Zonglei Zhen

Distinct gradients of cortical architecture capture visual representations and behavior across the lifespan

The paper shows two architectural gradients in human visual cortex that correlate with structural, functional, and behavioral traits across the lifespan.

Brainana: an end-to-end preprocessing framework for macaque neuroimaging

Brainana provides an automated preprocessing framework for macaque neuroimaging, enabling reproducible and scalable analysis across multiple sites.

Gyral crowns contribute to the cortical infrastructure of human face processing

The paper examines the relationship between gyral crown height and face-selective regions in the fusiform gyrus, finding reduced crown height correlates with impaired face recognition in developmental prosopagnosia and replicates this in a large neurotypical sample.

Overlooked neuroanatomical markers of face processing and developmental prosopagnosia in posteromedial cortex

The paper identifies a sulcal network in the posteromedial cortex associated with face processing and finds structural differences between neurotypical individuals and those with developmental prosopagnosia.

Functionally and structurally distinct fusiform face area(s) in over 1000 participants

The paper identifies two functionally and structurally distinct fusiform face-selective regions in the human brain using data from over 1000 participants.

A studyforrest extension, MEG recordings while watching the audio-visual movie "Forrest Gump"

The paper presents a public MEG dataset of 11 participants watching the movie 'Forrest Gump' to study neural dynamics with high temporal resolution.

The face module emerged in a deep convolutional neural network selectively deprived of face experience

This study shows that a deep convolutional neural network deprived of face experience still develops face-selective modules, suggesting domain-specificity can emerge without genetic predisposition.

Semantic relatedness emerges in deep convolutional neural networks designed for object recognition

This study shows that deep convolutional neural networks develop semantic relatedness among objects during training, similar to human WordNet structures, without explicit top-down guidance.

Hierarchical sparse coding of objects in deep convolutional neural networks

This study shows that deep convolutional neural networks use a hierarchical sparse coding scheme similar to the primate brain, with increasing sparseness and correlation with object recognition performance.

DNNBrain: a unifying toolbox for mapping deep neural networks and brains

DNNBrain provides a Python toolbox for exploring internal representations in deep neural networks and the brain, enabling cross-disciplinary research between deep learning and cognitive neuroscience.

Opposing transcriptomic gradients explain orthogonal maps in human visual areas

The paper shows opposing transcriptomic gradients explain orthogonal maps in human visual areas and predicts microanatomical differences and genetic susceptibility.

Apparent thinning of visual cortex during childhood is associated with myelination, not pruning

The paper investigates microstructural changes in the visual cortex during childhood and finds that apparent thinning is due to increased myelination rather than pruning.

Separate lanes for math and reading in the white matter highways of the human brain

The paper identifies shared and segregated white matter tracts for math and reading networks using multimodal MRI, revealing structural differences related to myelination in sub-bundles.

Human visual cortex is organized along two genetically opposed hierarchical gradients with unique developmental and evolutionary origins

The paper identifies two opposing genetic gradients in the human visual cortex that correlate with developmental and evolutionary features, linking cytoarchitecture and gene expression.

Intrinsic Hippocampal-Caudate Interaction Correlates with Human Navigation

This study examines the functional interaction between hippocampus and caudate in human navigation using fMRI and behavioral tasks, finding a positive correlation with navigation ability.