Pierre‐Louis Bazin

Selective nigrosome vulnerability in Parkinson's disease revealed by histology-anchored ultra-high-field quantitative MRI

This study uses MRI to show that nigrosomes in Parkinson's patients show specific magnetic properties changes, indicating vulnerability without direct neuronal loss.

Cortical contributions to attentional orienting and response cancellation in action stopping

This study uses fNIRS to examine cortical activity during action cancellation in a stop-signal task, finding preSMA involvement consistent with the Pause-then-Cancel model.

Giving you five: A neuroimaging atlas of the nigrosomes in the substantia nigra based on 3D histology

This paper creates a 3D histological atlas of nigrosomes in the substantia nigra aligned to MNI152 space, enabling MRI analysis of these structures in Parkinson's disease.

Multimodal laminar characterization of visual areas along the cortical hierarchy

This paper characterizes laminar organization across four visual areas using multimodal data, finding parvalbumin profiles as the most discriminative feature.

Pooling quantitative MRI data: A multi-protocol study of healthy subcortical ageing

This study evaluates how protocol and hardware differences affect pooling quantitative MRI data across sites in healthy aging studies, finding both benefits and drawbacks for analysis outcomes.

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.

Tempo-dependent selective enhancement of neural responses at the beat frequency can be mimicked by both an oscillator and an evoked model

The paper shows that neural responses to rhythm are selectively enhanced at the beat rate, which can be explained by both entrainment and evoked response models.

Assessing Quantitative MRI Techniques using Multimodal Comparisons

The paper analyzes quantitative MRI metrics in healthy adults to understand their relationships and potential for uncovering cortical gradients.

Mesoscale imaging of the human cerebellum reveals converging regional specialization of its morphology, vasculature and cytoarchitecture.

The paper uses mesoscale imaging to show cerebellar cortex heterogeneity in morphology, vasculature, and cytoarchitecture, challenging the notion of uniformity.

A unified imaging-histology framework for superficial white matter architecture studies in the human brain

The paper develops a computational framework to study superficial white matter organization using 3D histology and 7T MRI, finding high structural complexity in the first 2 mm below the cortical boundary and correlations with cortical geometry and connectivity.

Subcortical nuclei of the human ascending arousal system encode anticipated reward but do not predict subsequent memory

The paper investigates subcortical nuclei activity during reward anticipation and memory encoding, finding increased activity during reward anticipation but no predictive effect on memory.

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.

Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm

This study merges five fMRI datasets using a novel aggregatory method to analyze subcortical BOLD responses in the stop-signal paradigm, finding large subcortical activity for failed stops and highlighting the impact of smoothing on GLMs.

Joint models reveal human subcortical underpinnings of choice and learning behaviour

This study uses joint models to analyze human subcortical contributions to choice and learning, finding subcortical regions involved in decision urgency and reward prediction error processing.

The ageing stopping network: Regional and network changes in the IFG, preSMA, and STN across the adult lifespan

The paper examines anatomical changes in the response inhibition network across the adult lifespan using diffusion MRI and finds age-related changes in white matter tracts rather than regional structure.

Investigating working memory updating processes of the human subcortex using 7T MRI

This study investigates subcortical involvement in working memory updating using 7T MRI and finds subcortical activation during gate closing and substitution, suggesting a role in general updating processes rather than specific gating.

A Comparative Machine Learning Study of Connectivity-Based Biomarkers of Schizophrenia

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

Predictive coding during action observation - a depth-resolved intersubject functional correlation study at 7T

The paper uses intersubject functional correlation with 7T fMRI to show that predictable action sequences trigger more feedback input to parietal regions than unpredictable ones.

Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI

This study maps age-related changes in 17 human subcortical structures using in vivo 7 T MRI, revealing shifts in location and properties across the adult lifespan.

Motor Sequences - Separating The Sequence From The Motor. A longitudinal rsfMRI Study

This study examines resting state functional connectivity changes after sequence-specific motor learning, finding sequence-specific decreases in the right supplementary motor area during overall learning.

Mapping the Human Visual Thalamus and its Cytoarchitectonic Subdivisions Using Quantitative MRI

This paper uses quantitative MRI to non-invasively map the human lateral geniculate nucleus and its subdivisions, showing that T1 contrast reflects cyto- and myeloarchitectonic differences.

White matter microstructural changes in short-term learning of a continuous visuomotor sequence

This study investigates white matter microstructural changes during short-term motor sequence learning using MRI scans and finds significant changes in early learning phases and functional connectivity.

Multi-contrast Anatomical Subcortical Structures Parcellation

This paper introduces a new open-source algorithm for automatically parcellating subcortical structures in MRI data, validated against experts and tested on 17 structures.

3 versus 7 Tesla Magnetic Resonance Imaging for parcellations of subcortical brain structures

This study compares 3T and 7T MRI for parcellating subcortical brain structures, finding 7T provides better interrater agreement and contrast-to-noise ratios for smaller structures.

A flexible workflow for simulating transcranial electric stimulation in healthy and lesioned brains

The paper introduces a flexible workflow for simulating transcranial electric stimulation in healthy and lesioned brains using open-source tools.

Resolving multisensory and attentional influences across cortical depth in sensory cortices

The paper investigates how multisensory and attentional influences vary across cortical depth in sensory cortices using fMRI, finding distinct depth-dependent patterns in auditory and visual cortices.

Denoising High-field Multi-dimensional MRI with Local Complex PCA

This paper introduces a denoising technique for multi-parametric quantitative MRI that improves signal-to-noise ratio without compromising spatial accuracy or creating spurious boundaries.

High resolution atlasing of the venous brain vasculature from 7T quantitative susceptibility

This paper presents a high-resolution atlas of the human venous brain vasculature using 7T MRI data to characterize vessel location, diameter, and curvature.

Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 34 primate species

This study analyzes MRI data from 34 primate species to investigate the evolution of neocortical folding, finding a Brownian Motion model best fits the data and a stable fold wavelength across varying brain sizes.

Laminar signal extraction over extended cortical areas by means of a spatial GLM

This paper introduces a spatial GLM method to extract laminar signals from cortical data, showing improved signal localization and reduced partial volume effects.