MICAFlow provides a fast and robust MRI preprocessing pipeline that translates research workflows into clinical practice, achieving high registration accuracy and data reliability across diverse datasets.

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.

This study identifies four distinct HRF shape groups in the epileptic brain, showing HRF variability is linked to both anatomical location and pathology.

This study characterizes the human claustrum using multiscale methods, revealing MRI resolution-dependent features and defining practical measurement limits.

This study uses activity flow mapping to show reduced task activation prediction accuracy in TLE and FLE patients, linking intrinsic network dysconnectivity to memory impairments.

This study identifies patient-specific functional biomarkers in temporal lobe epilepsy using multimodal MRI data to predict clinical outcomes and guide precision therapeutics.

cuBNM accelerates brain network simulations using GPUs, enabling large-scale studies of neural processes previously limited by computational costs.