Jonathan C. Lau

This study maps the topographic organization of the human zona incerta using diffusion MRI and connectivity analysis, revealing gradients and clusters linked to specific cortical regions and functions.

Open browser platform embeds a language-model neuroanatomy tutor in an MRI viewer and scores landmark placements against 21 expert-annotated templates using trained-rater error distributions.

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

The paper identifies a human zona incerta subregion with characteristics of the rodent A13 nucleus using MRI and histology.

This study shows that sensory expectations influence motor preparation and corrective responses in humans and monkeys, with neural activity scaling with perturbation probabilities.

This study investigates neural population dynamics in motor cortex during reaching, revealing a compositional structure that enables posture-dependent control.

This paper identifies inaccuracies in existing spatial coordinates for the Allen Human Brain Atlas and provides a refined coordinate set to improve gene expression integration with neuroimaging data.

HippoMaps provides a toolbox and data warehouse for mapping and analyzing hippocampal data across multiple modalities and scales.

The paper shows that LPFC neurons time-multiplex task features during virtual navigation, enhancing temporal encoding of spatial and non-spatial information.

This paper describes a method for improving targeting accuracy in chronic microelectrode implantations in large animals using image-guided neuronavigation and custom cranial caps.

The paper releases curated anatomical fiducial placements for MRI datasets to improve image registration quality control and registration accuracy.

HippUnfold is an automated BIDS-App for hippocampal unfolding and subfield segmentation using deep learning and topological constraints, enabling individual-specific morphometric analysis.

This study assesses the feasibility and reliability of mapping the subcortical connectome using in vivo diffusion MRI tractography and test-retest data from the Human Connectome Project.

This study applies the anatomical fiducials framework to Parkinson's Disease clinical MRI data, showing it can measure registration errors and detect morphometric biomarkers of the disease.

This paper investigates how MP2RAGE sequence parameters affect T1 reproducibility and morphometry across sites, showing that B1+ inhomogeneities significantly impact results and that corrections improve comparability.

This paper uses high-resolution MRI to visualize and characterize the human zona incerta and surrounding brain structures in vivo.

The paper uses 3D histological data and computational unfolding to identify hippocampal subfields through clustering of laminar and morphological features, revealing subfield boundaries and longitudinal differences.

This paper introduces anatomical fiducials (AFIDs) to improve spatial correspondence in brain imaging and demonstrates their effectiveness over traditional voxel overlap metrics.

This paper introduces a computational method to unfold the hippocampus, enabling 2D mapping of subfields and revealing structural regularities validated by histology.